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Product recommendations

Engage's Product Recommendation engine looks at all historical purchases and identifies how products relate to each other through the behavior of your customers. Once the AI engine learns your customers' purchase and return behavior, it can use their favorite product categories, favorite brands, viewed relevant products online, and abandoned carts to present them with personalized product recommendations.

For an introduction to product recommendations in Engage, check out this article.

Prerequisites for product recommendations

To get started with the recommendation engine, your Engage environment (tenant) needs to have these features activated:

  • Product feed (Only products that exists in this feed can be recommended)

  • A BI-export to the Engage BI-lake

Getting product recommendations

There is an API endpoint to do this. You'll need the contact's unique contact ID.

GET /api/v2/contacts/{contactId}/productrecommendations

The response will be something like this:


If the request has not been successful, you'll get one of the following HTTP error codes:

  • 400 - InvalidContactId

  • 404 - ContactNotFound