It’s weird to think about now, but just a few years ago, the technology behind things like Google Glass still seemed unlikely to most of us — heck, even the functions of which our smartphones are now capable would’ve been deemed flukes in the universe’s timeline: products of luck rather than human-backed technological advancement. Nowadays, however, we use our smartphones to do things like take pictures of what we want to buy and match those with products online. Or, maybe, you don’t do this…because, well, when it comes down to fundamentals: image recognition shopping hasn’t improved since the idea was first introduced by Amazon. Slyce hopes to change that through its advanced visual recognition technology, and it’s got the funding to do it.
With Slyce, shoppers simply use their smartphones to take pictures of a product they see, and be instantly presented with the item, or a similar item, in a particular retailer’s stock. Unlike the technology created by Amazon, Slyce allows users to take pictures of products in real life and free-form (as in: not in some kind of packaging; so, users can take a picture of an outfit that is currently being worn by a friend and see if a particular retailer can find that same item). Retailers can integrate the technology into their own native mobile apps, giving them the opportunity to match competitor products with something they themselves provide.
Back in 2011, Amazon introduced Amazon Flow, an app for the iPhone that utilized augmented reality to allow people to scan a picture of a product in the real world — say, a book or a DVD – and receive more information about that product through the app, allowing a user to price comparison shop. You probably didn’t even realize that Amazon Flow was a thing, though, because you (along with the rest of the world — myself included) were too busy bitching about Netflix’s price hike; even if you were paying attention, you probably didn’t see any additional utility from Amazon Flow than you would from simply manually searching for a product via fingers on your smartphone. While largely ignored by consumers, Amazon Flow was significant for its role in trailblazing the path into image recognition shopping. Currently, Flow’s features have been integrated into Amazon’s main mobile platform, and that’s probably a good thing considering its limitations, largely: because the technology relies heavily on optical character recognition (OCR) and logo identification; image recognition shopping via Amazon is limited to products in their original packaging.
Considering Amazon’s limitations, it’s easy to see how Slyce’s technology can cause incredible changes in the picture recognition shopping experience. And, it seems, people have taken notice. Last month, the Toronto-based company raised $10.75 in its first round of funding, adding on to their initial seed funding of $3.75 million from last May.
“Right now, retailers are having to rapidly adapt to the changing ways consumers are choosing to shop,” says Mark Elfenbein, Chief Digital Officer. “Visual product search literally puts the retailer wherever their customer is when they become inspired to buy a product, making the entire physical world a showroom.”
But, even with the success of Slyce and its more accurate and unbound visual recognition technology, that doesn’t necessarily mean that they will overtake Amazon’s lead in the industry – right? Well, in order to do that, the company would need to find a way to increase its influence and use among actual consumers (since, that’s where Amazon Flow’s failure can be sourced). Right now, Slyce is working with six of the top 20 retailers in North America, integrating their image recognition shopping technology into their respective applications; basically, give it one or two years (or even just a few months), and we’ll see Slyce on the forefront of visual recognition shopping.
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