Founded in 2010, start-up Geoloqi offered smartphone users and developers an interesting proposition: What could your app do, if it knew where it was? And, what’s more, if it could transmit that data to servers programed to analyze the information according to specific rules?
Civic authorities, for instance, could notify citizens about events such as road closures or local emergencies based on their past locations or routes to work. Realtors could message prospective home buyers when their search criterion matches a house near their current location. And retailers could send offers to consumers—either as they entered the store, or passed it by.
Hence the buzz surrounding Geoloqi’s acquisition by geographic information systems (GIS) specialist Esri, the 800-pound gorilla of the location analysis market. Couple geospatial data to real-time location data and all sorts of things become possible.
“Esri is very good with adjectives, and we’re very good with verbs,” says Geoloqi co-founder and chief executive Amber Case, whose new title is director of Esri’s R&D center in Portland, Oregon, where Geoloqi is based.
Translated: Esri provides lots of ways to describe people, places and things—and for its part, Geoloqi has lots of ways to calculate and communicate place, journey time, speed and dwell time at a particular location. All continuously pumped out into the ether by the user’s regular Android or iPhone smartphone.
It takes a moment or two to get one’s head around the implications of this, concedes Case. Consider a hypothetical smartphone user about whom nothing is known. But each day, between the hours of sunset and sunrise, they return to a particular location in a residential area. Bingo: That’ll be home. And each day, they travel to a particular place, and stay there for eight or nine hours. Bingo, again: that’s where they work.
Throw in their route between the two places, regular stopping off points, and the time of day that each journey is typically made, and it’s possible to richly populate a picture that was previously virtually a blank canvas. Almost as an aside, Case throws in the fact that her Geoloqi co-founder Aaron Parecki has been continuously transmitting his present location at four-second intervals for four years—and has used the insights gleaned to inform a lifestyle-enhancing relocation.
All of which is neat, but is it useful? And profitable? And can it be ubiquitous enough to make a meaningful impact on the world—given that at present, Geoloqi’s users must consciously ‘opt in’ by downloading the app?
The short answer to all these questions is probably that the jury is still out: Case remains close-lipped about actual real-life use cases, and named customers. But those customers do exist, she insists—and one, from her vague description of it, would seem to be a government body using the Geoloqi-Esri combination to generate alerts if employees stray into dangerous areas. Indicative pricing for the Geoloqi app in such a corporate context, she adds, is $50 per person, per month.
Yet, even when forced to fall back on Geoloqi’s hypothetical examples, it’s still possible to see the logic behind Esri’s acquisition, and how putting the two businesses together creates synergies difficult to replicate through other means.
Take, for instance, a shopper entering a store such as a Home Depot or some other mass-market outlet catering for a wide demographic group. With dwell-time analytics providing accurate insights into the shopper’s home address, and Esri’s rich socio-economic contextual databases able to turn that address into a likely income bracket, it becomes possible to target that shopper with offers and information targeted to their particular income bracket, from the moment that the shopper enters the store.
And—here’s the real beauty of it—all without the store knowing anything else about the individual in question. They don’t have to be in a loyalty program, and nor do they have to have a mobile wallet.
“For us to succeed certainly doesn’t require mobile wallets to fail,” insists Case. “The use cases are very different: we have applications far outside the retail experience—public safety, forestry, route planning, and the general provision of service-related information in a location and dwell-time context.”
But if mobile wallets aren’t a roadblock, app adoption is—because for dwell-time enhanced location analytics to become pervasive, location-transmitting apps will need to be far more ubiquitous than they are now.
“Such apps don’t really have much utility in and of themselves,” says longtime Esri watcher Jonathan Raper, a visiting professor at City University, London, a former editor of the Journal of Location Based Services, and co-founder of Placr, a location-based transport information provider. “Longer-term, the technology must be baked into other technology services that people do find useful.”
Presently, he points out, location largely belongs to Apple and Google—the big beasts in consumer-centric mobile mapping, with consumers giving away that location information for free, in exchange for utilities such as Google Maps.
Yet longer term, that can’t be taken for granted, Raper says. Dwell-time analytics and similar location-based intelligence are simply too new for either consumers or technology companies to be able to put a firm value on it. But as the technology matures, that value will become clearer.
“Location is going to be a pervasive and commoditized property of everyone’s lives,” he sums up. “The question is: Who owns that location data?”
Freelance writer Malcolm Wheatley lives in Devon, England, and can be reached at firstname.lastname@example.org.