In the age of analytics and informed decision-making, financial institutions have a largely untapped source of internal data. We know where our current customers live and operate their businesses, and we have access to internal product and service utilization. Given this wealth of information, how can community banks utilize it to improve marketing results and ROI?

With so much data available, it’s easy to lose track of the purpose. It’s crucial to first establish clear objectives and outcomes. In the current environment, most banks are focused on acquiring more customers and growing deposits. This is apparent from the lucrative offers from Chase, Wells Fargo and others, with incentives ranging from $300-$2,500. Their seemingly infinite marketing budgets more than rival those of community banks. Given this reality, every dollar of your marketing budget must be spent strategically; data should be the true North Star guiding your decisions to drive better results.

Despite the prominence of and focus on online account openings, proximity to a physical branch is still the best indicator of which bank someone will choose. In fact, more than 90% of new checking account openings originate in a branch. Therefore, we look at prospective households through two different models of convenience: demonstrated and predicted.

Demonstrated convenience is defined by your existing customer base and your recent opening successes. They are the households who likely find your bank convenient based on where they live; they are the neighbors of your existing customers. This is, in essence, lookalike marketing. If you map your existing customer base with the data you already have, you will find concentrations in neighborhoods near your branches.

However, recent developments in technology have redefined convenience. This opens a less obvious but equally valuable audience: people who may not live near your branch but commute nearby for work, shopping or dining. Since branch lobbies are typically open from 9 a.m. to 5 p.m., consumers often use branch services near where they work. This commuter audience displays what we call predicted convenience, and it expands the pool of potential customers beyond what demonstrated convenience alone may reveal.

For example, consider Norman, Oklahoma. Norman has a population of approximately 131,000 and is a major employment center within the Oklahoma City metro area. Major employers such as the University of Oklahoma, Norman Regional Health System and Johnson Controls support a substantial daily workforce, drawing inbound commuters from across the region and making Norman an important destination for workers in the area.

By leveraging GPS data, you can identify people who work or commute near your locations. This sophisticated data-driven geo-targeting model is designed to identify additional prospects with a high probability of selecting your bank. Once identified, you can target these prospects through an omnichannel approach to build and maintain top-of-mind awareness.

While we cannot create demand, we can create awareness and steer existing demand to specific locations. By leveraging both demonstrated and predicted convenience, your marketing can be more precise and effective, decreasing customer acquisition costs while driving a higher return on investment.