Personalization Engine

Providing deeper context about individual users and consumers, personalization engines employ data science to deduce patterns that allow businesses to edit, buy, select, tailor and deliver personalized messaging, content, product selections, and other interactions. Personalization engine software solutions typically use machine learning algorithms such as collaborative filtering, which depends on the choices of similar individuals. A variety of variables can be used to better understand the consumer and provide accurate recommendations when creating a personalization engine, including past purchase history, site interactions, and psychographic data. Using an effective personalization engine increases conversion, ad effectiveness and consumer satisfaction, hence improving business outcomes.