The Rise of Visual Search: SEO Opportunities for Images

by | Jun 5, 2023

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rise of visual search

With the constant evolution of the internet, search engines came a long way. Gone are the days when people used to go through several web pages to find something on the internet. With the rise of visual search, users can easily find whatever they want within a few clicks. Visual search has gained massive popularity, and it is an indication of SEO professional’s focus on visual search. In this article, we will discuss how visual search affects SEO and different SEO opportunities for images.

What is Visual Search & Its Significance

In the most simple terms, visual search is where users can search data and information using an image instead of text. It uses Artificial Intelligence and Machine Learning technology to detect an image or a part of the image to provide the users with relevant results.

The convenience and ease of searching have made visual search more popular. More users prefer visual searches instead of keywords. According to a report, 62 of Millennials and Gen Z customers want visual search more than any other technology.

With so much demand, many brands have included visual search features in their mobile application and websites. Even though visual search has gained more popularity for shopping queries, it is not limited to that.

From translating to solving math sums, visual search can help precisely in several daily life problems. Apart from that, copying text, finding business information, detecting locations, and identifying flowers, animals, paintings, etc; visual search has completely changed the search landscape.

Google Lens for translation

Visual searches provide relevant and accurate results with the least inconvenience and effort. Moreover, text-based queries can have multiple meanings and intents which makes it more complicated for search engines to deliver helpful and relevant results. But visual search makes it easy.

Is Visual Search Similar To Image Search?

Even though both image and visual search includes visuals the difference here is of the search query. In image search, users either type or speak what they are looking for. Whereas in visual search, the image itself is a query.

Let’s understand this through the following examples

image search example

Image Search

visual search example

Visual Search

The image on the left side is an example of image search where the user has typed ‘blue denim jacket’. While the right side image shows a visual search where the user has to scan the image of the jacket and he/she can see similar results.

Image search uses text-based data such as alt texts, Image captions, and metadata to show the relevant queries. Whereas visual search uses computer vision and machine learning to understand the characteristics of the searched image query to show similar results.

Popular Platforms For Visual Search

1. Google Lens

The search engine giant first released its visual search tool in 2017. Google Lens was available on most Android and iOS devices in mid-2018. Since then Google has brought many updates and features to Lens to make it more useful. In 2022 the use of Google Lens reached 8 billion searches per month.

Google Lens

Source: Google Lens

2. Pinterest Lens

Pinterest introduced the beta version of Lens in 2017. Now according to Pinterest, users conduct over 600 million searches every month using Pinterest Lens. Users can search, shop, and save from Pinterest. Users can easily identify different visuals in a pin using the lens option.

Pinterest Lens

Source: Pinterest Lens

3. Bing Visual Search

Microsoft’s Bing is another visual search engine that shows products and other relevant information for the searched image query. Bing visual search has a significant benefit for developers. A developer has the ability to decide what actions to show with search results.

Bing Visual Search

4. Amazon Visual Search

The e-commerce giant Amazon is not back in the race of visual search. In order to provide their client with the most relevant products Amazon introduced a visual search. With its new update containing AR, users can take a virtual experience of how the product will look in their place.

Amazon Visual Search

Tips For Optimizing Images for Visual Search

1. Focus on Image Quality

Image quality is the most crucial element for optimizing your site for both image and visual search. High-quality photos are easily recognizable by your potential customers as well as search engines.

Post high-quality images on your site that are clearly visible, are easily understandable to the search engines, and create a better impression of your business. Blurry and unclear images, on the other hand, create a poor user experience.

Image quality also helps the search engine determine different elements shown in the image. Elements like business logos, landmarks, and other entities that can be found on the knowledge graph, must be clearly visible to get into search results.

focus on image quality

Here is an example of an image with the Domino’s Pizza logo. How Google Lens easily detects it as it is clearly visible.

2. Include Structured Data Markup

Nowadays searches have become more intent-specific and user intent is redefining the marketing funnel. That’s why visual search engines are constantly evolving to provide their users with the most relevant results based on intent.

Including structured data markup or schema markup helps the search engine understand the webpage and analyze its different elements. Moreover, by leveraging schema markup you can specify whether the image is an object, product, logo, feature image, or a thumbnail.

example of product schema markup

Above is an example of schema markup of a gaming computer webpage. Schema markup allows you to describe the type of image, its description, price, currency, and offers.

Using this structured data markup search engines can better analyze your web pages and visuals. This will increase the chances of your images appearing on the top of visual search results.

3. Use Suitable Alt Text

Using appropriate alternative text or Alt text is one of the image search optimization methods that are also useful in Visual search optimization. Alt text works as a description of the image that helps search engines understand the context and meaning of that image.

example of alt text


Alt text is added in the image’s HTML code and is not generally visible to users. It is shown when the image is inaccessible as shown in the below image.

alt text when image doesn't load

Alt text helps search engine bots understand the description of an image better so they can show it in the search results for a relevant query. You must include clear, valid, and concise alt text for every image you use on your website.

4. Image Sitemaps

Sitemaps are used to tell search engines which pages are important and which are not. This helps search engines prioritize the indexing process. That means the pages included in sitemaps are important, and search engines index them first as compared to those which are not included in the sitemap.

The same thing applies to image sitemaps. Even though sitemaps don’t directly affect the ranking or your chances of getting at the top of search results, they can increase the chances of your images being easily discovered by search engines.

5. Use Appropriate Size & File Type

Image size can have a significant impact on the page speed and loading time which can affect the user experience. This makes it of utmost importance to use small-size images with better quality.

There are a variety of file types available like PNG, JPEG, WEBP, SVG, etc. Based on the requirements and guidelines you can select the appropriate size and file type. For example, PNG and JPEG are common types but can become blurry when reduced.

File types like SVG and WEBP can be reduced without affecting the quality of the image. It is always recommended to keep your image size 100 KB.

6. Improve Image Focus

The position of elements present in the image is another crucial factor you need to consider while optimizing for visual search. Because search engine technologies determine the context of an image based on the focus on the elements in it.

Let’s understand this with the following example –

We analyzed two images using Google Cloud’s Vision AI and checked how AI detects both of these images

Image 1

Image 1

Image 2

Image 2

In image 1, the primary focus is on a person riding a bicycle and both person and bicycle are clearly visible. While in image 2, the primary focus is shifted majorly to the person.

Vision-AI-Cloud-Result 1

As per Image 1

Vision-AI-Cloud-Result 2

As per image 2

As in the first image, AI can detect the bicycle element with an accuracy of 92%; while for the second image, it is reduced to 81%. This indicates the importance of improving the composition of the image so can visual search engines easily detect it.

This is more important for e-commerce websites where products are listed. For such sites, one must use pictures with most of their focus on the main product. Apart from this, using appropriate white space is one of the helpful ways of using visual content on the website.

Future of Visual Search in SEO

Till now visual search technology has gained massive success in less time. And as Pinterest’s CEO Ben Silbermann said that “The future of search will be about pictures rather than keywords,” the number of visual searches is gradually increasing compared to text-based searches.

That is the reason many global brands (especially eCommerce) adopted the visual search and gained significant results.

Tommy Hilfiger, a leading lifestyle brand, for instance, implemented a visual search tool in their e-commerce application using which people can scan the images in pictures and billboards and find similar products on the app. This led to solid growth in customer engagement and helped improve their brand identity.

This technology is expected to grow more in terms of better convenience and accuracy. Apart from that, technologies like Artificial Intelligence, Machine Learning, and will shape the future of visual search and create a new landscape for searches in order to create a better user experience for users.

Summing Up

The bottom line is visual search technology has the ability to change the way people search on the internet. However, businesses need to adapt the technology and optimize their websites for potential visual searches.

Using high-quality images, including structured data & alt text, adding image sitemaps, and focusing on file type and image composition are some of the best ways to optimize images for visual search.

By adopting visual search optimization techniques, businesses can stay ahead of the curve, improve their online visibility, and provide seamless and engaging experiences to their users. As the visual search continues to evolve, it’s crucial to adapt and leverage its power to unlock new opportunities in the digital realm.

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