Cart Upsells

With Miso, you can offer upsells on the cart page right before the user goes through the checkout flow. These recommendations are usually related to the existing items in the cart, and often suggested as a replacement with a higher price to increase your average order value.

Example for Cart Upsells

Introduction

Before a user goes through checkout, Cart Upsells are the "last chance" to suggest items that may result in a more valuable conversion for your site. Typically, upsells are displayed directly on the cart page itself, or in a popup right before the user enters the checkout flow. They are often accompanied by UX strategies like discounting and urgency.

You can trigger Cart Upsells using the Filter Query parameter fq with the Product to Products API. This parameter is used to filter the recommendations that Miso returns. (For more on filtering and optimization, see our Deep Dive guide.) The Cart Upsells recipe is quite flexible. You can pass in a single product to get a laser-targeted upsell, or generate upsells across the entire cart. You can also narrow down your recommendations using product categories or other attributes. As always, upsells are personalized to the individual user and their real-time interactions on your site.

To fully optimize your checkout user journey, you may want to consider using the companion Cart Cross-Sells recipe to generate broader recommendations that go along with the items in the cart.

Before You Start

API Call / JSON Response

To fetch Cart Upsell recommendations, POST to the Product to Products API with the following parameters:

  • user_id: The user or anonymous visitor to personalize the recommendations for
  • product_ids: The set of products in the cart for which you want to generate upsells. (Note that it's also possible to generate an upsell for a single product_id )
  • fq: Use the Filter Query parameter to return results above a certain price and (optionally) matching other attributes like categories or brand. This filtering is what differentiates the Cart Upsell API recipe from the more generic You May Also Like recipe.

The API will return a list of recommended products that match the Filter Query.

Don't forget: there are many more parameters you can use to optimize and filter the results that Miso returns, such as 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_ids": ["breyers-reese-pint", "digiorno-frozen-pizza"],
    "fq": "categories:\\\"Ice Cream\\\" AND price > 4.99"
}

Example JSON Response

{
    "message": "success",
    "data": {
        "took": 81,
        "miso_id": "a4606bf0-ddd3-11eb-ba80-0242ac130004",
        "products": [
            {
                "product_id": "ben-jerry-ice-cream",
                "title": "Ben & Jerry Half Baked Ice Cream",
                "price": 5.99,
                ..., // Additional scoring information
            },
            {
                "product_id": "breyers-extra-creamy-vanilla",
                "title": "Breyers Extra Creamy Vanilla",
                "price": 7.99,
                ..., // 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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