What does the report include?

Per-engine scorecard with all five dimension scores, brand recognition detail, market competition section with web-grounded competitor donut charts and common comparison axes, analysis summary with key strengths and growth areas, contextual analysis, and a full sentiment analysis breakdown.

AI VISIBILITY AUDIT - FREE TOOL

What does AI know about your brand?

Q: How is the score calculated?

Each engine self-scores across five dimensions: Brand Sentiment (40 points), Presence Quality (20), Brand Recognition (20), Share of Voice (10), and Market Competition (10). The composite is the sum, capped at 100. Each engine's score is independent.

Audit how OpenAI, Anthropic Claude, and Google Gemini characterise your brand - from their training data, no live web search. Get a per-engine 100-point score across five dimensions and a written report you can act on.

Three engines audited side-by-side - OpenAI, Anthropic, Google.
Brand recognition and sentiment measured from training data - what the LLMs know about you natively.
Competitor map web-grounded - the real peer set you are benchmarked against.
Built by MO Agency - HubSpot Elite Partner specialising in RevOps and AEO.

Company name *

Location * The geography that best describes the reach of your business.

Industry * Aligned with the brand's core business activities.

Products or services * Be specific - describe your offering as your customers would.

We ask OpenAI, Anthropic Claude, and Google Gemini what they know about your brand - from their training data, no live web search. Typically takes 30-60 seconds.

HOW IT WORKS

Three steps. Sixty seconds.

Run the free AI Visibility Audit in under a minute. We ask three AI engines what they know about your brand and return a side-by-side report.

Tell us about the brand

Company, location, industry, and what you sell. Four fields - exactly enough to ground the engines.

Two-layer audit per engine

OpenAI, Claude, and Gemini each return a training-data characterisation AND a web-grounded competitor map - both validated against a schema.

Read the side-by-side report

Per-engine 100-point scores, dimension breakdowns, real competitors with share of voice, strengths, and growth areas - PDF copy emailed to you.

Per-engine scorecard

Three engines. Three answers. One scorecard.

Every serious AI visibility audit starts with the same uncomfortable truth: you cannot optimise for "AI search" as a single channel. ChatGPT, Anthropic Claude, and Google Gemini each train on different data, weight different sources, and surface different versions of your brand. The per-engine scorecard breaks down a 100-point AEO score across five dimensions - brand sentiment, presence quality, brand recognition, share of voice, and market competition - for each of the three engines that drive the overwhelming majority of consumer and enterprise AI traffic. You see exactly which engines view you as a leader, a challenger, or invisible. This is the foundation of any serious AEO or GEO strategy: you cannot fix what you have not measured per engine.

Brand Recognition

If LLMs do not know you, nothing else matters.

Recognition is the entry-level question every AI visibility audit must answer: when an LLM is asked about your category, does it surface your brand at all, and how confidently? This section quantifies your recognition score, market position (Niche, Challenger, or Leader), confidence level, mention depth, source quality, and data richness for each engine. Low recognition means the model has thin or shallow training data on your brand - the kind of gap that no amount of traditional on-page SEO can close. Improving it requires earned media, deeply indexed content, and authoritative third-party citations that AI training pipelines actually ingest. Brand recognition is the price of entry for AEO; without it, every downstream optimisation is wasted effort.

Market Competition

Your real competitive set, as AI sees it

Each engine uses its live web search tool to surface who your real competitors are right now - not who they were when the model was last trained. This is web-grounded competitive intelligence, not training-data guesswork. The audit returns a market score, a competitor breakdown with percentage share of category mindshare, and the common comparisons buyers are making in AI conversations about your industry. This is the data that tells you whether you are an 18% challenger or a 5% afterthought when ChatGPT recommends a vendor. For most brands it is the single most uncomfortable - and most actionable - section of the audit, because it forces you to confront the gap between how you market yourself and how AI actually frames the category.

Analysis summary

Strengths and gaps, per engine, in their own words.

The analysis summary is the action layer of the audit. For each engine, three key strengths are surfaced from training data alongside three growth areas to attack next. You see exactly what narrative each model has internalised about your brand - your established positions, your differentiators, your category associations - and where it sees gaps relative to category leaders. The growth areas read as a prioritised AEO and GEO roadmap: brand distinctiveness gaps, content depth gaps, sentiment management gaps, and digital footprint gaps that are holding your AI visibility back. This is the section your AEO agency or in-house team will work from for the next ninety days, and the one that converts a diagnostic into a strategy.

Contextual analysis

The narratives AI tells about your brand.

Contextual analysis surfaces the recurring narrative themes each engine associates with your brand - the stable patterns that emerge across thousands of AI conversations about you. These themes reveal what your brand is "for" inside the model: which category positioning has stuck, which differentiators have been encoded, and which associations are working for or against you. If you want to be known for innovation but every engine surfaces you as "established but undifferentiated", that gap is now visible and measurable. Narrative themes are downstream of your published content, press coverage, and third-party citations. Shaping them deliberately - through thought leadership, PR, and authoritative content - is the longest-leverage AEO investment you can make.

Sentiment analysis

Sentiment is four scores, not one.

Sentiment in AI is not a single number - it is four. The audit breaks brand sentiment into general perception (the baseline view of your brand), contextual perception (how you are framed inside your category), source-based sentiment (what tone the underlying sources actually carry), and polarisation (how consistent or divided opinions about you are). Each facet scores out of 100 with the key factors that drive it. This matters because LLMs do not just decide whether to mention you - they decide how to mention you. A brand can have strong recognition and poor sentiment, leading to mentions that actively undermine consideration. This is where AI visibility crosses over from quantity to quality, and where AEO becomes a brand-management discipline rather than a technical one.

WANT HELP RUNNING THESE PLAYS

Operationalise AEO across content, PR, and CRM-led nurture

MO Agency is a HubSpot Elite Partner specialising in RevOps and Answer Engine Optimisation. We help B2B brands move the scores - not just measure them.

Talk to us about AEO

WHY AEO MATTERS

The buying journey now starts in the AI answer, not the search results

ChatGPT, Claude, Gemini, and Copilot are answering questions that used to go to Google. For B2B buyers researching vendors, AI is increasingly the first surface where your brand is described - or omitted - before any salesperson is engaged. If the answer engine does not know your brand, you have lost the consideration before the buyer ever visited your website.

Most enterprise AI does not perform web search

Microsoft 365 Copilot, Slack AI, Salesforce Einstein, and ChatGPT without browsing answer questions directly from training data. No live retrieval. If the model does not know you, no amount of SEO will help - the request never reaches a search engine. AEO is about being known natively by the models.

Each engine has different training data

Being known to ChatGPT does not mean being known to Claude. Each engine ingests different sources, different snapshots, different volumes. A brand that ranks well in one engine can be invisible in another. This audit measures each one separately so you know which engines need work.

Wikipedia, schema, and third-party coverage move the needle most

Engines weight independent, authoritative sources heavily. Your own website is one input among many. The brands AI knows best have Wikipedia pages, indexed structured data, third-party reviews, podcast appearances, partner directory listings, and consistent factual signals across the open web.

The competitor set AI puts you in shapes how buyers compare you

When a buyer asks for the best HubSpot partners in South Africa, the engine returns a list. Whether you are in that list - and who you are listed alongside - sets the consideration frame. This audit pulls each engine's actual competitor set for your category and geography, so you see exactly where you stand.

WHO IT IS FOR

Brands that take AI visibility seriously

The teams already running an AEO programme - and the teams who know they need to start.

B2B SaaS and enterprise software

You are competing on consideration with vendors that have stronger AI training-data footprints. Map the gap, prioritise the fixes.

Specialist agencies and consultancies

Your buyers ask AI for shortlists. If you are not in the answer, you are not in the deal. Set a baseline and direct your content and PR programme.

Regional brands in global categories

You compete locally but AI has been trained globally. Find out whether engines know your regional context or default-list international names instead.

NEXT STEPS

Five plays that move the needle most

What to actually do with the report once you have it. The same plays we run for clients on retainer.

Audit competitor positioning

Run the audit on three direct competitors. Compare the per-engine scorecards. The gaps surface exactly which dimensions are differentiated vs commoditised in your category.

Fix the weakest dimension first

Sentiment is fixed at the source (third-party reviews, case studies). Presence is fixed by diversifying mentions. Recognition is fixed by reaching threshold scale of independent signals. The report tells you which lever to pull.

Get into the directories AI ingests

HubSpot Partner Directory, Clutch, G2, Capterra, Crunchbase, sector-specific review sites. AI engines weight these heavily because they are independent and structured. Audit your top 10.

Publish methodology-led content

Engines surface content that takes a position, defines a framework, or demonstrates a methodology. Generic corporate copy gets ignored. Concrete, opinionated, attributable content is what AI cites.

Re-run the audit quarterly

AI training data refreshes on roughly monthly cadences across the engines. Re-running every 3 months lets you correlate which programmes - PR push, directory submission, new content - actually moved the score.

What is AEO (Answer Engine Optimisation)?

AEO is the practice of optimising your brand's presence so that AI answer engines (ChatGPT, Claude, Gemini, Copilot, Perplexity) describe you accurately and surface you in the answers buyers ask. It is SEO's natural successor for the generative-AI era. Where SEO optimises for search ranking, AEO optimises for how AI describes and cites you when a buyer asks a question.

How is this audit different from a traditional SEO audit?

SEO audits measure how you rank in search results. AEO audits measure how AI characterises you in answers. Different surfaces, different mechanics, often different winners. A brand can rank well in Google but be invisible in ChatGPT, or vice versa. You need both.

Why training-data only - why not live web search?

Most enterprise AI use cases hit the model directly without retrieval - Copilot in Word, ChatGPT without browsing, Claude in enterprise tools. That is the surface where AEO actually matters. Mixing in live search gives a number that conflates two very different things: what the AI knows vs what it can google. We separate them. Sentiment and recognition come from training data; the competitor map comes from web search.

How accurate are the scores?

Each engine returns a structured self-assessment against a defined rubric. Two runs with identical inputs return very similar scores - the methodology is deterministic. The engines themselves do disagree (their training data differs), and that disagreement is the point: we show all three so you can see which engines have rich data on you and which do not.

How is the score calculated?

The point-allocation breakdown (40/20/20/10/10) is now in the Per-engine scorecard module. Tighten the FAQ answer to: "Each engine self-scores against the same five-dimension rubric described above. The composite is the sum, capped at 100. Each engine's score is independent - we do not average across engines because the disagreement between them is part of the signal.

What engines do you audit?

OpenAI (powers ChatGPT), Anthropic Claude (powers most enterprise copilots including the Claude API and many embedded AI assistants), and Google Gemini (powers Google AI and the Gemini app). These are the three engines that dominate enterprise AI use today.

Can I run the audit on a competitor?

Yes. The audit takes any brand. Run it on a direct competitor to see how AI characterises them - useful for positioning, sales battlecards, and gap analysis. The form takes four fields about the brand you want to audit; it does not have to be your own.

How long does the audit take?

30 to 90 seconds. We run all three engines in parallel, plus a web search per engine for the competitor map. Reports are delivered as a PDF to the email you provide on the form.

Who builds this tool?

MO Agency. We are a HubSpot Elite Partner specialising in revenue operations and AEO. We built the tool to give the agency conversation a defensible baseline - here is what AI says about you today, here is what we would do about it. If you want help moving the scores, that is the service.

What happens to my data?

The four audit inputs (company, location, industry, products) are sent to the three AI providers. Your email and the audit metadata are stored in our HubSpot CRM under standard GDPR and POPIA consent terms. We do not sell or share personal data. You can unsubscribe at any time.

Is this really free?

The audit is free. We run it as a lead-gen tool for our agency services. You are under no obligation - many people run the audit, get the PDF, and implement the recommendations themselves. The ones who want a hand reach back out to us. Either way works.