Customers Who Bought This Item Also Bought… Recommendation Algorithm
This ecommerce recommendation algorithm shows items frequently purchased together by customers who also bought the item being viewed—boosting cross-sales and overall revenue.
Start Free TrialFrequently Bought Together — Industry Examples
In Fashion:
When a customer is viewing a pair of pants, the products frequently bought together with it may be shoes or tops which go together with the item, because people are likely to have bought things that match aesthetically.
In Toys:
Items frequently bought together with the toy currently being viewed are likely to be those that belong to the same set, or that are popular among those with the same preferences.
In Electronics:
A customer viewing a tablet may see frequently bought together recommendations for cases, screen protectors, or other accessories that are popular for that particular tablet.
In Travel:
When a customer is viewing a flight the algorithm can show them travel insurance packages and hotels which were frequently bought with that flight.
How cross-sale recommendations work across your store.
This algorithm shows items frequently bought together by customers who also bought the current item — across product pages, listing pages, follow-up emails, transactional emails, and on-site sliders.
Customers Who Bought This Item Also Bought…
This e-commerce recommendation algorithm shows items frequently purchased together by customers who also bought the item being viewed — boosting cross-sales and overall revenue.
Product Listing Page Cross-Sale Recommendations
Use this algorithm to display cross-sale product recommendations with Product Bundling on category or listing pages for each visitor. Learn more about Personyze’s recommendation engine algorithms for e-commerce.
Cross-Sale Recommendations on Product Pages
ElectronicsWebsite example
FashionWebsite example
Cross-Sale Recommendations in Follow-Up Emails
When a visitor has recently purchased an item, you can follow up with an email containing cross-sale recommendations — items that other customers frequently bought together with that product. This encourages return visits and repeat purchases.
Example: an email sent two hours after purchase shows complementary products. Learn more about automated, personalized, and targeted emails.
Cross-Sale Recommendations in Transactional Emails
Cross-sale recommendations can be added to any transactional message such as purchase confirmations, verification emails, or existing templates — without coding or IT integration. Learn more about adding email recommendations to transactional campaigns.
Cross-Sale Slider on Mobile & Desktop
A responsive cross-sale slider showcases items that were frequently bought by customers who also bought the current item.
MobileScreen
DesktopScreen
Demo — “Customers Who Bought This Item Also Bought” cross-sale algorithm examples across product pages and emails.
An AI-powered recommendation & personalization engine.
Harness AI to show each visitor exactly what they are most likely to be interested in. Choose from algorithms for anonymous visitors on the homepage, “buy-it-together” on product pages, algorithms specifically for emails, items on sale from the visitor’s wishlist, or “Buy It Again” for repeat purchases. Build strategies that perform best for your store.