Google’s current How Search Works documentation says aggregated and anonymized interaction data is used to assess whether search results are relevant to queries.

Cited by documentation

Sources

• How Does Google Determine Ranking Results - Google Search

  Google (google.com How Search Works) · primary source · retrieved 2026-08-18

  “We also use aggregated and anonymized interaction data to assess whether search results are relevant to queries.” — Section "Relevance of content"

• Automatically generating and ranking results

  Google Search · primary source · retrieved 2026-08-18

  “We also use aggregated and anonymized interaction data to assess whether search results are relevant to queries.” — line 58

• Google Search Won't Explain How It Uses User Interaction Signals

  Search Engine Roundtable · retrieved 2026-08-18

  “it says this on the How Search Works site,” — Quotation of the How Search Works site

• Unbiased Learning-to-Rank with Biased Feedback

  arXiv · retrieved 2026-08-18

  “Implicit feedback (e.g., clicks, dwell times, etc.) is an abundant source of data in human-interactive systems.” — line 16

Related claims

• REPEATSThe 2020 Google presentation said learning from logs is a main mechanism behind ranking and identified major machine-learned ranking systems as relying on logs.Supported
• NARROWSGoogle’s current documentation says interaction data is transformed into signals that help machine-learned systems estimate relevance.Supported