The heart of the recommendations: the engine
Our exceptional machine learning algorithms recommend the most relevant products to your customers, based on their behaviour.
Entreprise-grade AI in your online store
Our recommendation engine has been developed for nearly 15 years and has remained unbeaten in over 40 A/B tests.
Whether it's the easy-to-install product recommendation boxes, the beta test of our personalized search engine, or an individually developed email recommendation, everything is served by the same engine.
Measurable business impact
Thanks to the 10-13% revenue growth on average, we build long-term partnerships with our clients. The effectiveness of our recommendations can be viewed with our analytics. We cover many different counters.
Read more about our results below:
The Yuspify recommendations are based on the most recent data.
Even the last click actively changes the list of products selected by the personalization engine.
New recommendations at every pageload
When your users load a new page, your webshop sends a request to the Yuspify engine. The engine calculates a product recommendation in milliseconds - based on the users' browsing history and location - then displays it on your webshop.
Business logics we use
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Displays personalized product recommendations to the user based on past behavior patterns.
Shows the most viewed products from the recent period.
Displays the products that have been added to the catalogue recently, in the past 1-3 weeks.
Others also liked
Recommends products that are often viewed or purchased together with the current product(s) by other users.
Frequently bought together
Offers products frequently pruchased together or complementary tot he selected product(s).
Often bought by you
Shows products that the user has previously purchased and are usually worth purchasing multiple times.
You may also like
Displays products that are often viewed or purchased together with the current product(s).
Recommends similar, but more expensive products.
Recommends the most purchased products from the recent period.
Want to know more?
Learn more about persionalized recommendations or request a callback from our experts.