How Do Personalization Engines and Recommendation Systems Work?

Personalization engines use AI and machine learning to aggregate data to give every user, employee, or shopper a custom experience.

Recommendations are a key feature of any personalized customer experience these days. Personalization engines are systems that aggregate massive amounts of data and offer up a customized experience for every employee, user, or shopper.

By tracking what one group of individuals likes or dislike or does or doesn’t do, the system can make recommendations for an individual with similar traits. A personalization engine plots these behaviors or sentiments and tries to make it’s best prediction for what similar users would want to see next or do next.
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