As humans, we’re extremely visual creatures. In fact, 90 percent of the information we receive is visual, and we can identify images almost instantaneously (fewer than 13 milliseconds). The goal of visual search is to use artificial intelligence (AI) to match that recognition and perform accurate searches. Visual search is naturally the next step in AI’s evolution towards human-level thinking.
In our visual landscape, text-based searches are becoming inefficient. If a coworker is carrying a bag you really love, but don’t want to ask where they got it, you could type in a description and hope for the best. But imagine if you could take a picture to find out what brand it is, where to get it, and then find other similar bags. That’s what visual search aims to do.
How does visual search work?
Visual search is fundamentally different from text-based searches in that, with visual search, the image itself is the query. When we, as humans, look at an image, we don’t see an assortment of points, lines, and colors. Instead, we see the image as a whole and instantly identify that object.
Visual search aims to teach machines to do the same by using AI’s neural networks and machine learning technology to identify images. Once those images are identified, the technology can go further by connecting users with retailers, show similar images and products, and provide consumer reviews.
Why use visual search?
According to a Slyce study, 74 percent of respondents noted text-based keyword searches don’t sufficiently help them find the products they’re searching for. This is where visual search comes in handy. With it, users will no longer need to type in a product or item description, but can instead enter an image directly to more efficiently complete their search.
Pinterest’s CEO Ben Silbermann even said, “the future of search will be about pictures rather than keywords.” Why? Because visual search can quickly and accurately answer questions like, “What are some affordable alternatives to these sneakers?” and, “What is this actor’s name?” That’s why 62 percent of Gen Z and Millennial consumers want visual search capabilities more than any other new technology.
How does video fit in to visual search?
It’s hard to talk about visual search without talking about video. The “3 V’s” took center stage at CES a few years ago (voice, visual, and video) and already, sites like Amazon are incorporating video into their visual search technology, allowing companies and people alike to upload a video and have items in that video be quickly recognized by their AI.
Technology like this is leading to a world with video catalogs, video search, shoppable 360 video, and point, shoot, and buy technology. It’s happening sooner than you might think!
What industries benefit from visual search?
Ecommerce and retail are the most obvious industries for the implementation of visual and video search. From clothes, to home decor, you can take photos of the items you want, and use visual search platforms to identify those products, and even locate special sales and offers.
However, ecommerce and retail aren’t the only relevant sectors. Visual search could prove to be extremely useful in the travel industry, as well. If you’re on vacation in a foreign country or a new city, for instance, and want to learn about the architecture or a specific monument, you can take a picture or video and get all the information you need.
Additionally, visual search can assist with language barriers. With programs like Google Lens, photos or videos of signs or pages in a foriegn language can be immediately translated on your screen. This can make international travel less stressful and allow you to enjoy things you may have missed otherwise!
How is visual search being used?
According to an eMarketer report, nearly three quarters of consumers search for a visual prior to completing a purchase. Though visual search can streamline the search process and is important to users, only eight percent of retailers support image searches at this time. However, major search engines and ecommerce sites have already noticed its effects.
For example, Pinterest Lens amassed more than 600 million monthly searches in 2018. Following Pinterest’s success, companies like Google, eBay, and Amazon have followed suit and launched their own visual search technologies. Even Snapchat has begun enabling Amazon product links related to users’ photos.
How do you keep up with visual search?
The growing trends in this search technology means businesses should capitalize on the opportunity and optimize their sites for visual search. Here’s how.
Include images in your sitemap.
It’s essential to build up a large image library. Photos should be original (avoid stock photos), clearly displayed, and well-organized. That way they can be easily scanned by visual search engines.
Optimize image size.
Images should be the highest quality they can be without slowing page load speeds.
Name each image.
Giving each image a unique name is important. Descriptive names alert crawlers what the image depicts if visual recognition fails.
Include image captions.
Like names, captions are beneficial because images aren’t always identified right away. Providing context can help search engines understand. According to Poynter Research, captions see 16 percent more readership than body text.
Utilize alt tags.
Alt tags, though similar to file names and captions, are a fully textual alternative to images. For example, if a browser can’t render an image, the alt text tells the crawler what it is.
Combine with text search.
Though it seems text and visual search are in competition with each other, you’ll gain more visibility by combining the two.
Increase your social media presence.
Twitter, Instagram, Snapchat, and other social networks are some of the most important platforms for visuals. Organizing photos will optimize visibility.
Integrate with chatbots.
Chatbot technology has become one the most important emerging technologies. If a chatbot includes visual search, you can take a photo and then be prompted with questions like, “Do you want to know what this product is?” or “Do you need more information?”
AI’s machine learning and neural network capabilities allow search engines to identify images, perform searches, and provide users with suggestions. Visual search can be used in multiple industries from retail, to travel and can make the search process more efficient and effective. Though visual search hasn’t quite reached its peak yet, it has quickly become an integral part of brand visibility.
By Amanda Peterson of Enlightened Digital