Ai Search

Multimodal Search

Multimodal search is AI-powered search that processes multiple types of input simultaneously — text, images, video, audio, and documents. Google Lens, ChatGPT's vision capabilities, and Gemini's document analysis are examples.

Why Multimodal Search Matters for SEO

Users increasingly search by image — Google Lens processes billions of monthly searches. Product images, infographics, and visual content can now drive discovery independently of text. Ecommerce, fashion, and visual industries are most immediately affected.

How Multimodal Search Works

Optimise images with descriptive, specific alt text. Implement image schema (Product, ImageObject) for product images. Add video schema and transcripts for video content. High-quality original images rank better in visual search than stock photography.

Common Mistakes

  • Neglecting image alt text and treating it as an afterthought
  • Using stock photography when original images would perform better
  • No video schema or transcripts for video content
About the Author

Lawrence Hitches is an AI SEO consultant based in Melbourne and General Manager of StudioHawk. He specialises in AI search visibility, technical SEO, and organic growth strategy. Book a free consultation →