Marketing’s Role in Data Analytics

Have you ever heard of the Baader-Meinhof Phenomenon? This phenomenon occurs when the thing you’ve just noticed, experienced or been told about suddenly crops up constantly. It’s like when you are looking at buying a white Ford Explorer, then suddenly you are seeing them everywhere.  I recently wrote on the subject of Banking and Big Data and right after doing so, I saw an article from the ABA Banking Journal on Marketing’s role in addressing big data.  BMP at work. Anyway, the article summarizes the results of an ABA July 2022 survey on how bank marketers are making use of the data they have. You can read the article Here.  The results are quite interesting.

Not surprisingly, bankers indicated that they have access to quite a bit of data useful for marketing. Consider this graphic from the article:


I was a bit surprised that Product Profitability was so much lower rated than product usage. It makes me wonder whether this means that the marketers don’t have access to the necessary data elements to calculate profitability or that there is no defined way to codify profitability that yields actionable data.  The problem is profitability can be calculated a number of ways and unless someone sets definitions for how profitability will be calculated for a particular product, service or relationship, it is likely that no profitability is calculated at all.  Which is a shame, since it is critically important to know which customers, services, etc. are profitable.  Remember, if a non-profitable customer leaves your bank for a competitor, the banks overall profit goes up!

Other takeaways I thought interesting from the article are bank marketers are getting more comfortable in using the data they have access to.  This is really important since bankers are predisposed to be cautious about how data is used to stay far away from the “creepy” line. Further, the survey indicated that bank marketers are not very confident about the quality/accuracy of the data they are using to make marketing decisions.  This is especially problematic since marketing decisions must to be from a position of knowing that the data is accurate.  It’s hard enough for marketers to show the efficacy of the campaigns they run without hampering them with low quality data.

The ultimate goal of marketing’s use of data comes from their ability to move the needle in building the brand, cross-selling and new product/service creation.  Consider the graphic related to this issue:

This couldn’t look more like the standard bell curve if Carl Gauss had drawn it.  The orange bar representing target marketing is the one that stands out the most for me.  At the end of the day, we must be able to get super granular about the specific subset of customers/prospects we want to reach with an appeal and be highly confident about our ability to accurately do so.  What’s amazing is that old school methods like snail mail marketing pieces are incredibly effective, IF they are targeted to a very specific sub group to which their appeal is uniquely tailored.

Bank marketers have a really tough job.  We need to, at a minimum, empower our marketers with accurate, targeting data that will enable focused marketing campaigns that can generate measurable results.  What are your thoughts?  Reach out to me at and share some ideas and stories.