How often should I re-test my AI presence?

Use a fixed cadence and prompt cohort that matches your decision cycle. Monthly is often practical, but repeated answers can vary; report engine, date, locale, N, and confidence rather than assuming one universal refresh cycle.

ChatGPT describes my company incorrectly. How do I fix that?

First identify the claim and its apparent source. Reconcile the visible homepage, approved product facts, controlled profiles, and independently published references. Structured data must match visible content; llms.txt is optional and does not override an engine.

Can I pay to appear in AI answers?

Paid placements and organic supporting links are different surfaces. Do not buy fabricated mentions, reviews, or manipulative links; measure and disclose any paid placement separately.

Does Your Site Appear in ChatGPT? Here's How to Check

By Hunter Spence · 2026-06-11 · 8 min read

Why isn't my site showing in ChatGPT? The observation can depend on several conditions: the prompt and engine, whether live search is enabled, direct crawler access, source availability, and the brand's independent evidence. Most teams only test one response, get a flattering or confusing answer, and stop. Here's the full protocol — fifteen minutes, no tools required (and the automated version at the end).

Layer 1 — Does the model know you exist?

Ask each engine, in a fresh session with web search off where possible:

What is {yourbrand}.com?
What does {YourBrand} do?
Who are the main providers of {your category}?

Score each answer against four outcomes:

Known + accurate — the model describes you correctly. Your entity layer is healthy.
Known + wrong — it confuses you with another company or describes a years-old version of you. Entity ambiguity; see the fix below.
Unknown — "I don't have information about…". Common and fixable for sites younger than the model's training data; live retrieval (layer 3) matters more for you.
Hallucinated — confident nonsense. Treat as "known + wrong," with urgency.

Layer 2 — Can the crawlers physically reach you?

Direct retrieval can depend on crawler access. Check documented tokens separately — GPTBot relates to potential model improvement while OAI-SearchBot relates to ChatGPT search; Anthropic and Perplexity publish their own crawler controls. Google-Extended is a policy token for certain Gemini training and grounding uses and does not affect Google Search or AI Overview ranking. Three configurations block silently:

A wildcard User-agent: * / Disallow: / written years before AI crawlers existed — it blocks all of them by fallback.
An allowlist robots.txt that names Googlebot and disallows everyone else.
A WAF or bot-manager (Cloudflare Bot Fight Mode is the classic) challenging AI user-agents before robots.txt is even read — your robots.txt can say "allowed" while the firewall says 403.

The free crawler checker parses your live robots.txt against documented crawler and policy tokens; the full audit additionally compares server responses to requests labeled with documented user-agent strings. That does not make the request a verified crawler-network request.

Layer 3 — Does live retrieval surface you?

Now turn web search on (ChatGPT with search, Perplexity, Google AI Overviews) and ask the questions your customers ask — not your brand name:

best {category} for {use case}
how do I {problem your product solves}
{competitor} alternatives

Record two things per engine: are you cited as a source (linked), and are you mentioned in the answer text? Citation without mention and mention without citation are different observations; neither reveals a single root cause. Repeat the prompt, inspect cited sources, compare classic rankings, and treat absent data as unknown rather than as a failure or pass.

What each failure pattern means

Pattern	Possible investigation	Acceptance test
Unknown and absent in repeated retrieval tests	Check direct access, indexation, query relevance, and independent references	Retest the same cohort and verify each technical layer separately
Known but described incorrectly	Trace the conflicting claim and reconcile controlled and third-party facts	Correct source is public, current, and consistently represented
Brand-query presence but no category presence	Compare relevance, evidence, classic rank, and independent authority	Non-brand presence improves across repeated measurements
Competitors cited for the topic	Inspect their evidence, sources, page construction, and authority	Publish standalone value and earn independent references

Automate the protocol

Manual testing is fine quarterly; it doesn't scale weekly and it misses the configuration layer entirely. The free CiteFuel audit runs all three layers in one pass — robots + WAF response comparisons, optional llms.txt and schema validation, internal passage scoring, extractability, and live sampling of AI answer surfaces — and returns a 0-100 score with the severity-ranked gap list. The methodology, including every check and weight, is public at /methodology.

Whatever tool you use: test all three layers, write down the date and the answers, and re-test after each fix. AI visibility is an engineering loop, not a vibe.