Product recommendation algorithms are specifically designed for various pages and scenarios, with a variety of algorithms for the homepage, product pages, cart page, and more.

Recommended for you

This machine learning-based algorithm uses the totality of user data to find patterns in how users of various types interacted with all of the items in your catalog.

Frequently bought together:

Recommend cross-sale items that were bought together often with the product they’re currently viewing, have in their cart, or have recently purchased.

Show those who viewed this also viewed/bought:

Suggesting the right alternatives, based on similarity or crowd data, will increase the number of products viewed and time spent in a convenient shopping flow.

Those who bought from this category also bought:

Recommend items frequently bought from other categories by customers who bought from the category they are viewing or just purchased from.

New in stock

Help customers stay up-to-date on items that are new on your shelves, with the option to fine-tune for items added to the site in the last 7 days, before the last visior, or based on visitor’s interests.

View it again/buy it again

Show the items they recently viewed or bought, so they can pick up where they left, or items they bought in the past so they can easily resupply.

Further, fine-tune your recommendations with filters: