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How banks and credit unions can grow big by thinking local

2025/04/11/06:22
in Banking
Reading Time: 5 mins read
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How banks and credit unions can grow big by thinking local
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Smaller financial institutions must scale nationally to compete with megabanks and fintechs. Research by Lisa Nicholas at Vericast reveals that consumer financial search behaviors vary dramatically even between neighboring communities, creating opportunities for community banks to leverage their local presence. By analyzing hyper-local search patterns and tailoring thousands of targeted campaigns instead of generic national ones, smaller institutions can turn their local knowledge into a competitive advantage.

For years, smaller and mid-sized financial institutions have been given the same message: Raise your digital game, get bigger, and try to compete nationally. That’s long been the mantra for banks and credit unions that want to compete both with digital-first fintechs and deep-pocketed nationwide banks.

But what if the better advice is to go in the opposite direction?

Here’s the state of play: Community-based banks and credit unions are squeezed from both sides — the scale and spend of the megabanks on one, the speed and UX acumen of fintechs on the other. Even some large institutions are scrambling to keep up, launching their own “in-house development mega-centers to fend off maturing fintechs,” McKinsey & Co. reports. As for smaller institutions, EY suggests they should aim to double their market share by “embracing the digital marketplace infrastructure model” and leaning into their trusted customer relationships.

But Lisa Nicholas, Senior Vice President at Vericast, wondered if there was a different way.

She started by analyzing search engine behavior, aiming to understand how financial institutions could improve their digital marketing. What emerged from the data was something bigger: a pattern of regional nuance that challenges the idea of “the American consumer” as a uniform group. Just as consumers in Ireland shop differently than those in Greece, people in New Jersey search for financial products very differently than people in Texas.

And the phenomenon proved even more granular than that: The search terms used in, for example, an urban zip code could vary greatly with a next-door suburb.

What Nicholas discovered reframes how banks and credit unions should think about growth. Instead of chasing scale for its own sake, many institutions could grow more effectively by thinking hyper-locally and marketing accordingly.

Nicholas’s search-data analysis led to the creation of a new Consumer Demand Index — a resource to capture and activate local-market interest data and insights. The project also gave rise to a practical framework for rethinking digital financial services marketing, starting with why hyper-local matters, and advancing to what the data reveals and how to act on it.

The Why

At first glance, it seems logical for financial institutions to take a national approach to marketing. After all, Google controls more than 87% of search and, when combined with Bing, Yahoo and DuckDuckGo, the top four search engines account for 99.5 percent of all search.

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But Nicholas found that by zooming in, more opportunities revealed themselves. By analyzing search behavior, she developed a scoring model that could estimate opportunity size by product, zip code, and even specific product features — such as whether consumers are more drawn to low interest rates or rewards.

“What if you could have thousands of campaigns instead of just a few?” she asked.

Search data can reveal which cities or states are generating search activity for which specific products, where your products are winning and where you are losing market share — invaluable insights for deciding where and how to allocate your marketing budget.

The What

Silver Spring and Baltimore are only 32 miles apart, but when it comes to how residents search for financial products, these Maryland towns are worlds apart.

Building the Consumer Demand Index, Nicholas found dramatic differences in behavior, even between neighboring communities. By reverse-engineering search patterns across products like checking accounts, credit cards, mortgages, and financial planning, she uncovered how deeply local these behaviors are.

“If you want to be hyper-local, and you want to really resonate with your community, you need to understand how the people in your community are engaging with search,” Nicholas said.

In urban Baltimore, for example, search tends to be broad and value-oriented — top terms include “free,” “quick,” “low interest,” and “no-fee online banking.” In contrast, for residents of suburban Silver Spring, searches are more focused, often seeking specific credit cards by name.

Search trends also vary by age group. Younger consumers, for example, rarely search for terms like “rewards checking” — and some may not even be familiar with the concept of a checking account. But they do search for the specific benefits a rewards account offers. As Nicholas pointed out, targeting those more granular search terms is far more effective than relying on broad product labels.

The How

Community-based financial institutions already hold a key competitive advantage: local branch presence. And in a digital world, that physical footprint doesn’t have to be a limitation — it can be a strength.

Using modern tools like artificial intelligence, community-based FIs can create and launch hyper-targeted campaigns at scale. Instead of running a few generic ads, they can deploy thousands of tailored messages that speak directly to local needs and preferences.

To make the most of this approach, institutions should optimize local ads and listings with real photos of local branches and team members and highlight their involvement in community-related sponsorships and events. These human, place-based touches build trust and relevance.

Search engine data can guide marketers not just where to focus your efforts, but when to so. While banking follows an overall seasonal pattern — slow in January and February, picking up in March, and peaking in August or September — local patterns diverge. But search data also reveals local peaks and troughs that can inform specific campaigns. For example, in college towns, financial services-related searches spike in August as students return to campus. That’s an opportunity to target relevant products at the right moment in the right place.

In some rural areas, where search volume is low or inconsistent, digital may not be the largest investment — direct mail still plays an important role in effectively reaching consumers.

Zooming out, the think-small approach may also have an amplifying effect on the core business models of smaller financial institutions by leveraging their local brand recognition and their deep-rooted market knowledge.

Consider mortgage underwriting: Where a national institution might be all about counting baths, bedrooms, square feet and acres, a local financial institution brings detailed insights about location too. They’d know about the views and the distance from amenities — and be better able to put comps in context.

Search engine marketing can yield similar opportunities, at scale. The key is to combine the power of local insight with the power of granular data. With access to hyper-local, granular data, banks and credit unions, especially small and mid-sized ones, can turn their ground-level knowledge into a scalable advantage.

Source: THE FINANCIAL BRAND

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