Search habits are no longer limited to text-based queries.
With tools like Google Lens and even visual search features on shopping platforms like Amazon and Etsy, users can now search by images. This shift has opened a new dimension in e-commerce SEO, where product images can drive discovery, impressions, and sales, independent of traditional keywords.
Retailers used to focus almost entirely on optimizing titles, descriptions, and category pages. While that’s still important, images now carry more weight in how customers find products.
Visual search enables users to bypass text entirely, allowing them to find visually similar items using an image. This changes how product pages should be built and how e-commerce platforms should approach content strategy.
In this article, we will discuss how visual search is changing e-commerce SEO strategies.
Table of Contents
Why Product Pages Need a Visual Strategy
A strong visual presence doesn’t just mean having clear, attractive photos. It also involves ensuring that those images are crawlable, appropriately tagged, and supported by on-page context.
For example, when a user submits a picture of a backpack, platforms try to understand shape, color, texture, and style. If your product page supports those visual features with descriptive text and proper metadata, the likelihood of being recommended increases.
Many retailers are adopting visual searches to improve customer experiences. According to ModernRetail, Wayfair, and ThredUp have also adopted them in 2024. These visual searches also leverage artificial algorithms (AI) and Large Language Models (LLMs) for search queries.
As search methods grow more flexible, image-based discovery is no longer separate from broader SEO planning. Therefore, businesses are now factoring in mobile searches, voice commands, social media algorithms, and image recognition as part of a single effort. Partnering with experts such as beBOLD Digital – trusted amazon account management services can help brands integrate these strategies seamlessly into their broader eCommerce growth plans.
According to the Connection Model, this blended approach is often described as search everywhere optimization. It focuses on optimizing searches across multiple platforms through various channels.
Search everywhere optimization is a mindset that acknowledges how people shift across platforms and search types without any fixed pattern. Optimizing for one channel alone no longer reflects how users interact with content.
How often should e-commerce brands update their product images?
Updating product images should be a regular part of content maintenance, especially for items with seasonal designs, packaging changes, or shifting trends. Refreshing visuals also help keep the site feeling current and give search engines new visual content to crawl and index for image-related queries.
The Role of Multimodal Search
Google and other engines are investing heavily in multimodal search. This means they blend visual, text, and sometimes even audio cues to deliver more accurate results.
It’s part of a larger move toward interpreting content in layers. For e-commerce sites, that means each image and each line of text plays a role in the broader search ecosystem.
Multimodal search allows users to snap a photo, ask a question, and get results that span multiple content types.
For sellers, this means their content needs to perform well in multiple formats, not just one. When a product image is paired with informative content and fast-loading mobile pages, it becomes more competitive across different entry points.
Search Engine Land explains that SEO today involves blending voice, visuals, and AI-generated insights. Multimodal discovery is redefining how search works by integrating images, text, and AI summaries into one experience.
Google has shifted from being a keyword-driven query engine to a system that anticipates intent across multiple inputs, including visual and conversational signals.
What’s the biggest challenge for small e-commerce stores in adapting to multimodal search?
One major challenge is the lack of resources to create content that works across formats. Smaller teams often struggle to produce high-quality visuals, write compelling product descriptions, and implement structured data simultaneously. Prioritizing pages with high traffic or strong potential can help manage this shift gradually.
Visual Search Brings High-Intent Traffic
Visual search introduces new ways for people to reach your products. Someone might not know how to describe what they want, but still find your item through a photo match. This type of discovery often comes with a strong intent to buy, since the user is already engaging with something they want to replicate.
According to Think With Google, Google Lens powers over 20 billion visual searches every month. Moreover, one in four of these searches has a commercial intent.
Being ready for this kind of search means looking beyond keywords and thinking about how your content looks and functions across devices. Alt text, structured data, and mobile image performance all help improve the odds of showing up when it counts.
According to Search Engine Land, brands can do visual optimization by ensuring:
- Relevance
- Image quality
- SafeSearch
- Entity identification
Does visual search affect the types of products customers ultimately choose?
Yes, visual search can shift customer preference by surfacing alternative products that are visually similar but from different brands or at lower prices. This can lead shoppers to explore options they might not have found through text search, impacting brand loyalty and influencing competitive positioning.
Visual Search Is Reshaping Keyword Strategy
Traditional e-commerce SEO revolves around predicting what users will type into search bars. With visual search, that approach becomes less reliable.
Shoppers are increasingly skipping the typing step altogether, letting images drive the discovery process. This means brands can’t rely solely on text-based keywords to bring in traffic.
Instead of optimizing only for phrases, e-commerce teams now need to ensure that visual cues match what users are likely to search for. Alt text, image filenames, and structured data should reinforce what the image shows, not just what the brand wants to say about it.
SEO is no longer just about matching words; it’s about matching visuals to user intent. Structured data has long helped search engines understand product pages, but it’s now playing a larger role in visual search. Markup that specifies color, size, material, and availability doesn’t just inform text results; it helps connect the image to the right context.
Some ecommerce teams still treat visual search as experimental. But the continued investment by major platforms shows that it’s not going away. Google, Amazon, Pinterest, and even TikTok are developing discovery tools that focus on what people see rather than what they type.
That means visual SEO is no longer a side task; it’s part of core optimization. It intersects with everything from product photography and page structure to how you name image files and build mobile-friendly layouts. Teams that treat visual content with the same care as written content will be better positioned for the changes that are already underway.