A GEO (Generative Engine Optimization) audit measures how often ChatGPT, Perplexity, Gemini, Claude, and Google’s AI Overviews recommend your brand versus competitors when your prospects ask category-defining questions. It maps the citation gap, identifies structural fixes (llms.txt, schema, entity coverage, content depth), and prescribes the 90-day work needed to become the source AI recommends.
A Property-Specific GEO Audit , Not a Generic Tool Report.
Free auto-tools scrape one AI model and call it a citation report. We run a full human-audited sweep across 8 platforms, benchmark you against your top three competitors, and deliver a fix plan your team can execute in 90 days.
Every category prompt is run against ChatGPT (4o, o1), Perplexity, Gemini, Claude Sonnet, AI Overviews, Copilot, You.com, and Grok. Citations, sentiment, and brand-mention position are logged , not just yes/no visibility.
We pick your three highest-priority competitors and quantify where AI cites them versus you: which prompts, which platforms, what content the AI is pulling from. Numeric gap, not vibes.
Full technical review of the machine-readable signals AI crawlers actually use , llms.txt, JSON-LD, Article/Organization/Product schema, robots directives, alt attributes, and entity coverage in structured data.
A topic-by-topic heatmap showing which category questions AI answers with your competitors’ content, what content assets they have that you don’t, and which gaps close the fastest at your DR.
Every finding sorted by effort × impact. Your team gets a prioritized backlog: fix in Week 1, publish in Weeks 2,4, earn links in Weeks 5,8, re-measure in Week 12.
Findings triangulated with your live GSC (impressions, queries, CTR) and Ahrefs (backlinks, keywords, referring domains) , so the plan reflects your actual authority, not textbook advice.
Five Documents. Every Citation Gap Quantified.
Not a generic checklist. A property-specific audit where every finding is triangulated against live AI-model output, your Ahrefs data, and your GSC performance.
The Citation Map
A matrix of every category prompt tested against every AI model. Cells are color-coded by who the AI cites: you, a named competitor, or nobody in your industry. The map is the single artifact your CMO reads to know where you stand.
- 30,60 category-defining prompts, tested against all 8 models
- Brand-mention position (1st, 2nd, buried, or absent)
- Sentiment classification (positive, neutral, comparative)
- Source URL AI is citing when it recommends the competitor
- Refresh cadence: models re-sampled at kickoff and week 12
Competitor Citation Delta
A horizontal bar chart quantifying who AI models cite most across your category. If a competitor is 5× more cited on the same buying prompts, the report shows exactly which content of theirs the AI is pulling.
llms.txt & Schema Audit
Every machine-readable signal AI crawlers use, reviewed on your site , llms.txt, JSON-LD schema, Open Graph, robots, and entity coverage. Findings are graded and paired with copy-paste fixes.
Content Gap Heatmap
Every category topic your prospects ask AI about, mapped to how well each of the five major models currently answers it , and who they cite when they do. Red cells identify the exact topics where publishing new content produces the fastest citation lift.
Publishing more content on topics you already own doesn’t move AI citations. The heatmap identifies the underserved intersections , topics your competitors haven’t dominated yet , where new content earns citations fastest.
90-Day Action Plan + Review Call
Every finding sequenced by effort × impact into a 12-week backlog your team can execute. Delivered with a 45-minute review call where your marketing lead walks the plan with our GEO analyst.
Get My GEO Audit →How We Run the Audit , Every Time.
Five stages. Same protocol every audit. Reproducible against future re-sweeps so you can measure lift, not just point-in-time visibility.
Category, ICP, and 3 competitors locked with your marketing lead in the kickoff call.
30,60 category-defining prompts assembled from your customer language, GSC queries, and Reddit/community signals.
Prompts run against 8 AI platforms with 3 rotations per prompt to control for model variance.
Citations coded by brand, sentiment, position, and source URL. Findings triangulated against your Ahrefs and GSC data.
Findings sequenced into a 12-week backlog. Delivered with a 45-min analyst-led review call.
The Citation Gap Is Bigger Than You Think.
Findings pulled from MV3’s aggregate GEO audit data across B2B SaaS accounts, Q1,Q2 2026.
Median AI citations for a B2B SaaS site pre-audit across 30 category prompts
of audits find at least one competitor 5× more cited on the same buying prompts
of B2B sites audited had no llms.txt file live at audit start
New citations earned within 90 days when the full plan is executed
Individual results vary by category maturity, DR, and existing content depth.
One-time. Delivered in 5 business days.
- Citation Map: 30,60 prompts × 8 AI models
- Competitor Citation Delta vs. your top 3 rivals
- llms.txt + JSON-LD + entity schema audit
- Content Gap Heatmap by topic × model
- 90-Day Action Plan sequenced by effort × impact
- 45-minute analyst-led review call
Bump into Growth AI ($5,997/mo) inside the review call and we credit the $997 against your first month.
Questions Buyers Ask Us.
Ryan runs the GEO audit program at MV3 Marketing. Every audit ships under his review. His work covers schema architecture, llms.txt implementation, and AI-model citation research for B2B SaaS clients ranging from Series A to public.
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