Recently a client of mine enthusiastically unveiled some fresh results from cross-sell marketing programs they were powering for a network of several dozen financial institutions (FIs).
Their enthusiasm was warranted: the results showed significantly superior improvements in impression-to-purchase ratios over traditional methods. The improvement in fact was over 3 times better!
This is an excellent example of the implementation of Big Data in a direct marketing application.
Traditional methods that an FI uses for targeting (when they use targeting at all; but that’s another story for another time) usually involve tabulating customer account data (e.g., who has a mortgage but doesn’t have a home equity line of credit?) and purchasing third party data for appending (e.g., demographic data based on zip code of the customer).
I like to call this “Who You Are” data. It is valuable but not rich and often out of date. It is often full of invalid indicators because all you can tell by looking at your account data for a customer is whether they have a home equity account with you … it doesn’t tell you anything about whether they have an account with another FI.
What’s needed is Big Data which is data that comes from many sources, is rich and voluminous (e.g., heavily sourced from transaction systems such as debit and credit card processing, bill payments, money transfers, ACH debits and credits, loan processing, etc.), and is handled by an analytic platform that can make sense of it and deliver it to a point of customer interaction or business decisioning -and if needed, in real time.
With Big Data you can add two key dimensions which I call “How We Behave” (which is a predictor of future behavior) and “What We Can Do” (which parses from the data what we can do based on our financial position and the trends in it). With these three dimensions a marketer trying to effeciently target customers with the right cross-sell offer has the insights needed to deliver superior results.
It is pretty cool! I’ll look forward to sharing more specific and detailed results when they are released soon.
Potential: Revealed 
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