> ## Documentation Index > Fetch the complete documentation index at: https://docs.miso.ai/llms.txt > Use this file to discover all available pages before exploring further. # Product to Products API > The Product to Products API returns the products that are related to an anchor product (often the product the user is currently engaging with) and are also likely to drive conversions by connecting with the user’s interests. It is different from the User to Products API as it not only considers the user’s interests but also considers the recommended products' relevancy to the anchor product. ### Applicable scenarios This API is frequently used in product detail page to show related products that users can consume further, such as "Related products you may like" on Amazon or "Up next video" on Youtube. It is one of Miso's best performing APIs. Our customers usually see more than 30% and some times 110% relative lift in click-through rate after deploying this a feature using this API. ### Basic usage To use this API, you just need to let Miso knows the `user_id` (or `anonymous_id`) and the `product_id` you want to get related recommendations for. For example, the following request will return the products that are related to the movie `Toy Story`. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"] } ``` * **product_id**: the id of the anchor product * **rows**: the number of related products to return * **fl**: like in other Miso API, you can use `fl` to control which fields to return for each Product The response will be like: ```javascript { "message": "success", "data": { "took": 56, "miso_id": "f98b1904-ddce-11eb-be53-fa1729b23183", "products": [ { "product_id": "toy-story-2-1999", "title": "Toy Story 2 (1999)" }, { "product_id": "toy-story-3-2010", "title": "Toy Story 3 (2010)" }, { "product_id": "the-lion-king-1994", "title": "The Lion King (1994)" } ] } } ``` * **products**: a list of products related to the anchor product * **products[ ].product_id**: the id of the recommended product * **products[ ].title**: the title of the recommended product. You can use `fl` parameter to make Miso return more fields ### Boosting and filtering Like every Miso API, you can utilize `fq` and `boost_fq` to fine-tune the recommendations returned by Miso, and Miso will guarantee to return the required number of recommendations that meet the given criteria. For example, the following request still recommends movies related to "Toy Story" but limits the recommendations to only the movies released after year 2010. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"], "fq": "custom_attributes.year: [2010 TO *]" } ``` For another example, the following request will *boost* the movies that are acted by `Tom Hanks`. The boosting is different from filtering as it only prioritizes those products that match the boosting criteria and are relevant to the anchor products, but it will not limit the results to only such products. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"], "boost_fq": "custom_attributes.actors:\"Tom Hanks\"" } ``` ### Multiple anchor products In the scenarios where you want to recommend products related to **multiple** anchor products, for example, for shopping cart cross-sell or up-sell, you can utilize `product_ids` parameter and have multiple product ids in it. For instance, the following request recommends products related to movies "Toy Story" and "Monsters, Inc." that will be of interest to the the current user. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_ids": ["toy-story-1995", "monsters-inc-2001"], "rows": 3, "fl": ["title"] } ``` ## OpenAPI ````yaml post /v1/recommendation/product_to_products openapi: 3.0.2 info: title: Miso API description: > # Overview Miso’s approach to personalization is to train machine learning Engines on three core data sets: 1. Your site’s log of historical and real-time interactions, 2. Your catalog of products and content, and 3. Your users. Miso provides the output of its Engines to you, so you can build search and recommendation experiences that are personalized down to the individual level (n=1 personalization). To see how Miso works and explore the power of its Engines, we recommend following [this tutorial](https://docs.askmiso.com/) to get started with our Playground data. Integrating your site or application with Miso happens in three basic steps: 1. Upload your data 2. Train your Engines 3. Build search and recommendation experiences with the output of your Engines. Miso provides two main integration points. The first is your [Dojo Dashboard](https://dojo.askmiso.com/), which is used to set up your Engines with the conversions you want to optimize and your training schedule. Dojo is also a great way to get familiar with Miso by manually uploading data and exploring the output of Miso’s Engines. In Dojo’s Sandboxes, you can tweak your Engine settings and see visual examples of Miso’s search and recommendations running on your live data. The second integration point is Miso’s API, which lets you automatically manage your data in Miso and build experiences that leverage the output of Miso’s personalization Engines. Miso’s API is composed of two major groups of REST API endpoints: Data APIs and Engine APIs. ### Data APIs Data APIs collect input to Miso's personalization Engines. These APIs all support high-throughput data ingestion through bulk insert, and satisfy GDPR and CCPA compliance by letting users delete their data from Miso. Subcategories of Data APIs are: * [Interaction APIs](#tag/Interaction-APIs), for managing your Interaction records. By uploading historical and real-time Interaction records, you tell Miso how users are engaging with the products and content on your site, and in turn, Miso’s Engines learn how to optimize your conversion funnels. * [Product / Content APIs](#tag/Product-Content-APIs), for managing your Product / Content records. These records provide a deep semantic understanding of your catalog and keep Miso up to date about your offerings so it can make smart and timely suggestions. The `product_id` is how Miso links Product / Content records to your Interaction records. * [User APIs](#tag/User-APIs), for managing your User records. These records tell Miso about your site’s users and visitors, so Miso can build an understanding of user segmentation and behavior in relation to products and content. The `user_id` is how Miso links User records to your Interaction records. As a rule of thumb, we recommend batching up data to avoid timeout risks. For the Product / Content and User Upload APIs, we recommend limiting each API upload call to about 100 records at a time. For the Interaction Upload API, we recommend limiting your calls to around 10,000 records at a time. ### Engine APIs Engine APIs provide the output of Miso's personalization Engines. We designed these APIs with a focus on low latency and high availability. Most of these APIs' 95th percentile response time is under 75ms, and the services are replicated to at least three separate instances for high availability. The types of Engine APIs are: * [Search APIs](#tag/Search-APIs), for getting Miso’s personalized search results for a user, with search-as-you-type and autocompletion. * [Recommendation APIs](#tag/Recommendation-APIs), for retrieving Miso’s recommendations that match users with the products, categories, and product attributes that are likely to drive conversions. # Authentication [View your API Keys in your Dojo Dashboard.](https://dojo.askmiso.com/docs/api-browser) There are three environments in Miso: * **Playground**, a read-only tutorial environment with sample data. * **Development**, for staging, QA, and experimentation. * **Production**, where you run your live integration with Miso. Access a Miso environment by passing in the corresponding API key in your API calls. There is one publishable key and one secret key per environment. API Key can passed with query parameter `api_key`, or using the `X-API-KEY` header. version: 1.1.4 servers: - url: https://api.askmiso.com security: [] tags: - name: Experiment APIs description: > Miso's experiment APIs let you do the A/B testing of your current result with Miso. ### Start an experiment in Dojo. Login to the [dojo](https://dojo.askmiso.com) platform. Create an experiment event for you. ### Start running A/B testing in your environment. #### Implement A/B testing code. Here's an example in NodeJS. You can also use any programming language of you choice. ```nodejs const axios = require('axios'); async function get_user_experiment_info(api_key, experiment_id, user_id) { data = {"user_id": user_id} endpoint = `https://api.askmiso.com/v1/experiments/${experiment_id}/events?api_key=${api_key}` return await axios.post(endpoint, data) } const api_key = '' const experiment_id = "" let user_id = 'user_1234' // use to evaluate a treatment for const user_experiment_info = get_user_experiment_info(api_key, experiment_id, user_id) user_experiment_info.then((response) => { let variant = response.data['variant'] if (variant['name'] == "treatment") { // insert code here to show "treatment" variant } else if (variant['name'] == "control") { // insert code here to show "control" variant } else { // unexpected variant name. raise error throw new Error(`Unexpected variant name ${variant["name"]}`) } }) ``` If you implement A/B testing code in FrontEnd, like JavaScript, and are also worried about exploding the secret api_key. You can choose to use anonymous_id with the public_api_key for this API. Here's an example. ```javascript const apiKey = ''; const experimentId = ''; const anonymous_id = 'user_1234'; // use to evaluate a treatment for function getUserExperimentInfo(apiKey, experimentId, anonymous_id) { const data = { user_id: anonymous_id }; const url = `https://api.askmiso.com/v1/experiments/${experimentId}/events?api_key=${apiKey}`; const options = { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify(data), }; return window.fetch(url, options) .then((response) => response.json()) .then((data) => { const variantName = data.variant.name; if (variantName === `${this.treatmentName}`) { // insert code here to show 'treatment' variant } else if (variantName === `${this.controlName}`) { // insert code here to show 'control' variant } else { // unexpected variant name, throw error throw new Error(`Unexpected variant name: ${variantName}`); } }) .catch((error) => console.error(error)); } getUserExperimentInfo(apiKey, experimentId, anonymous_id); ``` - name: Interaction APIs description: >+ Miso’s Interaction APIs let you manage your Interaction records stored with Miso. ### Interaction records Your Interaction records tell Miso about user interactions with products and content on your site or application. From these interactions, Miso understands how users move through your conversion funnels: which products or content assets attract the attention of each individual user, and which products or content ultimately will be purchased or consumed by each of them. With these insights, Miso makes real-time tailored recommendations for each user, and responds to each of their clicks and views on the site (even for anonymous users). Interaction records share some common attributes, but are distinguished by their type. Miso captures 23 different interaction types, divided into the following 6 groups: #### Core click-streams * `product_detail_page_view`: a user viewed the detail page for a product * `search`: a user made a search request with keywords and (optionally) filters The above interactions are the core fuel for Miso's personalization Engines, because they happen in a much higher frequency than other interactions and provide an unbiased and high-fidelity view of users' interests on the site. The collection of these interactions is highly important for Miso's personalization performance. At the minimum, you should implement the `product_detail_page_view` interaction to start with. #### Conversion (eCommerce) * `add_to_cart`: a user added a product to the shopping cart * `remove_from_cart`: a user removed a product from the shopping cart * `checkout`: a user checked out and started the payment process * `refund`: a user refunded the product * `subscribe`: a user subscribed to a product The above interactions are the main revenue drivers for eCommerce sites. It’s important to collect them so that Miso can not only drive click-through rates, but actually improve the revenue in a targeted way. To start with, you should at least implement the `add_to_cart` interaction. #### Consumption (content media) * `read`, `watch`, and `listen` interactions capture how and for how long a user consumed a piece of content. * `add_to_collection`: a user added an product to their personal collection * `remove_from_collection`: a user removed an product from their personal collection If you are a content site, the above interactions are the main drivers to users' satisfaction on the site. Collecting these interactions allows Miso to drive consumption rates and consumption durations for the content on your site. If you run a content site, you should implement at least one of these interactions. #### Feedback signals * `like`, `dislike`, `share`, `rate`, and `bookmark` are common ways users express their interests. These are strong signals for Miso to understand each user's preferences regarding your products or content. You should send these signals to Miso if you have any of these UI patterns on your site. #### Performance Checking * `impression`: a user saw or was presented with a product or content asset (but didn't yet interact with it) * `viewable_impression`: the product or content presented is actually viewed by the user (for example, minimum of 50% of the pixels were in viewable space for at least one continuous second.) * `click`: a user clicked on something (for example, a product item) #### Additional click-streams * `home_page_view`: user viewed your home page * `category_page_view`: a user viewed the page for a specific “group” or “family” or products or content in your catalog * `promo_page_view`: user viewed the promotion pages about certain products * `product_image_view`: user clicked on or otherwise interacted with the product image (e.g. enlarged the image) The above interactions are additional signals for Miso to understand users' behavior on the site. #### Custom * `custom` interaction types are reserved for you to define your own business-specific interaction types. Miso will analyze any custom interactions you define to infer users' interests and preferences. - name: Product / Content APIs description: >+ Miso's Product / Content APIs let you upload, read, and delete Product / Content records that represent your site's catalog. ### Product / Content records Miso analyzes your Product / Content records to provide personalized search and recommendations that connect users with products or content on your site or application. Much of Miso's search and personalization capability relies on understanding your catalog in-depth and drawing correlations between your catalog and your users' consumption or purchasing behaviors. In other words, Miso discovers that, with high correlation, users who are interested in certain product attributes would also be interested in other products with similar or related attributes. (For simplicity, we will often overload the word "products" to mean items for purchase if you are an eCommerce business, and content to consume if you are a content marketplace.) To fully optimize your search and recommendations, it is important to provide Miso with Product / Content records that are complete and accurate. We define a set of common attributes that capture the basics of most eCommerce and content media products, such as `title`, `description`, `categories`, `tags`, `material`, `authors`, etc. If your products' characteristics cannot be fully captured by these fields, we recommend that you specify `custom_attributes`. For Miso, the more complete the product information is, the better its personalized search and recommendations become. - name: User APIs description: >+ Miso’s User APIs let you upload, read, and delete User records that tell Miso about your site’s unique users and visitors. ### User records User records specify relatively static attributes for a given user, such as their `age`, `gender`, `city`, etc. As a rule of thumb, you should put information here that is not already captured in your [Interaction records](#tag/Interaction-APIs). For example, *last_bought_product* is probably not needed here because Miso already can tell that from the [Interaction records](#tag/Interaction-APIs). Miso will discover the correlations between a user's attributes and their behaviors on your site. For example, Miso might determine that users of a certain age group tend to be interested in certain products or a certain price range. These insights will be taken into account when predicting users' interests, in particular for new users who have not yet generated many interaction records. We define a set of common user attributes for e-Commerce and content media sites. Some of them, such as `name` are for display in the Dojo dashboard only. The rest are for model quality. Most attributes are optional and you don't need to specify them if you don't collect such data. On the other hand, you can specify your custom user attributes in the `custom_attributes` field. Miso will analyze custom user attributes to improve the model quality as well. - name: Bulk API description: > The Bulk API provides an efficient interface for making multiple Search / Recommendations / Q&A requests in one API call. These requests will be executed concurrently at the Miso side, and returned at once when all of them are finished. This API is particularly useful when you need to invoke multiple Miso APIs to respond to a user request. Using this API, you can batch multiple API calls into one, and significantly save the network round-trip times. ### Request schema The request schema for this API call is as follow: ``` POST /v1/bulk { "requests": [ { "api_name": "search/search", "body": { ... } }, { "api_name": "recommendation/product_to_product", "body": { ... } }, ... ] } ``` Each request object should contain: * **api_name**: name of the API you want to access. The name should contain a slash `/`. For example, search/search for search requests, search/autocomplete for autocomplete requests, etc. * **body**: the complete request body as if you are making the API request individually. Any errors in one of the requests will be returned, and will not prevent other requests from being executed. ### Response Schema Bulk API endpoint will return the API responses in the same order as they appear in the request. For example, if the Bulk API request is like the following: ``` POST /v1/bulk { "requests": [ {... request 1 ...}, {... request 2 ...} ] } ``` The response will be like: ``` { "data": [ // response for request 1 { "error": false, "status_code": 200, "body": { ... } }, // response for request 2 { "error": false, "status_code": 200, "body": { ... } } ] } ``` Each response object will contain the following fields: * **error**: whether there was an error with the request. You should check this field to determine whether to perform error handling. * **status_code**: status code of the request. * **body**: the response body of the request (as if the request was sent individually). Let's see a complete example with MovieLens data. The following requests will issue two requests in one API call that return the `Sci-Fi` movies directed by *Ridley Scott*, and *James Cameron* respectively in the first and second responses: ``` POST /v1/bulk { "requests": [ { "api_name": "search/search", "body": { "user_id": "test_user", "q": "sci-fi", "fq": "custom_attributes.director:\"Ridley Scott\"" } }, { "api_name": "search/search", "body": { "user_id": "test_user", "q": "sci-fi", "fq": "custom_attributes.director:\"James Cameron\"" } } ] } ``` The response will be like: ``` { "data": [ { "error": false, "status_code": 200, "body": { "data": { "took": 136, "miso_id": "19ab254c-5fb8-11ec-bd48-b20169940af9", "products": [ { "product_id": "blade-runner", "title": "Blade Runner (1982)" } ], "total": 6, "start": 0 } } }, { "error": false, "status_code": 200, "body": { "data": { "took": 116, "miso_id": "19ab254c-5fb8-11ec-bd48-b20169940af9", "products": [ { "product_id": "avatar", "title": "Avatar (2009)" } ], "total": 10, "start": 0 } } } ] } ``` - name: Ask APIs description: >+ Miso's new Ask API is the next generation of question answering APIs. It is designed to provide accurate and concise answers to your questions based on your existing product documents. Ask API offers a seamless and effective way to address complex queries in a near-realtime fasion. Miso preprocesses your product documents, breaking them into segments. When a question is received, Miso finds the most related product and segments, then summarize to a concise and informative answer based on the identified segments, including products related to the question. Possible use case includes: knowledge base, documentation search, customer support, and more. To use the Ask API, you first submit a "question" you want to ask. Question can be any human-readable text. Then a question ID will returned, and the question will be processed in the background. After receving question ID, you can then use the question ID to get latest answer to the question as it is being compiled. ---- For example: If you want to know about the inner workings of nginx: ```json { "question":"How nginx works internally?" } ``` The API would response with a question id. ```json { "data": { "question_id": "ff4775fa-345e-4d28-91b0-8fb8bf095e6a" }, "message": "success" } ``` Then you can send a GET request to `/v1/ask/questions/{question_id}/answer` to get the latest answer as it is being compiled and summerized. You can use `answer_stage` and `finished` to check current answer status. Here's the response of answer API when data is fetched and being verified, before answer is summerized: ```json { "message": "success", "data": { "question": "How nginx works internally?", "question_id": "ff4775fa-345e-4d28-91b0-8fb8bf095e6a", "parent_question_id": null, "answer_stage": "Verifying possible answers", "finished": false, "answer": "Verifying possible answers ...", "sources": [], "related_resources": [], "followup_questions": [] } } ``` Here's the response when answer is fullly summerized: ```json { "message": "success", "data": { "question": "How nginx works internally?", "question_id": "ff4775fa-345e-4d28-91b0-8fb8bf095e6a", "parent_question_id": null, "answer_stage": "Generating summary", "finished": true, "answer": "# How does Nginx work internally?\n\n## Internal requests [1]\n\nNginx differentiates between external and internal requests. External requests...[omitted for simplicity]", "sources": [ { "title": "Internal requests", "product_id": "9781788623551", "child_title": "Internal requests", "child_id": "203", "snippet": "<mark>Internal requests\nNginx differentiates external and internal requests.</mark>" }, { "title": "5. Nginx Core Architecture", "product_id": "9781484216569", "child_title": "5. Nginx Core Architecture", "child_id": "5", "snippet": "Checks if the client can access of the requested the resource.\n<mark>It is at this step that Nginx...[omitted]</mark>" }, { "title": "2. Managing Nginx", "product_id": "9781785289538", "child_title": "2. Managing Nginx", "child_id": "14", "snippet": "<mark>The Nginx connection processing architecture\nBefore you study...[omitted]</mark>" }, { "title": "3. Nginx Core Directives", "product_id": "9781484216569", "child_title": "3. Nginx Core Directives", "child_id": "3", "snippet": "<mark>Understanding the Default Configuration\nThe default configuration...[omitted]</mark>" }, { "title": "4. Nginx Modules", "product_id": "9781484216569", "child_title": "4. Nginx Modules", "child_id": "4", "snippet": "<mark>Based on the context like HTTP, MAIL, and STREAM, it creates a ...[omitted]</mark>" } ], "related_resources": [], "followup_questions": [ "What are the steps involved in processing a request and generating a response in Nginx?", "How do Nginx modules contribute to the internal workings of Nginx?" ] } } ``` Related product IDs will be returned along with human-readable answer. Related text section in the product will also be quoted. If a product has any children, they will also be matched, `child_id` and `child_title` will be included for sources belonging to the product's children. You can use `fq` to limit the search scope, for example, to a specific product type or other condition. If you only want to search for books (no articles of videos), you can use `fq=type:book` like this: ```json { "question":"How nginx works internally?" "fq": "type:book" } ``` If you want the answer to contain any other fields, set `source_fl` when submitting the question. - name: User Recommendations description: >- APIs for recommending products and content to users based on their interests. - name: Product Recommendations description: APIs for recommending related products based on a given product. paths: /v1/recommendation/product_to_products: post: tags: - Product Recommendations summary: Product to Products API description: >- The Product to Products API returns the products that are related to an anchor product (often the product the user is currently engaging with) and are also likely to drive conversions by connecting with the user’s interests. It is different from the User to Products API as it not only considers the user’s interests but also considers the recommended products' relevancy to the anchor product. ### Applicable scenarios This API is frequently used in product detail page to show related products that users can consume further, such as "Related products you may like" on Amazon or "Up next video" on Youtube. It is one of Miso's best performing APIs. Our customers usually see more than 30% and some times 110% relative lift in click-through rate after deploying this a feature using this API. ### Basic usage To use this API, you just need to let Miso knows the `user_id` (or `anonymous_id`) and the `product_id` you want to get related recommendations for. For example, the following request will return the products that are related to the movie `Toy Story`. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"] } ``` * **product_id**: the id of the anchor product * **rows**: the number of related products to return * **fl**: like in other Miso API, you can use `fl` to control which fields to return for each Product The response will be like: ```javascript { "message": "success", "data": { "took": 56, "miso_id": "f98b1904-ddce-11eb-be53-fa1729b23183", "products": [ { "product_id": "toy-story-2-1999", "title": "Toy Story 2 (1999)" }, { "product_id": "toy-story-3-2010", "title": "Toy Story 3 (2010)" }, { "product_id": "the-lion-king-1994", "title": "The Lion King (1994)" } ] } } ``` * **products**: a list of products related to the anchor product * **products[ ].product_id**: the id of the recommended product * **products[ ].title**: the title of the recommended product. You can use `fl` parameter to make Miso return more fields ### Boosting and filtering Like every Miso API, you can utilize `fq` and `boost_fq` to fine-tune the recommendations returned by Miso, and Miso will guarantee to return the required number of recommendations that meet the given criteria. For example, the following request still recommends movies related to "Toy Story" but limits the recommendations to only the movies released after year 2010. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"], "fq": "custom_attributes.year: [2010 TO *]" } ``` For another example, the following request will *boost* the movies that are acted by `Tom Hanks`. The boosting is different from filtering as it only prioritizes those products that match the boosting criteria and are relevant to the anchor products, but it will not limit the results to only such products. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_id": ["toy-story-1995"], "rows": 3, "fl": ["title"], "boost_fq": "custom_attributes.actors:\"Tom Hanks\"" } ``` ### Multiple anchor products In the scenarios where you want to recommend products related to **multiple** anchor products, for example, for shopping cart cross-sell or up-sell, you can utilize `product_ids` parameter and have multiple product ids in it. For instance, the following request recommends products related to movies "Toy Story" and "Monsters, Inc." that will be of interest to the the current user. ``` POST https://api.askmiso.com/v1/recommendation/product_to_products { "user_id": "user_123", "product_ids": ["toy-story-1995", "monsters-inc-2001"], "rows": 3, "fl": ["title"] } ``` operationId: product_to_products_v1_recommendation_product_to_products_post requestBody: content: application/json: schema: $ref: '#/components/schemas/YMALRequest' required: true responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/ProductToProductsResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - Secret API Key: [] components: schemas: YMALRequest: title: YMALRequest type: object properties: product_id: title: Product Id minLength: 1 type: string description: > The `product_id` of the *anchor* product. The returned recommendations will be the products that are similar or are liked by the same users who also like the anchor product. product_ids: title: Product Ids minLength: 1 type: array items: type: string minLength: 1 description: > The `product_ids` of a **list** of *anchor* products. The returned recommendations will be the products that are similar or are liked by the same users who also like these anchor products. For example, you can use the products in a user's shopping cart as the anchor products to make purchase recommendations for this user. product_group_id: title: Product Group Id minLength: 1 type: string description: > The `product_group_id` of the *anchor* product group. The returned recommendations will be the products that are similar or are liked by the same users who also like the anchor *product group*. You should use `product_group_id` on a *product group* page, before users select a specific product variant. For example, you should use `product_group_id` on the product group page of a T-shirt, and use `product_id`, once user choose any specific size or color variants of the T-shirt. product_group_ids: title: Product Group Ids type: array items: type: string description: > The `product_group_ids` of the *anchor* product groups. The returned recommendations will be the products that are similar or are liked by the same users who also like the anchor *product groups*. You should use `product_group_ids` in pages you want to recommend products related to multiple product groups. buy_together: title: Buy Together type: boolean description: >+ Whether to focus on the Products that are frequently *bought together*. `buy_together` parameter is by default `false`, which make the *Product To Products API* focus on Products that are related to the anchor products, e.g. the products with similar contents or frequently attract the interests of the same group of users. When `buy_together=true`, the ProductToProducts API will focus on the type of Products that are more frequently bought together along with the anchor product(s) in the same transactions or session. default: false engine_id: title: Engine Id type: string description: > The engine you want to get results from. When you have more than one engine, you can use this parameter to specify the specific engine you want to get results from. If not specified, the default engine will be used. user_id: title: User Id type: string description: > The user who made the query and for whom Miso will personalize the results. For an anonymous visitor, use `anonymous_id` instead. anonymous_id: title: Anonymous Id type: string description: >- The anonymous visitor who made the query and for whom Miso will personalize the results. Either `user_id` or `anonymous_id` needs to be specified for personalization to work. user_hash: title: User Hash type: string description: > The hash of `user_id` (or `anonymous_id`) encrypted by your [Secret API Key](#section/Authentication/Secret%20API%20Key). `user_hash` is required to prevent unauthorized API access if you are making API calls with a [Publishable API Key](#section/Authentication/Publishable%20API%20Key). You should generate the user_hash via HMAC scheme: you encrypt the desired user_id (or anonymous_id) with your [Secret API Key](#section/Authentication/Secret%20API%20Key) on your backend server, and then let the front-end code send the generated user_hash to Miso APIs to verify the identity of the API caller. As long as the [Secret API Key](#section/Authentication/Secret%20API%20Key) is kept secret, the user_hash prevents a malicious attacker from making unauthorized API calls or impersonating any of your users. Miso APIs accept the case-incentive "hex digest" of user hash, a sample Python 3 code to generate it on your backend server is as follow: ```python import hashlib import hmac YOUR_MISO_SECRET_API_KEY = "039c501ac8dfcac91" key_bytes = YOUR_MISO_SECRET_API_KEY.encode() user_id = "USER_123" # or anonymous_id user_id_bytes = user_id.encode() user_hash = hmac.new( key_bytes, user_id_bytes, hashlib.sha256).hexdigest() # user_hash is "7eb04da5e..." ``` You can find more examples for other languages in this [Github Gist](https://gist.github.com/thewheat/7342c76ade46e7322c3e) user_cohort: title: User Cohort type: object additionalProperties: anyOf: - type: boolean - type: string description: > The user cohort you want to cold-start the recommendation with. For example, the following query will make recommendations based on the preferences of the users whose `country="United States"`, and `gender="Female"` in the User Profile dataset. ``` { "user_cohort": { "country": "United States", "gender": "Female" } } ``` rows: title: Rows type: integer description: Number of product recommendations to return default: 5 type: title: Type type: string description: > The type of products to return. Use this parameter to make the API return only a certain type of products (see [Product APIs](#operation/content_write_api_v1_products_post)). This is particularly useful for sites that have multiple types of products: For example, on a marketplace site, YOu may model *merchandise* and *store* as two types of *products*. You can then use type parameter to limit the recommendation or search results to return only one kind of them. For instance, the following query will return only *store* products: ``` {"type": "store"} ``` For another example, on a travel website, you might have: *hotel*, *thing to do*, and *restaurant*, three kinds of products. You can use `type` parameter to limit results to one kind of them. For instance, the following query will limit the results to only *hotels* product: ``` {"type": "hotel"} ``` dedupe_product_group_id: title: Dedupe Product Group Id type: boolean description: > Whether to dedupe product based on `product_group_id`. If `dedupe_product_group_id=true`, Miso will prevent products with the same `product_group_id` from showing multiple times in the search or recommendation results. This is particular useful when one product has multiple variants (for example, different sizes, colors, or materials), and you only want to show this product only once in the search or recommendation results. Miso will then return the variant that is most likely to be of the user's interest. default: true additional_interactions: title: Additional Interactions type: array items: anyOf: - $ref: '#/components/schemas/ProductDetailPageView' - $ref: '#/components/schemas/Search' - $ref: '#/components/schemas/AddToCart' - $ref: '#/components/schemas/RemoveFromCart' - $ref: '#/components/schemas/Checkout' - $ref: '#/components/schemas/Refund' - $ref: '#/components/schemas/Subscribe' - $ref: '#/components/schemas/Unsubscribe' - $ref: '#/components/schemas/AddToCollection' - $ref: '#/components/schemas/RemoveFromCollection' - $ref: '#/components/schemas/Read' - $ref: '#/components/schemas/Watch' - $ref: '#/components/schemas/Listen' - $ref: '#/components/schemas/Like' - $ref: '#/components/schemas/Dislike' - $ref: '#/components/schemas/Share' - $ref: '#/components/schemas/Rate' - $ref: '#/components/schemas/Bookmark' - $ref: '#/components/schemas/Complete' - $ref: '#/components/schemas/Feedback' - $ref: '#/components/schemas/Impression' - $ref: '#/components/schemas/ViewableImpression' - $ref: '#/components/schemas/Click' - $ref: '#/components/schemas/Submit' - $ref: '#/components/schemas/HomePageView' - $ref: '#/components/schemas/CategoryPageView' - $ref: '#/components/schemas/PromoPageView' - $ref: '#/components/schemas/ProductImageView' - $ref: '#/components/schemas/Custom' description: > A list of additional interaction records. You can use this fields to simulate user interactions without actually writing them to the interaction dataset. default: [] fl: title: Fl type: array items: type: string description: > List of fields to retrieve. For example, the following request retrieves only the `title` field of each product along with the `product_id`, which is always returned. ``` {"fl": ["title"]} ``` You can also match field names by using `*` as a wildcard. For example, the query below retrieves the `title` and any custom attributes under the `attributes` dictionary. ``` {"fl": ["title", "attributes.*"]} ``` The following retrieves all the available fields: ``` {"fl": ["*"]} ``` For the lowest latency, use an empty array to retrieve just the `product_id` field (which is the default). ``` {"fl": []} ``` default: [] exclude: title: Exclude type: array items: type: string description: >- An array of `product_ids` of products you want to *exclude* from search results. custom_context: title: Custom Context type: object description: > Dictionary of custom context variables for the current browsing session. You can specify context variables specific to your websites or apps in a `{"KEY":VALUE}` format, where `KEY` must be a string, and `VALUE` can be: * a `bool` * a `string` or an `array of string` * a `number` or an `array of numbers` * an `array of objects` * `null` In certain cases, Miso will take these variables into account when generating results. example: session_variable_1: - value_1 - value_2 boosting_tags: title: Boosting Tags type: array items: type: string description: > When `boosting_tags` is given, and there are pre-defined boost rules have the same tag(s), those boost rules will be matched, regardless if the criteria is met or not. Useful when want to force trigger specific boost campaign. default: [] example: - tag-1 - quetag-2 fq: title: Fq type: string description: > Defines a query in Solr syntax that can be used to restrict the superset of products to return, without influencing the overall ranking. `fq` can enable users to drill down to products with specific features based on different product attributes For example, the query below limits the search results to only show products whose size is either `M` or `S` and brand is `Nike`: ``` {"fq": "size:(\"M\" OR \"S\") AND brand:\"Nike\""} ``` You can use `fq` to apply filters against your custom attributes as well. For example, the query below limits the search results to only products whose `designer` attribute is `Calvin Klein` ``` {"fq": "attributes.designer:\"Calvin Klein\""} ``` `fq` can also limit search results by numerical range. For example, the following query limits the results to products that have `rating >= 4`. ``` {"fq": "rating:[4 TO *]"} ``` boost_fq: title: Boost Fq type: string description: > Defines a query in Solr syntax that can be used to boost a subset of products to the top of the ranking, or to specific *boost positions* (See `boost_positions` parameter below.) For example, the query below will promote all the relevant products whose brand is `Nike` to the top of recommendation list: ``` { "boost_fq": "brand:\"Nike\"" } ``` For a slightly more complex example, the query below will promote the Nike products which have also been tagged as `ON SALE` to the top of the ranking: ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"" } ``` It is worth mentioning that, Miso will only boost products that are relevant and have high likelihood to convert, and will not boost a low performance product only because it matches the boosting query. Depending on your boosting rules, in certain cases, you would like to prevent recommendation results from being too monotone due to boosting. With Miso, you have two tools to do so. First, you can specify `boost_positions` to place promoted products at specific positions in the ranking. For example, the query below will place boosted products only at the first and fourth places in the ranking (positions are 0-based), and place the remaining products in their original ranking, skipping these two positions. ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"", "boost_positions": [0, 3] } ``` The second tool is `diversification`. `diversification` parameter, on a best-effort basis, will try to maintain a minimum distance between products that have the same attributes. For example, the following query will place products made by the same brand apart from each other. ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"", "diversification": { "brand": {"minimum_distance": 1} } } ``` boost_positions: title: Boost Positions type: array items: type: integer description: > Defines a list of 0-based positions you want to place the boosted products at. For example, the query below will promote products whose brand is `Nike` as the top and second recommendations: ``` { "boost_fq": "brand:\"Nike\"", "boost_positions": [0, 1] } ``` If `boost_positions` is not specified (which is the default behavior), all the boosted products will be ranked higher than the rest of the products. boost_rule_name: title: Boost Rule Name type: string description: >- Name of the boosting rule. Use this to identify a boosting rule in _boosted_rules in the response boost_rules: title: Boost Rules type: array items: $ref: '#/components/schemas/BoostingFilterBase' description: > Define a list of boosting rules that will be applied to the search or recommendation results simultaneously. `boost_rules` parameter is particularly useful when you want to boost more than one sets of products, and promote each of them to different positions. For example, the query below will promote products whose brand is `Nike` to the top and second results, and products whose brand is `Adidas` to the third and fourth results: ``` { "boost_rules": [ { "boost_fq": "brand:\"Nike\"", "boost_positions": [0, 1] }, { "boost_fq": "brand:\"Adidas\"", "boost_positions": [2, 3] } ] } ``` default: [] geo: title: Geo allOf: - $ref: '#/components/schemas/GeoQuery' description: > When set, filter result to include only products within certain geographic range from given point will be returned, or to boost product within the same range. Product should have a field that holds the location of the product, `location` is used by default, but other field can also be used. Distance can be in miles or kilometers. If `distance_unit` is not set, `mile` will be used. For example, to limit results to products within 100 miles of New York city: ``` { "geo": { "filter": [{ "lat": 40.73061, "lon": -73.93524, "distance": 100 }] } } ``` To boost products within 2 kilometers around Alcatraz Island according to `loc` field: ``` { "geo": { "boost": [{ "field": "loc", "lat": 37.82667, "lon": -122.42278, "distance": 2, "distance_unit": "km" }] } } ``` diversification: title: Diversification type: object additionalProperties: $ref: '#/components/schemas/DiversifyField' description: > Defines diversification rules to prevent products with the same attributes (e.g. sneakers made by the same brand or books from the same authors) from showing up too close to each other in the results. For instance, customers who have purchased many of sneakers from Nike may happen to have recommendations or search results where all top-5 entries are sneakers made by Nike. Purely considering accuracy, these recommendations appear excellent since the user clearly appreciates Nike sneakers. However, such results might be considered too "plain" by the user, owing to its lack of diversity. `diversification` parameter allows you to avoid this problem by enforcing a desired *minimum distance* between products. For example, consider a list of four products whose `brand` are *Nike, Nike, Adidas,* and *PUMA* respectively. The query below will make sure there are at least one different product between two Nike products, e.g. the diversified ranking may become *Nike, Adidas, Nike,* and *PUMA* : ``` { "diversification": {"brand": {"minimum_distance": 1}} } ``` You can also increase the minimum_distance to place products further apart. For example, the following query will make sure, for the two Nike products, there are at least *two* other products between them. As a result, the diversified ranking may become *Nike, Adidas, PUMA*, and *Nike*.: ``` { "diversification": {"brand": {"minimum_distance": 2}} } ``` The diversification algorithm reranks the products on a best-effort basis. For example, for the product list described earlier, it is not possible to place two Nike product three places apart from each other. Therefore, the diversified ranking will still remain *Nike, Adidas, PUMA,* and Nike* even if we set `minimum_distance=3`. dithering: title: Dithering minimum: 1 type: number description: > Dithering is an optional parameter (>= 1.0, and typically <= 5.0) in the recommendation APIs that introduces randomness to the order of recommended items. By adding noise to the original ranking, it shuffles the list, surfacing lower-ranked items to enhance list freshness and potentially boost user engagement. However, excessive dithering may reduce the accuracy of item ordering. See [this blog post](https://buildingrecommenders.wordpress.com/2015/11/11/dithering/) for more information. default: 1 pagination_id: title: Pagination Id maxLength: 512 type: string description: > A unique identifier to enable pagination in Recommendation APIs. By default, Recommendation APIs do not support pagination because the results from Miso, by its natural, will change in real-time with new user interactions. `pagination_id` allows you to implement pagination more easily by memorize what products we have returned to the current user with the same `pagination_id`. To enable pagination, you generate a `pagination_id` and set it in the first and subsequent requests in the same browsing session where you want to enable pagination. With `pagination_id` set, you can access recommendations in different pages using the combination of `start` and `rows` parameters, and Miso will ensure that no duplicated recommendation will be returned in different pages. For example, assuming you are implementing an infinite scroll with Miso Recommendation APIs. Before you make the first request, you generate a `pagination_id` using the `current datetime` or `uuid` like the following: ```javascript // current datetime var my_pagination_id = Date.now().toString() // OR uuid const uuidv4 = require("uuid/v4") var my_pagination_id = uuidv4() ``` You can then request the first page of results with `my_pagination_id` like the following: ```javascript { "pagination_id": my_pagination_id, "start": 0, "rows": 10 } ``` Then, you can request the next page of results with the same `my_pagination_id`, and Miso will ensure that no duplicated result is returned: ```javascript { "pagination_id": my_pagination_id, "start": 10, "rows": 10 } ``` Note that, a `pagination_id` will timeout if there is no further request associated with it for 30 minutes. Also, `pagination_id` is scoped by individual users: i.e. different users' results will not be affected even if they use the same `pagination_id`. start: title: Start type: integer description: > The start of the page you want to access. Combine this with `rows` to implement pagination. You can only set it when `pagination_id` is given. default: 0 additionalProperties: false description: Attributes for recommendation boosting ProductToProductsResponse: title: ProductToProductsResponse required: - data type: object properties: message: title: Message type: string default: success data: $ref: '#/components/schemas/ProductToProductsResponseBody' HTTPValidationError: title: HTTPValidationError type: object properties: detail: title: Detail type: array items: $ref: '#/components/schemas/ValidationError' ProductDetailPageView: title: product_detail_page_view required: - type type: object properties: type: title: Type enum: - product_detail_page_view type: string description: >- Used when a user views the detail page of a product. Viewing a product detail page usually indicates a user is interested in the product to certain degree, especially, when the `duration` of the page view is long. When `duration` of the page view is very short (< 5 seconds), `product_detail_page_view` may indicate neural or negative interest in the product. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Search: title: search required: - type type: object properties: type: title: Type enum: - search type: string description: > Used to record a search event with the keywords and filters the user used. What a user searches for is a very powerful signal about their interests and what they will eventually buy or consume, so it is important to capture this information with high fidelity. user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` search: title: Search allOf: - $ref: '#/components/schemas/SearchInformation' description: > The search keywords and filters the user uses. This is only required by `search` interaction. additionalProperties: false AddToCart: title: add_to_cart required: - type type: object properties: type: title: Type enum: - add_to_cart type: string description: > Used when a user adds a product into their shopping cart. This is a strong positive signal of the user's interest in the product, and may eventually lead to a purchase. quantities: title: Quantities anyOf: - type: array items: type: number - type: number description: > The quantities of products the user adds to their cart or checks out with. This field should be a list of positive values. Specifically, if `product_ids` is a list of N products, the `quantities` needs to be a list with N numbers as well. If `quantities` are not specified, we will assume the quantity to be 1 for every product. Example: ``` {"quantities": [1, 2]} ``` example: - 1 - 2 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false RemoveFromCart: title: remove_from_cart required: - type type: object properties: type: title: Type enum: - remove_from_cart type: string description: | Used when a user removes a product from their shopping cart. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Checkout: title: checkout required: - type type: object properties: type: title: Type enum: - checkout type: string description: > Used when a user enters checks out with a set of products. For an eCommerce site, this is the strongest signal of the user's interest and has a high probability of leading to an eventual purchase. revenue: title: Revenue type: number description: > Total revenue associated with the checkout. The revenue should include generally shipping, tax, etc. that you want to include as part of your revenue calculations. example: 23.32 quantities: title: Quantities anyOf: - type: array items: type: number - type: number description: > The quantities of products the user adds to their cart or checks out with. This field should be a list of positive values. Specifically, if `product_ids` is a list of N products, the `quantities` needs to be a list with N numbers as well. If `quantities` are not specified, we will assume the quantity to be 1 for every product. Example: ``` {"quantities": [1, 2]} ``` example: - 1 - 2 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Refund: title: refund required: - type type: object properties: type: title: Type enum: - refund type: string description: | Used when a user requests a refund of products they bought. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Subscribe: title: subscribe required: - type type: object properties: type: title: Type enum: - subscribe type: string description: > Used when a user subscribes a product, for example to receive alerts when the product comes back in stock or if the price drops. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Unsubscribe: title: unsubscribe required: - type type: object properties: type: title: Type enum: - unsubscribe type: string description: > Used when a user unsubscribes a product, for example to stop receiving alerts when the product comes back in stock or if the price drops. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false AddToCollection: title: add_to_collection required: - type type: object properties: type: title: Type enum: - add_to_collection type: string description: > Used when a user adds a product to their personal collection. This is a strong signal of their interest in the product. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false RemoveFromCollection: title: remove_from_collection required: - type type: object properties: type: title: Type enum: - remove_from_collection type: string description: | Used when a user removes a product from their personal collection. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Read: title: read required: - type type: object properties: type: title: Type enum: - read type: string description: > Used to record when and for how long a user reads a piece of written content. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Watch: title: watch required: - type type: object properties: type: title: Type enum: - watch type: string description: > Used to record when and for how long a user watches content that is of a video format. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Listen: title: listen required: - type type: object properties: type: title: Type enum: - listen type: string description: > Used to record when and for how long a user listens to content that is of an audio format. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Like: title: like required: - type type: object properties: type: title: Type enum: - like type: string description: | Used to record when a user indicates a `like` for a product. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Dislike: title: dislike required: - type type: object properties: type: title: Type enum: - dislike type: string description: > Used when a user indicates a `dislike` for a product or indicates they would like to not be recommended content or products like this in the future. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Share: title: share required: - type type: object properties: type: title: Type enum: - share type: string description: | Used when a user shares a product or piece of content. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Rate: title: rate required: - type type: object properties: type: title: Type enum: - rate type: string description: | Used when a user gives a rating to a product or piece of content. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` rating: title: Rating type: number description: > The rating the user gave in the range of [0, 5]. This field is only required by the `rate` interaction. As a convention in the RecSys community, a rating >= 3.5 is considered positive, a rating <= 2 is negative, and otherwise a rating is neutral. If you use any other rating scale, please normalize it to a [0, 5] scale. example: 5 additionalProperties: false Bookmark: title: bookmark required: - type type: object properties: type: title: Type enum: - bookmark type: string description: | Used when a user bookmarks a product. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Complete: title: complete required: - type type: object properties: type: title: Type enum: - complete type: string description: > Used when a user "complete" a product (e.g. complete a course or a video). product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Feedback: title: feedback required: - type type: object properties: type: title: Type enum: - feedback type: string description: | Used when a user sends feedback on provided results. question_id: title: Question Id maxLength: 512 type: string description: > A unique identifier representing the specific question for which feedback is being provided. example: question_123 result_type: title: Result Type type: string description: > Indicates the type of result the provided feedback is associated with, e.g., an answer or a suggestion. example: answer value: title: Value type: string description: > Specifies the user's perspective on the provided result, with possible values being helpful, not helpful, or unselected if the user has not provided any feedback. example: helpful user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Impression: title: impression required: - type type: object properties: type: title: Type enum: - impression type: string description: >- Used to record when a user saw or was presented with a product or content asset. An impression does not mean a user is interested: for example, if there is an impression for a certain product, but no further interaction occurs with that product, we assume the user is probably not interested in it. For an impression that was generated by Miso's search results or recommendations results, it is important to include the `miso_id` associated with the results so that we know the impression is from Miso product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false ViewableImpression: title: viewable_impression required: - type type: object properties: type: title: Type enum: - viewable_impression type: string description: > When a product or content asset is presented to the user, it is not guarantee that the user will see it. An viewable impression is an impression that is "viewable" by the user. Usually, content asset is considered viewable if more than 50% of its area is visible on screen. You can also use different definition for what is considered viewable. Miso will automatically find the best recommendation as long as the difference between viewable and non-viewable impression is consistant. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Click: title: click required: - type type: object properties: type: title: Type enum: - click type: string description: > Used when user clicked on something, and does not belong to any other interaction type. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Submit: title: submit required: - type type: object properties: type: title: Type enum: - submit type: string description: | Used when a user submits a form or a survey. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false HomePageView: title: home_page_view required: - type type: object properties: type: title: Type enum: - home_page_view type: string description: | Used when a user views your home page. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false CategoryPageView: title: category_page_view required: - type type: object properties: type: title: Type enum: - category_page_view type: string description: > Used when a user views a category page for a specific “family” or “group” or products or content. This is a strong indicator of what types category of products or content the user is interested in. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` category: title: Category type: array items: type: string description: > Categories usually fall in a hierarchy, such as *Home & Garden > Kitchen & Dining > Kitchen Tools & Utensils > Sushi Mats* Use this field to specify the full hierarchical list describing the category the user is viewing. The levels should be listed from broad to narrow: `["TOP_LEVEL_CATEGORY", "SUBCATEGORY_1", "SUBCATEGORY_2", ...]`. This field is only used by the category_page_view interaction type, but this data is very useful for determining the user’s interests. Example: ``` [ "Home & Garden", // TOP_LEVEL_CATEGORY "Kitchen & Dining", // SUBCATEGORY_1 "Kitchen Tools & Utensils", // SUBCATEGORY_2 "Sushi Mats" // SUBCATEGORY_3 ] ``` additionalProperties: false PromoPageView: title: promo_page_view required: - type type: object properties: type: title: Type enum: - promo_page_view type: string description: > Used when a user views a specific promotional or curated marketing page about certain products or content. duration: title: Duration type: number description: > How long (in seconds) the user stayed on this page, or consumed (listened, read, or watched) a product. This field is optional, but it's very important in scenarios where consumption duration matters, including `product_detail_page_view`, `category_page_view`, `watch`, `listen`, and `read`. For example, if a user only views or consumes a product for less than 5 seconds, that user is probably not interested in the product. On the other hand, if a user stays on a page for a while, it usually means they are seriously engaging with or considering the product. When `duration` is absent, we will use the timestamp of the next interaction to infer a rough duration value. Example: ``` {"duration": 61.5} ``` example: 61.5 product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false ProductImageView: title: product_image_view required: - type type: object properties: type: title: Type enum: - product_image_view type: string description: > Used when a user views the image of a product (e.g. to enlarge a product photo). product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` additionalProperties: false Custom: title: custom required: - type - custom_action_name type: object properties: type: title: Type enum: - custom type: string description: > Used when you want to record any other kinds of interactions between users and products. product_ids: title: Product Ids type: array items: type: string maxLength: 512 description: > Products or content the user is interacting with. This field is required by almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso. Therefore, it is important to keep this consistent between the two datasets. Example: ``` {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]} ``` default: [] example: - 123ABC-BLACK product_group_ids: title: Product Group Ids type: array items: type: string maxLength: 512 description: > The product groups the user is interacting with. You only need this field if you model product variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a user is interacting with a *product group* rather than a specific product variant, for example, when the user is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or color (i.e. a product variant) yet. In such situations, the `product_id` is not applicable because we only know the user is interested in this T-shirt (a product group), but don't know which particular product variant the user is interested in. Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`. In the situations where specific `product_ids` are available, for example, when user selected a particular size of the T-Shirt, use `product_ids` instead. Example: ``` {"product_group_ids": ["123ABC"]} ``` example: - 123ABC user_id: title: User Id maxLength: 512 type: string description: >- Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have not signed in, see `anonymous_id`. example: user_1234 anonymous_id: title: Anonymous Id maxLength: 1024 type: string description: >- A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id` is not given, we will default it to `SHA1(:::)`. When a visitor signs in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id` along with the past interactions associated with it. example: 86D51273AD8BF84217E1567B6CBE7152D7034404 timestamp: title: Timestamp type: string description: > The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we will default to the server's time. If you're importing data from the past, make sure you provide a timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution. Example: ``` {"timestamp": "2018-11-07T00:25:00.073876Z"} ``` format: date-time miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance, as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid example: 123e4567-e89b-12d3-a456-426614174000 context: title: Context allOf: - $ref: '#/components/schemas/WebBasedContext' description: > Dictionary of extra information that provides useful context about an interaction. We use context information to make recommendations tailored not only for each user, but also for their current browsing context. For example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile phone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very different interests than a user who visits your site directly. Context information is also useful for personalization for entirely new visitors, as we can immediately personalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through). Example: ``` {"context": { "campaign": { "name": "spring_sale", "source": "Google", "medium": "cpc", "term": "running+shoes", "content": "textlink" }, "truncated_ip": "1.1.1.0", "locale": "en-US", "region": "US East", "page": { "url": "https://example.com/miso-tshirt-123ABC", "referrer": "https://example.com/", "title": "My Product Page" }, "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)" }, "custom_context": { "other_context_var_1": "value_1", "other_context_var_2": "value_2" } } ``` custom_action_name: title: Custom Action Name type: string description: | The name of the custom interaction that you have defined. additionalProperties: false BoostingFilterBase: title: BoostingFilterBase type: object properties: boost_fq: title: Boost Fq type: string description: > Defines a query in Solr syntax that can be used to boost a subset of products to the top of the ranking, or to specific *boost positions* (See `boost_positions` parameter below.) For example, the query below will promote all the relevant products whose brand is `Nike` to the top of recommendation list: ``` { "boost_fq": "brand:\"Nike\"" } ``` For a slightly more complex example, the query below will promote the Nike products which have also been tagged as `ON SALE` to the top of the ranking: ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"" } ``` It is worth mentioning that, Miso will only boost products that are relevant and have high likelihood to convert, and will not boost a low performance product only because it matches the boosting query. Depending on your boosting rules, in certain cases, you would like to prevent recommendation results from being too monotone due to boosting. With Miso, you have two tools to do so. First, you can specify `boost_positions` to place promoted products at specific positions in the ranking. For example, the query below will place boosted products only at the first and fourth places in the ranking (positions are 0-based), and place the remaining products in their original ranking, skipping these two positions. ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"", "boost_positions": [0, 3] } ``` The second tool is `diversification`. `diversification` parameter, on a best-effort basis, will try to maintain a minimum distance between products that have the same attributes. For example, the following query will place products made by the same brand apart from each other. ``` { "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"", "diversification": { "brand": {"minimum_distance": 1} } } ``` boost_positions: title: Boost Positions type: array items: type: integer description: > Defines a list of 0-based positions you want to place the boosted products at. For example, the query below will promote products whose brand is `Nike` as the top and second recommendations: ``` { "boost_fq": "brand:\"Nike\"", "boost_positions": [0, 1] } ``` If `boost_positions` is not specified (which is the default behavior), all the boosted products will be ranked higher than the rest of the products. boost_rule_name: title: Boost Rule Name type: string description: >- Name of the boosting rule. Use this to identify a boosting rule in _boosted_rules in the response GeoQuery: title: GeoQuery type: object properties: filter: title: Filter type: array items: $ref: '#/components/schemas/GeoDistanceQuery' description: >- When set, filter result to include only products within certain geographic range from given point. default: [] boost: title: Boost type: array items: $ref: '#/components/schemas/GeoDistanceQueryBoost' description: >- When set, boost products within certain geographic range from given point. default: [] DiversifyField: title: DiversifyField type: object properties: minimum_distance: title: Minimum Distance type: integer description: Minimum distance between two products that have the same value default: 1 always_together: title: Always Together type: boolean description: >- If always_together=true, all the products that have the same value for this field, will be put side-by-side. default: false ProductToProductsResponseBody: title: ProductToProductsResponseBody required: - products type: object properties: took: title: Took type: integer description: Number of milliseconds Miso took to retrieve the results. default: 0 miso_id: title: Miso Id type: string description: > Miso-generated unique Id for each recommendation or search result. Maintaining this Id for subsequent page views is important to Miso's performance as we use `miso_id` to track and fine-tune the performance of personalization and search results. When a user clicks on a recommendation or search result, you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`, `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn't. Example: ``` {"misoId": "123e4567-e89b-12d3-a456-426614174000"} ``` format: uuid default: 00000000-0000-0000-0000-000000000000 example: 123e4567-e89b-12d3-a456-426614174000 products: title: Products type: array items: $ref: '#/components/schemas/Record' description: Product recommendation results. ValidationError: title: ValidationError required: - loc - msg - type type: object properties: loc: title: Location type: array items: type: string msg: title: Message type: string type: title: Error Type type: string WebBasedContext: title: WebBasedContext type: object properties: campaign: title: Campaign allOf: - $ref: '#/components/schemas/Campaign' description: > The campaign that resulted in the interaction. Campaign dictionary contains standard UTM parameters: `name`, `source`, `medium`, `term`, `content`. We use campaign information to infer users' interests and fine-tune the personalization and search results based on the current user's campaign information. truncated_ip: title: Truncated Ip type: string description: > User's truncated IP address. We use IP address to determine the country of the users. format: ipv4 example: 1.1.1.0 locale: title: Locale type: string description: Locale string of the current session, for example en-US. example: en-US region: title: Region type: string description: > The region/location of the site the user is visiting. This is for sites that serve different regions or markets. You can define your own region keywords, for example, `US East`, `Europe`, `LATM`, etc. example: US East page: title: Page allOf: - $ref: '#/components/schemas/Page' description: >- The current page in the browser. Page dictionary containing referrer, title and url. we will use page view as a pseudo interaction to infer users' interest. user_agent: title: User Agent type: string description: > User agent of the device making the request. We use this to determine if a user is browsing the site on mobile or desktop, and tailor the recommendations and search results accordingly. Example: ``` {"user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0"} ``` example: >- Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0 custom_context: title: Custom Context type: object additionalProperties: anyOf: - type: boolean - type: integer - type: number - type: string - type: array items: type: number - type: array items: type: string - type: array items: type: object additionalProperties: anyOf: - type: string - type: number - type: integer - type: boolean description: > Dictionary of custom context variables for the current browsing session. You can specify context variables specific to your websites or apps in a `{"KEY":VALUE}` format, where `KEY` must be a string, and `VALUE` can be: * a `bool` * a `string` or an `array of string` * a `number` or an `array of numbers` * an `array of objects` * `null` Miso will take these variables into account when generating recommendations. example: session_variable_1: - value_1 - value_2 SearchInformation: title: SearchInformation type: object properties: keywords: title: Keywords type: string description: > The search keywords user use. Search keywords are strong signals to users' interests. default: '' filters: title: Filters type: object additionalProperties: type: array items: type: string description: > Dictionary of filters users apply to the search results in the following format: `{"FIELD": ["SELECTION_1", "SELECTION_2"]}`. GeoDistanceQuery: title: GeoDistanceQuery required: - lat - lon - distance type: object properties: lat: title: Lat maximum: 90 minimum: -90 type: number description: Latitude of the center point, should between 90 and -90 lon: title: Lon maximum: 180 minimum: -180 type: number description: Longitude of the center point, should between 180 and -180 field: title: Field type: string description: >- Name of the field in product data that holds geographic coordinate. Defaults to `location` default: location distance: title: Distance type: number description: >- Distance to center point, in kilometer or mile (according to `distance_unit`) distance_unit: title: Distance Unit enum: - km - mile description: Unit of distance(`km` or `mile`). Defaults to `mile` default: mile GeoDistanceQueryBoost: title: GeoDistanceQueryBoost required: - lat - lon - distance type: object properties: lat: title: Lat maximum: 90 minimum: -90 type: number description: Latitude of the center point, should between 90 and -90 lon: title: Lon maximum: 180 minimum: -180 type: number description: Longitude of the center point, should between 180 and -180 field: title: Field type: string description: >- Name of the field in product data that holds geographic coordinate. Defaults to `location` default: location distance: title: Distance type: number description: >- Distance to center point, in kilometer or mile (according to `distance_unit`) distance_unit: title: Distance Unit enum: - km - mile description: Unit of distance(`km` or `mile`). Defaults to `mile` default: mile boost_positions: title: Boost Positions type: array items: type: integer description: |2- Defines a list of 0-based positions you want to place the boosted products at. If `boost_positions` is not specified (which is the default behavior), all the boosted products will be ranked higher than the rest of the products. Record: title: Record required: - product_id type: object properties: product_id: title: Product Id maxLength: 512 type: string description: |2- The unique identifier for the product. example: 123ABC-S-Black Campaign: title: Campaign type: object properties: name: title: Name type: string description: >- Name of the campaign. Identifies a specific product promotion or strategic campaign. (see [UTM parameters](https://en.wikipedia.org/wiki/UTM_parameters)) example: spring_sale source: title: Source type: string description: >- Source of the campaign. Identifies which site sent the traffic. (see [UTM parameters](https://en.wikipedia.org/wiki/UTM_parameters)) example: Google medium: title: Medium type: string description: >- Medium of the campaign that identifies what type of link was used, such as cost per click or email. (see [UTM parameters](https://en.wikipedia.org/wiki/UTM_parameters)) example: cpc term: title: Term type: string description: >- Term of the campaign that identifies search terms. (see [UTM parameters](https://en.wikipedia.org/wiki/UTM_parameters)) example: running+shoes content: title: Content type: string description: >- Content of the campaign that identifies what specifically was clicked to bring the user to the site, such as a banner ad or a text link. It is often used for A/B testing and content-targeted ads. Identifies search terms. (see [UTM parameters](https://en.wikipedia.org/wiki/UTM_parameters)) example: textlink Page: title: Page required: - url type: object properties: url: title: Url type: string description: Url of the page example: https://example.com/miso-tshirt-123ABC referrer: title: Referrer type: string description: Url of the referrer page example: https://example.com/ title: title: Title type: string description: Title of the page example: My Product Page securitySchemes: Secret API Key: type: apiKey description: >+ Your secret API key is used to access every Miso API endpoint. You should secure this key and only use it on a backend server. Never leave this key in your client-side JavaScript code. If the private key is compromised, you can revoke it in [Dojo](https://dojo.askmiso.com/docs/api-browser) and get a new one. Specify your secret key in the `api_key` query parameter. For example: ``` POST /v1/users?api_key=039c501ac8dfcac91c6f05601cee876e1cc07e17 ``` in: query name: api_key ````