Knowledge is power and most bankers have figured out that they’re sitting on a treasure trove of information about the consumers and businesses they serve. However, using this information to empower their account holders and deliver services tailored to their needs has been a difficult goal for banks and credit unions to achieve.
One of the many changes brought by COVID-19 was an acceleration in the participation of the delivery economy. This level of participation is likely to continue to rise as more businesses develop viable online ordering and delivery offerings. Companies such as Amazon, Google, and Apple have made personalization of offers and the anticipation of the consumers’ needs prerequisites to any successful online engagement. So, as the delivery economy expands, successful offerings will need to reflect these same characteristics delivering the convenience and speed consumers now consider mandatory as a basis for loyalty.
The spread of the delivery economy puts additional pressure on financial institutions already being challenged to improve their digital banking experiences in general, specifically in the area of personalization. This means that data literacy should no longer be a journey starting in the latter stages of a three-year plan for institutions. Instead, it is an area where material progress must be demonstrated within 18 months at banks and credit unions intent on sustaining and growing.
Yet, to quote a Scottish proverb, if wishes were horses, beggars would ride. Even in the largest of institutions, it is an error to assume that an understanding of leveraging data to personalize digital experiences is common. Though, admittedly, the largest and regional nameplates are able to hire the understanding they need to mind their gap in this area. For community banks and credit unions this option is seldom available. This does not mean data literacy is not possible for this market segment. It means that these institutions must ‘know where to look” to find the partners they need to bring their data literacy up to par. Those partners exist though perhaps not in the places these banks and credit unions typically look.
But I’m a Banker, Not a Retailer
Even though the word “retail” is used in banking to delineate the services offered to consumers, few bankers think of themselves as retailers. Regardless, it is the retailers – more specifically “e-tailers,” that have reset the customer expectations of what makes up an acceptable digital experience.
To meet these expectations, it is more prudent to seek outside expertise to assist than attempt to download the mind of a retailer into a banker. Specifically, find a partner with a demonstrated track record of using data to help retailers attract and retain customers. This is counter to the logic that may be found at some financial institutions where marketing partners – whether fluent in data extraction and application or not – are selected based on demonstrated expertise in banking.
This is where the mold needs to be broken. Utilizing the digital channels to deliver personalization that empowers the end user and institution, bringing value to the former and revenues to the latter, is not a goal specific to banking. The tools needed to do it effectively have little to do with the tools required to be a good banker. One industry guru once stated (paraphrase): “Any banker not focused on using the data available to deliver personalization to consumers the way successful retailers do, will not be in banking in five years.”
His timeline for “getting it” is a bit too generous, but the outcome predicted is more likely true than not.
Don’t Try This at Home
For some institutions, there may be a temptation to experiment – on their own or with an outside agent – with the application of data. This is not an uncommon approach to initiatives for banks and credit unions of all sizes. Prototypes and small sample groups are used to test the viability and value of a new offering and/or technology. Data is different. Prototyping in the area of data literacy can be a risky play as a misstep – not uncommon in prototype environments – can disproportionately damage an institution’s brand.
As consumers, we are intolerant of marketing that is irrelevant to our needs. Even though technology continues to bring a number of positives to daily life, it sometimes seems to have only increased the incidences of this type of mismatch. This is what makes “trying on” data literacy to see if it is a fit for an institution hazardous. Unlike testing a mobile wallet or other innovation to determine potential adoption rates, data literacy is personal; it speaks to the quality of a relationship between the consumer and the institutions.
A promotion that misses the mark (suggesting a Maserati purchase to a Prius family, for instance) telegraphs the message “I don’t know you.” It’s then a short leap to giving the impression “I don’t care about you,” which can erode loyalty. Offering that same Prius family a deal on solar energy installation not only demonstrates knowledge of their preferences but shows an association with the values they hold as important.
On the other hand, we as consumers respond positively (and profitably) when an offer matches our need. Data literacy is not a “new feature” that needs to be added to the set of services that a financial institution offers through its digital channels. Data literacy is the foundation for ensuring those digital channels extend and deepen the relationship a bank or credit union has with the end user.
When it comes to data literacy, keep your hands off the “Approved” stamp until you are able to clearly enunciate a set of customer-in-mind objectives and have engaged the proper outside expertise to effectively execute that vision.
The Bottom Line: Banks and credit unions rarely possess a true 360-degree view of their customers. Acquiring additional data from outside sources can certainly help to complete the picture, but this is best saved for a longer-term initiative. FIs have more than enough data - and arguably the most valuable and enlightening kind - already within their walls. The first challenge is building a pathway to that data- which runs through different pipes, resides in different silos, and often must be extracted and distilled from the systems of third-party core providers.
There’s no shortage of tasks on this front. Community banks and credit unions may not have a stable of data scientists on staff. Yet, they can enlist partners with the data and technical chops to understand how to use the tools available to make this accessible and actionable. From there, you can initiate informed conversations with retail-minded experts to plan how it can be leveraged to mutual benefit.
For more on the pandemic-grade need for digital, read COVID-19’s Digital Transformation Wrecking Ball.
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