Recommendation system for cross-selling

Data-based product recommendations enable a consistent and individual customer approach at all touchpoints.


75% of the recommendations are rated as helpful by the sales experts

One algorithm for recommendations at multiple customer touchpoints

Enabling the further development of the recommendation system through know-how transfer


A B2B mail order company wants to increase its turnover through better cross-selling offers. Customers are to be addressed uniformly and individually both through classic sales and in the growing online area.


A recommendation algorithm is developed based on transaction data. The quality of the recommendations is continuously validated by sales experts during the development. Together with the client's IT department, a concept is developed for recording user activities in the web shop in order to enrich the algorithm with this data.


Customer-specific product recommendations are provided uniformly in the sales system and in the web shop. An automated feedback loop from the sales department enables the continuous further development of the recommendations.

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