Have you ever noticed a declining trend in your landing page visits? Or an increase in product impressions but no clicks?
If your customers can't make out what a certain component of your image is, their trust goes for a toss and they trace their way back from your website. The inability to define an image results in a poor user experience. high-cost acquisition per lead and disturbed marketing ROI.
Consumers tend to judge products based on whether they visually like them or not. And sometimes they just fall for a perfect table they saw online but don't know its name. This is where visual search comes in - a technology that meets human nature.
Labeling the categories of your product images internally with image recognition software can build better visual experiences and enable website visitors to circle and search for any term or product they like. Let's learn visual search in detail.
Visual search is a computer-vision-enabled search technique that identifies traceable terms from images, videos, and other forms of visual content and runs a search on the web to categorize these terms. Powered by machine learning and image recognition software, visual search analyzes image pixels to categorize images for users.
The visual search follows the logic of optical character recognition (OCR) and query, key, and value technique of search engine to extract features from the search query and display image results. Visual search relies on either metadata or data samples of the input image.
These engines are useful to help customers search for uncategorized components in an image and find quick answers.
Visual search is a solution that fills the gaps where words fail to describe what the customer is trying to find. It identifies objects within an image and searches for other, similar ones.
Visual search engines utilize artificial intelligence and machine learning technologies, which means that such systems are constantly improving based on the experience they gain. In short, the more images a visual search engine has analyzed, the more precise it becomes.
The technology uses visuals as 'search queries,’ and analyzes shapes, colors, and sizes to find the best matching search results. Following the example of the perfect table, if you take a picture of it, a visual search can help you find and shop for either identical or very similar tables. It also analyzes image metadata or image samples to get more information and predict accurate search results for the user.
Do you know? The image recognition market will grow from USD 46.7 billion in 2024 to USD 98.6 billion by 2029.
It was back in 2017 when Ben Silbermann, CEO of Pinterest said “the future of search will be all about pictures, not keywords.” Since then, the industry’s key players have invested heavily in research to develop and improve their visual search applications.
With intelligent visual search benefits being incorporated into apps, websites, and prominent platforms such as Amazon, Facebook, Pinterest, and Google, visual search is irreversibly changing the search marketing landscape. Below are the eight most creative visual search examples that are trending in the market today.
Google’s visual search engine, Google Lens, has found wide application in everyday activities. Among others, it helps with:
Amazon has gone a step further and announced the visual search for their retail application. This update would help you purchase anything you see and search for the item on your app. If it is a new pair of sneakers your friend is wearing, or a coffee powder within a to-go cup, Amazon's visual search would make your lifestyle simple.
Source: Amazon
This feature would also allow you to select an image from your photo gallery and parse it to personalize your feed. One easy scan would not only describe the nature of the photo but also show more products in case the item has gone out of stock.
The idea is to enable visual suggestions for visually impaired or even generic audiences. Other features include text-to-image search, "more like this (to show similar items)", video search, and circle to search for an immersive shopping experience.
If you’re on Pinterest, you’ve spotted the tiny magnifying glass button located in the bottom right corner of every pin.
Source: Pinterest
It’s the Pinterest Visual Search Tool, which is a dream come true if you’re in retail and using the platform to market your products. By clicking on the button, Pinterest users can hover over a particular product pictured in the pin. Software like retail image recognition software is an important function for retail establishments. The visual search technology will pull up more content featuring that particular product, helping them to find the retailer.
As a marketer, remember to redirect to the product category if your product is not available anymore. Otherwise, you’ll miss out on potential sales.
Pinterest has recently upgraded its visual search engine by introducing the Pinterest Lens. The Lens feature lives behind the tiny camera icon within Pinterest’s search bar. Once you click on it, you’ll be able to quickly upload or take a photo, and Pinterest will pull up similar images for you. What’s more, the tool is now integrated with shoppable fashion and home product pins, redirecting users directly to the checkout page on the retailer’s site.
Pinterest also developed Shop the Look Pins, a free product-tagging tool for fashion and home decor. Anyone with a business account can manually tag items using a self-serve tool. The tags appear as small white dots. When users tap on one of the dots in a Shop the Look Pin, they’ll see more information, including pricing and availability, and a link to buy the item. It’s clear that this feature, combined with visual search, can bring tangible sales results.
Neiman Marcus is a high-end department chain that is expanding their image recognition capabilities in the product. They are integrating their online web e-commerce storefront with something called "Snap, find and shop". Users can click a snap and the visual search engine will pull up shopping suggestions for the audience.
They have partnered with a visual marketing firm, known as Slyce to create the upgrade of visual search for everyone to take advantage of the utility. Neiman Marcus has been able to amass wide attention and broaden user experience via categories of women's apparel, men's apparel, pet's fashion, and shoes and handbags.
Source: Rapyd
In collaboration with Amazon, Snapchat introduced a visual search engine in 2018. The general idea was to let users identify products just by capturing them within the photo frame, and easily order the recognized elements through Amazon.
In addition, the app allows users to scan barcodes to access product information. Once a product is recognized, the app displays an Amazon product card showing the item and similar ones along with their titles, prices, thumbnails, average review scores, and Prime availability. Users can simply tap on the card and order the product on Amazon.
Source: Endgadget
In 2017, eBay launched their visual search engine claiming that the technology would “make the whole internet shoppable”. The app offers two features: Find It On eBay and Image Search.
Find It On eBay allows the app’s users to upload images from any social media profile or web page. Once that’s done, the app displays listings of either the indicated item or other, similar ones.
Source: DataForSEO
With reverse image search, users can upload photos from their camera roll or take a photo at the very moment and apply the image to the eBay search bar. The app then displays listings that match the item in the photo.
Machine A has made news in the last couple of years with its augmented reality marketing (AR Marketing) for luxury shoppers. To activate it, users simply had to download the Machine A visual filter on Instagram and the 3D content would be overlaid on their physical surroundings.
These digital stores contained a query database for all the 3D items displayed on the shop floor. Along with displaying the price, runway edition, and other details, the 3D store also displayed quotes from famous cloth designers.
Source: YouTube
Content is king. You’ve probably heard that a million times. But actually, visual content is the true ruler. According to a recent report, 56.2% of marketers said that visual content plays an important part in their marketing strategy.
While creating your content strategy, you shouldn’t forget about its less amusing but crucial part, optimizing your visuals for better search results.
The image title plays an SEO role similar to blog post titles, and as in the case of blog post titles, it should contain a relevant keyword. It’s best to use either long-tail or location-based keywords. Long-tail keywords help your website’s ranking in Google.
The more precise the keyword, the better the chances that people with a solid purchase intent will find you in Google search results. For example, “mid-century wooden coffee tables” will give you better results than just “wooden tables”. Location-based keywords will display your content for users in a defined area, for example, “mid-century wooden tables in Florida”.
In simple words, alt text is what will replace your image in search results if, for example, a user’s internet connection is too weak to upload images. But alt text is more than that. Search engines use it to understand what your image is and how to rank it via SEO meta tags. So apart from your target keywords, try to use these 125 characters to describe the image as accurately as possible.
If the content management platform you use allows image descriptions, make sure to fill it in. Descriptions give you space to provide context for the image and further insights into what you’re offering. It should be compelling and consistent with your brand image. And include your primary and secondary keyword(s) for better crawlability and targeting.
Both size and format are crucial factors that affect website speed and can make your content load very slowly or not at all. It’s usually best to go for JPEGs; this format is small in size and does not compromise image quality. Use PNGs for images with transparent backgrounds. Keep in mind that image dimensions should not exceed the average desktop screen resolution, which is up to 2560 pixels in width in most cases.
These are the general, universal guidelines, but it is also important to optimize your content for specific media outlets. Before you even start to create your content, make sure it meets the guidelines of your target medium.
For example, on Pinterest, the ideal pin size is 600 x 900 pixels. When posting to social media, always look up recommended image sizes and remember to fit the style and contents of your visuals to every individual platform's audience.
Apart from the obvious benefit of optimizing for image search and better organic visibility, marketers have many reasons to be interested in the technology.
Following the example of recent buzz around OpenVerse and its creative common search to diversify knowledge and build ethical standards, visual search gives omni-sensory experiences for people to make the most of virtual worlds. You can also go for a long-term collaboration and incorporate AI tools into your offer. For example, if you’re in the fashion industry, you may think about partnering with tools such as Canto that generate outfit recommendations based on what your customers are interested in.
Look for apps and websites dedicated to your niche. For example, if you’re in the furniture industry, look into adding your product content to the virtual design program of Living Spaces, a visual designer tool that allows people to use their product base in visual projects.
Once you research trends using visual search, use your insights to reverse engineer the content creation process. Research-driven content creation is key to getting your products in front of valuable audiences – trends and competitive analysis will help you pin down the best practices.
Visual search has empowered businesses to deploy artificial intelligence on a larger scale and get the maximum return on investment out of it. Below are some trends sweeping the industries with the visual search adoption in 2024.
Visual search is empowering B2C and B2B brands to deploy computer vision capabilities to replicate human sentiments and suggest personalized products to their end audiences. The vision is being refined, and customer-centric content is turning out to be a prioritized focus for brands that want to genuinely invest in brand and consumer growth.
Become more adept at using VR visualization software tools to bring visual search to the forefront of your marketing strategy today.
This article was originally published in 2020 and has been updated with new information.
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