While you might think of visual search as something new, it has actually been around for quite some time. It is becoming more and more obvious that our culture is one that is facilitated by images (see the rise of platforms like Instagram and Snapchat).
Even though there has been a significant rise in the in the advancements made in search technology and SEO with things like, personalization, voice learning and natural language conversions, the power of images in search has largely remained untapped.
So, What Exactly is Visual Search?
The tricky part about visual search is that it is harder for a computer than it is for a human. Not exactly surprising, right?
With visual search, everything is imaged based. So, instead of a search engine using a text-based query, it queries an image then attempts to find the best visual to match that request. However, this requires a much more complicated process than a traditional text-based query.
This process usually involves networks and algorithms that mimic how a human brain functions when identifying images or patterns. Search Engine Watch wrote a great article on this, read it here.
With Google Lens, your smartphone camera won’t just see what you see, but will also understand what you see to help you take action. #io17 pic.twitter.com/viOmWFjqk1
— Google (@Google) May 17, 2017
History
There is a lot, so I will try to keep it brief.
To be fair, TinEye was the first image search engine to leverage image association technology back in 2008. However, the first ones to really put this technology into action was, wait for it, Google! Could you see that coming? Anyway, Google released ‘Google Goggles’ in 2010. These ‘Google Goggles’ were fairly basic in the fact that they could identify unique items such as barcodes, landmarks and books then provide some additional information on them. But, it wasn’t good at recognizing everyday type objects, like animals, cars or clothing.
Then came CamFind, which is still around if you are interested. This app’s use of visual search technology allows users to snap a photo of any object then pulls the information that is relevant to that object along with shopping results. Awesome, I know! And while CamFind is quite accurate, it didn’t engage users.
Enter Pinterest. Pinterest has always been focused on visuals, so visual search is nothing new to them. But, Pinterest is different from the other social platforms. Pinterest, while engaging, is not meant to be outwardly engaging. The app is truly for discovery, the sharing of products and DIY ideas.
Perfectly summed up in a recant blog post, Ben Silbermann, CEO and co-founder Pinterest said,
“As a Pinner once said to me, “Pinterest is for yourself, not your selfies”—I love that. Pinterest is more of a personal tool than a social one. People don’t come to see what their friends are doing. (There are lots of other great places out there for that!) Instead, they come to Pinterest to find ideas to try, figure out which ones they love, and learn a little bit about themselves in the process.”
In February 2017, Pinterest released Lens. This new functionality allows Pinners to take a photo of something, in the app, then Pinterest aggerates similar pins. Basically, the same thing that CamFind does. Except, in my own experience, CamFind does it better. Sorry, Pinterest. Still love you though.
Oh, and then there is Google’s Lens which was announced back in May, but was previewed in a more formal format last week. Read more about that here.
Visual Search and Ecommerce
So, starting a conversation can be hard. Especially if you want to know where that stranger at the coffee shop got her shoes. I mean, how many times have you wished that you could be creepy and snap a pic of that person’s amazing shoes? Well, good news! Now you can! As mentioned above, there’s an app for that.
The things is, ecommerce is visual. Searching for the right dress online is a visual experience. The more pictures and specifics a brand provides the user about a product, the more likely the shopper is to purchase. Case and point, have you ever received something that was nothing like the product you saw online? How did you feel? Not happy, right?
How Visual Search Improves SEO
Visuals are already apart of your brand’s ecommerce site and search engines are frequently indexing images and videos which attribute to your rankings score.
Here is how visual search works in relation to SEO. The user no longer needs to remember a products name, they can simply snap a pic of the product and upload it to your ecomm site. Then, similar to the on-site search functionality that currently exists, your site will full results of similar products. No typing required.
SEO is really about improving the user’s experience. And while your website might not have the functionality of true visual search, start with alt-tagging your images and optimizing all your product images. This way, your site will not only be recognized by search engines, it will be better for the users.
While similar to current on-site search, there’s a lot of potential with visual search
- Enhances the user’s experience
- Narrows search results
- Improves bounce rate
- No typing
- More exposure to similar products
To the Future
The reach of visual search is boundless. And while it hasn’t exactly gone mainstream yet, it will. We know that technology changes seemingly faster than we can wrap our heads around the last innovation. I mean, most people I talk to (outside of work of course) don’t even know that this type of technology exists.
Soon, text-based SEO won’t be the focus. It will be all about the visuals. And while, as a writer, that is sad it is also exhilarating! Just think, ecommerce is really only scratching the surface of what could be possible for visual search. I wonder what’s next…
