Case Studies — AI Visibility Audits of Real Brands
Real AEO, GEO, and Agent Readiness audits of well-known brands. See how they score, where they fall short, and what it means for AI search visibility.
Key findings from our analysis
- ● Our analysis found that even market-leading brands score below 70 on AEO visibility — structured data gaps are universal
- ● AEO Scanner measured Agent Readiness scores below 50 for all four brands — the agentic web is not yet a priority
- ● GEO citation readiness averaged just 50 across all brands — most content is not formatted for AI citation
- ● Our data shows the most common gap is missing FAQ schema despite having FAQ content on the page
- ● No brand in our study had machine-readable pricing — agents cannot evaluate or recommend any of these services
HubSpot
Market-leading CRM with massive content library, but structured data gaps leave it underperforming in AI search.
Searchable
Strong technical AEO foundations, but the lowest GEO score in this set reveals a citation readiness gap.
Omnia
Citation monitoring platform that struggles with its own AI visibility due to missing foundational schemas.
Shopify
Powers millions of stores but scores just 66 on AEO — missing schema and AI context files cost visibility.
AEO Scanner is an AI search visibility audit tool by Convrgent that scans websites across 64-plus checks in 12 categories and delivers three independent scores measuring AEO visibility, GEO citation readiness, and Agent Readiness. Each case study on this page shows the actual results from running the Convrgent scanner against a real public website without any modifications, producing a detailed breakdown of structured data gaps, meta tag issues, brand narrative weaknesses, and machine interoperability signals. The four brands audited on this page — HubSpot, Searchable, Shopify, and Omnia — were chosen specifically because they represent different business models: a major CRM platform, an AEO monitoring tool, a global e-commerce platform, and a citation monitoring service, giving readers a cross-section of how AI visibility problems manifest across industry categories.
Every case study includes the exact AEO Score, GEO Score, and Agent Readiness Score that the Convrgent scanner produced, an AI Identity Card showing how AI engines would describe the brand, and a prioritized list of top issues drawn from the full 64-plus check breakdown. According to published analysis from Qwairy in 2025 based on 118,101 AI answers with 669,065 citations, Perplexity cites 2.8 times more sources per query than ChatGPT, meaning brands with weak citation signals are disproportionately punished by the faster-growing AI search engines. The case studies here demonstrate that even category leaders with massive content libraries score below 70 on AEO visibility when they lack the structured data, llms.txt files, and citable passage formatting that AI search engines parse directly.
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