Community banks can leverage data to stay competitive

Katie Horvath

Community and midmarket banks have typically maintained competitive advantages over large national banks with personalized service and strong community relationships. Yet, let’s face it. We live in a digital world where consumers demand online and mobile app options for commercial transactions — including banking — and a more personalized experience. 

Consumers now view personalization as the default standard for engagement. Personalization in marketing matters more than ever before, and especially for midmarket banks for whom the days of white-glove service are dwindling.

McKinsey & Company recently found that 71 percent of consumers expect companies to deliver personalized interactions, while 76 percent get frustrated when this doesn’t happen. The research firm also discovered that “companies that grow faster drive 40 percent more of their revenue from personalization than their slower-growing counterparts.”

Advanced data analytics is one key to this level of hyper-personalization. As with all businesses, banks generate massive amounts of data that is typically siloed, which leaves it untapped for a variety of uses — such as marketing. To unlock the value of this data, banking institutions need to aggregate it, integrate it and cleanse it. This is a significant challenge that can be difficult and time consuming.

For this reason, enterprises are adopting advanced analytics, artificial intelligence and machine learning solutions to leverage data generated both inside and outside of their organizations to achieve actionable business insights. There are a number of data platforms and analytics solutions with predictive capabilities available to enable them to extract strategic customer intelligence, expand products and services, monitor key performance indicators to fine-tune their marketing strategies and potentially increase market share.

While large banks are likely to have the financial and personnel resources to use analytics technology, midsize banks don’t. That is changing, with new data platforms and AI-driven customer intelligence technologies that are delivered along with the required expertise in a “side-by-side” model. With this model, midmarket banks can also leverage their data to gain the customer insights they need to provide greater personalization.

Using advanced data analytics, midsize banks can learn more about their customers to grow their lifetime value, predict churn by service underutilization, and understand which products to introduce to their customers and when. With data-driven insights bankers can deliver timely, personalized messages to customers with the right product recommendations. 

It’s important to target the right customer at the right time. Don’t market a new mortgage loan to someone who just refinanced with your bank in the past week. That will certainly annoy the customer. Instead, accurately identify the most appropriate marketing targets for the best possible response and ROI to improve campaign performance.

Banks can also target-market more efficiently to a subset of customers and prevent waste. If a customer has a loan with a bank, but does not have a deposit account, offer the customer a deposit account. Identify subsets of potential customers to whom you can offer products or services that would accommodate their needs. Once these prospects are identified, apply individualized campaigns to them and make sure you emphasize the advantages of solutions that precisely meet their requirements.

Another approach is to target high-value customers by using purchase history, credit score and/or other behavior data to determine the next best product to offer each customer.

And finally, banks can win business away from competitors. Identify customers who have an investment or mortgage with a competitor, and approach them with a better offer once the loan payment or investment amount is known. This data can be used to win new business from existing customers and yield a lower customer acquisition cost for the new revenue.


Katie Horvath is chief marketing officer of Aunalytics, a data platform company that works with community banks to accelerate their digital transformation.