As shopping becomes more visually driven, imagery plays a central role in how people evaluate products.
Images and videos can unfurl complex stories in an instant, making them powerful tools for communication.
In ecommerce, they function as decision tools.
Generative search systems extract objects, embedded text, composition, and style to infer use cases and brand fit, then
LLMs surface the assets that best answer a shopper’s question.
Each visual becomes structured data that removes a purchase objection, increasing discoverability in multimodal search contexts where customers take a photo or upload a screenshot to ask about it.
Shoppers use visual search to make decisions: snapping a photo, scanning a label, or comparing products to answer “Will this work for me?” in seconds.
For online stores, that means every photo must answer that task: in‑hand scale shots, on‑body size cues, real‑light color, micro‑demos, and side‑by‑sides that make trade‑offs obvious without reading a word.
Multimodal search is reshaping user behaviors
Visual search adoption is accelerating.
Google Lens now handles 20 billion visual queries per month, driven heavily by younger users in the 18-24 cohort.
These evolving behaviors map to specific intent categories.
General context
Multimodal search aligns with intuitive information-finding.
Users no longer rely on text-only fields. They combine images, spoken queries, and context to direct requests.
Quick capture and identify
By snapping a photo and asking for identification (e.g., “What plant is this?” or querying an error screen), users instantly solve recognition and troubleshooting tasks, speeding up resolution and product authentication.
Visual comparison
Showing a product and requesting “find a dupe” or asking about “room style” eliminates complex textual descriptions and enables rapid cross-category shopping and fit checking.
This shortens discovery time and supports quicker alternative product searches.
Information processing
Presenting ingredient lists (“make recipe”), manuals, or foreign text triggers on-the-fly data conversion.
Systems extract, translate, and operationalize information, eliminating the need for manual reentry or searching elsewhere for instructions.
Modification search
Displaying a product and asking for variations (“like this but in blue”) enables precise attribute searching, such as finding parts or compatible accessories, without needing to hunt down model or part numbers.
These user behaviors highlight the shift away from purely language-based navigation.
Multimodal AI now enables instant identification, decision support, and creative exploration, reducing friction across both ecommerce and information journeys.
You can view a comprehensive table of multimodal visual search types here.
Dig deeper: How multimodal discovery…
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