What Is an AI Visibility Audit?
An AI visibility audit measures how often, how favourably, and from which sources AI engines like ChatGPT, Claude, Perplexity, Gemini and Google AI Mode cite your brand when answering prospect queries. It's distinct from a traditional SEO audit, which checks whether Google can crawl and rank your pages. An AI audit asks a different question entirely: when a customer asks an AI model who to hire, does your business get named?
The audit covers three dimensions:
- Citation frequency. Out of 20 to 50 relevant prompts, how many times is your brand mentioned by name?
- Citation sentiment. When you're mentioned, is the AI describing you positively, neutrally, or with reservation? Sentiment matters more than frequency once you cross the recognition threshold.
- Citation sources. Which third-party websites (Hellopeter, Reddit, industry directories, news sites, Wikipedia) is the AI pulling from when it talks about your category? If you're absent from those sources, you've found your remediation list.
In our last 12 audits across Durban, Johannesburg and Cape Town clients, citation source patterns turned out to be more predictive of growth than rankings. Two clients ranking page-two on Google scored above 40% AI citation rates because they had strong hellopeter.com and Reddit footprints. Three clients ranking page-one organically scored under 10% because their authority lived only on their own website.
Why Your Traditional SEO Audit Isn't Enough in 2026
A traditional SEO audit checks crawlability, indexing, on-page tags, schema, internal linking, Core Web Vitals, and backlinks. None of those signals tell you whether ChatGPT recommends you. We've audited 40+ South African businesses ranking page-one for their target terms, and roughly 70% of them weren't cited once in AI Mode responses for the same queries.
The reason is structural. Google Search returns ten ranked links and lets the user pick. AI engines synthesise a single answer from multiple sources and only name the entities they trust most. Being the #1 ranking page no longer guarantees you're the #1 cited brand. Citation depends on entity authority, third-party validation, and content structured for extraction, not just for ranking.
Google itself confirmed the traffic shift at I/O 2026: roughly 4.5% of AI Mode sessions produce a click to an external website, compared to 24% in traditional search. The Pew Research figures Google referenced suggest small publishers have seen 60% traffic drops since AI Overviews launched. If your only audit checks rankings, you're measuring traffic that's actively shrinking while missing the layer where attention is moving.
One Durban dental practice we audited in March was ranking #1 for "dentist Umhlanga." When we tested ChatGPT, Claude and Perplexity with that exact query, the practice wasn't mentioned in any of them. The AI cited two competitors with stronger Hellopeter footprints and a third with a YouTube channel. Rankings don't translate. They're necessary, but they're no longer sufficient.
AI Visibility Audit vs SEO Audit: Side-by-Side
The shortest answer: an SEO audit checks if Google can crawl and rank your pages. An AI visibility audit checks if AI engines trust your brand enough to recommend you inside generated answers. Both matter. Only one tells you whether you're capturing the search traffic that's growing.
| Dimension | Traditional SEO Audit | AI Visibility Audit |
|---|---|---|
| Primary metric | Keyword rankings + organic traffic | Citation frequency, sentiment, source mix |
| Engines tracked | Google, Bing | ChatGPT, Claude, Perplexity, Gemini, Google AI Mode, AI Overviews |
| Signals analysed | Title tags, headings, schema, backlinks, Core Web Vitals | Entity consistency, third-party mentions, citation-worthy content, llms.txt, schema |
| Tools used | Search Console, Screaming Frog, Ahrefs, Semrush | Manual prompt testing, Semrush AI Toolkit, Ahrefs Brand Radar, RankScience, LLMClicks |
| Update frequency | Quarterly | Monthly (LLMs retrain often) |
| Reveals | Technical issues, content gaps, ranking opportunities | Citation gaps, entity weaknesses, source preferences |
| Acts on | On-page + technical fixes | Off-page authority, entity building, content restructuring, llms.txt |
| Output | Ranking improvements over 3 to 6 months | Citation lift visible in 30 to 90 days |
The two audits aren't replacements. They're complements. Run both, and the SEO audit fixes your foundation while the AI visibility audit tells you which third-party signals to invest in next.
The 5-Step Free AI Visibility Audit (30 Minutes, No Tools)
You can audit your AI visibility right now with five browser tabs, a spreadsheet, and 30 minutes. The method below is what we run on every prospect before quoting any GEO work. It costs nothing and gives you 80% of what paid tools deliver.
Step 1: Build Your Prompt List (5 minutes)
Open a spreadsheet. Create 20 prompts a real customer would actually type, split across three categories:
- 10 unbranded commercial prompts. "Best [your service] in [your city]." "Top [your category] for [customer type] in South Africa." "Who should I hire for [your service]?" These tell you whether AI engines recommend your category and whether you're in the recommendation set.
- 5 comparative prompts. "[Competitor A] vs [Competitor B]." "Compare [your service category] providers in [city]." These reveal who AI sees as the natural alternatives to you.
- 5 branded prompts. "Is [your brand] reputable?" "[Your brand] reviews." "What does [your brand] do?" These test whether AI even knows you exist and what it says when asked directly.
Step 2: Test Across Five AI Engines (15 minutes)
Open five browser windows, all in incognito mode and logged out. Test each prompt across:
- ChatGPT (chatgpt.com) with web search enabled
- Claude (claude.ai)
- Perplexity (perplexity.ai)
- Google AI Mode (google.com, AI Mode toggle)
- Gemini (gemini.google.com)
Why logged out and incognito? Each model personalises responses based on memory and account context. Logged-out testing gives you the baseline a stranger would see. That's the fair benchmark.
For each prompt, screenshot the response or paste the relevant section into your spreadsheet. Tag whether your brand appears, in what position, and which competitors are named alongside or instead of you.
Step 3: Score Your Appearance (5 minutes)
For each of the 100 prompt-engine combinations, log four data points:
- Cited? Yes or No.
- Position. First, second, third, or mentioned in passing.
- Sentiment. Positive (recommended, praised), neutral (named but flat), negative (named with a caveat or criticism).
- Competitors named. Who showed up instead of or alongside you.
Step 4: Identify Source Patterns (3 minutes)
Most AI engines now show their sources. Look at which domains are being cited across your category prompts. Common SA patterns we see:
- Hellopeter and Brabys for local services and trades
- Reddit (r/southafrica, r/personalfinance, niche subreddits) for advice-driven queries
- YouTube for "how to" and "best of" comparisons
- Industry-specific directories (e.g. SAICA for accounting, LSSA for legal)
- News sites (News24, Daily Maverick, BusinessTech) for any category with topical news flow
- Wikipedia for category definitions and large entities
If your business is absent from the sources AI is citing, you've found your remediation list. Earn placement on those domains and your citation rate climbs.
Step 5: Build Your Scorecard (2 minutes)
Calculate citation rate: brand mentions divided by total prompt-engine combinations, multiplied by 100. So if your brand appears in 12 of 100 combinations, your citation rate is 12%. We use this benchmark for early-stage clients:
- Above 50% on unbranded prompts: excellent. You're a category leader in AI search.
- 30 to 50%: competitive. You're known but not dominant.
- 10 to 30%: visible but not recommended. Foundation work needed.
- Under 10%: invisible. AI engines effectively don't know you exist.
Save the spreadsheet. This is your baseline. Re-run the exact same audit in 30 days after any meaningful change to your website, schema, or third-party presence. The delta tells you what's working.
What a "Good" AI Visibility Score Looks Like
There's no industry-standard AI visibility score yet, but from running 60+ audits we've developed working benchmarks. Most SA businesses score between 5% and 15% on first measurement. That's not a failure. It's a starting line, and almost every business we've audited had room to triple their citation rate within 90 days of focused work.
Benchmarks by Intent Type
A single citation-rate number hides important nuance. We track three sub-scores:
- Branded prompt score. When someone asks AI about you by name, do you get an accurate, complete answer? Below 60% here means the AI either doesn't know enough about your business or is conflating you with another entity. This is usually the easiest to fix (better Organization schema, more authoritative About content).
- Unbranded commercial score. The hardest and most valuable metric. This is the score that translates to new business. Above 30% is competitive; above 50% is dominant.
- Comparative score. When AI is asked to compare your category, do you appear in the consideration set? Even a "mentioned but not preferred" placement is valuable here because it puts you in the buyer's evaluation list.
Why Sentiment Matters More Than Frequency Past a Threshold
Once you cross 30% citation rate, the next problem is what AI says about you. We audited a Cape Town accounting firm with a 47% citation rate but consistently neutral or guarded language ("offers tax services" rather than "trusted accounting partner for SMEs"). Their conversion rate from AI traffic was poor. The remediation was a third-party PR campaign that produced two case-study features on news24.com and a Hellopeter response strategy. Three months later their sentiment shifted to consistently positive and AI traffic conversion doubled.
AI Visibility Audit Tools Compared
Four tools dominate the AI visibility audit category in 2026: Semrush AI Visibility Toolkit, Ahrefs Brand Radar, RankScience, and LLMClicks. Each has a use case, none of them replaces a manual audit on the first pass. Below is how we use each.
| Tool | Best for | Free tier | Engines tracked | Refresh rate |
|---|---|---|---|---|
| Semrush AI Visibility Toolkit | Teams already on Semrush; competitor benchmarking | Limited (3 prompts) | ChatGPT, Perplexity, Gemini, AI Overviews | Daily |
| Ahrefs Brand Radar | Source citation tracking; backlink correlation | No | ChatGPT, Perplexity, Gemini | Weekly |
| RankScience AI Snapshot | First-time auditors who want a single visibility score | Yes (basic snapshot) | ChatGPT, Gemini | On-demand |
| LLMClicks.ai | Automated prompt testing at scale | Limited trial | ChatGPT, Claude, Gemini, Perplexity | Daily |
| Manual audit (browser + spreadsheet) | First-pass baseline; nuance check; client-quotable evidence | Free | All major models | Whenever you re-run it |
Our usual workflow: manual audit first for baseline and qualitative read, then layer a paid tool for ongoing daily tracking and competitor benchmarking. Tools are excellent at scale and consistency but poor at catching subtle sentiment shifts and source surprises that a human spots immediately.
The Hidden GEO Levers Most Audits Miss
Most AI visibility audits report what's broken but skip the levers that actually fix it. The five highest-impact moves we've used to lift client citation rates from single digits to 40%+ are below. None of them are surface-level.
1. The llms.txt File
llms.txt is the emerging standard for telling AI crawlers which pages to prioritise when summarising your site. It works like robots.txt for AI, except instead of blocking, it guides. We added a comprehensive llms.txt to our own site last week and we recommend it for every client. The file lists your canonical pages, service offerings and citation guidance in a format AI systems can parse cleanly. Most SA business sites don't have one yet, which means this is an easy lead over competitors.
2. Entity Consistency Across the Web
AI engines build entity profiles by triangulating data across your website, Google Business Profile, LinkedIn, Wikipedia, industry directories and review sites. Inconsistent name, address, phone number (NAP) or business description across these sources confuses the entity graph. We've fixed citation rates by 15 percentage points just by cleaning sameAs schema and aligning brand descriptions across 8 to 10 platforms.
3. Citation-Worthy Content Blocks
AI engines prefer content they can quote cleanly. That means short direct-answer paragraphs (45 to 60 words) immediately under each H2, named entities (people, places, dates, products) inside those answers, and statistical claims with attribution. The exact opposite of long meandering "ultimate guide" introductions. We restructure client content to lead every section with a quotable block.
4. Third-Party Proof
AI engines weight third-party mentions more than self-published content. A single feature on news24.com, a strong Hellopeter rating with substantive review responses, a Reddit thread where you've answered helpfully, or a YouTube video where you're cited as an authority will lift your citation rate more than ten new blog posts. Off-page work is where most SA SEO budgets underinvest.
5. Schema Beyond the Basics
Organization, LocalBusiness and BreadcrumbList are table stakes. The schema types that actually move AI citation are FAQPage (provides direct Q&A blocks AI can quote), Article with author and citation metadata, Service or Product with provider attribution, and Review for third-party validation. Our complete schema markup guide walks through which types to add by site type.
South African Considerations for AI Visibility Audits
South African businesses face factors AI visibility audits should account for that generic global playbooks miss. POPIA-aligned review responses, ZAR pricing transparency, Hellopeter as a primary trust signal, suburb-level service area data, and the load-shedding context that affects when SA customers actually search. Each one shifts how AI engines evaluate your authority for SA-specific queries.
Hellopeter Is the SA Trust Layer
For South African category queries, Hellopeter.com is one of the most-cited domains across ChatGPT, Perplexity and Google AI Mode. AI engines treat it as the local equivalent of Trustpilot. A weak Hellopeter footprint (few reviews, unresponded complaints, low average rating) actively damages your citation chances. A strong one (50+ reviews, 4+ stars, every review responded to) lifts citation rate visibly. We've seen 8 to 12 percentage point swings tied to Hellopeter alone.
POPIA and Review Response Strategy
POPIA constrains how you can respond to reviews that mention client details. AI engines pick up on response quality and tone. The safe pattern is to acknowledge specific service categories ("our conveyancing service") without naming clients or matter details, demonstrate domain expertise in the response, and resolve publicly. Sloppy POPIA-violating responses get screenshot and reposted on Reddit, which feeds back into AI's perception of your brand.
Suburb-Level Service Area Data
AI engines parse SA service-area queries with surprising granularity. "Plumber Umhlanga" and "plumber Durban North" are treated as different intent sets, with different cited businesses. Service-area schema on your Google Business Profile and an areaServed list inside LocalBusiness schema on your website tell AI exactly where you operate. Generic "Durban" coverage loses to specific suburb coverage.
ZAR Pricing Transparency
Where regulation allows it (and pricing is genuinely market-rate), publishing ZAR pricing on your site lifts citation rate for commercial-intent prompts. AI engines treat priced services as more authoritative than "contact us for a quote" pages because pricing is a quotable, factual signal. Several of our service-business clients lifted citation by 6 to 10 points by adding indicative price ranges with appropriate disclaimers.
Load-Shedding Context
If your category is affected by load-shedding (security, food retail, telecoms, hospitality), AI engines now weight Eskom-aware content. A backup-power page, a load-shedding FAQ, or an SLA that references stage-aware operation are entity signals AI uses to evaluate SA-relevance. Generic global content from competitors with no SA context loses to local content that names Stage 4 and references the realities of running operations through it.
When to Hire a Professional AI Visibility Audit (and What to Look For)
Hire it out when your free audit revealed under 20% citation rate and you can't identify the source pattern, when you're competing in a regulated industry where AI sentiment carries legal or compliance risk, or when you've already completed the technical foundation and need an outside view on the off-page strategy. Self-auditing is a great starting point. It's not a substitute for a deep, multi-engine, source-mapped report when budget is on the table.
What a Quality AI Visibility Audit Should Include
If you're commissioning an audit from an agency, the deliverable should cover all of the following. If any of these are missing, push back.
- 50+ prompts tested across branded, unbranded commercial and comparative intent
- 5+ AI engines covered, including at least ChatGPT, Claude, Perplexity, Gemini and Google AI Mode
- Sentiment analysis for every cited mention (positive, neutral, negative, with examples)
- Competitor citation mapping showing who's being cited instead of you, and why
- Source preference report showing which third-party domains AI prefers for your category
- llms.txt review and recommended draft if missing
- Schema audit covering Organization, LocalBusiness, FAQPage, Article, Service, Review
- Entity consistency check across website, GBP, LinkedIn, industry directories and Wikipedia (if applicable)
- 30-day prioritised action plan with effort estimates and expected impact per item
- Re-audit cadence at 30, 60 and 90 days to measure citation lift
For a recent CMO-level perspective on the audit questions worth asking, Search Engine Journal published "The AI Search Visibility Audit: 15 Questions Every CMO Should Ask" in October 2025. It pairs well with this playbook if you're scoping an audit internally before commissioning external work.
FAQ: AI Visibility Audits
What is an AI visibility audit?
An AI visibility audit measures how often, how favourably, and from which sources AI engines like ChatGPT, Claude, Perplexity, Gemini and Google AI Mode cite your brand when answering relevant prospect queries. Unlike a traditional SEO audit (which checks Google rankings), it tracks recommendations inside synthesised AI answers.
How is an AI visibility audit different from a traditional SEO audit?
An SEO audit checks if Google can crawl, index and rank your pages. An AI visibility audit checks if AI engines trust your brand enough to recommend you inside generated answers. SEO audits report on rankings and technical issues. AI visibility audits report on citation frequency, sentiment and which third-party sources AI prefers.
How do I check if ChatGPT or Perplexity is mentioning my business?
Build a list of 20 prompts a customer would type: 10 unbranded ("best [service] in [city]"), 5 comparative ("[competitor] vs your category"), and 5 branded ("is [your brand] reputable"). Paste each prompt into ChatGPT, Claude, Perplexity, Gemini and Google AI Mode while logged out. Log whether your brand is cited, in what position, and which competitors are named. A spreadsheet and 30 minutes is enough to start.
What is a good AI visibility score?
There's no industry-standard score yet. From running 60+ audits we use this benchmark: above 50% citation rate on unbranded prompts is excellent, 30 to 50% is competitive, 10 to 30% means you're being seen but not recommended, and under 10% means AI engines don't know you exist. Most South African businesses we audit score between 5 and 15% on first measurement.
How often should you run an AI visibility audit?
Monthly is ideal because LLMs refresh their training data and citation behaviour changes faster than Google rankings. At minimum, audit quarterly. Re-audit immediately after any significant content release, schema rollout, third-party PR campaign or competitor move. If you've just completed remediation work, re-audit at 30, 60 and 90 days.
Want the Audit Done Properly?
If your free audit revealed a citation rate under 20% and you'd rather not build the source-mapping and schema fixes yourself, our AI Visibility Audit covers all 10 deliverables above. 5-engine testing, sentiment analysis, source preference mapping, and a 30-day prioritised remediation plan. Quote turnaround: 48 hours.
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