Instant coffee, instant noodles, instant entertainment and instant answers – it’s the age of instant gratification. Thanks to the Internet, we’ve become used to having instant access to whatever meets our fancy. When was the last time you really racked your brain to remember the name of that song you were talking about with your friends? It’s probably been a while. We bring together the few sparse details we remember and rely on the power of the Internet to give us the answer since it has millions of songs tagged and indexed.
A similar movement is taking place in the world of shopping. For the past few years now, the momentum has been building for image recognition technologies in commerce. The fashion and apparel industry have been early adopters of the technology in order to completely redefine the way that consumers search for products. Given the proclivity that people have for taking pictures on their smartphones (the fact that “selfie” is now an officially recognized word is testament to that), it was only a matter of time before the tendency to take pictures was monetized in some way.
It’s a huge step up from QR code scanning, which also allows consumers to look products up online and purchase. But visual search is more fun, engaging and appealing to the common consumer. We call this Product Awareness – it is the capability to access, rich, deep and comprehensive product information in real time from the Web, sensors, and smart wearable devices.
Combined with mobile payment capabilities and the maturity of services like Apple Pay, this will end up being an extremely gratifying and delightful service for consumers.
In a nutshell, image recognition technologies allow shoppers to take pictures of things they like and then like magic, similar items from the Web are presented to them. This completely changes the frustrating situation of admiring your coworker’s new slim fit patterned shirt and then trying all different keywords to find the right one online, but never being content with the result.
Recently, companies like Macy’s and Neiman Marcus (powered by Cortexica and Slyce respectively) have enabled image recognition based search within their apps. So all you need to need to do it take a picture of that lovely handbag your friend has, and instantly get options to buy similar items sourced from the retailer’s entire inventory.
The application of image recognition can go way beyond just fashion and accessories. It can be more utility focused as well. If looking a AA battery at work reminds you that you need some at home, you can just take a picture, find it online and order it instantly. However, this is contingent on an app being developed to enable the search. This is what the Firefly feature on Amazon’s Fire Phone was trying to achieve. The phone may not have done as well as the anticipated hype, but the promise of the technology still prevails.
In a few years, this will become the norm. The ideal situation will be when matches are found from all across the Web and not just the app of the particular store that you’re looking at. This will mean that matches are being found from a much richer assortment. There are apps like ASAP54 that are trying to achieve that scale. Some day, there will be a universal database powering these apps.
Image recognition technologies are based on learning algorithms. As more people use them, the algorithm is trained to return products with more precision. This is the future of product search and discovery, and combined with the growing adoption of smartphones and mobile commerce, it’s a critical part of the commerce revolution.