Big data is part of everything from marketing to fraud detection these days, but surprisingly few credit unions use it to choose branch locations. That could put some credit unions at a disadvantage, experts said, because today even small cooperatives can capitalize on vast amounts of data – demographics, traffic patterns, geography and more – to find lucrative sites worthy of multi-million-dollar investments and long-term leases.

However, the gut is still mightier than the spreadsheet for most credit unions. Fewer than half the clients of the El Dorado Hills, Calif.-based Integrated Builders Group, which specializes in credit union building and design, have done any data-driven site selection in the last five to eight years, for example. Many rely on intuition instead, President/CEO Patrick Sende said.

Mike Goman, president of the East Hartford, Conn.-based Accubranch, which performs location analysis for credit unions and community banks, said his team often hears the same thing from credit union executives.

“We'll say, 'So how did you pick your last location?' They'll kind of look at each other and say, 'A guy submitted a location to us and, you know, we went out at lunch and parked and kind of stood on the corner and looked at each other and said there's traffic going by and there's a Starbucks, what do you think? Oh, you know, I think this is okay,'” he said.

Of course, big data isn't free. At Accubranch, site selection work often runs $10,000 to $15,000 for modest-size credit unions and takes six to eight weeks. A full network analysis from Integrated Builders Group starts at around $15,000 to $17,000.

But valuable patterns do emerge from big data – patterns Sende and Goman said demonstrate its competitive advantages. Here are some highlights.

1. The side of the road matters. Traffic data reflects consumer behavior.

“Being on the going-home side of the street is going to make a difference in volume versus being on the going-to-work side of the street,” Goman said. “We know people will stop into a credit union on their way home. They won't do it on their way to work.”

2. Work is more important than play. Daytime employment data is also a performance predictor. Having 200 workers within a five-minute walk of the branch probably won't boost branch performance, Goman noted. “On the other hand, if it's 1,500 people that are within a five-minute walk, then we know it's going to add something to it,” he said.

3. Some neighbors hurt performance. Certain kinds of tenants nearby could increase traffic 2% or 3%. Supermarkets are a good example due to their daily traffic, Goman said. But operating near a bar or pawn shop will likely reduce traffic by 2% or 3%.

“It's a negative image,” he explained.

4. Intercept locations are key. These spots prevent members from seeing too much of the competition, Goman said.

“If there's a stretch of road that has seven banks and credit unions, we really don't want our client to be at the far end of the traffic pattern,” he explained.

5. Certain sites create synergy. Combining data about different sites can also reveal opportunities, Sende explained. He recalled a client that was considering sites in two areas a few miles apart.

“The first area was an older demographic not really needing loans, but definitely from a high-deposit standpoint [they] could put deposits in. The second credit union was a younger demographic definitely in need of loans but a not much of a deposit-type base,” he explained.

Each site when considered on its own wouldn't have made the cut, he said, but together they created a symbiotic relationship.

“[The credit union] would have never known that if they had not done the analysis,” he said. “They were able to create a lot of value.”

6. Beware low rent. “It's cheap for a reason: It's not a very good location,” Goman warned. “Sometimes the most expensive location in a market is actually going to give you the highest return on your investment. Even though you're paying a lot for the location, your volume of business is going to more than justify that higher price. Don't think of it in terms of the cost of the real estate – think of it in terms of the productivity of the real estate.”