A GEO audit examines how your brand appears in AI answers: whether it is mentioned, which pages are cited, whether product facts are correct and how well recommendations match the buyer's needs. It gives enterprise marketing teams and agencies a practical way to decide what needs correcting, improving or further investigation.
The output should be a short list of findings backed by answers and source pages, with an owner and a next action. This seven-step framework takes you from choosing the questions to reviewing the results.
What a GEO audit adds to an SEO audit
SEO audits examine areas such as crawling, indexing, site structure, backlinks and search performance. A GEO audit adds the answer itself: is your product included, what does the answer say about it and which sources can the reader inspect?
A good search ranking does not tell you whether an AI answer describes your pricing correctly. Equally, a brand mention does not mean your website was cited. Reviewing the answer and its sources helps you identify the actual issue before changing a page.
The work overlaps with SEO when a useful page is hard to find or access. Keep those checks, but connect them to the pages and buyer questions your audit identifies.
The seven-step GEO audit framework
Step 1: Choose the platforms and markets to audit
Start with the AI Search experiences your customers use and the markets your team serves. Depending on your audience, this can include ChatGPT Search, Perplexity, Claude with web search, Microsoft Copilot, Gemini, Google AI Overviews and Google AI Mode.
Keep distinct experiences separate. Gemini and Google AI Mode are different surfaces; an AI Overview is also a separate observable AI engine. Record the surface and whether web search was used where that information is available.
For each, ask:
- Does your brand appear in responses to direct queries?
- Are you mentioned in category or comparison queries?
- Is your website cited, is a third-party page cited, or is the brand mentioned without a visible source?
- Are the product facts and recommendations appropriate for that market?
Compare the same questions and markets across the chosen surfaces. When a country is unknown, label it as unknown rather than treating it as your target market.
Step 2: Cover the questions buyers actually ask
Build the audit around customer conversations, sales objections and support questions. Include the following three groups, keeping questions that name your brand separate from discovery questions.
Direct brand queries
- "[Your brand] features"
- "[Your brand] pricing"
- "[Your brand] vs competitors"
Category queries
- "Best [your category] tools"
- "How to choose [your category] software"
- "[Your category] comparison"
Problem-solution queries
- "How to solve [problem your product addresses]"
- "Best way to [use case]"
- "[Industry] challenges and solutions"
Add the buying constraints that change the answer, such as company size, integrations or local availability. Choose enough questions to cover the decisions in scope; a fixed prompt count is not a quality standard. Our prompt-selection guide explains how to build and maintain that coverage.
Keep a compact evidence record: the question, surface, date, market/language, saved answer or screenshot, brands mentioned and exact cited URLs. Add the issue and its source evidence when you identify a finding. That gives a colleague enough information to understand and check it.
Step 3: Read the answer and inspect its sources
Review important answers across five separate dimensions:
- Presence: is your brand named, and is it recommended or only mentioned in passing?
- Citations: does the answer visibly link to your domain, a competitor or an independent source? Open the exact page and read the relevant section.
- Accuracy: are pricing, features, availability and other material facts current? Compare them with the relevant product page or documentation.
- Sentiment: is the description positive, neutral or negative? Record the reason, and review ambiguous cases. An answer without a brand mention has no brand sentiment to assess.
- Buyer fit: does the recommendation match the question's needs, budget and constraints? A positive recommendation can still be a poor fit.
These observations tell you different things. An answer can recommend your product accurately while citing a third-party review. It can also cite your research without recommending your product. Keep accuracy separate from sentiment so a flattering answer with old pricing still gets attention.
Use the source-analysis guide for deeper investigation of recurring domains and pages. A visible citation identifies a page to inspect; it does not establish which source produced every statement in the answer.
Step 4: Compare visibility and competitors consistently
Choose relevant competitors, including brands that appear in the answers even if they are absent from your usual SEO competitor list. Compare them on the same questions, surfaces, markets and dates.
For the rates below, use completed, usable answers: saved responses that can be inspected for mentions and visible citations. Include answers where your brand is absent or no citation is shown. Keep failed, empty or unusable collections outside the denominator and report them separately. Count each answer once per brand for Brand Visibility and once for owned-domain Citation Rate, even if it contains repeated mentions or cites several owned pages.
- Brand Visibility: answers mentioning your brand ÷ all usable answers × 100.
- Owned-domain Citation Rate: answers visibly citing at least one URL on your owned domain ÷ all usable answers × 100.
- Sentiment: the positive, neutral and negative descriptions among answers mentioning your brand.
Always retain the counts behind the rates. An illustrative sample of 100 usable answers, with 30 mentioning the brand and 20 citing its website, has 30% Brand Visibility and 20% Citation Rate. The citation calculation is 20 ÷ 100, regardless of how often the brand is named.
Also compare where brands appear in recommendations, which features are highlighted and whether the descriptions are accurate. If you report mention-based Share of Voice, use a fixed competitor set and counting method; it is a competitive view of the sampled answers, not market share.
Use your own baseline and relevant competitors for context instead of a universal pass mark. The measurement-framework guide covers baselines and reporting in more detail.
Step 5: Find gaps your team can usefully address
Look for questions where competitors appear but your brand does not, missing use cases or features, and differences in how products are described. Read the answers before treating every absence as a content gap.
Focus on gaps where you have genuine competitive advantages or unique value. If your product meets a buyer's requirement but the relevant page never explains it, improve that page with clear details and evidence. If a competitor is recommended because it has a capability you do not offer, record the product insight rather than trying to write around it.
Inspect cited competitor pages for useful differences: a clearer explanation, current integration details, a relevant customer example or an answer to a question your page overlooks. Preserve your own useful material and fill the specific gap. Citation frequency helps choose pages to inspect; it does not prove their quality or that copying their format will improve visibility.
Step 6: Check the pages behind the finding
Start with the owned pricing, product, comparison, documentation or case-study pages relevant to your findings. Give the website team a page and a specific check:
- Access: can the relevant crawler reach the page, or do robots rules, a login, a CDN or a security challenge block it? Check the applicable crawler and access evidence with your technical team.
- Content: is the important pricing or feature information available as readable text or perhaps behind PDF? Check the rendered page as well as what your inspection tool can retrieve, especially when content loads dynamically.
- Discovery: can people and crawlers reach the page through useful internal links? Does navigation still point to an outdated version?
- Consistency: do pricing, product pages and documentation agree? If structured data is present, does it match the visible information?
- Google eligibility: for a page you expect in AI Overviews or AI Mode, check its indexing and snippet eligibility in Search Console.
Google says its AI Search features use the existing SEO foundations and require no special schema. Meeting the requirements does not guarantee inclusion. See Google's AI features guidance; other platforms need their own checks.
Review relevant directory listings or third-party product pages when answer evidence points to them. A missing Wikipedia entry or a schema field is not, by itself, an explanation for a visibility gap.
Step 7: Assign actions and set a review point
Finish with a manageable list of findings, each with the answer evidence, affected page, proposed action, owner and next check. Prioritize material customer-facing errors and useful information gaps alongside their business importance and effort.
As a starting routine, scan important answers weekly for errors, review comparable patterns monthly and revisit the audit scope quarterly. Product launches, pricing changes or serious inaccuracies can warrant earlier attention. The content-refresh cadence guide explains how to choose the next review.
Retain a stable set of questions for comparison. Record additions to questions, engines or markets separately so broader coverage is not mistaken for an improvement in visibility.
What a completed audit finding looks like
The following is an illustration using a fictional product and invented answer and page details. It is not an observed customer result.
Turn findings into proportionate improvements
An audit should leave the team with specific work, rather than a general instruction to produce more content.
- Correct an owned page: update inaccurate pricing, features or availability; make the current version easy to find; and resolve contradictory documentation.
- Request a third-party correction: identify the exact error, provide a reliable current source and track the publisher's response.
- Improve useful content: clarify an existing use-case page, add missing integration details or make a relevant case study easier to access. Create a new resource when the buyer's question needs one and the existing corpus does not cover it.
- Investigate or observe: check repeated answer patterns when the cause is unclear. An accurate recommendation of a better-fit competitor may need no content change.
Avoid labelling every schema change, new article or external listing a quick win. Effort and value depend on the finding. A confirmed correction can be worthwhile even before a visibility rate changes.
How agencies can use GEO audits with clients
For agencies, a focused GEO audit can introduce prospective clients to how their brands appear in AI Search. It can also extend existing SEO, content and brand engagements with an assessment of the questions buyers ask, the answers they receive and the sources those answers link to. The first audit should surface concrete opportunities, such as inaccurate product details or unanswered buyer questions, rather than promise a visibility increase.
Make the approach transparent to clients. Document the questions, AI Search experiences, markets, dates and counting rules used. Show representative full answers and exact cited URLs, distinguish observed findings from recommended changes, and agree on a follow-up check under comparable conditions. A repeatable method makes it easier to explain what changed and whether further work is justified.
For a first client engagement, a month-long GEO visibility audit is a practical starting point. Unlike a technical site scan, which can produce automated findings in minutes or hours, visibility auditing benefits from repeated AI answer collection. We recommend at least a week of monitoring, with approximately one month providing a stronger baseline for identifying recurring patterns across relevant questions, engines and markets. The agency can then present the findings, explain their business relevance and propose targeted improvements or ongoing monitoring.
Tools that support a GEO audit
Manual checks and screenshots are useful for an initial look, but a few hand-picked prompts are a weak basis for a recurring client benchmark. Answers and links may vary by question wording, time, market and session context; ad hoc collection can also miss failed responses or apply inconsistent counting rules. For client-facing audits that inform investment, use an AI Search measurement solution with documented collection methods, repeatable question and market settings, saved full answers, exact cited URLs and comparable historical observations. Still inspect the underlying answers and pages before recommending action.
AI Search analytics platforms, including Superlines, Peec AI and Semrush, support monitoring at greater scale. Compare tools' collection methods, engine and market coverage, source access and reporting options before treating their measurements as interchangeable.
Superlines, the publisher of this guide, is a full GEO platform centered on AI Search visibility for enterprise marketers and agencies. It combines visibility, citations, sentiment, competitor and source intelligence, and reporting across brands and markets. Action Center recommendations help teams plan improvements; website audits, technical/schema optimization and content generation support that work.
Its native website audits assess technical SEO, content quality and AI Search readiness. Use those checks alongside answer and source inspection: a website audit alone does not establish whether an AI answer has the right price, which third-party page repeats an error or whether a recommendation fits the buyer.
Current Superlines plans list monthly site audits on Pro and weekly audits on Growth and Enterprise; Starter does not include Site Crawl & Audit. Starter, Pro and Growth include three chosen answer engines, with broader coverage on Enterprise. Exports start at Pro, API access at Growth, and MCP access is included across plans. Match the plan to the brands, markets, history and review workflow your audit needs.
Check what changed after the work
Review the corrected pages first, then return to comparable answers and the core metrics. Report whether the information is now accurate, whether the important recommendation changed and how visibility and citations compare with the baseline. Mark changes in collection coverage.
Review identifiable AI referral visits, website conversions and CRM outcomes separately from changes in answer visibility.
An effective audit ends with a clear finding and an appropriate response: correct, improve, investigate or continue observing. Start a Superlines trial to inspect your brand's AI Search visibility, or book a demo to discuss an audit across your brands and markets.