75% of Consumers Demand Visual Search in 2024

A staggering 75% of consumers now use visual search at least monthly to find products online, and it’s completely changing how brands have to set up their digital storefronts. This isn’t a passing fad. It’s a fundamental reset of what customers expect when it comes to finding things quickly and intuitively. Brands that aren’t prepared for this visually-driven demand are already falling behind.

75% of Consumers Use Visual Search Monthly

Everyone has a smartphone, and AI is getting smarter, which has dragged visual search right into the mainstream. A 2024 Statista report found that three-quarters of online shoppers are doing this every month. This is active buying intent, not just casual browsing. When a consumer spots something they want in the real world or scrolling through social media, their instinct now is to snap a picture and let the tech find it. For anyone in marketing, this means your old keyword-focused playbook for product discovery just isn’t enough anymore. You can have perfectly optimized product descriptions, but if your images aren’t machine-readable and findable through visual cues, a huge chunk of your audience will never see them. The impact goes way beyond your own website. Think about Pinterest Lens or Google Lens, which are essentially personal shoppers for millions of people. Brands that haven’t invested in good image recognition are simply invisible to this huge group of shoppers.

62% of Gen Z and Millennials Prefer Visual Search Over Text

Generational shifts are always a leading indicator of where the market is headed, and the preference for visual search among younger people is a loud one. Research from eMarketer in 2025 found that 62% of Gen Z and Millennial consumers prefer visual search over typing into a search bar. This is hardly a shock, given they grew up in a world dominated by social media and visual communication. They use images and videos to talk to each other, so of course that’s how they want to shop. For brands, this requires a serious adaptation of content strategies. Just having product photos is table stakes. Your images have to be high-quality and diverse, showing products in real-world contexts, from every angle, and ideally mixed with user-generated content, and they must be accurately tagged and categorized. Without that groundwork, your product images are just digital noise instead of tools that lead to a sale. You can see this playing out right now on sophisticated platforms like Pinterest Business, where visual signals drive engagement and sales far more directly than text ever could.

E-commerce Sites with Visual Search See a 20% Increase in Conversion Rates

The business case for visual search isn’t theoretical. It delivers tangible ROI. Data from a 2024 IAB report on visual commerce shows that e-commerce sites with visual search see a 20% lift in conversion rates on average. This is a direct result of the functionality. When a user can upload a picture of a dress they saw on a friend and your site instantly shows them similar items, the friction in the buying journey just evaporates. High intent leads directly to the product page. Compare that to a text search, which forces the user to guess at keywords, wade through bad results, and constantly refine their search terms. Visual search eliminates most of that work. The trick is making sure the feature is accurate and fast. A slow or inaccurate visual search tool is actually worse than having none at all, since it just causes frustration and leads to people leaving your site. The algorithms demand continuous training and refinement, and you might even need to incorporate regional style preferences to get the results right.

Only 15% of Brands Fully Use AI for Image Tagging and Categorization

Despite the obvious upside, a huge gap exists between what visual search can do and what companies are actually doing. A recent industry survey by HubSpot in late 2025 found that only 15% of brands are fully using AI for automated image tagging and categorization. This is a major oversight. Trying to do it manually is incredibly time-consuming, full of errors, and impossible to scale for a big product catalog. AI-powered tools can analyze an image, identify objects, colors, patterns, and even style attributes with scary precision, assigning tags that make products show up for very specific visual queries. For instance, an AI can tag a photo as a “navy floral midi dress with puff sleeves” instead of just “blue dress,” making it findable for someone who saw exactly that. The brands that are behind on this are building roadblocks for customers who are trying to give them money. It’s about giving your merchandisers better tools, not replacing them, so that every single product photo helps with discovery.

Why “More Images” Isn’t Always the Answer

There’s this old-school wisdom that “more content is better,” and people apply that to product images. For visual search, just dumping a ton of images onto your server without any real strategy can actually hurt you. The common thinking is that more pictures means a higher chance of a match. I disagree. The effectiveness of visual search depends on quality, diversity, and strategic context, not sheer volume. A massive library of similar, badly lit, or out-of-context images can confuse the image recognition algorithms and make them less accurate. What you actually need is a curated set of high-res images showing the product from different angles, in different environments, and (ideally) on different people or with user-generated photos. Take a handbag: one great shot of it on a model, another showing the inside compartments, and a third that’s a close-up on the texture will perform way better than twenty nearly identical studio shots. Plus, the metadata tied to those images, whether crafted by a human or generated by AI, is just as important. A single, perfectly optimized image with rich, accurate tags is worth more than a dozen generic ones without them. Your job is to tell a visual story the machine can understand, not just flood the server with pixels.

The future of finding products is visual, period. Brands that get serious about integrating good visual search tech and commit to high-quality, findable imagery are going to have a serious advantage. It’s about meeting customers where they are, and more and more, they’re holding a smartphone with the camera app open, ready to find what they just saw. For a deeper look at improving the overall journey, you should understand the value of personalized B2B CX, which relies on similar data-driven thinking to tailor every interaction.