Explainer graphic - how the Yusp recommendation engine gathers information on the visitors of your site.

Gather Information

Yusp tracks the movement of all users on your site. The back-end system collects data, enriches that with contextual parameters, captures user preferences, and product similarities. With every click a user makes, Yusp learns more and more about them, to serve them better.

Recognize Context

Yusp collects contextual information like location, time, device, and referrer to automatically adapt recommendations accordingly. In the Yusp Dash you have the ability to adjust the importance of many different factors, including context, giving you the ability to fine-tune the recommendations based on your preferences.
Explanatory graphic about how the Yusp recommendation engine recognizes the context of each visit on your site?
Explainer graphic - How the Yusp recommender system analyzes user behavior?

Analyze User Behavior

Yusp creates unique profiles for each user as it gathers more data. This enables Yusp to determine what a user likes and does not like as well as which suggestions resulted in positive user engagement and which ones did not. Yusp can then match these profiles with timely, relevant, and personalized offers from your inventory.

Personalize the User Journey

Like a good bartender, Yusp knows what you want before you even ask for it. The goal of Yusp is to take that personal touch into the online experience. We make it possible for you to build a personal relationship with your customers, communicating with each and every one of them individually to determine their needs.
Explainer graphich - How the Yusp recommendation as a service platform personalizes the user journey of the visitors on your site?
Explanatory graphic about how the Yusp recommender system let's you build your own recommendation logics.

Build Your Own Logic

Our engine automatically learns and analyzes user behavior, matching the right visitor to the right products or content at the right time. Customize, and build on top of our existing segmentation: set up your own user groups, rank importance of metrics in recommendations, or set up A/B tests for experiments.