In addition to the beacon technology, such as Apple’s iBeacon, that enables retailers to locate, track, and interact with shoppers as they move through stores, the latest development in geolocation relies on social media information to make appropriate recommendations to customers. Specifically, the technology embedded in the Flayr service uses reviews and ratings issued by members of a consumer’s social network, combines them with the user’s own personal information, and produces suggestions of things the person might like, as well as convenient places to buy them.
This extension of geolocation technology creates two main benefits for retailers and consumers. First, it makes push marketing efforts more pertinent and timely. Rather than annoying shoppers with unappealing discounts for products that appear unrelated to their lifestyles, Flayr can determine whether each person prefers water or snow skiing—based on vacation pictures posted to social media or hotel bookings—and provide offers accordingly.
Second, consumers walking by a particular store see not what the retailer wants to sell them but rather what their friends think they should buy, according to their tastes, preferences, and reviews. Thus the offers should be better aligned with the tastes of not just the consumer but also his or her reference group and influential others. The virtual shop window provided by Flayr also allows consumers to bring up the recommendations later, after they get home for example, and make their purchases then, when they have the leisure to do so, rather than having to do it on their lunch hour trip to the mall, for example.
Such capabilities, if leveraged effectively and appropriately, seemingly could give even Amazon’s remarkably accurate recommendation algorithm a run for its money.
What geolocation models are being implemented by retailers to encourage purchases while customers are near or in their stores?
Source: Serguei Netessine, Karan Girotra, and Christoph Pennetier, INSEAD Knowledge Blog, November 3, 2014