Recommender System

Recommender System

Example online store: ``You might also like this``

Too much product selection overwhelms the human brain and minimizes the likelihood of a possible purchase, in short: “Paradox of Choice”. How do you keep the user on your platform and increase the shopping cart value at the same time?


With a recommender system, a methodology for recommendation contexts, we use big data and self-learning algorithms to develop product recommendations. The user thus gets virtual expert advice at his side.


Focus on: reducing uncertain purchase decisions, generating additional and impulse purchases, and increasing the average shopping cart value.


A recommender system helps the user in the selection phase to maintain an overview instead of getting lost in a multitude of similar offers. Optimal recommendations create structure and accelerate the purchase decision – resulting in higher customer satisfaction and return customers.


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Applied Frameworks