We at RMG saw this recent posting from our friends at The Financial Brand. The article, by Ron Shevlin, summed up our approach and belief succinctly and we felt it important to share.
During a presentation at strategic planning session for a large credit union, I challenged the management team’s notion that the FI was–or could be–“competing on superior service.” My argument went as follows:
- The market isn’t big enough. Only so many consumers choose a financial provider for its “superior service capabilities.” Many consumers choose an FI based on convenience–not service–related factors. Even there, “convenience” is not a single or well-defined concept, as convenience could mean nearby branches, or extended hours (like it means to one bank here in the Northeast), or it could mean the provision of technology-based tools to make the consumer’s financial life easier to manage.
- The strategy isn’t measurable. Managers need to be able to gauge two things: 1) To what extent is their chosen strategy a smart strategy, and 2) How well are they executing on their chosen strategy. There’s no shortage of financial institutions (especially credit unions) who claim to provide superior customer care — with no ability to measure or prove that claim. Without adequate measurement, focus/alignment/discipline becomes impossible to achieve.
- The strategy isn’t specific enough. An FI that chooses to compete by providing “superior service” still needs to determine the level of quality it needs to provide regarding convenience, value and product quality. I’m not saying this is impossible, but, in practice, focusing on creating an advantage through superior customer care may lead managers to neglect the value and product quality dimensions. The lack of specificity also means that focus/alignment/discipline will be hard to achieve.
You Don’t Know Jack
One of the executive team members then said:
“You don’t get it. We do have superior service. It comes down to knowing our members better than any mega-bank could ever know them.”
I looked at him and said, “Dude, you don’t know JACK! Or Jill, Jim, Jeffry, Jenny, or any of your other members whose names start with the other 25 letters of the alphabet.”
Well, I said it in my head.
I did say–out loud–that the credit union knows just a thin layer of who its members are. Sure, when a member walks into a branch, credit union employees know that it’s Jack Jones, that his wife’s name is Jill, and that they have two wonderful kids, Jenny and Jeffry who attend Jefferson College.
I explained, however, that the credit union doesn’t know:
- How much money Jack has. You only know how much he has with you. And if he’s got any money, it’s a good bet he doesn’t have much of it, let alone all of it, with you. So you really don’t know his investment needs or risk tolerance.
- What Jack’s financial goals are. Oh sure, you have a PFM app that has a goal tracking capability. But PFM users account for what, 10% of your overall member base? What’s the chance that Jack is one of those members and uses the goal tracking feature?
- How Jack makes his money. Oh sure, you might know how much he makes because you can see that direct deposit coming in every month, but you don’t know if that stream of income is safe and stable, or if Jack works in an industry that is on the decline.
- How Jack (and his family, for that matter) spends his money. You’ve got a piddly percentage of your member base using your online bill pay platform, and it’s a good bet you didn’t issue all the credit cards he has, so you really don’t know where the money is going. And worse, you’re not even doing anything to analyze the debit card spend data you do have.
I then put the icing on the cake by asserting, “You don’t know your members nearly as well as you think you do. And as I look around the industry, it’s the megabanks and fintech startups–not the community banks and credit unions–that are doing something about it.”
Big Data Delusions
In a recent CU Times article on marketing trends, a consultant was quoted as saying:
“Where big data holds out great promise for credit union marketing, i.e., the ability to enrich target marketing, forecast next best products for members, and generate more efficient marketing budgets; it also yields great strategic value. Big data – better said, your data, can create unrivaled value for your members. Your data produces more than the next best purchase or transaction; it initiates models for loyalty and lifetime value from your members.”
Now, I don’t want to insult this guy, or start an argument, but what is he talking about? What, exactly, is this “big data” that he’s referring to?
Most FIs I’ve talked to over the past two to three years keep telling me that they don’t do enough with the “small” data they have. And trust me when I say it takes every ounce of energy I have to stop myself from saying:
“Small data? What the hell are you talking about? What the hell is small data?”
The Yin and Yang of Data
There’s a yin and yang to the concept of data in marketing:
Yin=You have to have useful data.
Yang=You have to be able to do something with that useful data.
Here are two problems in the industry today:
- It has become popular to say that banks and credit unions have all this data they’re sitting on that they don’t make good use of, but few firms really know what data elements are good (or useful) for what marketing purposes; and
- Consultants that spew big data nonsense–and dropping terms like predictive analysis and next best product models–are talking about the Yang (data analysis capabilities) without any consideration of the Yin (data quality).
And here are two realities about individual financial institutions today:
- The job of data quality typically falls to the IT group whose job it is to get the data in one place, get it cleaned, and make it accessible. But that really doesn’t address the need to determine the utility of the data.
- Data is boring. Try this (if you have no concerns about furthering your career): Go into an executive team meeting at the FI you work for, and tell them that the big strategic initiative this year is going to be gathering, consolidating, and improving the quality of the data the FI has. That will be your last presentation to the exec team.
The term gentrification typically refers to the renovation and improvement of rundown properties. Financial institutions’ data assets, warehouses, and analytical capabilities are similar–rundown properties in need of gentrification. My contribution to the Top 10 Retail Banking Trends and Predictions for 2017 article was the following:
“Over the next few years, banks will embark on data gentrification efforts – not just cleaning up the data they have, but collecting and using BETTER data.”
Because you have to face the truth: Your customer data sucks–and it’s a strategic problem, not just a nuisance.