RECOMMENDATION SYSTEM FOR IMPROVING USER EXPERIENCE

The development of e-services is also increasing the information flow targeted at the user. However, the users’ ability to receive information is limited, therefore, it becomes critical to only provide information that is relevant for a particular user.

STACC’s recommendation system is an analytics solution, which helps to choose from a variety of objects the ones that might interest the user the most. It’s an artificial intelligence system that enables to:

  • collect, store and process information about the online behavior of the users;
  • predict user intent (what the user wants to do in the new environment);
  • predict objects that match the user profile (which objects are suitable for the user at a particular time point);
  • set business-specific rules (which objects can’t be recommended together, which objects are subject to special rules, etc.);
  • conduct A/B testing (which recommendation model makes the best recommendations in terms of the business objective);
  • monitor the recommendation system (how users react to the recommendation system and how accurate the system is);
  • improve the system constantly (using machine learning, the system learns to become more familiar with the user over time and makes its recommendations more accurate).

If you’re interested in implementing an AI recommendation system, order a free consultation by filling out the form below.

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