Recommandation systems

The behavior of a client on your website is an important indication for optimizing sales and better meet the expectations of your visitors. In this lab, we propose to test a solution to implement a dashboard indicating the number of views by product, category, sales tracking, monitoring baskets, research, etc. Beyond this single metric aspect, these information can be used dynamically to recommend a product to a user.

The solution investigated in this lab is Ezako, it is mainly based on a recommendation engine accessible via a set of APIs. The system can be deployed very quickly on any website with some settings. The establishment of such a system requires three steps for which you will be guided in this lab.