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From incomes to outcomes: Banks move from limited tunnel vision to unlimited focus

April 15, 2014

What if you were the chief marketing officer of a bank and you heard that within your organization, hiding in plain sight, was a magic crystal ball that could significantly improve customer acceptance of bank offers, anticipate customer needs and predict future actions more accurately than ever before? That magic ball surely would be worth a lot, wouldn’t it?

While there is no magic crystal ball, the good news is that you don’t need one. Banks already have a treasure trove of information that will tell them more about what their customers want and need, and what products or services would be best to offer. However, many banks are not yet taking advantage of this data, using limited data sources and outdated technologies to analyze customer needs and learn what products or services would be best to offer them. There is a wealth of additional insight in the many interactions a customer has with a bank that, if analyzed, can yield significant improvement in offer acceptance, wallet share, customer retention and revenue. 

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Typically, banks will analyze a subset of data and assign customers to a general segment, looking at demographic factors, current product portfolio and possibly transaction behavior of the segment. They then make offers to this large segment, which are so broadly targeted that offer acceptance can be as low as .5 percent.

By utilizing new big data and analytics capabilities, banks can analyze more data types, in larger amounts and with greater speed than ever before, revealing deeper insight into customer needs at the micro-segment or even the individual level, and giving banks the ability to truly monetize data they already have.   

Banks can better predict customer actions and what offers they are most likely to accept by analyzing interaction data, which is not traditionally included in their customer analysis. By analyzing correspondence, contact center notes and teller notes (in addition to previous analysis) a large Italian bank used an IBM Big Data & Analytics solution to better predict what their customers required and improved the bank’s offer acceptance rates by more than 50 percent.

Customers tell banks a lot about their needs and intentions just by their actions and interactions with the bank website, the contact center and email or chat correspondence. Now it is time for banks to really listen.

Watch this video to learn more about optimizing offers and cross sell using Smarter Digital Banking with IBM Big Data & Analytics.