In Fashion:
When a shopper views a pair of pants, “You May Also Like” surfaces similar styles, cuts, and colors—other pants and complementary pieces that match their taste, keeping them exploring your catalog.
Recommendation Algorithms
You May Also Like — Recommendation Algorithm
The "You May Also Like" algorithm surfaces products similar to the one a visitor is viewing—based on attributes, behavior, and what similar shoppers explored—keeping people browsing and lifting product discovery.
Start Free TrialYou May Also Like — Industry Examples
In Toys:
A shopper viewing one toy sees similar toys—same age range, franchise, or play category—so they can compare alternatives and find the perfect match without leaving the page.
In Electronics:
A customer viewing a tablet sees similar models and comparable devices at different price points, helping them weigh options and find the right fit faster.
In Travel:
When a traveler views one destination or hotel, “You May Also Like” surfaces comparable stays and trips that match their budget and style, keeping them inspired.
In this story
How “You May Also Like” recommendations work across your store.
This algorithm surfaces products similar to the one a visitor is viewing — based on attributes, behavior, and what similar shoppers explored — across product pages, listing pages, follow-up emails, and on-site sliders.
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You May Also Like…
This e-commerce recommendation algorithm surfaces products similar to the item being viewed — by attributes, category, and the behavior of similar shoppers — deepening product discovery and time on site.
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Product Listing Page “You May Also Like” Recommendations
Use this algorithm to display similar-product recommendations with Product Bundling on category or listing pages for each visitor. Learn more about Personyze’s recommendation engine algorithms for e-commerce.
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“You May Also Like” on Product Pages
ElectronicsWebsite example
FashionWebsite example
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“You May Also Like” 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.
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Similar Items 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.
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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.
Leverage the power of
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.