You May Also Like

You May Also Like is one of the most common, successful recommendation models out there. It takes the product the user is interacting with and suggests related products that they might also be interested in.

Example for You May Also Like

Introduction

You May Also Like is the most popular product recommendation model on the web today. Almost all major eCommerce sites and marketplaces have a "You May Also Like" or "Related Products" ribbon toward the end of their product details page (PDP), showcasing other products for the user to consider. These are usually similar to the product in the PDP, and serve as a way to continue engaging the user in case the current item is not exactly what they're looking for.

With Miso, you can generate You May Also Like recommendations using the Product to Products API. By passing in the anchor product and user session id, you will receive a list of recommendations for related products that are also personalized. Miso's engines automatically figure out which items are likely to drive conversions for the user. Additional input parameters can be used to tune these recommendations, for example to increase the diversity or boost certain results to the top.

You May Also Like is in many ways the foundation for all kinds of product recommendations that you can build with Miso. Recipes like Frequently Bought Together and Cart Upsells use the same Product to Products API , with some slight differences.

Before You Start

API Call / JSON Response

To fetch your You May Also Like recommendations, POST to the Product to Products API with the following minimum parameters:

  • user_id: The user or anonymous visitor to personalize the recommendations for
  • product_id: The anchor product

The API will return a list of recommended products.

Don't forget: there are many parameters you can use to optimize and filter the results that Miso returns, such as fl , fq , boost_fq , and diversification .
Read more in the deep dive

Example API Call

POST /v1/recommendation/product_to_products?api_key=<API_KEY> HTTP/1.1
{
    "user_id": "user-123",
    "product_id": "air-jordan-1-retro-high-85",
    "fl": ["title", "price"]
}

Example JSON Response

{
    "message": "success",
    "data": {
        "took": 56,
        "miso_id": "f98b1904-ddce-11eb-be53-fa1729b23183",
        "products": [
            {
                "product_id": "air-jordan-1-retro-high",
                "title": "Air Jordan 1 Retro High OG BG",
                "price": 129,
                ..., // Additional scoring information
            },
            {
                "product_id": "air-jordan-1-mid-smoke",
                "title": "Air Jordan 1 Mid 'Smoke Grey'",
                "price": 216,
                ..., /// Additional scoring information
            },
            ...
        ]
    }
}

Read more about the scoring information that Miso returns in the API response.

Before You Launch

Using this API recipe as a starting point, test API calls to your engine in development
If you haven't already, build pipelines to stream your real-time data updates to Miso via API. Your Miso solutions engineer is here to help with the integration.
Start using this API recipe to power the UX on your site in staging. If you need UX recommendations, ask your Miso solutions engineer about Bento .
Run an A/B test with Miso on simulated website traffic. If desired, your Miso solutions engineer can perform this test and provide a report.
If this is your first time launching with Miso, ask your Miso solutions engineer to unlock your production environment.
Replicate your Data and Engine API calls on production and set up the same engine in your production environment in Dojo.
Review your data and engine performance in Dojo.
Turn on this recipe for a percentage of your users and scale up to a full rollout. Notify your Miso solutions engineer who will monitor the launch metrics.

API Reference

💻

Need more info on the API? Check out our dedicated API page with all the info you could ever want.

Read API Reference
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