The segmentation models banks traditionally use to target customers based on their age, income or residence are “completely broken”, W.UP’s Head of International Sales and Business Development Tamás Braun said at Amsterdam Fintech Forum 2018.
Banks can do so much better than grouping potential clients into age-old segments. Predictive methods can help them map out customers’ behaviour, from their sporting schedule, mobile usage, and online entertainment preferences to their eating out habits, and set up customer profiles. These characteristics will predict what products customers are likely to buy.
To build these profiles, banks need to use both transactional and location data, e.g. where customers use their cards or mobile banking apps. The grocery shopping profile, for example, shows customers’ shopping habits: whether they have a big shopping day at the beginning of the month when their salary arrives or they do their shopping every Friday. Their favourite retailers and brands are also included.
Watch Tamás’s presentation for more about how to create customer profiles and how to analyse customer behaviour for more effective strategies in digital marketing.
[youtube]https://www.youtube.com/watch?v=yxZqrHfUBj8[/youtube]
For more best practices in digital banking sales and key performance indicators (KPIs) with actual banking sales data, download W.UP’s white paper Digital sales: 12 strategies for banks to win in the digital world war.
