Predicting customer segments and their patterns of behaviour based only on information from their shopping receipts. Suitable for supermarket chains seeking to find a big data alternative to loyalty cards.
WHO IS IT FOR?
- Supermarket chains seeking to find big data alternatives to loyalty cards (or who wish to implement loyalty cards)
- Particularly suitable for the retail industry, but can also be used for clients who operate with large databases of their customers (e.g. finance and banking, fashion, production, etc.)
- The goal is to get precise prediction of customer segments and their patterns of behaviour based only on information from their shopping receipts
- Entry data: deep analysis of the client’s database on all customer transactions (easy handling of multi-billion entries) and matching it with existing client databases on their customers collected from prizes and other marketing activities
- The first step is to recognize trends and clusters of shopping items and predict which items group together; this allows for better optimization to encourage impulse buying
- The second step is to use the BASON survey to create a profile of the average shopper based on recognized patterns of consumer behaviour in real time
- The final step is to design suitable microtargeting solutions specific to the recognized patterns of behaviour
- Other useful solutions for retail:
- Validated learning on the effectiveness of existing marketing campaigns (which one works and which doesn’t)
- Warehouse optimization and lean store management
- Situation room: real-time predictions of demand for individual items based on our existing software solutions