In short: Bing Webmaster Tools now shows how often your website is cited in AI-generated answers across Microsoft Copilot, Bing AI summaries, and select partner integrations. For the first time, brands can see which URLs are referenced in generative answers and which query themes trigger those citations. For companies evaluating how AI search affects visibility, this is a structural shift. We now have a native reporting layer inside a major search platform.
At CadenceSEO, we see this as an exciting step toward more formalized generative visibility reporting. It does not yet provide a complete view of AI search performance, but it introduces a framework for measuring how content is retrieved and referenced in live AI environments.
Table of Contents:
- What Is Bing’s AI Performance Tool?
- What AI Citation Data From Bing Looks Like in Practice
- What Bing’s AI Performance Tool Does Not Measure
- Is Bing AI Data Meaningful If Google Dominates Search?
- Bing’s AI Performance vs. Other AI Visibility Tools
- Why AI Citation Visibility Is a Competitive Advantage
- The Most Actionable Insight: Grounding Queries
- How to Improve AI Citation Eligibility
- What’s Next for AI Performance Reporting?
- Want to Understand How Your Brand Is Performing in AI Search?
- Bing AI Performance Tool FAQs
What Is Bing’s AI Performance Tool?
Bing’s AI Performance report is a dedicated dashboard inside Bing Webmaster Tools that focuses on AI citations rather than rankings or clicks. It shows when and how your site is used to “ground” AI-generated answers in Copilot, Bing AI summaries, and select Microsoft AI experiences. It is Bing’s first native reporting layer focused specifically on AI answer visibility rather than traditional SERP performance.
The AI Performance dashboard introduces several AI-specific metrics designed for answer visibility rather than classic search performance.
Total Citations
Total Citations is the number of times your content is displayed as a source in AI-generated answers during the selected time frame. It reflects frequency of citation, not ranking position or placement inside the answer.
Average Cited Pages
Average Cited Pages shows the daily average number of unique URLs from your site that appear in AI answers. It’s a useful proxy for the breadth of your visibility across Bing’s AI surfaces.
Grounding Queries
Grounding Queries are grouped phrases the LLM used when retrieving and referencing your content. This is one of the most actionable elements in the report because it reveals how Copilot rephrases and clusters user intent when it goes looking for sources.
Page-Level Citation Activity
Page-Level Citation Activity shows citation counts for individual URLs, so you can quickly see which pages are most often referenced and which are rarely or never used in answers.
Visibility Trends Over Time
Visibility Trends show how citation activity changes over time across Bing’s supported AI programs.
What AI Citation Data From Bing Looks Like in Practice
Below is a snapshot from our own Bing AI Performance dashboard.
Figure 1: Sample page-level citation activity from CadenceSEO’s Bing AI Performance dashboard (February 2026, BETA)
In our case, foundational educational content such as “What Is SEO?” shows over 7,000 citations during a 90 day period inside Bing AI answers, while targeted blog content and tools show smaller but meaningful citation volume.
What Bing’s AI Performance Tool Does Not Measure
- It’s just as important to be clear about the blind spots.
- It does not show ranking position within AI answers or the prominence of your citation in the response.
- It does not report clicks, sessions, or conversions from AI answers, so you cannot yet tie AI visibility to traffic or revenue in this dashboard.
- It does not measure ChatGPT, Claude, Perplexity, Google AI Overviews, or other non‑Microsoft LLM ecosystems.
Additionally, grounding queries and timelines are sampled and aggregated, so they should not be treated as complete keyword logs.
Is Bing AI Data Meaningful If Google Dominates Search?
Google may dominate traditional search share, but Bing AI data still provides actionable insight.
There are a few reasons:
- Copilot’s footprint goes beyond bing.com. Microsoft Copilot is deeply integrated into Windows, Microsoft 365, and enterprise workflows, so its reach extends into productivity and workplace use cases.
- AI systems tend to converge on similar content patterns. How one major LLM ecosystem retrieves, structures, and cites content often mirrors how others behave, especially in terms of clarity, structure, authority, and freshness.
- Citation behavior is a structural signal. If your content is consistently cited (or consistently ignored) in Bing’s AI experiences, that can reveal strengths and weaknesses in how you structure and support your content, even beyond a single engine.
We do not treat Bing AI data as a complete market view, but it does provide a live signal of how your content performs in one major generative ecosystem.
Bing’s AI Performance vs. Other AI Visibility Tools
AI Performance differs from most AI visibility tools in one key way: it is first-party, engine-native reporting rather than prompt-based sampling.
Other AI Visibility Tools Agencies Are Using
| Dimension | Bing AI Performance (Webmaster Tools) | Dedicated AI visibility / AEO tools (e.g., Nobori, Promptwatch, Peec) | Big SEO suites w/ AI layers (Ahrefs, Semrush, SEOmonitor) |
| Data source | First‑party Bing/Copilot logs of grounding events and citations. | Sampled prompts run against multiple AI engines; answers stored and analyzed. | Scraped SERP/AI Overview data and large prompt sets across selected AI products. |
| Engine coverage | Bing only (Copilot, Bing AI summaries, some MS partners). | Multi‑engine (typ. ChatGPT, Perplexity, Gemini, Google AI Overviews, Copilot, etc.). | Often Google‑first (AI Overviews/AI Mode) plus a subset of other AI |
| Metrics | Citations, average cited pages, grounding queries, page‑level trends. | Visibility % per prompt/platform, Cited Pages/Domains, share‑of‑voice, sentiment/themes. | Presence in AI Overviews, affected keywords, share‑of‑voice vs. competitors, overlap with rankings. |
| Query insight | Real grounding queries from Bing, albeit sampled/aggregated. | Prompts defined by you (buyer‑intent, ICP queries), not real user logs. | Mix of your tracked keywords + vendor prompt sets; not first‑party user query logs. |
| Competitive view | Minimal; focused on your own URLs. | Strong: leaderboards, competitor visibility, Cited Domains where competitors win and you don’t. | Strong: domain‑level comparisons, AI Overview filters in Organic Research/Position Tracking. |
| Traffic/ROI linkage | None yet (no click or session data from AI answers). | Some tools estimate impact via share‑of‑voice and funnel mapping, but still inferred. | Best positioned to correlate AIO visibility with rankings and organic traffic, but still indirect. |
| Cost & audience | Free; ideal baseline for anyone with Bing traffic. | Paid; price points geared toward agencies and brands serious about AEO. | Paid; fits into existing SEO budgets and workflows. |
Why AI Citation Visibility is a Competitive Advantage
AI-generated answers are now layered above traditional organic listings. For many informational and commercial queries, users may never scroll to the blue links; they skim the summarized answer and, at most, glance at cited sources.
If your content is not structured in a way that generative systems can retrieve and cite, your effective visibility may decline even if your classic rankings remain stable. AI citation visibility does not replace SEO, but it certainly expands it into a new dimension where structure, clarity, and authority directly affect whether you are included in answers at all.
The Most Actionable Insight: Grounding Queries
Grounding queries show the query patterns AI used when retrieving your content, and they often differ from what you see in traditional keyword reports.
In practice, you’ll notice that:
- AI may rephrase intent differently than human searchers.
- Query clusters may combine multiple related concepts into a single “job to be done.”
- High‑intent phrases may surface that you never explicitly targeted in H1s or metadata.
That creates opportunities to:
- Align existing pages more clearly with the language AI uses around your topics.
- Improve structural clarity (headings, tables, FAQs) for those themes.
- Expand depth where AI signals partial coverage but still cites you sparingly.
How to Improve AI Citation Eligibility
Before you chase AI citations, shoring up fundamentals will increase your eligibility to be cited at all.
Lead With Clear Answers
Use answer‑first structures (with routes in the Minto Pyramid Principle) that resolve the main question in the opening paragraphs or sections. AI systems prefer content that surfaces the core answer quickly and cleanly.
Use Intent-Matched Headings
Descriptive H2s and H3s that mirror real query patterns help AI systems understand topical scope and map sections to specific intents.
Strengthen Structure
Tables, FAQ blocks, and clearly segmented sections make key information easier to extract and cite.
Support Claims With Credible Sources
Evidence-backed content with citations to credible external sources builds trust and authority signals, which can influence whether your page is chosen as a reference.
Keep Content Fresh and Indexable
Regular updates, clean internal linking, and fast indexing help ensure AI systems ground answers in current information.
None of these tactics are “new,” but they matter more in a context where AI systems skim and structure your content at scale.
What’s Next for AI Performance Reporting?
Bing’s AI Performance dashboard is still in public preview, and several metrics are still under development. Grounding queries represent sampled data, not complete query-level transparency. Placement, click behavior, and cross-platform visibility are not yet available.
We expect future iterations to include:
- More granular query reporting
- Expanded AI surface coverage
- Clearer attribution modeling
- Greater interoperability with other search reporting systems
Want to Understand How Your Brand Is Performing in AI Search?
If you are unsure whether your content is citation-ready or if your existing SEO strategy accounts for generative search, we can help.
During a free strategy session, our team will:
- Analyze your citation eligibility across AI surfaces
- Review structural and technical alignment
- Identify gaps between traditional rankings and AI visibility
- Outline a practical roadmap for LLM optimization
We won’t try to talk you into a long-term contract or bribe you with inflated promises. We are SEO nerds who value straight talk!
Schedule your free consultation with our CadenceSEO team.
Bing AI Performance Tool FAQs
Does Bing’s AI Performance tool include ChatGPT, Claude, or Perplexity data?
No. AI Performance reports citation activity across Microsoft Copilot, AI-generated summaries in Bing, and select partner integrations only. It does not directly measure citations inside ChatGPT, Claude, Perplexity, or other independent LLMs.
Does this reflect Google AI Overviews?
Not directly. However, many of the structural patterns that improve citation visibility in one generative system (think clear headings, depth, freshness, and strong entity signals) tend to translate across others.
Should we create new content specifically for AI?
In most cases, the first priority is to improve the structure, clarity, and alignment of existing high‑value content before publishing new pages. Once your core assets are optimized, you can identify genuine content gaps from query patterns.
What about older content that was not optimized for LLMs?
Older content is often a strong candidate for refreshes: clearer headings, better sectioning, updated data, and more explicit answers to high‑intent grounding queries. Those improvements can significantly boost citation eligibility without starting from scratch.
Will similar reporting tools emerge from other platforms?
Yes, and hopefully soon. Microsoft is currently the first major platform to expose this level of AI citation data in a webmaster console, and industry observers expect other engines to follow with their own GEO reporting over time.
How often is the AI Performance data updated?
Microsoft hasn’t published a precise refresh cadence, but in practice, data tends to update daily with some lag. Treat trends as near‑real‑time, not live.
Can we export AI Performance data or access it via API?
As of now, Microsoft has not released a public API for AI Performance export. Most teams are relying on manual exports or screenshots until an official programmatic option exists.
What is a “good” number of citations?
There is no universal benchmark yet. We recommend tracking your own baselines and watching the direction of change: more unique cited pages and more consistent citations on key topics over time are positive signals.
How long does it take to see impact after we optimize?
Expect to wait several weeks for changes to be crawled, indexed, and reflected in AI answers. AI systems may also take time to “relearn” which pages they trust as sources for specific questions.
Why don’t citations match GA4 traffic?
Citations reflect how often your content is referenced in AI-generated answers, not how many users click through to your site. GA4 only tracks visits, so zero-click AI responses can generate citations without producing traffic.
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References:
- https://blogs.bing.com/webmaster/February-2026/Introducing-AI-Performance-in-Bing-Webmaster-Tools-Public-Preview
- https://newsletter.rwazi.com/p/google-retains-90-search-dominance-despite-the-ai-hype
- https://blogs.bing.com/search/February-2026/Elevating-the-Role-of-Grounding-on-the-AI-Web
- https://www.mckinsey.com/alumni/news-and-events/global-news/alumni-news/barbara-minto-mece-i-invented-it-so-i-get-to-say-how-to-pronounce-it
