GOOGLE’S VISUAL SEARCH: THE NEW FRONTIER
For 74% of consumers, traditional text-based keyword searches are inefficient at helping find the right products online.
But much of your current search behavior is based on the false premise that you can describe things in words. In many situations, we can’t.
And this shows in the data. Sometimes we forget that Google Images accounts for 22.6% of all searches — searches where traditional methods of searching were not the best fit.
Developments in computer vision have led to a visual marketing renaissance. Just look to visual search leader Pinterest, who reported that 55% of their users shop on the platform. How well do those users convert? Heap Analytics data shows that on shopping cart sizes under $199, image-based Pinterest Ads have an 8.5% conversion rate. To put that in context, that’s behind Google’s 12.3% but in front of Facebook’s 7.2%.
Not only can visual search drive significant conversions online. Image recognition is also driving the digitalization and monetization in the real world.
The rise of visual search in Google
Traditionally, image search functioned like this: Google took a text-based query and tried to find the best visual match based on metadata, markups, and surrounding copy.
But for many years now, the image itself can also act as the search query. Google can search for images with images. This is called visual search.
Google has been quietly adding advanced image recognition capabilities to mobile Google Images over the last years, with a focus on the fashion industry as a test case for commercial opportunities (although the functionality can be applied to automotive, travel, food, and many other industries). Plotting the updates, you can see clear stepping stone technologies building on the theme of visual search.
- Related images (April 2013): Click on a result to view visually similar images. The first foray into visual search.
- Collections (November 2015): Allows users to save images directly from Google’s mobile image search into folders. Google’s answer to a Pinterest board.
- Product images in web results (October 2016): Product images begin to display next to website links in mobile search.
- Product details on images (December 2016): Click on an image result to display product price, availability, ratings, and other key information directly in the image search results.
- Similar items (April 2017): Google can identify products, even within lifestyle images, and showcases similar items you can buy online.
- Style ideas (April 2017): The flip side to similar items. When browsing fashion product images on mobile, Google shows you outfit montages and inspirational lifestyle photos to highlight how the product can be worn in real life.
- Image badges (August 2017): Label on the image indicate what other details are available, encouraging more users to click; for example, badges such as “recipe” or a timestamp for pages featuring videos. But the most significant badge is “product,” shown if the item is available for purchase online.
- Image captions (March 2018): Display the title tag and domain underneath the image.
Combining these together, you can see powerful functionality. Google is making a play to turn Google Images into shoppable product discovery — trying to take a bite out of social discovery platforms and give consumers yet another reason to browse on Google, rather than your e-commerce website.
This fundamental change in Google Image search comes with a big SEO opportunity for early adopters. Not only for transactional queries, but higher up the funnel with informational queries as well.
It’s not always about Google
Visual search is not limited to Google. And no, I’m not talking about just Bing. Visual search is also creating opportunities to be found and drive conversion on social networks, such as Pinterest. Both brands allow you to select objects within images to narrow down your visual search query.
Digitize the world with camera-based search
The current paradigm for SEOs is that we wait for a keyword search to occur and then compete. Not only for organic rankings, but also for attention versus paid ads and other rich features.
With computer vision, you can cut the keyword search out of the customer journey. By entering the funnel before the keyword search occurs, you can effectively exclude your competitors.
Who cares if your competitor has the #1 organic spot on Google, or if they have more budget for Adwords, or a stronger core value proposition messaging if consumers never see it?
Consumers can skip straight from desire to conversion by taking a photo with their smartphone.