A cloud-based Personalization service leverages artificial intelligence and machine learning technologies to deliver optimized customer experience. With Personalization, you capture events that represent preferences and interests of your users, apply models to quantify these findings, and combine them by using scenarios to generate recommendations, which you can then present in a form of personalized content to visitors of one or more websites hosted by the Ibexa DXP instance.
Both event tracking and result publishing is done by users with administrator privileges, according to a procedure described in the developer documentation.
There are different areas where you can apply recommendations. The most common ones are eCommerce and content publishing.
eCommerce vs. content publishing
Documentation mentions eCommerce use cases more often, but provides a thorough understanding of the content publishing context as well.
Both products and Content items can be referred to as content and the BUY event can be understood as the CONSUME event.
Before you can use the Personalization service, you must enable it. Then, for the service to generate relevant recommendations, you can change the default configuration. Finally, you can feed it with data, or wait until the service gathers enough information about the content and events. On a website with more than 100 clicks per day, a day of collecting data should be sufficient for the first recommendations to be relevant. Recommendations become better with time and the amount of data collected.