This Fortune 50 US Retail bank has 10 million mobile users (running the bank’s mobile app on their smart phones). The bank has agreements with more than 10,000 merchants and wants to push coupons and discount offers to their credit card holders, depending on the user’s profile and location. The bank’s main goal was to improve coupon redemption rate through real-time, location-based personalized offers.
The project covered a first market trial with fifteen months of data, consisting of:
NGDATA partnered with the bank with its CDP to be used for its storage, search, user profiling and recommendation capabilities:
- All data was uploaded into the solution utilizing the CDP’s ETL connectors and Data Loader.
- The data was then stored in the consumer database, running on top of the CDP’s Big Data Repository.
- Two of the CDP’s Recommendation Engines were deployed, thereby supporting multiple propensity scoring approaches, including: Collaborative Filtering and Knowledge Based
- The Recommendation Engine(s) calculates, in real-time, the customer propensity for all merchants created in the solution.
- The CDP’s API’s were used to integrate with the bank’s mobile app running on the smartphone and the offer creation / management solution.
- Finally, the CDP’s connectors to SAS and R were used to offer deep dive analytical features.
“Introducing big data and machine learning not only resulted in higher performance, but it allows us to introduce disruptive business concepts and opportunities.”
—Senior Vice President of the Bank