The Fed funds rate, which has hovered just above 0% since the financial system melted down in 2008, is bound to increase soon. Smart financial institutions are preparing themselves for the inevitable change. As a result, internal funding will become more attractive, meaning that it’s time for banks and credit unions to start shoring up their deposits.
One way financial marketers have historically increased deposits is to offer free checking accounts — essentially as “loss leaders.” However, the value of these deposits is significantly negated if the cost of providing “free” checking accounts isn’t offset with some sort of fees or revenues. So how are banks and credit unions going to generate deposits now? How can they reduce attrition rates as their competitors go gunning for their customers? How can they upsell money-making products — credit cards, auto loans, premium checking — to consumers that are often skittish about data collection? How can they earn a higher share of the consumer’s wallet and make free checking worthwhile again? Here are three steps financial marketers can take right now.
1. Create an Automated ‘Graduation Strategy’
“Don’t sell a Cadillac to a Kia shopper,” as car salesmen say. It seems like common sense, doesn’t it? But many financial institutions don’t have any kind of “graduation strategy” that aligns with the needs and budgets of their consumers. For instance, if a consumer was properly placed into a free checking account product, he or she should subsequently be targeted for lower-end credit cards. And yet plenty of financial institutions squander their marketing capital trying to cross-sell free checking customers high-value premium products.
Once a bank or credit union brings initiates a new relationship with a loss-leading product such as free checking, there is a 45-60 day window to upsell or cross-sell that person into a profitable suite of products — otherwise those relationships start costing the institution money. This very narrow marketing window means that your product graduation strategies must be as built as efficiently and effectively as possible. Most importantly, this process needs to be fully automated and personalized, so consumers can be quickly targeted with the right products at the right time.
Now this may sound obvious and intuitive, but most banks and credit unions aren’t doing it (or at least aren’t doing it very well). One obstacle that is holding many financial institutions back is that they lack a unified data strategy — precisely what they need to deploy an automated graduation process.
2. Focus on Effective, Unified Data Collection
Is it possible to know if a particular consumer might be more receptive to an offer for a credit card or an auto loan? Yes, it is.
Financial institutions have access to tremendous amounts of valuable consumer data that can be used to generate all sorts of valuable marketing intelligence, but… all too often that information is kept in silos that make it difficult (sometimes impossible) to utilize in any predictive capacity. Credit card, deposit and investment teams each have important data that — when brought together — provide incredible insight into each customer. Transaction data, for instance, is one of the most dependable ways to understand and predict a consumer’s interests.
This is not to say that banks should embark on a quest to collect and analyze all their consumer data. That would be prohibitively expensive, inefficient and impractical. Instead, the initial focus should be on the strongest predictive indicators, particularly payment and deposit data. Additional data points continuously added in.
With enough data, financial marketers will start to see correlations emerge between behaviors and interests in certain products — trends that can be used to drive marketing strategy. For example, if the data shows that a salary raise of more than 10% makes a consumer far more likely to upgrade to a premium checking account, then it makes sense to target consumers meeting that criteria with marketing messages for premium checking accounts.
Now take that basic example and incorporate specific customer transactional data — the merchants a consumer has interacted with, the transaction amounts, frequency, etc. When combining transaction-level data with product specific indicators, the image of each consumer that emerges is far more complete. Having an understanding of what makes each consumer stand out from the general population can become an extremely potent component in your marketing mix — targeted products and personalized messaging.
3. Reach Consumers Where They Are
Consumer visits to branches are declining as online and mobile channels have grown in popularity — everyone knows this. However, without the critical physical touchpoint of a branch visit, few financial institutions have effectively adapted their sales and marketing strategies.
Once you can identify the indicators that trigger a product sale or opening, the next step is to reach consumers on their mobile devices and desktop browsers with ads specifically targeted to their needs. Consumers are reluctant to click on online ads… that are generic and intended for the mass market. But when ads are relevant, customer engagement rates skyrocket.
Combining the right product with the right messaging goes a long way towards increasing the likelihood of both clicks and conversions, and helps rekindle the kind of personal relationship that has eroded across the industry as branch visits have evaporated.
While using consumer data to inform sales and marketing decisions seems obvious, the inherent complexity at most financial institutions can make establishing an effective analytics program a major undertaking. It is nonetheless worthwhile, and will increasingly become more and more essential.
Consumer banking patterns have changed irreversibly, and the value of a unified view of the customer will only grow over time.
Keith Weitz is the Director of Data Strategy and Analytics at Segmint, where he helps financial institutions securely maximize the marketing value of their consumer data. He has worked as a VP in banking analytics for over a decade at institutions such as SunTrust, PNC Bank and KeyBank.