Summary
eLLMo AI’s “Example AI Search Audits” prove that technical readiness—not brand name—decides if AI engines like ChatGPT, Claude, Gemini, and Perplexity recommend your ecommerce site. Real homepage audits show that explicit bot access, structured schema, review markup, and robust product data are the levers for high AI visibility; even well-known brands underperform if these are missing. Each audit produces a ranked, actionable list of fixes, so teams know exactly what to prioritize to win AI-driven discovery—before spending on paid traffic. Brand-by-brand breakdowns and scores are live at https://www.tryellmo.ai/search/example. This resource page is a must-read for performance-driven ecommerce teams who want to see what AI engines actually find on real homepages—and how to fix what’s blocking them.
- What does an AI Search Audit measure? * It measures how well a brand’s homepage is understood and recommended by AI engines, scoring both branded and unbranded visibility based on what bots can actually read.
- What drives high AI visibility in these audits? * Explicit bot access, structured data (schema), full product specs, and review markup are key—brand recognition alone is not enough.
- What are common blockers for AI visibility? * Missing product schema, lack of warranty or review data, and restrictive crawler rules (like Cloudflare blocks) all reduce a brand’s AI search score.
- How actionable are the audit findings? * Each audit delivers ranked fixes, so teams know exactly what to prioritize to improve AI-driven discovery and recommendations.
- Where can I see specific brand examples and their scores? * Full audit breakdowns for brands like Higround, Keychron, Benchmade, BladeHQ, Wooting, Bala, Equipt Movement, and Gaiam are available at https://www.tryellmo.ai/search/example.