Amazon, Google, and Facebook have changed the way consumers think of advertising. Generalized offers (say, the kind blasted out to a newspaper’s entire readership) used to be acceptable. Now they’re not. Today’s consumers expect ads that are personal and directly relevant for them. They’re accustomed to digital companies that look at aggregated and anonymized user data and create targeted offers based on that data.
The old, generalized model is gone. The new model, as exemplified by Google's targeted marketing, has replaced it.
Unfortunately, most financial institutions keep failing on this front. To illustrate, a 2013 study from Gallup shows that 53 percent of fully engaged customers received an ad for a product they already had and 66 percent felt like the offer was very general and could have applied to any of their customers.
Imagine if a company like Amazon, with all their attention to their “Recommended for You” feature, made these kinds of mistakes. How much would their sales decline? It would be brutal.
The implications for financial institutions are similarly enormous. In their report “Banking Outlook 2014” KPMG asserts that proper data analytics is key to growth in the digital age. They say, “Banks that develop an infrastructure allowing them to analyze data quickly, that staff up to do that work, and that make revenue-oriented analytics part of their culture, are the banks most likely to grow their top lines.”
At the very least, financial institutions should know enough about their users to not offer a product they already have at their institution. Ideally, through the use of platforms that enable account aggregation, financial institutions should also know what products their users have with their competitors and be able to target based on that data. Banks and credit unions that do this will have the edge on the competition and soon start winning market share as a result.
It's time for financial institutions to catch up to the precedent set by the savviest tech giants. After all, banks and credit unions are sitting on the right data to do it well.