Bing AI Performance: Track Citations in Webmaster Tools

How to Access and Optimize Your Content for Bing AI Citations: A Practical Dashboard Guide

Quick Takeaways

• New visibility metric: AI Performance shows which of your pages get cited in AI-generated answers across Copilot and Bing’s AI products
• Track grounding queries: Export a CSV of queries that triggered citations from your content to understand what topics drive AI visibility
• Page-level data matters: See which specific URLs get cited most frequently and prioritize optimization efforts accordingly
• 30-day rolling window: The dashboard shows citation trends over the last 30 days, making it easy to spot visibility changes
• CSV exports enable automation: Download grounding queries and build Python pipelines to correlate with traffic data and identify optimization patterns
• Context beats rankings: AI answers value contextual authority and relevance over traditional SEO signals, requiring different optimization approaches
• Early access advantage: This launched in February 2026 as public preview, giving you a head start on competitors still optimizing for traditional search

If you’ve been wondering how your content performs in AI-generated answers, Bing finally gave you the answer. The platform just released AI Performance in Bing Webmaster Tools, and it changes how you approach visibility in generative search.

This isn’t speculation about where AI is going. This is real data about what’s happening right now. According to ALM Corp’s analysis, AI referrals grew 357% year-over-year to 1.13 billion visits by June 2025. Your content is already being cited in AI answers. Now you can see which pages, which queries, and what you can do about it. The dashboard shows exactly what queries triggered citations from your site, how many pages got cited, and how that activity changed over time. Most importantly, you can export the data and actually do something with it. Let’s walk through how to set this up and make it work for your optimization strategy.

What is Bing AI Performance Report?

Bing AI Performance is a dashboard tab in Bing Webmaster Tools that tracks when your content appears in AI-generated answers. It’s not clicks, impressions, or traditional ranking data. It’s citation data. When Microsoft Copilot or Bing AI generates an answer and sources your content, that shows up here.

The report tracks four key metrics. First, total citations: the raw count of times your pages got cited in AI answers over the period. Second, average cited pages: how many unique pages from your site got cited on average per day. Third, grounding queries: the specific search queries that triggered citations from your content. Fourth, page-level activity: which URLs contributed most to your citation count.

Bing’s official documentation emphasizes that this shows content usage in AI-generated answers across Copilot and partner products. It’s not limited to Bing.com. When your content gets cited anywhere in Microsoft’s AI ecosystem, it appears in this dashboard.

The timing matters. Search Engine Land reported that this launched February 11, 2026 as a public preview. That means it’s still evolving, but the core functionality is stable. This represents the first generative engine optimization tooling from Bing, making it worth paying attention to even if your traffic is split between Google and Bing.

How to Access and Set Up in Bing Webmaster Tools

First, you need a verified site in Bing Webmaster Tools. If you dont have one already, go to webmaster.bing.com and add your site. You can verify using a meta tag, XML file, CNAME, or Google Analytics account. The process takes about 10 minutes.

Once verified, log in and you’ll see your dashboard. Look for the left sidebar menu. You should see “AI Performance” as a new option alongside Search Appearance, Search Traffic, and other tabs. Click it.

The dashboard loads a default 30-day view. At the top, you’ll see three numbers: total citations, average cited pages per day, and grounding queries. Below that, two charts show citation trends over time and your top cited pages.

Here’s where the real power starts: click “Export” in the grounding queries section. This downloads a CSV with every query that triggered a citation from your content in the past 30 days. Some sites see 50 grounding queries. Others see 400+. Search Influence found sites with over 400 grounding queries clustered by topic, which is actionable data for content planning.

The CSV includes three columns: query, citation count, and sometimes source URL. Download it monthly. Store the files. You’ll use them to spot patterns and trends in what topics drive AI visibility from your site.

Key Metrics Explained: Citations, Grounding Queries, and More

Total Citations is straightforward: it’s the count of times your content got cited in AI answers over 30 days. This isn’t unique visitors or impressions. It’s raw citation events. A single user might trigger multiple citations if they ask follow-up questions that source the same page. So a high number means your content is being used repeatedly to ground AI answers.

Average Cited Pages tells you how many of your unique URLs got cited on average per day. If you have 100 total citations but only 5 pages cited, that’s concentrated visibility. If you have 100 citations spread across 50 pages, that’s distributed visibility. The first scenario means you should focus on those 5 pages. The second means your content strategy is working across many topics.

Grounding Queries are the actual search queries that triggered citations. A user asks Copilot “how to optimize websites for AI search” and the AI cites your article. That query shows up in your grounding query list. This is invaluable. You’re seeing real questions about your topics that people are asking AI. You can use this to identify content gaps, new angles, and topics worth doubling down on.

Page-level Activity shows which of your URLs contributed most citations. It’s ranked by citation count. Your homepage might have 50 citations. A specific blog post might have 200. This shows exactly which pieces of content are delivering AI visibility. That informs your content amplification strategy. Pages with high citation counts should get more internal linking, social promotion, and potentially expansion into related topics.

The key insight from Manticore Marketing’s analysis is that AI answers prioritize contextual authority over traditional ranking signals. A page doesn’t need to rank #1 to get cited. It needs to provide clear, well-sourced information on a specific topic. That’s a fundamentally different optimization target.

Real-World Analysis: Interpreting Your Data

Let’s say you run a SaaS blog and pull your grounding query export. You see 200 total queries. Most are variations of “how to use [feature]” but you also see clusters around “why should I switch from [competitor]” and “pricing comparison [category]”. That tells you something: people using Copilot want educational content about your product, but also comparative content. Your current blog might be heavy on tutorials and light on comparisons.

Now check your page-level activity. Your product tutorial pages have 300 citations total. Your one comparison article has 50 citations. Yet the grounding queries show demand for comparison content. You’ve found an optimization gap. Write more comparison content, and you’ll likely see citation numbers rise. This is actionable intel that Google Search Console doesn’t give you.

Another pattern: if you see zero citations for a month, there are three possibilities. First, your site isn’t verified or indexed properly in Bing. Second, your content isn’t being selected by Bing’s AI because it’s too generic or poorly sourced. Third, nobody is asking questions that your content answers. The grounding query export solves this. If you see grounding queries but low citation counts, your content exists but isn’t being prioritized. That’s a content quality issue. If you see zero grounding queries, the queries people ask simply don’t match your content topics.

Build a spreadsheet that tracks metrics monthly: total citations, average cited pages, unique grounding queries, and top 5 cited pages. This gives you a trend view. Are citations rising month-to-month? Falling? Stable? You can correlate this with content updates, new articles, and optimization changes. That’s how you learn what moves the needle for AI visibility on Bing.

GEO Optimization Strategies for Higher Citations

Getting more AI citations requires a different mindset than SEO ranking. You’re not optimizing for click-through. You’re optimizing for selection as a source. Here’s the practical approach.

First, structure your content for extraction. AI models source passages, not full articles. Write with clear sections, bullet points, and definitions. When someone asks Copilot “what is X”, the AI will extract your definition. If you buried the definition in paragraph three, it might not find it. Put definitions upfront. Use headers to signal structure.

Second, focus on topic depth. Don’t chase rankings. Write comprehensive content on topics where your audience asks questions. Look at your grounding queries. Those are your topics. Go deep on them. Add examples, data, counter-arguments, and nuance. More comprehensive content gets cited more because AI models can extract richer context from it.

Third, cite your sources. This sounds backwards but it works. Content with clear attribution and source links is deemed more credible by AI models. You’re training Copilot to cite you by demonstrating that you cite others. It’s a trust signal. Articles with 5-10 source links get cited more than unsourced articles on the same topic.

Fourth, optimize for question formats. Look at your grounding queries. Many will be questions. Write content that directly answers those questions in the first 100 words. Use the question as your H2 headline. This makes it trivial for the AI to extract the answer.

Fifth, build topical clusters. If you have three articles on “how to implement X”, your citations might be split. Consolidate into one comprehensive article or create a hub with internal links. Topic clusters signal expertise. AI models cite pages that demonstrate depth across related topics more than scattered coverage.

Troubleshooting and Common Issues

If you see zero citations for a month, verify three things. First, check that your site is fully verified in Bing Webmaster Tools. Go to Settings and confirm verification status. Second, make sure your sitemap is submitted and Bing is crawling your content. Check the Crawl > Crawl Stats section. Third, ensure your robots.txt and meta tags aren’t blocking indexing.

If you see citations but very low numbers (under 10 per month), your content might be too niche, too similar to other sources, or not authoritative enough. Check your grounding queries. If there are few queries, your topics don’t match what people ask AI. If there are many queries but low citations, your content ranks below competitors in Copilot’s selection logic. In that case, improve content depth and sourcing.

If you’re getting citations for unexpected queries, that’s actually useful. It means your content is broader or more applicable than you thought. Look at those queries and consider expanding your content strategy around them. You’ve found an unplanned market for your expertise.

The dashboard sometimes shows a lag. Data can take 24-48 hours to appear. Don’t export and check every day. Monthly exports are enough. Also, remember that citations fluctuate based on user behavior. Traffic might be lower on weekends, so trends matter more than individual days.

One gotcha: the dashboard doesn’t show negative data (queries where you could have been cited but weren’t). You need to infer that yourself. If you rank for a query in Google but don’t appear in Bing grounding queries, that’s a signal. It means either Bing doesn’t rank your content for that query, or Bing’s AI chose competitors instead. Use this to guide content improvements.

Putting This Into Practice

Here’s how to implement AI Performance optimization at different levels:

If you’re just starting: Verify your site in Bing Webmaster Tools right now (if you haven’t already). Navigate to AI Performance and pull one grounding query export. Open it in Excel or Google Sheets. Spend 30 minutes reading through the queries. What topics come up most? Create a simple spreadsheet with columns for query, topic cluster, and current content URL. This teaches you how people ask questions about your domain. No optimization yet. Just learning.

To deepen your practice: Pull three months of grounding query exports (monthly). Load them into a spreadsheet and build a pivot table by topic cluster. Which topics drive the most grounding queries? Cross-reference with your page-level citation data. Which pages handle those topics now? Identify the top three topic areas where you could create new content or expand existing content. Write one comprehensive article on the highest-opportunity topic. Publish and track citations next month. Use this data to guide your next three content pieces.

For serious exploration: Build a Python pipeline that connects to your Bing Webmaster Tools data (via CSV export for now, watch for API access), correlates grounding queries with your web analytics traffic, and identifies topics where AI citations are high but web traffic is low. Those are opportunities. Also correlate with ranking data from your SEO tool. Topics where you rank well but get few AI citations are signals to improve content structure or sourcing. Use this to build a quarterly content roadmap driven by data, not intuition.

Here’s a simple Python script to analyze your grounding query CSV:

import pandas as pd
import re
from collections import Counter

# Load grounding queries CSV exported from Bing AI Performance
df = pd.read_csv('bing_grounding_queries.csv')

# Extract key terms from queries (simple version)
def extract_topic(query):
    # Remove common stop words and get main nouns
    stop_words = {'how', 'to', 'what', 'is', 'the', 'a'}
    words = query.lower().split()
    filtered = [w for w in words if w not in stop_words]
    return ' '.join(filtered[:3])

df['topic'] = df['query'].apply(extract_topic)

# Group by topic and sum citations
topic_citations = df.groupby('topic')['citation_count'].sum().sort_values(ascending=False)

print("Top 10 topics by citation volume:")
print(topic_citations.head(10))

# Find high-volume queries
top_queries = df.nlargest(15, 'citation_count')
print("\nTop 15 grounding queries:")
print(top_queries[['query', 'citation_count']])

Save your grounding query export as `bing_grounding_queries.csv`, update the column names if needed, and run this script. You’ll get topic clusters and top queries instantly. Use this data to decide what content to create or update next.

Conclusion

Bing AI Performance is the first real lens into how your content performs in generative AI answers. It changes what optimization means. You’re not chasing rankings anymore. You’re competing to be cited as a source. That’s a fundamentally different game, and Otterly AI correctly points out that this launched as a public preview in February 2026, giving early adopters a window to get ahead.

Here’s what matters: you have visibility into AI citations right now. Most competitors don’t know this dashboard exists yet. Your grounding queries show you exactly what questions people ask AI about your domain. Your page-level data shows which content is actually working. That’s asymmetric information. Use it.

Start with the basics. Verify your site. Pull your grounding queries. Spend an hour understanding what topics drive AI visibility. Then pick one content piece to optimize or one new article to write based on that data. Track the citations next month. Repeat quarterly. You’ll build a content engine optimized for AI visibility instead of guessing.

The shift from traditional search to AI search isn’t theoretical anymore. It’s happening now in Bing’s results. Copilot is generating 1.13 billion visits. Those visits are sourcing your competitors’ content. You need to be part of that conversation. AI Performance gives you the tools to do it. The only question is whether you use them.