Short answer: Grounding queries reveal sampled retrieval language and can expose subtopics that classic keyword tracking misses. For Grounding Queries in Bing AI, measurement should begin with a data contract, not a dashboard. Bing now exposes AI citation activity directly in Webmaster Tools, including cited pages and grounding queries. That makes AI visibility observable without pretending citations are rankings.
Define the metric before collecting it
Write five fields for every metric: name, numerator, denominator, observation window and known blind spots. This prevents a citation count, prompt sample or referral session from being presented as if it measured total demand.
Baseline design
Choose a stable group of pages or topics before the intervention. Record total citations, cited-page breadth, grounding-query samples, referral traffic and outcomes. Preserve the same cohort during the first comparison window unless the purpose of the experiment is specifically to change the cohort.
Event taxonomy
Separate events into four layers:
Availability. Crawl, index or source eligibility.
Visibility. Mention, citation, supporting-link or measured appearance.
Engagement. Visit, scroll, return, download or another audience behavior.
Outcome. Lead, sale, subscription, pipeline, revenue or another business target.
The layers can influence one another, but they are not synonyms.
Measurement table for Grounding Queries in Bing AI
| Question | Example signal | Reporting rule |
|---|---|---|
| Are we available? | crawl/index state | binary or coverage, not a rank |
| Are we being used? | total citations, cited-page breadth, grounding-query samples, referral traffic and outcomes | report platform and sample scope |
| Do users engage? | qualified sessions / actions | separate known referrals from inferred influence |
| Does it matter commercially? | target conversion | use assisted views when last-click is incomplete |
Experiment design
Change one meaningful element: source structure, technical access, evidence depth, page ownership or update policy. Record the date. Give the system enough time to recrawl or re-evaluate. Compare against the baseline and against a reasonable control group when available.
Do not retroactively choose the metric that moved most. The success criterion belongs in the plan before the result.
Sampling and uncertainty
Many AI visibility tools work from prompt panels or sampled platform data. Report the engine, locale, model or interface when known, prompt set, date range and sample size. “Share of voice” without a denominator is an attractive label, not a reproducible metric.
Executive reporting
A useful executive page contains fewer metrics, not more: availability health, visibility trend, qualified audience behavior and business outcome. Add a short evidence note explaining what is directly observed and what remains inferred.
Conclusion
Grounding Queries in Bing AI should improve decision quality, not produce more charts. Define the metric contract, protect the baseline, separate visibility from value and report uncertainty explicitly. That makes the data useful even when AI platforms expose incomplete measurement.
Bing and Copilot-specific operating context
Bing Webmaster Tools now exposes AI Performance data that is unusually useful for publishers: citation counts, cited-page information and grounding-query samples. The important caveat is equally explicit: a citation count is not a ranking position and does not prove authority or importance inside an answer.
That makes Bing a good environment for disciplined measurement. Start from a URL-level question: which pages are being used, for what grounding-query themes, and how does that pattern change after a real editorial or technical intervention? Then compare citation behavior with classic search impressions, referral traffic and business outcomes without assuming that one caused the other.
IndexNow adds a separate freshness mechanism. It can notify participating engines that a URL changed, but notification is not a substitute for accurate content, canonical hygiene or crawlable pages. Use it when the underlying resource genuinely changed, especially for volatile facts, rather than as a repetitive “ping for visibility” tactic.
Applied question for this article
The specific decision is Grounding Queries in Bing AI. Use the principle in the short answer as the hypothesis to test; document one concrete page, source or workflow where it applies; then record one counterexample or condition where it does not. This keeps the article tied to its own intent instead of drifting into generic AI-search advice.
Sources reviewed
- Bing Webmaster Blog — AI Performance in Bing Webmaster Tools: https://blogs.bing.com/webmaster/February-2026/Introducing-AI-Performance-in-Bing-Webmaster-Tools-Public-Preview
- Bing Search Blog — Elevating the Role of Grounding on the AI Web: https://blogs.bing.com/search/February-2026/Elevating-the-Role-of-Grounding-on-the-AI-Web
- IndexNow — Documentation: https://www.indexnow.org/documentation
