The problem this bank faced was identifying the most likely prospects to shop in a particular merchant among those who normally did not shop at that merchant. Previously, the bank was focusing efforts on a broad group of customers who had previously shopped in that merchant or other merchants that they deemed to be similar.
A major bank in Southeast Asia needed a solution to improve the speed to offer and relevance of credit card usage promotions conducted via email. They had the latest data science software but low prioritization in IT and limited access to data scientist support meant timeframes of 6 to 12 months from idea generation to implementation.
A large insurance and financial services company in Southeast Asia was seeking a solution for cross-selling its products to customers across the group. For operational, as well as regulatory issues, they had no central data warehouse that would allow a single customer view.
This major bank in ASEAN was looking to improve the process for offering new products to customers when they contacted to bank, either in person when they visited branches or when they called customer service. The existing process relied on the judgement and experience of staff using very basic rules, resulting
A mass market retailer needed a solution for recommending relevant products when their offline customers began using their website for shopping. This was complicated by silos around offline shopping and online shopping.
Selling ad opportunities to package goods companies/agencies
The operator of a loyalty program that includes a diverse group of outlets - shopping malls, hotels, supermarkets, schools, sports, retail - wanted to maximize the opportunities to sell targeted product offers to those customers most likely to be interested in those offers.