Google's feature allowing combined text and image queries, expanding how users search and how content needs to be optimized.
Multisearch is Google's search feature that allows users to combine text and image inputs in a single query, enabling more complex and contextual searches. Instead of searching with just keywords or just an image, users can upload a photo and add descriptive text to refine their search, creating a more precise query that uses both visual and textual information.
This capability represents a significant shift in how people interact with search engines, moving beyond traditional text-based queries toward more intuitive, multimodal search experiences. Multisearch typically works through Google Lens integration on mobile devices, where users can point their camera at an object and then add text like "near me" or "in blue" to find specific variations or local availability.
Why It Matters for AI SEO
Multisearch fundamentally changes content optimization strategies because it requires thinking beyond traditional keyword targeting. When users combine visual and textual queries, they're often in later stages of the buying journey with highly specific intent. For example, someone photographing a piece of furniture and adding "cheaper alternatives" has clear commercial intent that differs from a basic text search for "affordable furniture." AI-powered content optimization tools like MarketMuse and Clearscope are beginning to incorporate visual context considerations, but most SEO strategies haven't fully adapted to this search behavior. Sites with rich visual content, detailed product descriptions, and strong image optimization are better positioned to capture multisearch traffic, as Google's algorithms must understand both the visual elements and surrounding text context.
How It Works
From a technical standpoint, multisearch relies on Google's advanced computer vision and natural language processing capabilities to understand both image content and text modifiers. When optimizing for multisearch, focus on comprehensive image optimization including detailed alt text, descriptive filenames, and surrounding content that provides context about what's shown in images. Implement structured data markup for products, recipes, and other visual content types, as this helps Google understand the relationship between images and descriptive text. Tools like Schema Pro can help automate this process. Additionally, ensure your image file names and alt text align with the descriptive language users might add to their visual searches. For local businesses, optimize images with location context since "near me" queries are common multisearch modifiers.
Common Mistakes
Many businesses treat multisearch as simply another image SEO opportunity, focusing only on visual optimization while ignoring the text component. The real power lies in the combination—users are providing additional context through text that makes their intent more specific. Another mistake is assuming multisearch only applies to e-commerce; the feature works for any visual content including recipes, DIY projects, fashion inspiration, and local business searches. Failing to optimize the contextual text surrounding images means missing opportunities to match the descriptive language users add to their visual queries.