Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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New AI Visibility Insights in Bing Webmaster Tools: Intents, Topics, Citation Share, Compare

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Earlier this year, we introduced the AI Performance Report in Bing Webmaster Tools, giving publishers and site owners new visibility into how their content appears in AI-generated answers across Microsoft Copilot, Bing, and select partner AI experiences. We coupled that launch with information about our broader vision behind the AI Performance Dashboard: helping organizations better understand how they show up across the AI web. 

Today, we are excited to expand that foundation with four new capabilities available in preview globally within Bing Webmaster Tools: Intents, Topics, Citation Share, and Compare.

The original AI Performance experience helped answer an important question: Where is my content being cited in AI-generated answers? These new capabilities build on that foundation by helping publishers better understand why their content is being surfaced, which broader subject areas they are gaining visibility in, how their presence evolves relative to other cited sources, and how citation patterns change over time. 

As AI-powered experiences continue to evolve, publishers increasingly need tools that go beyond traditional rankings and keyword analysis. AI-generated answers are dynamic, contextual, and often synthesized from many sources at once. Understanding visibility in these systems requires more than a single metric or surface-level citation count. With these expanded preview capabilities, Bing Webmaster Tools is expanding first-party reporting to provide deeper insight into the query context, thematic patterns, relative citation presence, and changes over time that shape how content appears in AI-powered experiences.

That is the goal behind these new capabilities. 

Feedback_Icon_PNG.png 

Understanding the Intent Behind Citations 

One of the biggest challenges publishers face today is understanding the context behind AI-generated citations. A query alone often tells only part of the story.

In AI-generated answers, grounding refers to the source material and web evidence the system uses to support and cite its response. For deeper understanding of grounding – refer to Elevating the Role of Grounding on the AI Web and our recent Microsoft WebIQ announcement. 

With the new Intents feature, grounding queries in the AI Performance Report are now classified into broader categories such as Informational, Commercial, Navigational, Learn and Solve, Research, Creation, Local, and more. This helps publishers move beyond simply seeing which queries triggered citations and begin understanding the broader query context our systems associate with those citation appearances. 

For example, an e-commerce publisher may discover strong visibility in comparison-oriented or shopping-focused AI experiences, while an educational publisher may find that their content is frequently surfaced in research or learning-oriented interactions. These insights can help publishers better align content structure and depth with the types of experiences where AI systems are surfacing their content. 

Seeing Visibility Through Topics Instead of Individual Queries 

We are also introducing Topics, which group related grounding queries into broader thematic clusters. AI systems reason across concepts and themes rather than isolated keywords. Topics help publishers understand visibility in the same thematic structure that modern AI systems use to organize information.

Instead of analyzing visibility one query at a time, publishers can now start understanding which larger subject areas are driving citation activity. Queries such as “solar panels,” “solar energy efficiency,” and “residential solar installation,” for example, may all map into a broader topic cluster like Solar Energy. 

This creates a more natural way to analyze AI visibility. Content teams and publishers often think in terms of themes, editorial areas, and audience interests rather than isolated keywords. Topics help bridge that gap by turning grounding query data into a more thematic view of AI engagement. 

These insights can help publishers identify emerging areas of authority, discover gaps in topical coverage, and better understand how AI systems semantically group related content.

Like Intents, Topics are powered by evolving AI/ML classification systems. During the preview phase, some labels may still be broad – especially for highly specialized or niche domains – but the system is already beginning to reveal meaningful thematic patterns. We expect quality and precision to continue improving as the models mature and learn from broader real-world usage. 

Introducing Citation Share 

The next new capability we are introducing today is Citation Share.

While total citation counts show how often your content appears in AI-generated answers, Citation Share shows how much of the citation space your site receives for a specific grounding query. It is calculated as the percentage of citations attributed to your site out of all citations shown across all sites for that same grounding query. This helps publishers understand not just whether they were cited, but how much visibility they received within the full set of cited sources for that query. 

This can provide a more directional view into how visibility is evolving over time. Publishers may begin to identify areas where their content has strong and growing representation in AI-generated experiences, as well as areas where visibility may be more fragmented across many sources. 

Importantly, Citation Share is designed as an observational metric – not a ranking system or a competitive scoreboard. It does not expose competitor domains, represent traffic share, or assign quality scores to content. 

AI citation ecosystems are inherently dynamic. Citation patterns can shift due to changes in user behavior, evolving models, freshness signals, partner refresh cycles, and broader changes across the web itself.  

Compare Changes Over Time 

We are also introducing Compare, which allows publishers to overlay a previous time period directly onto the current reporting view. 

This makes it easier to visually understand how citation activity is changing over time and observe shifts that may correlate with content updates, seasonality, changing demand, or broader ecosystem changes. 

For example, publishers can compare the current 30-day period against the prior 30 days or select custom date ranges to better understand evolving citation trends. 

Compare is designed to help publishers observe changes over time. Citation activity can be influenced by many factors including evolving AI models, competing content, freshness signals, and shifts in user demand.

Compare_Graph_Table_PNG.png 

Increasing transparency 

These new capabilities are part of Microsoft’s ongoing effort to provide greater transparency into how content appears across AI-powered experiences. As AI answers become a larger part of how people discover information, publishers need more than raw citation counts – they need reporting that helps them understand the context, topics, relative presence, and changes over time behind those citations. 

That is what this work is designed to advance. Intents, Topics, Citation Share, and Compare give publishers a more practical way to observe citation activity, identify visibility patterns, and make more informed decisions about their content strategy. They do not turn AI visibility into a single ranking or score, but they do give webmasters a richer set of signals for understanding how their content is being represented across evolving AI experiences. 

As the AI web continues to evolve, we will continue investing in new reporting capabilities, richer analytics, and better visibility tools for webmasters and content creators. These preview features are early steps in a broader effort to make AI visibility more understandable, actionable, and useful for the publisher ecosystem.

Availability and Providing Feedback 

Intents, Topics, Citation Share, and Compare are now beginning to roll out in preview within Bing Webmaster Tools globally today. These capabilities are early preview innovations built on continuously advancing AI/ML systems and aggregated citation signals. As more data becomes available and more publishers engage with these experiences, we expect the quality, coverage, and precision of these capabilities to continue strengthening over time. 

We encourage publishers, content creators, GEOs, and site owners to explore these new capabilities. Additionally, we are now introducing a preview feature to provide us with your feedback within the AI Performance Dashboard context through an easy-to-use UI.

Feedback_Dialog_PNG.png

To learn more about the existing AI Performance experience, see: 

Krishna Madhavan, Meenaz Merchant, Saral Nigam, and Trishna Shah
Product Managers, Microsoft AI 

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Daily Reading List – June 16, 2026 (#806)

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I do this daily list for three reasons: personal discipline, self-learning, and sharing with others. In that order. If I just did it for learning and sharing knowledge with others, I could talk myself into skipping a day or two. But making it a “required” part of my day actually takes one decision off my plate. Do you have things you do just to build discipline?

[blog] More Than Syntax. Are developers still wrapping their identities in languages and frameworks? If so, nowadays is it less about being syntax experts and more about the community and using certain tools as a preferred way of solving problems?

[blog] The Knowledge Source: Reliable Product Docs for AI Agents via MCP. Helen leads our Google Cloud “Information Experience” team and shares how our technical docs are evolving with the times. Good insights.

[blog] AI demands more engineering discipline. Not less. What a piece. Agents are good at coding now, which means we need to ensure even more engineering rigor.

[article] AI Is Rewriting the Economics of Outsourcing. Can someone do standardized work faster than you? Maybe that’s not true anymore. This article has some useful framing for how to think about it now.

[article] The Subsidy Ended: What Tool-Using Agents Actually Cost. Smart point here. The cost of agentic work hasn’t really changed. The meter became visible.

[article] How does GenAI change when and how teammates talk to each other? Has AI changed our interaction patterns with our peers? Yes. Looks like routine questions go to LLMs, and we go to humans for context-specific expertise.

[blog] Building a Visualizer for Antigravity Agentic Development Sessions. Neat. AI tools make it simpler to build tools to help us understand what our tools are doing.

[blog] A fool’s folly with local AI models. With some craziness around US models, everyone’s hot on open/local models again. Regarding local, there are caveats (especially around resources) that you need to factor in.

[youtube-video] I am done with Golang. While I (really) enjoy reading and watching things that complement our products, I also seek out critical feedback. Prime is unhappy with our consideration of generics, and anything that spoils this straightforward language.

[blog] 10 Indispensable Prompts Our Team Refuses to Build Without. Use, modify, or ignore the prompts you see from others. But all of them can be informational.

[article] SpaceX to acquire Cursor for $60B in stock, days after blockbuster IPO. Already signaled months ago. But probably feels cheap today after SpaceX’s rocket ship IPO.

[blog] How to turn a 180% commit boost into shipped software. Check out this data and analysis by Karl. If you don’t invest in downstream automation, all the AI coding frenzy goes for naught.

[article] AI Coding Agents Get a Stack Overflow of Their Own. Creative product expansion, I’ll give it that!

[blog] How I learned Go in a Day with Antigravity 2.0 and How You Can Do the Same. No one deeply learns anything right away. But the barrier to entry to using different programming languages has literally never been lower.

Want to get this update sent to you every day? Subscribe to my RSS feed or subscribe via email below:



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v7.6.3 Release of PowerShell

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7.6.3

Build and Packaging Improvements

Update to .NET SDK 10.0.301

  • Remove the unused Publish-NugetToMyGet command from packaging module (#27576)
  • Verify Apple codesign immediately after ESRP signing (#27542)
  • Remove unused step to clone Internal-PowerShellTeam-Tools repo in PMC publish pipeline (#27496)

SHA256 Hashes of the release artifacts

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v7.5.8 Release of PowerShell

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7.5.8

Code Cleanup

Update to .NET SDK 9.0.315

  • Remove the unused Publish-NugetToMyGet command from packaging module (#27575)

Build and Packaging Improvements

Update to .NET SDK 9.0.315

  • Update branch for release (#27581)
  • Skip Store Publish when No Channel Selected (#27572)
  • Verify Apple codesign immediately after ESRP signing (#27541)
  • Remove unused step that clones Internal-PowerShellTeam-Tools repo in PMC publish pipeline (#27498)

SHA256 Hashes of the release artifacts

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  • PowerShell-7.5.8-win-x86.msi
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v7.4.17 Release of PowerShell

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7.4.17

Code Cleanup

  • Remove the unused Publish-NugetToMyGet command from packaging module (#27574)

Build and Packaging Improvements

Update to .NET SDK 8.0.422

  • Update branch for release (#27580)
  • Skip Store Publish when No Channel Selected (#27571)
  • Verify Apple codesign immediately after ESRP signing (#27540)
  • Remove unused step that clones Internal-PowerShellTeam-Tools repo in PMC publish pipeline (#27497)

SHA256 Hashes of the release artifacts

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  • powershell-lts-7.4.17-osx-x64.pkg
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  • PowerShell-LTS-7.4.17.msixbundle
    • 603D2D0F10A7B38C9CF944AF185CF09F54064B66BE10EDF91C4E7B714B153385
  • powershell-lts_7.4.17-1.deb_amd64.deb
    • F49C86AF3A10983D318FEB29E29C0B80AB4A683C3CA38F39CBAA38A5893566D4
  • powershell_7.4.17-1.deb_amd64.deb
    • 1428E026706076483C471486A0EDF5670611DEB77825188F2B409B17D1E32270
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