Five growth strategies for finding your next high-performing location

Technology is leveling the playing field for restaurant and retail operators. The increased democratization of data means that powerful location strategy tools that were once only affordable for large chains are now accessible to even small businesses. At the same time, capabilities are continuing to race forward with more detailed, accurate, and transparent data that is backed by powerful A.I. and machine learning that help operators make smarter decisions and avoid costly mistakes.

Location intelligence solutions have reached that fear-of-missing-out moment, and choosing to not use the same tools that your competitors are using to identify the best location opportunities is creating greater business risk. In order to maximize the full potential of location intelligence tools, operators also need to rethink traditional site-selection models and adapt to process change.

Here are five tips that can help your business find its next successful location.

1. Identify “real” traffic counts

   

   High traffic counts are a big selling point for potential locations. But how good is that data you’re using? Historically, data firms have measured traffic counts by laying rubber tubes across the road to count cars. Yet it’s impossible to put those sensors at every intersection from coast to coast, which means that firms are relying on flawed data right out of the gate. Just because there are 50,000 cars driving past Main & Main everyday doesn’t mean the same volume of cars travel past the intersection six blocks down the road.

   Location intelligence solutions are throwing out old-school methods and instead using cell phone data. Cell phones provide extremely rich and granular data on traffic volume and patterns that include both vehicles and people. Phones that almost everyone carries these days are leaving bread-crumb trails of data that make it easier to pinpoint the volume of people in an area along with when and where they’re traveling.

2. Cotenants vs. competitors

   

   Restaurant and retail operators often view neighboring businesses as either a competitor or a complimentary cotenant. Traditionally, there has not been a lot of hard data to support that “friend-or-foe” mentality. But location strategy tools are now able to paint a different picture.

   There are many more synergistic companies out there than people realize. For example, a sandwich shop might view Chipotle as a competitor because they are fighting for the same fast-casual customer. The reality is that customers don’t eat Chipotle every day. That sandwich shop can benefit by opening near Chipotle and tapping into a customer base that wants much the same thing in terms of convenience, service, and price, but with more variety.

   Location intelligence tools can tap into data such as NAICS classification codes to identify nearby businesses on a macro basis and then drill down further to identify locations near other “like” businesses that have a similar customer profile. Location tools also allow an operator to look at that data to see whether those synergies hold up across different markets. Will the benefits of locating near Chipotle be the same in an urban Chicago market versus Suburban Nashville?

3. Ditch cookie-cutter models

   

   Chains often use regression models to forecast sales at new stores. The problem is that those “cookie-cutter” models try to draw the same conclusions on vastly different markets. For example, a restaurant operator opened a new restaurant location in Los Angeles, where annual sales were projected to hit $7 million. The restaurant flopped, making only half that amount and ultimately closed.

   So why such a big fail for a proven model? The answer is that what drives a Los Angeles location is vastly different from what drives a location in Chicago or Tampa or Des Moines. There are similarities, but it is difficult to drop the exact same model into different markets with different dynamics and drivers.

   In Manhattan, there is no parking. So parking is not a relevant variable in a sales model. But open a store in a smaller market like a Nashville or Charlotte, and a lack of parking could kill a business. Location strategy tools need real-time, dynamic modeling solutions that can take different market nuances and characteristics into account.

4. Gut check: use data to test instincts

   

   Site selection is a balance of both art and science. Those that have been in the business for years have honed strong “gut instincts” on what makes a good location. For example, if an operator is looking to add 20 new locations across Florida, the company probably has an idea of which areas are going to be on the short list.

   Layering data on top can provide more detailed insights into where to locate within those broader markets. Planning site selection without data is like taking a “shotgun” approach that can become very costly, whereas leveraging data helps maximize results. Including location data also helps to provide a cross-check in eliminating personal biases or opinions from third-party brokers and consultants.

5. Let the data tell a story

   

   Analysis paralysis is one of the biggest excuses for not embracing big data. People can be overwhelmed and intimidated by the growing mountain of data available today. Putting the work in to understanding data can seem like a daunting task. The downside is that if you don’t make the effort, you run the risk of opening a sub-par location.

   The good news is that even though there is more data than ever, it’s more transparent, centralized, and digestible. For example, SiteZeus can feed hundreds of different metrics into the same model to create that single source for location-analysis reports. People can fight technology all they want, sticking with their flip phone and avoiding Facebook, but the reality is that data analytics is the future of optimizing location strategy, and there is real power in letting the data tell the story.