Product Recommendations

Understand product interests & buying behaviors at individual customer level

Understanding Customer journeys is challenging - we help you to find the answers and to use the insights

what we can offer you

Improve customer experience by offering personalized recommendations

Allows A/B testing and optimization of recommendation algorithms

Cross-sell and upsell products more effectively

Cross Sell

By clustering similar customers based on observed buying behavior or other descriptive parameter, we identify white-spot items, which have a high likelihood being interesting for the customer. The results can be further enhanced with time-series models, to predict item trends seasonality effects.

Buying pattern

By analyzing historic transactions we can identify strong customer-product relations, which reflect needs and affinities. These customer individual core/ regular products can be used to identify basket composition patterns and to predict future transactions and customer needs quite accurately.

Check out our case study

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