AI Search Audit

An AI search audit is the starting point for any GEO strategy. Without a baseline measurement, you cannot tell whether your optimization work is having an effect or whether visibility is drifting.

What an AI Search Audit Covers

1. Citation Rate Baseline Test representative queries across target AI platforms (ChatGPT, Perplexity, Google AI Overviews). Measure what percentage mention your brand.

2. Platform Breakdown Citation rate varies significantly by platform. An audit shows where you are strong and where you are invisible.

3. Competitive Citation Gap Analysis For each query where a competitor is cited and you are not, identify why — technical block, content gap, or entity weakness.

4. Technical Signal Audit

• robots.txt: Are AI crawlers (GPTBot, ClaudeBot, PerplexityBot) allowed?
• llms.txt: Does one exist? Is it accurate?
• Schema markup: Product, Organization, FAQ schema present and valid?
• Crawler accessibility: Do key pages return 200 OK to bots?

5. Content Signal Analysis Are key pages written with TLDR-first structure? Do they directly answer the questions customers ask AI?

6. Prioritized Recommendations Ranked by estimated impact and implementation effort.

Audit Cadence

A baseline audit establishes your starting point. Re-auditing every 90 days tracks progress. Monthly citation rate monitoring (lighter than a full audit) detects visibility drift between deep dives.

Frequently Asked Questions

How is an AI search audit different from an SEO audit?

An SEO audit assesses organic search ranking factors — page speed, backlinks, keyword targeting. An AI search audit assesses citation signals — crawler access, structured data, entity recognition, and content clarity for AI synthesis. Some signals overlap (structured data, content quality) but the measurement and priorities differ.

How many queries should an AI search audit test?

A meaningful audit tests at least 50–100 queries mapped to your customer journey: category discovery, product comparison, use-case, and brand-specific queries. Testing fewer than 30 queries risks missing category-specific gaps.

Can I do an AI search audit manually?

You can test a handful of queries manually, but a systematic audit requires running many queries across multiple platforms and analyzing the results consistently. Manual testing at scale is time-consuming and prone to sampling bias.