{"schema":"record/v1","id":"art_01M5P0ATKZ3DGFHR9XJFJ35M22","type":"article","revision":1,"etag":"\"r1.s0\"","title":"What does the 0-100 Google Trends index mean, and how is it normalised and sampled?","summary":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.","status":"active","body":{"text":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Correction folded 2026-10-24 from C3-B715-01 (curator-reviewed discovery audit): Problem. Trends numbers are misread as search counts. Conditions. Google Trends FAQ page. Method. The FAQ says each data point is divided by the total searches of its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches on all topics; regions with the same interest do not necessarily have the same total volumes. Correction. The earlier finding's \"so 100 is the peak of the displayed series\" and \"compare terms inside one chart rather than across separate pulls\" are not statements on this page; treat them as unsourced domain knowledge or inference unless a Google page that says so is cited. Version/date. Page read 2026-10-23.\n\nLimitations: The doc does not explain run-to-run variation; explaining it would be speculation. The doc is undated. Corrected by C3-B715-01; where the correction disagrees, the correction governs. The unamended original was withheld and never admitted.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://support.google.com/trends/answer/4365533","note":"How is Google Trends data normalized?; Overview"}]},"categories":["T01","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://support.google.com/trends/answer/4365533","claim":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.","locator":"How is Google Trends data normalized?; Overview","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-c8184501fd9d58b55c981873d5dcafb3e3af1baa/record.json#p-c8184501fd9d58b55c981873d5dcafb3e3af1baa/record","import_batch_id":"pipe-c4ccc0c80710c51be36db2601baa9f8179d83e86","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-c4ccc0c80710c51be36db2601baa9f8179d83e86","original":{"body":{"text":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Correction folded 2026-10-24 from C3-B715-01 (curator-reviewed discovery audit): Problem. Trends numbers are misread as search counts. Conditions. Google Trends FAQ page. Method. The FAQ says each data point is divided by the total searches of its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches on all topics; regions with the same interest do not necessarily have the same total volumes. Correction. The earlier finding's \"so 100 is the peak of the displayed series\" and \"compare terms inside one chart rather than across separate pulls\" are not statements on this page; treat them as unsourced domain knowledge or inference unless a Google page that says so is cited. Version/date. Page read 2026-10-23.\n\nLimitations: The doc does not explain run-to-run variation; explaining it would be speculation. The doc is undated. Corrected by C3-B715-01; where the correction disagrees, the correction governs. The unamended original was withheld and never admitted.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://support.google.com/trends/answer/4365533","note":"How is Google Trends data normalized?; Overview"}]},"tags":[],"type":"article","links":[],"title":"What does the 0-100 Google Trends index mean, and how is it normalised and sampled?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.","evidence":{"claims":[{"url":"https://support.google.com/trends/answer/4365533","claim":"Problem. Trends numbers are often read as search counts. Conditions. Any topic-selection work using Google Trends. Method. Google's FAQ says Trends is a sample of actual searches, normalised: each data point is divided by total searches for its geography and time range, then scaled 0 to 100 based on a topic's proportion to all searches. So 100 is the peak of the displayed series, not a volume; different regions with equal interest need not have equal total searches. Compare terms inside one chart rather than across separate pulls. Failure modes. Treating 50 as 'half a million searches'. Limitations. The page does not give the sampling size or say why separate pulls differ; so any claim that results change between pulls is outside what this page states. Version and date. Help page read 23 Oct 2026.","locator":"How is Google Trends data normalized?; Overview","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T01","T20"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":1,"topic_ids":["CAT:T10.SOC.08"],"confidence":"The doc does not explain run-to-run variation; explaining it would be speculation. The doc is undated.","limitations":["The doc does not explain run-to-run variation; explaining it would be speculation. The doc is undated.","Corrected by C3-B715-01; where the correction disagrees, the correction governs. The unamended original was withheld and never admitted.","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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