The human brain is hardwired to excel at visual selection – neurons devoted to visual processing take up to 30% of the cortex versus only 10% combined for touch and hearing. We can look at a picture, and in 13 milliseconds or less, know exactly what we’re seeing.
Whilst traditional search engines will remain key to answering fact-based questions, visual search is becoming increasingly important in the discovery process. Imagine a question like “where can we go for dinner?” There is no right answer but a host of creative possibilities to help influence a semantic and visual decision-making process. Consumers are increasingly time-poor and crave convenience which a visual search facilitates.
What is visual search?
An image search is when a user inputs a word into a search engine and the search engine spits out related images. A visual search on the other hand uses an image as a query instead of text. It identifies objects within the image and then searches for images related to those objects. For instance, based on an image of a car, you’d be able to use visual search to shop for a car identical or similar to the one in the image.
Visual search isn’t likely to replace text-based search engines altogether. Currently, visual search is most useful in the world of retail and sales but in the future it could. To understand visual search, you need to understand the process behind matching search images with relevant content and links to where to purchase.
Visual search technology
The challenge for visual search technology development is to create technology that can understand images as quickly and effectively as the human brain. These tools must also be able to identify specific objects within the image and then generate visually similar results. It isn’t enough for the machine to identify an image. It must also be able to recognise a variety of colours, shapes, sizes, and patterns the way the human mind does.
The increasing importance of visual search as a tool is reflected with Pinterest’s latest figures – it has 200 million active monthly users and a 50% year on year increase in its impressions. Visual search is a rapidly growing technique that brands and marketers need to embrace.
One of the most recent examples of these developments is Google Lens, an app that allows your smartphone to work as a visual search engine. The app works by analysing the pictures that you take and giving you information about that image. For instance, by taking a photo of an clothes shop your phone can tell you its name, customer reviews, and tell you if your friends have been there. This data comes from Google’s vast stores of data, algorithms, and knowledge graphs, which are then incorporated into the neural networks of the Lens.
Pinterest uses different machine learning applications to identify visual similarities, categorise pictures and provide recommendations based on browsing history. This investment in visual search has given then an average £35 order value in 2017, higher than any other social media channel. Pinterest is able to focus solely on the development of its visual search engine and as a result, Pinterest are a leading contender in visual search technology.
Instagram has now introduced shoppable posts and fashion retailer ASOS also released a visual search tool on its website. Visual search reduces the number of choices and helps shoppers find what they want more effectively.
What visual search means for SEO
Search engines are already capable of indexing images and videos and ranking them accordingly. Yet despite this surge in video and image content, SEO still needs to be used to rank higher on search engines.
However, the ‘see-snap-buy’ behavior of visual search makes image SEO more of a challenge. This is because the user no longer has to type, but can instead take a photo of a product and then search for the product on a retailer’s website.
Currently, SEO functions alongside visual search image optimisation, schema markup, and metadata as with such minimal text used visual search, these types of data are the only sources of textual information for search engines to crawl. Metadata strengthens the marketers ability to drive online traffic to their website, in both the HTML of web pages and its images.
The future of visual search
Visual search engines are set to revolutionise the retail industry and the way we use technology, but it’s still easier and quicker to search for information with words. Visual search engines are convenient, but they’re not ultimately necessary for every industry to succeed. The service industry may be more likely to rely on textual search engines, whereas sales may be more likely to rely on visual search engines. And undoubtedly the future of SEO is set for rapid change.