About Website Auditor
AI Website Audit analyzes how AI assistants name businesses by asking category-specific, buying-intent questions to ChatGPT, Claude, Gemini and Perplexity. The report gives per-platform appearance rates, lists competitors the assistants recommend, and identifies the pages and sources the models cited.
It inspects crawler access and site markup, highlighting structured data, sitemaps and meta tags that affect discoverability. The audit also includes security, performance, broken-link and form checks aggregated in one report.
Scores are reported with 90% Wilson score intervals and sample counts so changes can be assessed as statistically meaningful or within expected variance. Results tie assistant answers back to crawler and markup findings to explain visibility gaps.
The approach combines direct assistant queries with a site-readiness scan to measure AI visibility rather than infer it from traditional SEO signals.
Key Features
Use Cases
Who is it for?
It inspects crawler access and site markup, highlighting structured data, sitemaps and meta tags that affect discoverability. The audit also includes security, performance, broken-link and form checks aggregated in one report.
Scores are reported with 90% Wilson score intervals and sample counts so changes can be assessed as statistically meaningful or within expected variance. Results tie assistant answers back to crawler and markup findings to explain visibility gaps.
The approach combines direct assistant queries with a site-readiness scan to measure AI visibility rather than infer it from traditional SEO signals.
Key Features
- Queries multiple AI assistants (ChatGPT, Claude, Gemini, Perplexity) with category-specific, buying-intent prompts to analyze naming and recommendations
- Generates per-assistant appearance rates, lists recommended competitors, and identifies pages and sources cited by models
- Inspects crawler access and site markup, highlighting structured data, sitemaps, and meta tags that affect discoverability
- Runs technical checks for security, performance, broken links, and form functionality aggregated in one report
- Reports scores with 90% Wilson score intervals and sample counts and correlates assistant answers with crawler/markup findings to explain visibility gaps
Use Cases
- Optimize your website to appear in conversational AI responses by using cross-model buying-intent queries (ChatGPT, Claude, Gemini, Perplexity), analyze AI model naming and appearance rates, and act on recommended competitors and cited sources to improve content, schema and AI visibility
- Run a comprehensive technical audit that combines crawler-based crawlability checks, markup and structured data discoverability, security, performance and link analysis with statistical scoring, producing per-platform reports and prioritized remediation steps for development teams
- Prepare for launches or migrations with a site readiness scan and AI assistant visibility audit that measures assistant recommendation rates, assesses structured data and naming hygiene, benchmarks competitors and delivers actionable, cited fixes to maximize discoverability in AI assistants
Who is it for?
- Seo specialists and consultants
- Digital marketing managers
- Local business owners and franchise operators
- Brand managers
- Product managers (search/ai features)
- Technical seo engineers and web developers
- Marketing and creative agencies
- E‑commerce managers
- Growth teams and growth marketers
- Ctos and site reliability/it leads
- Customer experience (cx) managers
- Competitive intelligence and market researchers
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