Market Basket Analysis AI in BDC to support Promotion and Assortment Planning:
Uncover Hidden Buying Patterns, Make Better Decisions

How retailers use SAP Business Data Cloud and AI to analyse POS receipt data for buying patterns – and turn them into concrete recommendations for placement, promotions and replenishment.

Which products are frequently bought together in one store, but not in another? And which product combinations sell out over the holidays?

In most retail businesses, questions like these are still answered ad hoc, manually and in silos: analysis based on Excel extracts, run only on request, with products, promotions and stores each viewed in isolation. Yet the purchase affinities are already sitting in your POS data – they are just rarely put to systematic use. The result: decisions on placement, promotions and replenishment are based on assumptions rather than real shopping behaviour.

In this webinar, we show how retailsolutions uses SAP Business Data Cloud, SAP Datasphere and SAP Databricks to build a governed data foundation for market basket analysis. Product affinities are calculated using association rule mining: support, confidence and lift for every product and category pair.

This foundation unlocks a wide range of use cases that deliver concrete recommendations for placement, promotions and replenishment. In the webinar, we will demonstrate this using real market data.