From scanning consumers’ Pinterest boards to letting them upload their own photos, new image-based methods of searching for items are enhancing the digital retail experience

The proliferation of options for online shoppers might seem like a good thing—until consumers are lost among too many choices with limited help in narrowing down the possibilities to what’s most relevant or interesting to them.

This is why online retailers are now investing in layering visual-recognition capabilities into the digital search process, aiming to help shoppers find the products they’re after by simply snapping a photo. Here’s how three major brands are implementing visual search tools that put more agency into the hands of consumers and help them find exactly what they’re looking for more efficiently:

Target is partnering with Pinterest to integrate its visual search technology known as Lens into Target’s apps, allowing Target shoppers to snap a photo of any product, and then find similar items available for sale at Target. When a consumer sees something they like out in the real world, they can simply take a picture with Pinterest’s app and then find out additional information, like where to buy the item, how much it costs and more. Lens will help connect online and mobile shoppers to Target products, even if the photo they snapped is not something found at the retailer itself.

West Elm
West Elm’s Pinterest Style Finder is an online AI tool that scans Pinterest to recommend furnishings. To start, shoppers upload pictures for inspiration. Then, using a neural network-powered visual recognition service provided by New York-based AI startup Clarifai, the Style Finder tool gets a sense of style from a shopper’s or anyone else’s Pinterest board of images and returns a shortlist of furniture, rugs, curtains, mirrors and other items in about 10 seconds. West Elm Pinterest Style Finder is an extension of the in-person service West Elm provides at its 100 stores in the U.S., Australia, Canada and the U.K.

eBay’s two visual search tools allow online shoppers to use photos they snap, have saved on their phone or even those they find while browsing the web or other social networking sites, in order to find matching products from eBay’s catalog. The tools, Image Search and Find it on eBay, leverage advancements in computer vision and deep learning, including the use of neural networks.

Image Search allows mobile consumers to take a photo of something they want to buy or use an image saved to their phone’s Camera Roll in order to shop eBay. The website will then return listings of items that are either a close match or at least visually similar to the product you’ve photographed.

Find it on eBay allows shoppers to start their search on any social platform or while browsing the web on a mobile device—like reading a favorite blog or website, for example. They can then “share” an image they find with eBay, and the app will surface similar listings.

Marshaling consumers’ own images and integrating visual searches into their online shopping services generally is just one way that brands are improving user-friendliness and optimizing the customer experience. For more information on how increasing incorporation of visuals is improving how people engage with brands online, see PSFK’s report Camera As Consumer Engagement Tool.

Lead image: hands using smartphone stock photo from ImYanis/Shutterstock

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