AI visibility has several layers
A brand can appear in an answer without being cited, be cited without receiving a click, or receive a visit after earlier research in another channel. A single visibility score can hide these differences.
A defensible measurement plan separates answer presence, cited-source presence, referral traffic, landing-page behavior, and aggregate outcomes.
- Answer presence
- Citation presence
- Outbound referral
- Landing-page engagement
- Channel transition
- Aggregate outcome
GEO and SEO overlap, but their evidence differs
SEO usually measures crawlability, ranking, impressions, clicks, and on-site outcomes. GEO also needs to observe how assistants formulate answers, select sources, and move users between AI platforms, classic search, websites, and apps.
Keyword rankings can remain useful, but they do not describe every conversational query or the research that occurs before a referral.
Public benchmarks establish context, not product coverage
Public studies show growing chatbot adoption, rapid referral growth, a large scale gap with classic search, and different click behavior when AI summaries appear. Each source covers a specific population, period, and definition.
BGraph Research preserves those definitions and labels its own calculations. Public figures are not represented as BGraph customer results or proprietary coverage.
- Keep source periods visible
- Separate surveys from behavioral panels
- Do not merge incompatible vendor estimates
- Flag methodology changes
Private conversations are outside the standard claim
BGraph does not describe the standard product as access to private AI conversations or named individual prompt profiles. The focus is aggregated market behavior and approved query-derived signals where source rights and legal review support them.
Sensitive topics, small groups, cross-border transfers, and high-impact uses require additional exclusion or assessment.