Let’s get visual: Shopping from within images
Columnist Christi Olson outlines exciting developments that bring image search and shopping together to enhance the search experience for users.
A little over a year ago, I published an article on the importance of data feeds as influencers of future search:
Structured data feeds front-load the search engine results pages (SERPs) with user-rich information, creating a new search experience for more personalized, localized and actionable results.
Fast forward to today, and we’re seeing innovation in visual shopping experiences using AI to identify an element within an image and show you similar images, similar products and where you can buy said products. From movies to local business listings and voice search results, structured data — both on websites and in data feeds — is playing a central role in moving search forward.
The search engines and retailers continue to pursue newer, better — more structured — ways to communicate and for consumers to take action. This includes the transformation of image search into a visual search which takes shopping to a new level, as searchers can now use images as query inputs. It’s a win-win — searchers can easily shop related images, and retailers can reach even more customers through the ease of shopping feeds and structured data.
How visual search works for shopping
Have you ever looked at a picture, magazine ad or celebrity photo and wondered how you could find out more about a particular item? With visual image search, you can search, browse, and then discover where to purchase products within a few short clicks. Here’s how:
In the example below, a Bing search has been conducted for “Oscar dresses,” and the searcher has clicked on the “Images” tab. There, the searcher can browse through the images; if the store icon appears in the top left corner of the image, it’s signaling that a retailer sells this particular item. (Note: this functionality is specific to Bing, my employer, at the moment.)
After clicking on an image, the searcher is able to view an assortment of related products or images. The product details are pulled from a variety of sources, ranging from the structured HTML on the page to shopping feeds. From here, users can shop similar items without leaving the image results page.
Searchers can then click on the store listing, which will direct them to retailer sites where they can make purchases.
Searchers can also zoom in on pictures to search particular sections of a photo. For instance, let’s say I fall in love with the belt on Brie Larsen’s Oscar dress. I click on the photo in search results, then click the search icon within the photo. This allows me to adjust the search box to zoom in on the desired area. From there, it refines the results of similar products and images.
The results return a wide array of related images, which I can then further browse or shop.
My examples above are clothing-based because I love to peruse the web for what to wear; however, the ability to home in on an element within an image to find that product or similar products is endless. There are numerous opportunities for retailers to have their products appear and shine within image search results, whether in fashion, babies and children, automotive, gardening, home decor, outdoor activities or sports.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.