Everyone in the TV industry knows about the overnights. Such Nielsen ratings let executives know which shows are taking off and which aren’t. Perhaps that’s why TV is such a vibrant business. Some 65 percent of new shows are canceled every season, according to one estimate.
Other industries haven’t had this luxury. In particular, retailers often have to wait weeks to determine if a new product is taking off, if advertising is working, and if footfall traffic is rising or falling. When they find out, it’s often too late.
Technology is finally bridging this gap. By profiling mobile users in an anonymous and aggregated way that respects their privacy, retailers can get much greater visibility into their operations. Early adopters will have an edge over those who stick with the old way.
The Old Way
Retailers, of course, have always been intensely interested in foot traffic. The old method of getting a read on foot traffic was to conduct surveys. Such surveys — based on interviews with customers — often cost around $2,500 per store and would take several weeks to complete.
In addition, they were subject to human error. For example, if a certain portion of the respondents only spoke Spanish, and the interviewer didn’t, then those customers were undercounted. Furthermore, the data relied on customers who were compliant about being asked questions, ignoring those who refused to take part. That said, the data from surveys wasn’t bad per se. It was good for the time, but a new era is upon us.
The Smartphone Solution
Smartphone-based data doesn’t have the biases or issues like data from more traditional sources. Smartphone data comes quickly, like the Nielsen overnights, and its quality is also better. Using smartphone-based analytics, retailers can map out consumers’ paths to purchase. They can see where the majority of customers are coming from. If they employ the data across a few stores, they can identify which ones are doing well and which are lagging.
There’s other data as well. Retailers can see how much time consumers are spending in stores and where they’re going right before they visit a store.
There are myriad ways retailers can take advantage of such information. For example, the data might show that though there’s a lot of traffic, the number of people who purchase is relatively small. Or perhaps the average purchase is lower than it could be. The retailer can then tinker with various offers and new products to attempt to raise that figure.
Smartphone-based data can also assess the efficacy of an ad campaign. If the business is a fast-food restaurant, for example, then franchisees can tell quickly if a campaign for, say, a new sandwich, is prompting consumers to come the store and buy that item. Advertisers can also experiment to see what combination of media (TV, online, mobile, etc.) nets the highest amount of foot traffic.
In addition, smartphone-based data can give the retailer a view of the local landscape. If a competitor is doing particularly well, the data will reveal it. If a section of town seems to be getting a surge of traffic, then a retailer might consider opening a location there. Such patterns have typically emerged over a relatively long period of time. Now there’s a possibility to offer retailers a sort of heat map of the general area, exposing traffic changes as they occur. That data is much more useful and actionable.
Such nearly real-time data could present a paradigm shift for retail. Rooted in brick-and-mortar, traditional retail has typically been slow-moving compared to online. That doesn’t have to be the case though. With some 94 percent of purchases occurring offline, consumers clearly haven’t given up on brick-and-mortar.
With new visibility into consumer behavior, retailers shouldn’t either. Instead, they should take advantage of the opportunity to build a new, more reactive relationship with their customers.
Antonio Tomarchio is the CEO of Cuebiq, a location intelligence company that provides actionable insights about real-world consumer behaviors and trends.