"AI visibility" sounds abstract until you break it into things you can actually inspect. There is no dashboard equivalent to a Google Search Console ranking report — no single number a platform hands you. But the underlying causes of whether an AI assistant recommends a business are concrete, checkable, and mostly outside the business's marketing department: they live in robots.txt, in schema markup, in review platforms, in page copy, and in directory listings.
This is the same five-signal method AEO Radar's free scan runs automatically. Here's how to check each signal by hand, what a pass or fail actually looks like, and which signal is worth fixing first.
The five signals, in order of impact
Signal 1 — Crawler access (the gate)
Before on-site content can appear in an answer, the relevant search crawler has to be able to retrieve it. Check the effective robots.txt policy for OAI-SearchBot, Claude-SearchBot, and PerplexityBot — the published search or retrieval crawlers for ChatGPT, Claude, and Perplexity. A blanket User-agent: * / Disallow: /, or a specific block for one of these agents, prevents that crawler from fetching the affected pages. A missing robots.txt file is not a failure: crawling is allowed by default. Training-only crawlers are a separate privacy choice and are not treated here as a search-visibility signal.
Signal 2 — Structured schema (the clarity layer)
LocalBusiness or Organization JSON-LD markup tells an AI system unambiguously what your business is, where it operates, and when it's open — rather than requiring the model to infer this from unstructured prose, which it can get wrong. Check by viewing your page source and searching for application/ld+json, or by running your homepage through Google's Rich Results Test. A controlled Ahrefs study (1,885 pages, difference-in-differences methodology) found schema markup's independent effect on AI citation rate ranged from −4.6% to +2.2% — a range that overlaps zero.1 Schema is worth having for accuracy and rich-snippet eligibility. It is not, on its own, a citation driver — don't over-invest here relative to the signals below.
Signal 3 — Reviews and UGC (the strongest measured signal)
Among the signals SOCi studied, review data showed the strongest relationship with AI recommendation. Across 350,000+ locations, the average rating of locations recommended by ChatGPT was 4.4 stars; Perplexity, 4.3; Gemini followed Google's 4.2-star average.2 These are descriptive averages, not platform thresholds or minimums, so RaveHQ uses them as context rather than a pass/fail gate. Recency adds a separate customer-trust signal: BrightLocal's 2026 survey found 74% of consumers only trust reviews from the last three months, and 32% only trust reviews from the last two weeks.3
Signal 4 — Content structure (the extraction layer)
AI systems quote and cite content that directly answers a question in an extractable format — a question as a heading, followed immediately by a direct, specific answer. A Princeton GEO (Generative Engine Optimization) study found content containing citations, statistics, and direct quotes earns approximately 40% more AI visibility than equivalent content without cited evidence.4 Check your own site's key pages: do they lead with vague, adjective-heavy marketing copy ("award-winning service in a welcoming environment") or with specific, checkable claims ("Invisalign Diamond Provider since 2019, 340 verified Google reviews")? The second format is what gets extracted and quoted.
Signal 5 — Directory presence (the sourcing layer)
Different AI platforms source local citations from different places. Yext's citation-sourcing analysis (6.8 million citations) found ChatGPT draws roughly 49% of its local citations from third-party directories, Yelp chief among them, while Gemini draws roughly 52% from brand-owned websites.5 Check whether your business has claimed, accurate profiles on Yelp, Bing Places, and Facebook — an unclaimed or stale listing is worse than no listing, because it can surface outdated information as if it were current.
"Reviews are the strongest single lever measured. Schema is the most over-invested-in. Most businesses have the priority order backwards."
What to do with the result
Once you've checked all five, the pattern usually points at one or two clear gaps rather than a uniformly weak or strong profile. A business can have excellent schema and zero AI visibility because its Yelp profile is unclaimed. Another can have a 4.7-star rating and still be invisible to ChatGPT specifically because its content never answers a question directly enough to quote. The fix is almost always narrower than "improve everything" — it's usually one or two of the five signals doing most of the damage.
Notes and sources
1 Ahrefs controlled study, 1,885 pages, difference-in-differences methodology. Finding: LocalBusiness schema markup moved AI citation rates by −4.6% to +2.2% (not statistically significant). ahrefs.com
2 SOCi, The Factors Driving AI Invisibility, 2026. Dataset: 350,000+ locations, roughly 3,000 brands, and 3.2 million queries. Observed average ratings among recommended locations: ChatGPT 4.4★, Perplexity 4.3★; Gemini followed Google's 4.2★ average. These are not platform thresholds. soci.ai
3 BrightLocal Local Consumer Review Survey 2026, n=1,002 US consumers. Findings: 74% trust only reviews from the last 3 months; 32% trust only reviews from the last 2 weeks. brightlocal.com
4 Princeton GEO (Generative Engine Optimization) study. Finding: content with citations, statistics, and direct quotes earns ~40% more AI visibility than equivalent content without cited evidence.
5 Yext local citation-sourcing analysis, 6.8 million citations. Findings: ChatGPT draws ~49% of local citations from third-party directories; Gemini draws ~52% from brand-owned sites. yext.com