Think about how you shop for, say, new shoes.
Do you head to a mall and amble in and out of several stores, browsing the racks and maybe trying on a few things before settling on one or two items to buy? Do you remember that some stores have a weekend sale planned, and thus save your shopping trip until then? Do you just go online? Groupon? Do you get bedazzled by the array of things on offer and give up, darting to a coffee shop for solace? I suspect it's a variation on all of these plus more, because that's how most of us shop now. But that's about to change.
Store browsing is fun for some, tiresome for others but it's very often a tale of accidental self-discovery of something you'd like to buy. Advertisers and other enterprises like fashion magazines have long attempted to help you discover things you'd like to buy, but it tends to be very narrowly focussed—promoting just a few articles that represent the new look for this season.
That's been changing of late now that we're all used to having the mobile web and, more recently, digital editions of magazines in our smartphones.
But for a leap forward, check out Snapette, a digital fashion app. Launched in 2011 as a social network for women to "share images of their favorite fashion finds" it's just been completely overhauled as a new app that does something rather more powerful. The company is even heralding it as the "first location-based shopping application." It works by delivering information to the shopper based on location data. If it detects you're standing in a shopping district in New York City for example, it'll serve up to you information on items available in nearby stores as well as special offers, so you can work out if there's anything interesting in a store before you go in. Simultaneously, the app is a discovery engine because it may reveal to you something in a particular store that really appeals to you, even if you habitually never shop with that retailer.
There's also the ability to browse to discover fashion items by trend (locally, and internationally) or by brand. Meanwhile the most powerful bit is that "brands can also send real-time notifications to potential customers already shopping nearby with special discounts and the inside scoop on exclusive one-of-a-kind pieces." In other words, stores—or brands, knowing which stores their items are stocked in—can actively ping users of the Snapette app with a pop-up notification that says "Just in: New stripey green socks!" (Hey, they can look good with the right outfit!) Such notifications will excite consumers, drive sales, and drive foot traffic too.
Let's consider a couple of the subtleties in this idea. Firstly, the app may yield a very different kind of shopping experience: You may consider starting your shopping by sitting down in a coffee shop and using it to discover if there are any products or special offers nearby. Secondly, there's a ton of money to be made in the act of helping you to discover things you may like to buy. Snapette itself makes money by inserting itself into your shopping trip as a discovery agent. It relies on both user buy-in and brand/store adoption, without a userbase the app's makers would have no commodity to sell to their advertising partners, and without ubiquitous product placements and active participation from stores and brands then users would fall out of love with it. But it's likely to be closely followed by many other apps of its sort, perhaps evolving from services like Yelp—because if they make themselves the shopping app de rigueur, they may stand to make a lot of money by changing the entire shopping experience.
And simultaneously there's a booming technology that will help the precision of location-based "discovery" shopping—indoor GPS. Google and other companies like Apple have made special effort to try to invent indoor navigation systems, using data sources like Wi-Fi signals to replace GPS (which really doesn't work indoors) and user-submitted maps. But a new system from Duke University dubbed UnLoc does something even cleverer, because it uses "invisible landmarks" to help a smartphone work out where it is, and it doesn't require the same sort of wardriving system that Google's promoting. It also uses less battery power because it works out the landmarks using the phone's motion sensors—which react as their owners move through a space, or go up an escalator—in combination with sensing Wi-Fi dead spots or 3G signal drop-outs. Its inventors tested it out on campus and at the Northgate shopping mall in Durham, because they've already envisaged its use for shopping apps, and found it could locate phones to around 1.6 meters in accuracy.
Which means the next-generation of apps like Snapette will not only be able to alert you to nearby sale items, but also steer you directly to where it is—inside a store—or to direct you around a large shopping mall or department store. And with one more step it's possible to imagine a system like this seamlessly integrated into something like Apple's Siri or Google's Glass.