Y U So Mad?

A New, Revolutionary Way to Search the Web


Ever fallen in love with an item, such as a bag, shoes, or even a coffee maker someone else owned but didn’t know what the name of it was? When that happens to consumers, wasted time will be spent across internet search engines in a vain attempt to find the appropriate keywords to locate an item. An article published in MIT Technology Review describes a technology that could possibly be an answer to these frustrations. A company called Slyce has created an image recognition technology that can analyze an image and put shopping results for similar products conveniently into the hands of the potential buyer. This could possibly be a game-changer for consumers and companies alike.

The article highlights Pinterest and Shoes.com as companies taking advantage of this technology. When viewing a pin, Pinterest users can click on the visual search tool in the upper right corner of the image. A moveable and resizable box will appear on the original pin. The user can easily maneuver this box over any part of the image. Pinterest will show the user similar pins to the highlighted selection. On Shoe.com’s Canadian store, the user can utilize the visual filter to select the perfect shoe. Consumers are shown twelve shoes and pick the one they like the best. This selection brings up eleven similar shoes, which they can keep selecting from until they find the best match. The article explains that while the technology has a long way to go, some CEOs, such as Roger Hardy of Shoes.com, are very optimistic about the potential of this technology to boost company sales.

Image Recognition Will Forever Change Retail


Imagine going out with a friend and noticing their handbag. It is unique, like nothing you have ever seen before. Unfortunately, she received it as a gift and, therefore, has no idea where to buy it. A simple picture with a camera phone and voila, there it is, complete with a buy button. Two seconds later and it is on its way to its proud new owner.

Sound like something out of a science fiction movie? It is not, nor is it a technology that is way off in the distant future. It is called image recognition, and it is here to revolutionize the way retail is done.

Instant gratification is the buzz phrase of the century. We shop from home. Pay our bills online. We can even order a pizza simply by tweeting an emoji. Slyce is a pioneer that streamlines the way retail is done and takes our need to be instantly satisfied one step further with image recognition technology.

It is not just the end-user needs that are being met by immediately being able to purchase the things they see and love. While this will obviously add countless dollars to the bottom lines of merchants everywhere, the technology goes much further than that. Instant image recognition and tagging can be used on sites like Instagram to add product hashtags and information. The proprietary system even adds in marketing recognition with exact matching to print materials and billboards to generate even more sales on the fly.

Slyce’s slogan is “See it. Slyce it. Buy it”, and it is that simple. Gone are the days when an interested shopper had to enter keyword after keyword to find ‘it’, often to no avail. Visual search is the method of processing an image and its many attributes into a cohesive search engine of products with stunningly accurate results. It keeps getting better as well with the addition of more products.

Neiman Marcus is a retail pioneer giant that is utilizing visual search. The company added the technology to their app, initially testing on shoes and handbags in 2014. CMO Wanda Gierhart said the company wanted to be the first to bring it to the market, knowing the impact this breakthrough is going to make in the marketplace. While it augments regular search instead of replacing it, she says that the overwhelming response is a positive one, with customer feedback being one of complete amazement. In fact, the initial testing was so successful that the luxury retailer has added their full line of products to the ‘Snap. Find. Shop’ section of their application. With a reported 95 percent accuracy rate on the app, who could argue?