Recommendation System

The number of web stores and products offered by them is growing rapidly, but people’s attentiveness hasn’t improved. Therefore, the critical challenge for every web store is to guide users to products that they are interested in and to do so in a way that would help to achieve business objectives.

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STACC’s recommendation system is an analytics solution, which helps to choose from a variety of products the ones that might interest the client 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 web store);
  • predict products that match the user profile (which products are suitable for the user at a particular time point);
  • set business-specific rules (which products can’t be recommended together, which products 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).