Overview
A recommendation engine uses machine learning algorithms to recommend relevant content, products, or services to a particular user or customer. There are three main types of recommendation engines: collaborative filtering makes suggestions based on other users with similar preferences. Content-based filtering recommends similar items based on a user’s preferences and past purchases. Hybrid models combine both content-based recommender systems and collaborative filtering systems. Our Recommendation Engine solutions involve collecting customer data – which can be implicit data or explicit data – and storing it in a scalable location. The next step is data analysis, and the final step is data filtering using one of the methods outlined above.
