Basic information
Personalized recommender systems work in the background of online shops and create suggestions, as well as recommendations for products, all matched individually to the buying behavior of each registered customer.
Everybody who has already shopped online knows the procedure: After purchasing a specific item, product recommendations are presented, which try to promote further articles to the customer. Basically, these recommendations are a clever idea. There is just a problem with unpersonalized recommendations, which have been generated according to the preferences of the mass. This is where personalized recommender systems come in. Suitable recommendations are created, which are based on the individual buying behaviour of the past to meet the customer’s taste.
Potentials
The aim of such innovative recommendation models is to improve the accuracy of statistical calculations, to generate more suitable product suggestions and, in the long run, to reach the following goals:
- Higher customer satisfaction
- Higher customer loyalty
- Extension of market share
- Sales increase
