The fact that smartphones are perfect surveillance devices has been kicked around for a long time. And the data are immensely useful in B2B.
Wolf here: Most of the discussions center on how smartphones spy on their users in order to bombard them with the most effective ads and sell them more stuff. But there are other aspects to their spying that have been commercialized for entirely different purposes, where this user data is being used in actionable behind-the-scenes business-to-business dealings. So here is an example of how immensely useful the consumer data is in commercial real estate…
By John E. McNellis, Principal at McNellis Partners, for WOLF STREET:
Geofence: A virtual boundary set up around a geographical location, such as a shopping center or retail space.
Owning retail has been challenging since the Great Recession. You likely know the reasons why: overbuilding, the internet, rapacious private equity, too many lackluster tenants. You also know that every move you make—every breath you take—is recorded by your mobile phone. This latter circumstance has allowed a clever company, Placer AI, to develop the most useful tool for commercial real estate since Hewlett Packard introduced the HP-12C in 1981. (A phenomenal financial calculator, the 12C has become the abacus of our time, used by a slowly dwindling number of mandarins).
While Placer’s software is no doubt breathtakingly complex, its tool is—in essence—as simple as a bouncer counting a nightclub’s patrons with a clicker. Placer allows one to set up a “geofence” around a shopping center, a retail building or even a tiny tenant’s space and then calculate that finite area’s walk-in traffic by counting the phones crossing its threshold. By using those phone visits and an algorithm or two, Placer delivers an accurate traffic count of the geofenced area. A Swiss Army knife looks like a spoon compared with the multiple uses this traffic count offers.
On offense, a landlord can use Placer to prove her center has more foot traffic than, say, three competing centers and thus entice potential tenants to lease her vacant space. She can use this data to figure out the “path to purchase”, that is, where her center’s customers are coming from and, incidentally, where they live. (If your phone stays put long during the day, the algorithm says you work there; at night, that you live there.) With this information, she can approach a tenant already in the trade area, show it’s getting no traffic from a key zip code and argue that it should add a new store at her center to fill that void.
On defense, it works like this: The tenant says, “I have no customers, I can’t pay rent.” The savvy landlord replies, “Actually, Placer says your foot traffic is fine. Pay up.” Or when it comes time to renew a lease, that multi-billion dollar purveyor of coffee says, “You need to drop our rent by 20 percent or we’re walking.” You hand over the Placer data…