High-tech traffic counters dig deep
Continued innovation in site selection tools is making it easier for franchise groups to identify high-traffic hot spots. In the past five years, site selection firms have stepped up their game in delivering traffic count data that is more accurate, timely, granular and hyperlocal.
Traditionally, companies have relied on Department of Transportation (DOT) data that tracks vehicle traffic counts along key roads, highways and intersections. That data is still a quick and easy way to identify busy, highly visible locations.
However, the old days of driving over a sensor on the road to collect vehicle traffic counts has given way to more sophisticated systems that leverage cameras, GPS location data, beacon technology and the Internet of Things to collect and analyze big data.
Where people move
Added to that, data firms are expanding the depth and breadth of the traffic data available. Urbanization has shifted the focus from counting cars and trucks to also include foot and bike traffic.
“That is getting to be more and more important than ever, because as projects become more urban and dense and rents are much higher, you want to spend your money where you are going to get the most amount of traffic,” says Spencer Bomar, a principal and lead of the Retail Group at Avison Young in Atlanta.
When Tom Blazer first launched eSite Analytics nearly two decades ago, drive time technology was still in its infancy. Data providers relied on static traffic counts that were of variable quality. “Now we have a great deal of empirical data about when and where people move and on what corridors,” says Blazer, CEO of Charleston, South Carolina-based eSite.
One of the key sources of that data has been smartphones. More than two-thirds of the adult population owns a smartphone, and people carry those devices with them when they drive, walk, shop or wherever they happen to go. There are a number of companies that collect data from the navigation apps and location based services on mobile devices. It is a bit reminiscent of Big Brother, but at least for now, the data is made anonymous by the companies who collect it.
“It doesn’t tell us who is moving on a demographic or individual basis, but it tracks crowds of people in general to identify key traffic patterns and trade areas,” says Blazer. The new wave of “movement analytics” is not just pinpointing key trade areas. It is able to hone in on where the best possible locations are within a particular trade area.
“If we know how people move, we know how we can help our clients be in the right place, at the right time, with the right product,” he says. The more detailed understanding of traffic patterns is valuable in high-traffic locations, as well as evaluating potential cannibalization of new stores.
Real-time traffic data
One of the biggest complaints about DOT traffic count data is that it can be dated and shows traffic flow in a general area. For example, a data collection point might be a mile or more away from a specific property address. San Francisco-based Motionloft is one firm that has developed technology that offers real-time, hyperlocal traffic counts.
The company uses computer vision-based sensor technology in a device that can be mounted in a variety of locations, such as inside and outside of stores, shopping malls, parking garages and sign posts. The device acts a bit like the human eye in that it “sees” movement within its wide angle lens. A computer program processes that movement and identifies it as a person or vehicle. It also tracks which direction people and vehicles are moving and how fast they are going.
Motionloft collects data in real time and communicates it via a cellular connection to an online dashboard. “The way that the industry has evolved over the past five to six years is that the real time nature of data is a critical component,” says Christopher Garrison, Motionloft co-founder and vice president of business development and sales. “You no longer have to request a report and get outdated data.”
Data that is now available 24/7 allows a business to evaluate traffic at specific times of the day that may be critical to the business model. For example, a restaurant that relies on big breakfast sales may be drawn to a location that has a high daily vehicle count. However, a more detailed traffic study can show how much traffic is passing by that storefront on any given day between 7 and 9 a.m.
Traffic tools continue to evolve
One of the biggest changes ahead is getting end users—restaurants, retail and service businesses —to embrace the new tools. Many franchise groups still rely on state DOT websites.
Accessing that data is free, and some operators don’t want or need to commission a separate traffic study on what they know is already a busy retail hub. Other operators are happy to follow the path of some of the bigger national chains that have already done the heavy lifting in terms of site analytics and traffic studies.
Yet businesses also recognize that DOT data doesn’t give a clear view of how traffic is moving within a trade area. “In my office in Charleston, there is a road in front of me with 60,000 cars a day. But, there is a stretch at my office that is a mile long where you can’t get off that road,” says Blazer. “So, traffic counts can be misleading purely as a database of points that show counts.”
Traffic count technology has come a long way in the past few years. Tools are more than just sophisticated people counters. Firms are offering more real-time information on where people are going, what they are doing and how much of that passing traffic stores are capturing in customers and sales. And there is more change ahead with innovation that opens the door further to include more demographic information and greater insights on traffic patterns and predictive behavior analytics.
For example, Motionloft is launching a new version of its sensor technology in first quarter 2017 that will be able to deliver purely anonymous demographic data on pedestrian traffic that will include gender and age groups such as children, adults and seniors.
Another big piece of site selection analytics is not just finding the people, but also gaining a better understanding of how those potential customers are behaving. What are people doing when they are around a particular property? Are they commuters in a rush who don’t have time to stop? Or, are people lingering in a particular area? To that point, there is more emphasis on tracking dwell time. “These are all different metrics that you can start to paint a picture with about the potential value of a location in the site selection process,” says Garrison.
The next step that can be layered on top is predictive analytics to understand customer behavior in a particular location and any seasonal trends. For example, when students head back to school there may be a significant downturn in traffic and sales at a particular location.
Another key trend for traffic count tech will be integrating with other data sets, such as point of sale data, demographic data and household data. “The more data you have and the more accessible it is in a streamlined manner, the richer story you can tell to the individual retailer or property owner,” adds Garrison.