When Microsoft quietly introduced AI Performance inside Bing Webmaster Tools, it didn’t just add another reporting tab. It gave SEOs something they’ve never had before: a window into how AI systems actually search the web when they answer a question. We can now see the queries that AI models generate behind the scenes, called grounding queries, and the number of times those models cited our content. The gap between those two numbers is eye-opening, and the implications for SEO strategy are significant.
Also Read: SaaS Content Marketing Strategy for 2026 (Proven Framework + Examples)
1. What Are Grounding Queries? (And Why Should You Care?)
Let’s start with the basics. When you type a question into an AI tool like Microsoft Copilot, ChatGPT
The AI breaks your question into smaller, more specific sub-questions
It sends those sub-questions to a search engine
It retrieves web pages to “ground” its answer in real information
It synthesizes everything into a response
Example
Say you ask Copilot:
“Which project management tool should I use for my remote team?”
The AI might internally search for:
“best project management tools 2025”
“Evaluate Asana vs Monday.com features”
“remote team collaboration software comparison”
“project management tool review”
None of those are what you typed. They’re what the AI typed on your behalf. And until now, website owners had no visibility into this behavior at all.
Grounding query in Bing’s new report is an aggregated view of these sub-searches. It shows you the actual language AI models use when they go looking for information, and that language is often very different from what humans type into a search bar.
Core Insight
The prompt a user types is not the query your website needs to rank for.
The AI’s search behavior is.
2. The Data That Stopped Us in Our Tracks: 75 Clicks vs 30,000 AI Citations Here’s the kind of finding that makes you put down your coffee.
Case Study: 90-Day Performance Snapshot
~75
Organic Clicks
30,000+
AI Citations
That’s not a typo. A site that barely registers in traditional click analytics was being cited by AI systems hundreds of times per day.
How is this possible?
Because AI tools like Copilot don’t just search once when someone asks a question. They run multiple structured evaluation searches often using patterns like:
AI Evaluation Query Patterns
“evaluate [Brand Name]”
“compare [Brand] vs competitors”
“[Brand] performance monitoring review”
“[Category] vendor feature analysis”
A human searcher rarely types “evaluate [brand name].” But AI systems do it constantly, especially when generating brand summaries, vendor rankings, or “best of” comparisons.
The Implication
Your Google Search Console click numbers might dramatically undercount
how often AI systems are referencing your content.
AI models using your pages as source material.
3. Why the Word “Evaluate” Is Surprisingly Important One of the most unexpected insights from grounding query data is how often the word “evaluate” shows up.
Here’s why. A growing category of tools called GEO (Generative Engine Optimization) tools generates AI-powered brand reports. To do this, they prompt models with something like: “Evaluate Brand X’s positioning in the market.”
That prompt gets broken down into search queries, and those queries often include the word “evaluate.”
What This Means in Practice
If your website contains content like:
“How we evaluate [category] tools”
“Brand evaluation criteria for [industry]”
“Performance evaluation checklist”
“Compliance evaluation framework”
…you may be appearing disproportionately in AI-generated brand summaries, vendor reports, and comparison outputs not because you gamed anything, but because your language naturally matches the vocabulary AI models use when they search.
Practical Example
Why framing matters for AI-generated vendor comparisons:
AI-Friendly Framing
“How to Evaluate HRIS Software: A Buyer’s Guide”
Structured, evaluation-focused language that matches how AI systems analyze and compare vendors.
Traditional Marketing Framing
“Our HR Software Features”
Feature-focused messaging that may be strong, but doesn’t align with comparison-driven AI queries.
4. Is GEO Different From SEO? The Honest Answer This question generates a lot of debate, and the Bing data helps settle it. Here’s the nuanced truth:
What Hasn’t Changed
✓
You still need to rank in search engines.
LLMs still rely heavily on web search to retrieve source material.
✓
Authority, relevance, structured content, and technical SEO
still matter just as much.
✓
No shortcut bypasses traditional ranking signals.
What Has Changed
🤖
There’s now a new type of “user” searching your content:
the AI model itself.
🔎
This user has different vocabulary preferences
and searches more frequently than a human.
📊
It generates queries in structured, evaluative language
designed for comparison and analysis.
You’re no longer optimizing only for people — you’re optimizing for machines that think in structured search logic.
Think of it like this: imagine a new type of very well-read, very systematic researcher started visiting your website dozens of times per day but they never clicked your “Buy Now” button. Traditional analytics wouldn’t notice them. But they’re the ones writing the reports that influence the humans who do buy.
GEO isn’t replacing SEO. It’s adding a new layer, a new query generator that you now have the data to optimize for.
5. How to Use Grounding Query Data Strategically The Bing AI Performance dashboard isn’t just an interesting data curiosity. It’s an actionable research tool. Here’s how to apply what you find:
Step 1: Identify the Language Patterns Look at your grounding queries and spot recurring words and phrases. Common AI-native search modifiers include:
Keyword / Query Clusters
evaluate
assessment
analysis
vendor comparison
alternatives to
best tools
top platforms
features
dashboard
integrations
performance review
monitoring
These words represent how AI models frame searches. They’re different from how your customers type into Google and that difference is now measurable.
Step 2: Quick Wins Update Existing Pages If a grounding query closely matches an existing page on your site, you don’t need to build something new. Instead:
Content Optimization Action Steps
1
Add the grounding query phrase early in the page
(ideally in the first paragraph or H2 heading)
2
Create a comparison table or structured evaluation section
3
Add explicit evaluation criteria to guide AI and human readers
Example: If you discover a grounding query like “evaluate [Your Brand] compliance features” , and you already have a features page, add a section titled “Evaluating Our Compliance Features” with a structured breakdown. Small changes can make a meaningful difference in whether AI models select your page as a source.
Step 3: Build Dedicated Evaluation Pages If grounding queries are surfacing topics your site doesn’t currently cover well, that’s a content gap worth filling. High-value page templates to consider:
AI-Friendly Headline Examples
“[Brand] Evaluation Guide”
“[Category] Vendor Comparison: What to Look For”
“Best [X] Tools in 2025/2026: How We Evaluated Them”
“[Your Brand] vs [Competitor]: An Honest Comparison”
AI models have a strong preference for structured comparison content. If you publish clear, well-organized evaluation content, you’re creating exactly what grounding queries are looking for.
Step 4: Treat It as a New Keyword Research Channel Here’s a real strategic advantage: grounding query data surfaces keyword patterns that traditional tools like Semrush or Ahrefs would never find. Why? Because roughly 15–25% of daily search queries are brand new, never searched before, and many of those are AI-generated queries that never existed in any historical dataset.
Grounding queries give you a live feed of emerging language patterns that represent real retrieval behavior. This is a new keyword research channel that your competitors may not be tapping into yet.
6. Reputation Management in the Age of AI When AI systems generate vendor comparisons, feature breakdowns, and “top 10” lists, they’re synthesizing information retrieved through grounding queries. Whoever ranks for those queries shapes the narrative.
This isn’t about manipulation, it’s about clarity and completeness.
What Good AI-Era Content Strategy Looks Like
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Publish honest, structured comparisons (including your own weaknesses)
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Clearly articulate your differentiators in plain language
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Address common objections directly on the page
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Use language that matches evaluation and comparison queries
Why transparency actually helps: AI models are retrieving multiple sources and synthesizing them. If your content is clear, balanced, and well-structured, it’s more likely to be quoted accurately. If your content is vague or purely promotional, the model may skip it in favor of a more informative source. A cybersecurity company that publishes “Where [Our Product] Excels And Where You Might Need Additional Tools” will likely be cited more accurately and favorably in AI-generated vendor summaries than a competitor whose entire site is pure marketing copy.
7. A Word of Caution: Model Drift One important caveat: AI models change. The specific vocabulary patterns they use for grounding queries will shift as models are updated, retrieval algorithms are tuned, and new language models are deployed.
This makes GEO slightly more dynamic than traditional SEO, where a well-optimized page can hold its ranking for years. With grounding queries, the “right” language may evolve over months.
How to Stay Ahead of AI Drift
01 — MONITOR
Check your AI Performance dashboard regularly
(monthly is a strong cadence).
02 — TRACK
Identify whether recurring grounding query terms
are changing over time.
03 — OBSERVE
Watch for new evaluation language
emerging in your category.
04 — ADAPT
Update relevant content sections when you notice
significant shifts .
The good news: language variation is bounded. The core concepts evaluate, compare, review, and alternatives tend to be stable even as specific phrasing evolves. If you build a solid foundation of evaluation-oriented content now, you won’t need to rebuild it from scratch with every model update.
8. Do You Need Specialized GEO Tools? A growing market of GEO tools promises to optimize your content for AI visibility. Some of these are genuinely useful. But the Bing dashboard reveals something worth knowing: many of these tools generate their insights by running simple “evaluate [brand]” prompts through AI models, which means the data they surface is itself a product of AI query behavior you can now observe directly.
Before paying for a GEO tool, ask whether the Bing AI Performance dashboard, combined with careful manual analysis, might give you comparable insight for free.
What Delivers Strong AI Visibility in Practice
🔗
Strong internal linking and clear topical architecture
🏛️
High-authority cornerstone pages on key topics
📊
Structured comparison and evaluation of content
⚙️
Clean, crawlable technical SEO fundamentals
The difference between traditional SEO and GEO isn’t the mechanics; it’s adding an awareness of the vocabulary layer that AI models use when they search.
9. The Big Picture Microsoft’s AI Performance dashboard is significant not because it changes everything, but because it reveals what was already happening. LLMs have been using your content or ignoring it based on grounded query retrieval for a while now. We just couldn’t see it.
Now we can. And that visibility is genuinely useful.
The key takeaways:
LLM visibility still depends on search engine visibility. There’s no secret AI optimization track that bypasses ranking. You still need to earn search authority the traditional way.
AI models are a new type of search user with a distinct vocabulary. They search in evaluative, structured language that humans rarely use. This vocabulary is now measurable.
Grounding query data is a new keyword research channel. It surfaces AI-native language patterns that traditional keyword tools miss entirely.
Your click numbers may dramatically undercount AI citation frequency. A site with 75 organic clicks and 30,000 AI citations isn’t anomalous it may be a preview of how content consumption is shifting.
Final Checklist: What to Do This Month If you want to improve your AI citation visibility, here’s where to start:
Open your Bing AI Performance dashboard and export your grounding query dataLook for recurring evaluation language words like “evaluate,” “compare,” “review,” and “alternatives.”Map grounding queries to existing pages. Where are the gaps? Where are the quick wins?Add targeted evaluation sections to your highest-traffic pagesPlan one new comparison or evaluation page targeting your most common grounding query themesSet a monthly reminder to check for query drift
The fundamentals of good SEO haven’t changed. The surface area you’re optimizing for just got bigger, and for the first time, you have the data to see it clearly.
