AI VISIBILITY AUDIT

AI Visibility Audit: What Free Checkers Can't Tell You

An AI visibility audit (sometimes called an AI search audit) shows how ChatGPT, Gemini, Perplexity, Claude, Microsoft Copilot, Google AI Overviews and AI Mode describe, cite and recommend your brand against named competitors, and why. I'm Ajay Padhy, a GEO and SEO consultant with 14+ years in search. I build the prompt set around your revenue, analyse the sources behind each answer and hand you a ranked fix list your team can act on.

An audit clipboard scoring brand visibility across AI assistants

At a glance

  • Fixed scope: a one-off audit that takes about a week at most, with a walkthrough session. No retainer required.
  • Custom prompt set: built from your sales conversations and search data, not a generic template — and yours to keep for tracking.
  • Beyond a score: every finding traces back to the sources the AI cited, so fixes are specific rather than "create more content".
  • Accuracy check: I flag every factual error AI systems repeat about your pricing, products, locations or leadership.
  • Honest fit: if a free checker would answer your question, I'll tell you — the DIY checklist below is a genuine starting point.

OUTCOMES

What this engagement is measured on

Every client's goals are different, and most are a mix. In the first weeks we agree which of these matter to you, record a baseline, and report against it every month. Targets are set after the audit, never promised up front.

Visibility, AI search and brand reach

A baseline of your mention, citation and recommendation rate against named competitors.

What we measure
Keywords in the top positions, presence in Google AI Overviews, how often AI assistants mention and cite you, and branded search demand.
What usually moves first
Answer-ready pages appearing in AI Overviews and AI citations; more keywords entering the top 10.
What follows
More branded searches and more recommendations by AI assistants.

Authority: backlinks and topic authority

A list of the sources AI systems use for your category, and where you are missing.

What we measure
Relevant referring domains, link quality, Domain Authority/Rating trend and how much of each topic your site covers and ranks for.
What usually moves first
New links from relevant sites and more of your topic pages indexed and ranking.
What follows
Rankings on the competitive head terms that need authority to move.

Who this is for

Search "AI search visibility" and the results are mostly free checkers and tracking dashboards. They're useful. They'll tell you, for a set of generic prompts, how often your brand name appears. What they can't tell you is whether those are the prompts your buyers actually use, why a competitor wins the answer, or which single page, profile or review site to fix first.

That's the gap a human AI visibility audit fills. I start from your commercial reality — the questions prospects ask on sales calls, the comparisons they make, the objections they raise — and turn that into a prompt set. Then I read the answers the way a buyer would, trace every cited source and score the patterns. The measurement approach is explained in how to measure AI search visibility.

If you want ongoing automated tracking afterwards, I'll recommend a tool from the options compared in AI visibility tools and load the audit's prompt set into it, so the baseline carries over.

  • Marketing leaders who need a defensible AI search baseline before approving GEO budget
  • Brands that ran a free AI visibility checker, got a score, and don't know what to do with it
  • Companies whose sales team hears "ChatGPT suggested…" and it isn't them
  • SEO teams adding AI search to their reporting and needing a credible starting prompt set
  • Businesses that suspect AI answers contain inaccurate facts about them

DIAGNOSIS

Problems I solve

Common constraints teams face before we begin working together.

Hurdle 01

"The checker gave us 23/100. Now what?"

A score without causes is a number to worry about, not a plan. You need to know which sources drive it and what to change.
Hurdle 02

"Are these even the right prompts?"

Generic tools test generic questions. Your buyers ask about budget, integrations, location and use case — the prompts that decide deals.
Hurdle 03

"Prospects arrive with wrong information"

They quote a price you changed last year or a limitation you fixed. Something the AI trusts is out of date, and you don't know what.
Hurdle 04

"I need to justify the spend to leadership"

You want a baseline you can re-run in three months and show movement against, not a vague sense that AI matters.

AI visibility audit vs free checker vs tracking tool

They answer different questions. Many brands need more than one, in sequence.

DimensionFree AI visibility checkerTracking tool (paid)Human AI visibility audit
Answers"Are we mentioned at all?""Is it trending up or down?""Why, and what do we fix first?"
PromptsGeneric, pre-setYou supply themBuilt from your sales and search data
CompetitorsOften auto-detectedYou configureChosen with you, analysed in depth
Source analysisMinimalDomain listsPage-level, with why it's cited
Accuracy checkNoRarelyEvery answer read and logged
OutputA scoreDashboardsRanked fix list + walkthrough
Best forA first lookOngoing monitoringSetting strategy and a baseline

What's in the report: a sample deliverable outline

This is the structure every audit report follows, so you know exactly what you're buying.

  1. Executive summary — one page: where you stand, the three biggest gaps, the first five actions.
  2. Prompt set — every prompt, grouped by theme (your brand, competitor comparisons, recommended as the solution) and funnel stage (TOFU, MOFU, BOFU), with why each was included.
  3. Scorecard — mention rate, citation rate, recommendation share and sentiment for you and each competitor, by platform, theme and funnel stage.
  4. Answer examples — verbatim excerpts showing how each platform describes you versus competitors.
  5. Source analysis — the domains and pages cited most often, which ones mention competitors but not you, and which of your own pages are never retrieved.
  6. Accuracy log — each wrong or outdated fact, where it appears and the probable source.
  7. Problem classification — each priority prompt marked as absent, described wrongly, mentioned but not recommended, or cited but not named, with the fix for each.
  8. Readable by AI and entity checks — AI search crawlers (OAI-SearchBot, PerplexityBot) allowed in robots.txt, CDN and firewall; key pages that make sense without JavaScript; indexation and snippet eligibility; schema; and consistent facts across your profiles.
  9. Ranked fix list — actions with impact, effort, suggested owner and how we'd measure the effect.
  10. Re-measurement plan — which prompts to re-run, how often, and with what tool.

Findings are grouped under the three pillars of my Read–Know–Recommend framework: readable by AI, known and corroborated, and recommended in the answer.

Free DIY mini-audit: run this yourself in an afternoon

If you only have a few hours and no budget, do this. It will tell you whether a full audit is worth it.

  1. Write 15 prompts your buyers would ask, five per theme. Your brand ("what does [brand] cost?", "is [brand] good for…"); competitor comparisons ("[you] vs [competitor]", "alternatives to [competitor]"); and recommended as the solution ("best [category] for [use case]", "how do I fix [problem]?"). Mix early-research and ready-to-buy questions in each.
  2. Run them logged out, set to your buyers' location, in ChatGPT, Perplexity and Google (check for an AI Overview). Run each prompt several times on each platform, because answers vary. Repeat the set monthly.
  3. Log it in a sheet: were you mentioned (Y/N), recommended (Y/N), cited with a link (Y/N), and which competitors appeared.
  4. Copy every cited URL. Sort by domain. The domains that appear repeatedly are the sources that shape your category's answers.
  5. Check those sources for your presence. Are you on the review sites, lists and comparison articles that keep getting cited? If not, that's your off-site gap.
  6. Mark every factual error about you. Search for the wrong fact in quotes to find where it came from.
  7. Check your own key pages are indexed in Google Search Console and actually answer the question in the first paragraph.

For a deeper method, see how to improve brand visibility in AI search.

Who should skip the audit

I'd rather tell you now than sell you something you don't need.

  • Your Google SEO fundamentals are broken. If key pages aren't indexed or you don't rank for your own brand name, fix that first — SEO consulting will do more for you than an AI audit.
  • Your buyers don't use AI assistants to research. Some local trades and very niche B2B categories still buy by referral. Run the DIY check; if nobody in your category is being recommended, the channel may not matter yet.
  • You only want a number for a slide. A free checker gives you that. The audit is for teams that will act on the fix list.
  • You have no capacity to act for three months. The audit's value decays as models update. Run it when someone can own the fixes.

If you're ready to act and want the full programme rather than a one-off, see my generative engine optimization services.

DELIVERABLES

What you get

Tangible assets, strategic roadmaps and documentation provided during the engagement.

✓

Custom prompt set

Typically 40–100 prompts, depending on scope (the guides suggest 30–50 if you're starting on your own), at each stage of the buying journey (TOFU, MOFU and BOFU) across three themes: how AI sees your brand, how it compares you with competitors, and whether it recommends you as the answer to your buyers' problems. Documented so you can re-run them.
✓

Visibility scorecard

Mention, citation, recommendation share and sentiment by platform, theme, funnel stage and competitor.
✓

Cited-source analysis

The domains and pages each platform relies on for your category, and where you are missing from them.
✓

Accuracy log

Every factual error found, the likely source of it and how to correct it.
✓

Problem classification

Each priority prompt classified into one of four problems (absent, described wrongly, mentioned but not recommended, or cited but not named), with the fix for each.
✓

Ranked fix list

On-site, entity and off-site actions ordered by expected impact and effort, with owners suggested.
✓

Walkthrough session

A recorded call where I take your team through findings and answer questions.

WORKFLOW

How an engagement works

A clear, four-phase delivery model ensuring accountability from kickoff to ongoing impact.

  1. 01Phase 1

    Scope

    A short call to agree platforms (by default ChatGPT, Gemini, Perplexity, Claude, Microsoft Copilot, Google AI Overviews and AI Mode), 3–5 competitors, markets, the buyer questions that matter commercially, and the languages your buyers use, including Hindi, Hinglish or regional languages where relevant.
  2. 02Phase 2

    Run

    Run each prompt several times per platform, logged out and set to your buyers' location, capturing every answer, citation and variation between runs.
  3. 03Phase 3

    Analyse

    Score visibility, trace sources, log inaccuracies and find the patterns behind competitor wins.
  4. 04Phase 4

    Hand over

    Deliver the report, prompt set and fix list in a walkthrough, with a recommendation on next steps (including "do it yourselves").

Ways to work together

Every engagement is led by me personally. For execution, I work with a small team of specialists — technical SEO, content, development and automation — so you get senior thinking without agency layers, account managers or hand-offs.

Audit & roadmap

A fixed-scope diagnosis with a prioritised roadmap your team can act on. Typically 2–4 weeks.

Advisory retainer

Ongoing senior guidance: monthly strategy, reviews of your team's work, and a direct line to me when decisions come up.

Strategy + execution

I own the strategy and stay your single point of contact; my specialist team handles implementation — technical fixes, content, builds and reporting.

TOOLING

Tools I use

Industry-standard platforms and custom automation stacks used to audit, track, and execute.

ChatGPT
Gemini
Perplexity
Claude
Microsoft Copilot
Google AI Overviews
Google AI Mode
Google Search Console
GA4
Python

FAQ

AI visibility audit: questions clients ask

Straight answers to what people usually want to know before a first call.

An AI visibility audit, sometimes called an AI search audit, measures how AI assistants such as ChatGPT, Gemini, Perplexity, Claude, Microsoft Copilot, Google AI Overviews and AI Mode mention, cite and recommend your brand compared with competitors. A good audit also explains why: which sources the AI relies on, which facts it gets wrong and which specific fixes are likely to change the answers.

They are accurate for what they measure: whether your brand appears for a generic set of prompts at one moment. Their limits are prompt relevance, single-run snapshots and no explanation of causes. Use one for a quick first look, then build a prompt set that reflects real buyer questions before making decisions.

Yes, several software companies offer one. It's a fair first look, but it is a single snapshot of generic prompts, usually run once each, with no explanation of why a competitor wins. The DIY checklist on this page is the next step.

About a week at most from scoping call to walkthrough. The prompt count depends on scope, usually 40 to 100 prompts depending on the number of platforms, competitors and markets. Most of that time goes into running prompts repeatedly, tracing cited sources and checking accuracy by hand — the parts automated tools skip.

Monthly is a sensible default for tracking, using the same prompt set so results are comparable. A full audit is worth repeating every six to twelve months, or after a major model update, rebrand or product launch changes what AI systems should be saying about you.

AI brand visibility tracking is repeated, scheduled measurement of how often and how favourably AI systems mention your brand for a defined set of prompts. It shows trend over time. It works best when the prompt set comes from an audit, so you are tracking the questions that actually drive buying decisions.

The audit shows exactly where it happens: which prompts use your URL as a source while the answer credits the information generically or names a competitor. It usually means the model takes your facts but doesn't connect them to your brand. The fixes are putting your brand name next to your original data and definitions, naming your company consistently everywhere, and earning mentions on sites that name you.

Analytics only shows part of it, because many people read an AI answer and then visit directly or search your brand name. Add "An AI assistant (ChatGPT, Perplexity, Gemini…)" as an option in your enquiry form's "How did you hear about us?" field, and the same value as a lead source in your CRM. It won't catch everything, but it records influence that would otherwise show up as direct or branded search.

Yes, in the longer run. AI won't show you overnight: like Google, it builds an understanding of context and relevance before recommending a brand, so consistent presence raises your chances over time. AI answers the general questions itself, and users click through when their intent is higher, so the visits may be few but they tend to matter more.

Have a growth problem worth solving?

Tell me where you're stuck. On a 30-minute intro call I'll tell you where I think the constraint is and what I'd look at first — whether or not we end up working together.