July 16, 2026 • Search Engine Land
Before a business invests more in local SEO, it should measure whether AI platforms mention it at all, according to a new Search Engine Land guide by Adam Heitzman. The five-step "local GEO baseline audit" runs structured prompts across ChatGPT, Perplexity, Gemini, and Google AI Overviews, then scores every response on five data points: mention, mention order, sentiment, factual accuracy, and cited sources. The stakes are larger than most owners assume — in research cited by the guide, ChatGPT recommended only 1.2% of 350,000 analyzed business locations, versus 35.9% appearing in Google's local 3-pack. That is a roughly 30-fold visibility gap between traditional local search and AI recommendations.
Key takeaways
- A local GEO (generative engine optimization) baseline audit benchmarks how AI platforms describe, recommend, or ignore a business before any optimization work begins.
- Audit prompts are organized into four categories — discovery ("best [service] in [city]"), comparison ("[brand] vs. [competitor]"), trust ("[brand] reviews"), and logistics (hours, address, phone) — and tested across ChatGPT, Perplexity, Gemini, and Google AI Overviews with location and login state controlled.
- Each response is scored on mention, mention order, sentiment and framing, factual accuracy, and cited sources, then rolled up into visibility and accuracy percentages.
- Gaps fall into three types with different fixes: invisible (blocked AI crawlers, thin citable content), inaccurate (inconsistent business data, outdated site information), and misframed (weak review profiles and authority signals).
- Business-information accuracy averaged 68% on ChatGPT and Perplexity versus 100% on Gemini, which draws on Google Maps data — and the guide recommends repeating the audit quarterly.
What a local GEO baseline audit measures
The audit establishes a benchmark for AI visibility — share of voice, citation rate, and accuracy — so progress can be tracked over time. The underlying problem it exposes: most local owners concentrate on their Google Business Profile while staying invisible to AI assistants, because AI weighs signals differently than traditional local search. Traditional search prioritizes proximity; AI systems prioritize data confidence, authority, and consistency. A strong map-pack ranking is not a reliable predictor of whether an AI assistant will recommend the business, which is why baseline measurement belongs before any new SEO spending decision.
How the five-step audit works
Step one assembles the inputs: real customer-style queries in four categories — discovery, comparison, trust, and logistics — tested across ChatGPT, Perplexity, Gemini, and Google AI Overviews. Variables are controlled by testing from defined locations, running both logged-in and logged-out sessions, and date-stamping every result.
Step two runs the prompts and records five data points per response: whether the business is mentioned, where it appears in the answer (first, middle, last, or missing), how it is framed (positive, neutral, or negative), whether hours, services, and prices are correct, and which URLs and directories the AI cited. Those results roll up into two summary metrics — a visibility percentage and an accuracy percentage — that become the baseline for future comparisons.
Steps three through five diagnose the gaps, fix them in sequence, and make the audit repeatable on a quarterly cadence, tracking mention rate, positioning, factual error rate, citation count, and competitor share of voice. Notably, the guide advises measuring success in business signals — calls and direction requests — rather than clicks.
Three kinds of gaps — and the order to fix them
Every gap the audit surfaces lands in one of three buckets. An invisible business does not appear for relevant queries, which usually traces back to blocked AI crawlers, too little citable content, or few third-party mentions. An inaccurate listing appears with wrong details — outdated addresses, incorrect hours, discontinued services — typically caused by stale on-site information or inconsistent name, address, and phone data across directories. A misframed business is mentioned but buried beneath competitors, which generally reflects a thin review profile and weaker authority signals — the territory of reputation management.
The fix sequence matters: eligibility first (confirm AI crawlers can access the site, including robots.txt and Cloudflare settings, keep business data consistent, and add LocalBusiness, Organization, FAQ, and Service schema), trust signals second (reviews, ratings, and responses across Google Business Profile, Yelp, and industry sites), and relevance last (location-specific content with real local detail rather than cookie-cutter pages with swapped city names). The Cloudflare point is not theoretical — the network announced it would block AI crawlers by default, which can zero out AI visibility regardless of content quality.
What it means for small businesses
For local service businesses, the four prompt categories map directly onto how customers already ask AI assistants about providers: who is good, who is better, who can be trusted, and how to reach them. A baseline audit answers a budget question before it becomes a budget mistake — if AI never mentions the business, the first dollars belong in crawler access, data consistency, and schema, not more content. If AI mentions the business but gets the facts wrong or ranks competitors first, the priorities shift to data hygiene and reviews. That diagnostic-first sequencing is the same logic behind a good Google Business Profile setup, extended to the platforms where AI-search visibility is now decided.
The ONmetrics Take
This guide is the audit-before-action principle applied to AI search, and the three gap types are the useful part: invisible, inaccurate, and misframed are three different problems with three different budgets. Most local businesses guessing at "AI SEO" are spending on relevance content while failing the eligibility check — the cheapest fix on the list, and the one with the biggest downside when missed, now that Cloudflare blocks AI crawlers by default.
For London, Ontario businesses, the numbers argue for measuring before moving. A 1.2% recommendation rate on ChatGPT against 35.9% local 3-pack visibility means a business can dominate the map pack and still not exist in the channel a growing share of customers ask first. And the guide's advice to track calls and direction requests instead of clicks matches how we think about measurement generally: business outcomes, not traffic totals.
If you want to know whether AI recommends your business, gets your hours right, or hands the conversation to a competitor, get a free digital marketing audit and we will baseline your local and AI-search visibility together.
Source
Original reporting: Search Engine Land — "How to run a local GEO baseline audit." https://searchengineland.com/local-geo-baseline-audit-482477