Rule: Monitor priority keywords for AI Overview presence + local-pack position so the strategy is data-driven, not folkloric
Rule
Rule: For every active client, track the priority keyword set on three dimensions: (a) does an AI Overview appear, (b) is the client cited inside it, (c) what is the local-pack position. Snapshot regularly, not just once.
Why: AI Overview prevalence is moving fast and is uneven across query types (Whitespark Q2 2025 local-search study — AI Overviews appeared on 15% of simple local-intent queries vs 92% informational vs 97% hybrid; local pack appeared on 93% of local-intent vs 6% of informational, Local Falcon (2025) — AI Overviews on 17.2% of commercial queries vs 58.3% of informational; including a location name reduced AI Overview appearance (35% vs 46%)). Semrush tracked a swing across 2025. Recommendations grounded in last-quarter's data will go stale quickly. Without measurement we can't tell when a client crosses from "local-pack-driven" to "AI-Overview-impacted."
How to apply: If AI Overviews begin appearing on the client's core "near me" / commercial queries at scale (today ~15% per Whitespark), shift effort toward being cited in AI answers and toward paid placement (Ads inside AI Overviews reached Canada on December 19, 2025 (one of 12 total English-language countries); sensitive verticals excluded). If informational blog traffic drops sharply (the Pew/Seer pattern), pivot that content toward conversion-oriented, experience-rich pages.
Related entries
Depends on
- reference Ads inside AI Overviews reached Canada on December 19, 2025 (one of 12 total English-language countries); sensitive verticals excluded
- reference Whitespark Q2 2025 local-search study — AI Overviews appeared on 15% of simple local-intent queries vs 92% informational vs 97% hybrid; local pack appeared on 93% of local-intent vs 6% of informational
- reference Local Falcon (2025) — AI Overviews on 17.2% of commercial queries vs 58.3% of informational; including a location name reduced AI Overview appearance (35% vs 46%)