Short Description: Analytics driven Customer Behavior Ranking for Retail Promotions using POS data
Profile Customer based on their Buying behavior using POS(Point of Sale) data from a Retail stores.
Normalised Behavior scores are computed based on their Shopping patterns and a Analytics Segmantation
is run to identify Customers like Gold Class, Customers with Up Sell prospects or Customers at Risk and
Dormant Customers. These Segments ofCustomers are then used for launching specific Promotions.

Technology used:
Watson Data platform, DB2, Data-Science, Python Notebooks