MarTech outlines five steps for visual SEO in AI search
Visual SEO now requires aligning images with entity data and context to work with AI systems. Google’s Lens handles over 25 billion monthly visual searches, with one in five showing commercial intent. The shift from keyword-based to semantic search demands consistency across images, structured data, and metadata—ensuring AI interprets visuals the same way customers do.
Key points
- Visual SEO now demands aligning images with structured data, metadata, and context for AI interpretation
- Five key steps include entity consistency, attribute depth, content alignment, freshness, and DAM governance
Marketers must optimize for entity consistency, attribute depth, content alignment, freshness, and DAM governance. Entity consistency ensures images link to correct products, locations, or services. Attribute depth means imagery must clearly depict features AI can recognize, like room types or product details. Content alignment ties visuals to surrounding text, captions, and structured data. Freshness requires updates for dynamic entities like event pages or multi-location brands. A digital asset management (DAM) system acts as the source of truth, tracking provenance, approvals, and versioning for assets across channels.
How to build a visual SEO strategy for AI search
MarTech · 29 September 2026
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This text was published by MarTech and written by Benu Aggarwal. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
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