What is Visual Search?
As per a statistical report, 62% of millennials and Gen Z would use visual search over all other search methods.
Before we dive into the best practices, let’s see what Visual Search is and the best practices to implement one, if you haven’t already.
What is Visual Search?
Visual Search exploits Artificial Intelligence (AI) to help people perform their search by means of the real-world imagery rather than text search.
For example, if a person takes a photo of an object by Google Lens for example, teh software can identify the object within the image and provides feedback and details about it to the user.
This technology is especially useful to retail and eCommerce businesses — if you implement well-optimized content, you can stand a chance of being the returned search result for a user.
Such an approach will result in attracting more users and increased profit.
How does Visual Search differ from Image Search?
Visual Search involves searching for the specific item via text, voice and vision — it belongs to a category known as ‘sensory search’.
Both visual and image search are based on imagery but there is an important difference — for image search, people still use words while for visual search, users can utilize an image to handle the same search.
Image search has been present for a long time, nearly 20 years — Google introduced this search format back in 2001 due to the inability of a search engine to cope with all the searches of Jeniffer Lopez and the green dress she wore on Grammy Awards back in 2000.
Visual Search works with a combination of Computer Vision and Machine Learning.
Computer Vision helps machines to interpret what they ‘see’ before deciding what to do with the information.
Computer vision has been present for a long time but with the progress of Machine Learning it became more advanced.
Machine Learning brings details that Computer Vision needs to understand better what is on the image.
Google lens, with help of this technology, cross-referenced the details with Google Knowledge Graph.
The Biggest Platforms in Visual Search
Google and Bing visual search are mainly used for information retrieval alongside shopping while each of the major visual search platforms offer slightly different search options.
With Pinterest Lens, users can submit images of almost anything and the platform can save the or shop the object on the photo. Pinterest stated that 90% of users’ purchasing decisions were enabled via the information gathered through this technology.
Clothes retailers can post ‘shop by look’ pins so that users may identify or search for garments within a certain image.
The engine can also find similar items to recommend to users in case a user decides that they do not want the exact product but would like something else similar to the original one.
In the following year, Google Lens was integrated with Google Image Search and in 2019, a study was published stating that their image recognition technology was more accurate than other similar platforms.
Google Lens technology is present in many Android applications like Photos, Google Assistant and Google Search.
The capabilities to combine multiple apps gives Google Lens a head start over the other similar engines — for example, if a user takes a photo of a sign in a foreign language via Google Lens, it can instruct Google Translate app to provide a translation in their own language.
Bing Visual Search
Bing Visual Search is a bit different as it provides users with both information and products, similar to Bing search engine. It provides users with related items and pricing details.
Bing works similarly to other visual search engines and it has an extensive developer platform.
For example, if Bing guides a user to a particular item on your website, a developer has the ability to define the actions that will be offered to the user.
Amazon’s visual search app was announced in June 2019 — it allows users to take photos of objects or products using this function within Amazon’s mobile app and then users are provided with the relevant details and similar items.
Amazon StyleSnap has already been working with Instagram platform for creating an integrated shopping experience for its users.
This technology is very useful for companies that sell on Amazon as they can get their products in front of consumers in an already competitive market.
Developers are also given the opportunity to read the latest guides for implementing StyleSnap.
Snapchat Camera Search
Snapchat announced their Camera Search in September 2018 inviting users to search for products on Amazon via their app.
It works in a way that the app recognizes a barcode and then an Amazon card is provided to a user offering a link to a specific product or selection of similar products from their store. If the user has their app, they can click on the app and will be directly led to the wanted page.
Unfortunately, Snapchat did not post any latest updates or additional features, but you can read more about their AR and other features in their help guide.
Visual Search Best Practices
There are numerous benefits if implemented visual search but we will talk about these in one of the future articles.
Let’s check the best practices that websites should stick to so to appear in visual search:
Use Structured Data
One of the most important things is to provide as much information as possible to search engines, when adding any kind of content to your website.
The best is to use structured data for images as it can help your website to appear in Google rich snippets.
Add Alternative Text
Alternative texts are also known as ‘alt tags’ or ‘alt descriptions’ — it appears in place of an image in case it fails to load on the screen.
Alternative text is ‘read’ by search engines to help understand the meaning of the image. Users that use screen readers would also need alt text to understand the context of the photo. Alternative text should be authentic, concise and well written.
For example, if your image shows a man holding a red cup of coffee, your alternative text may sound like this: ‘Young man holds a red cup of coffee at home’ or in more details.
Use Descriptive Filenames
A popular phrase today says: Context is everything.
Majority of image files are commonly named like this: ‘IMG 12345.JPG’ but you should try better and provide as many details as you can.
If we follow the above example, instead of using such an impersonal name, rename it to: ‘man-with-red-cup-of-coffee.jpg’.
Although it is difficult, try to provide a unique filename to that image besides being clear and concise.
Have an Image Sitemap
If you provide an image sitemap, Google will easily identify, crawl and index your images.
Use Suitable Image Size and File Type
Having optimization of your content in mind, it is important to use the appropriate file size of images as it can affect the loading time of your site for your users. A site with slow loading speed can trigger users to leave your site.
Besides file size, pay attention to the type of files you use on your website. For example, Google Images supports the following file types:
Each file type has its pros and cons, where for example GIFs may not be suitable for some commercial websites.
The above listed recommendations relate only to images, but you should consider the other elements like SEO and other associated items to appear in visual search results:
- Overall site speed
- Overall site performance
- Your site’s accessibility
- Quality of images
- Originality of the content and the images
Today’s technologies like Augmented Reality (AR) and Virtual Reality (VR) can help provide users with sensory search in all its forms.
As major search platforms push the boundaries of search features, it is vital for marketers and website owners to make plans for the future search options.
Keep in mind that younger internet users will expect such features so try to decide which approach can be the best for your business to follow.