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Query Fan-Out Study — Methodology & Dataset
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Source: Averi (averi.ai). Collected June 2026.
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Method: 50 priority B2B SaaS queries, drawn from Averi’s own Google Search Console impression data and
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curated for on-ICP relevance and balanced across four intent types (Commercial, Informational, Category, How-to).
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Each query was run once through Google AI Mode in a clean session. For each, we recorded the number of distinct
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domains AI Mode cited to synthesize its answer (“citation fan-out breadth”), the specific top domains surfaced,
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whether Averi appeared in the linked sources, and whether Averi was mentioned in the answer text.
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What this measures: the breadth and composition of sources AI Mode consults per query (citation footprint).
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What this does NOT measure: the verbatim sub-search strings AI Mode issues internally (not exposed to users).
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Limitations: single snapshot, single run per query, one collector, AI Mode output varies by session and over time.
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Directional findings, not a longitudinal benchmark. Reproducible via the query list in the Dataset tab.
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