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                "text": "Attribution ladder"
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        "markdown": "---\ntitle: Attribution in Zero-Click Search | NRLC.ai\ndescription: A bounded attribution method that separates source citation, brand mention, referral click, and business outcome instead of treating them as one event.\norganization: Neural Command LLC\ncanonical: https://nrlc.ai/en-us/ai-search-measurement/attribution-in-zero-click-search/\n---\n\n← Back to measurement\n\n← Back to Measuring Visibility in AI Search\n\nMethod status: NRLC treats these as separate observable stages, not as a causal attribution model.\n\nUnder this method, referral sessions are downstream events. An observed answer may display source attribution without generating a referral click. Track citations and mentions on the prompt log; treat clicks as a separate, optional downstream event.\n\n## Attribution ladder\n\n- Source citation: the saved answer visibly attributes a URL or domain.\n- Entity mention: the monitored entity appears without source attribution.\n- Referral click: analytics records a visit from an identifiable answer surface.\n- Business outcome: a separately measured conversion or offline result occurs.\nReport each stage independently. A source citation is evidence of visible attribution in that observed answer; it is not proof of a click or business outcome. A mention without a citation does not identify the retrieved source.\n\n## Zero-click reporting\n\nFor each prompt, retain the answer, source attribution, engine, interface, and date. Aggregate source citations with the same C / P convention used by the citation-tracking guide. Keep referral sessions and conversions in separate columns, and use “unattributed” when no defensible link exists.\n\n## Limitations\n\nThis method measures observed outputs, not private model reasoning. Results can vary by engine, interface, prompt wording, account state, and time. A citation occurrence does not prove that a source caused an answer, produced a click, or generated revenue. NRLC has not published a worked citation-rate example because there is not yet an observation log with a prompt count, engine, dates, citation count, or citation rate. A missing visible citation cannot prove that a page was not used internally by an engine.\n\n## Evidence\n\nMethod\n\nNRLC AI Search Measurement method\n\nObservation window\n\nDeclared per measurement run; no aggregate run is claimed by these method pages.\n\nDataset\n\nVersioned prompt set and answer-observation log supplied by the operator\n\nMethod\n\nFreeze prompts, name the engine and interface, classify observed citation and mention outcomes, preserve exclusions, then calculate C / P over eligible prompts.\n\nAuthors\n\nJoel David Maldonado\n\nSources\n\nNRLC AI Search Measurement method, Google Search Console Performance report documentation\n\nLast verified\n\n2026-09-21\n\nConfidence\n\nfirst-party operational convention; not asserted as an industry standard\n\nLimitations\n\nObserved outputs vary by engine, interface, prompt wording, account state, and time. The method does not expose private model reasoning or establish causal attribution.\n\nView resource\n            Methodology\n\n- Performance report (Search results) — Google Search Console Help\n\n\n---\n\nSource: https://nrlc.ai/en-us/ai-search-measurement/attribution-in-zero-click-search/\nPublisher: Neural Command LLC\nLicense: Editorial use with attribution\n"
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