Understanding Bing’s Topics Portfolio Beta in AI Performance Reporting

Adsroid Blog
Bing's Topics Portfolio beta groups AI-cited queries into broader topics, revealing content gaps and opportunities to improve site presence in AI-generated search answers.

Summarize with AI

Connect Claude to your Ad Accounts in less than 5mn

Discover the most powerful advertising MCP and unlock 140+ tools to analyze, optimize and manage your campaigns with AI.

Bing’s Topics Portfolio beta is an innovative feature within the AI Performance report that categorizes queries your site is cited for into broader topics. This functionality helps website owners identify areas where their site is referenced in Bing’s AI answers and discover opportunities where competitors appear but they do not, providing valuable insights for content strategy and SEO optimization.

Introduction to Topics Portfolio

Located in a new tab adjacent to Citations & Pages in Bing’s AI Performance section, Topics Portfolio organizes the grounding queries Bing’s AI uses to source citations in its answers into thematic groups. These queries, referred to as grounding queries, represent search terms that Bing leverages for content citation through its Copilot, AI summary, and partner integrations. The Topics Portfolio only appears for sites with sufficient data volume, meaning smaller websites might not have access to this feature due to limited citation frequency.

Key Metrics Provided

For each topic where Bing identifies a meaningful presence of your site, three primary metrics are displayed. The “Topic Size” estimates the total citations for all sites within that topic over a specified timeframe, effectively measuring search demand driven by AI. “Sites Cited” reveals the number of websites cited for queries in the topic, offering insight into competitive presence. Lastly, “Queries” indicates the count of distinct grounding queries associated with the topic, providing a sense of breadth for content coverage.

Opportunity Queries Explained

One of the most valuable elements of Topics Portfolio is the “Top Opportunity Queries” list. This compilation includes queries under your topics where other sites are cited but your domain is not, highlighting potential content gaps. These opportunities are presented with citation volume ranges rather than precise counts, maintaining the data as directional signals rather than exact measurements. This approach aids content teams in prioritizing areas for creation or optimization without overwhelming granularity.

How to Utilize the Data

Clicking on a topic within Topics Portfolio advances to a detailed view that shows the total topic size, your site’s citation volume within the topic, and the number of queries involved. Beneath this overview, tables differentiate between queries your site currently appears for and those opportunity queries identified as gaps. This dual-view fosters a strategic approach to evaluate strengths and weaknesses across topic domains.

Bing supports adjustable time windows for this data—one, two, or three months—enabling trend observation and performance monitoring over time.

Improvements Since Initial Release

The Topics Portfolio enhances previous AI Performance features launched in June by aggregating total citation metrics across all sites at the topic level, in addition to listing non-cited queries tied to your website’s thematic areas. Prior to this, Bing showed grouped citations but lacked comprehensive ecosystem context or opportunity query identification—capabilities now central to this beta.

Bing’s evolving AI Performance toolset reflects a broader industry trend toward greater transparency in AI-driven search insights, empowering marketers to align their content with how AI engines reference and rank web data.

Limitations of the Beta Feature

As an AI-generated product, Topics Portfolio carries certain caveats. Queries might be categorized under topics that differ from human label expectations, or competitor brand searches may appear as opportunities—for example, a shoe retailer might see a competitor’s branded search grouped under broad Running Shoes topics as a gap. Bing explicitly encourages users to interpret the data as directional rather than authoritative.

"Treat the numbers as directional signals for planning, not as a precise ledger."

Users can provide feedback on individual query or topic rows through thumbs up or down votes, enabling Microsoft to refine classification accuracy and opportunity selection over time.

Significance for SEO and Content Strategy

Topics Portfolio offers content teams actionable insights by identifying which parts of their thematic scope are overlooked by Bing’s AI citations through competitor presence. This revelation is invaluable for discovering untapped or underdeveloped content segments that could increase visibility in AI-powered search results. While exact citation numbers remain estimates, the comparative nature of data assists strategic prioritization.

Incorporating these insights into an SEO workflow complements traditional keyword research and competitive analysis, especially as AI elements increasingly influence search behavior. For further enhancing SEO strategies, integrating solutions such as automated content performance tools can provide continual optimization aligned with evolving AI data.

Get Alerts When Competitors Launch New Ads

Ad Radar automatically monitors your competitors across Google, Bing and Meta. Get alerted when a new ad appears for your tracked keywords, so you can spot new offers, messaging and opportunities without constantly checking.

Context Within Broader Search Developments

Bing’s move towards transparent AI citation analysis parallels innovations in SEO performance measurement. For instance, recent advancements like Chrome’s tracking of soft navigations in Core Web Vitals offer nuanced metrics for single-page applications, refining site performance assessment methods relevant to AI evaluation frameworks. Understanding and leveraging these multidimensional data sources is crucial to maintaining competitive positioning.

Additionally, expert analysis on effective SEO testing methodologies remains essential when iteratively developing content strategies informed by AI insights to ensure data-driven decisions yield tangible ranking improvements.

Looking Ahead: Future Enhancements

Currently, Bing provides limited official documentation on Topics Portfolio, with most guidance derived from beta release notes and direct user feedback mechanisms. The absence of a definitive timeline for removing the beta label suggests ongoing refinement. As Microsoft accumulates more user inputs, enhancements in topic classification and more precise opportunity identification can be expected.

Continued updates may also introduce integrations with other Bing Webmaster tools, facilitating a more unified SEO workflow. Marketers should monitor these developments closely to capitalize on evolving AI-driven search engine dynamics.

Turn On Copilot. Let AI Optimize Your Ads 24/7.

Your AI agent works in the background, continuously watching your campaigns and finding ways to improve them. When it spots an opportunity, it tells you what to do, and you simply approve the action.

Final Recommendations

To maximize the value of Bing’s Topics Portfolio, website owners should regularly review opportunity queries and align content development plans accordingly. Coupling this with AI-powered campaign management tools can optimize both organic and paid efforts by creating consistent messaging across search channels.

Moreover, expanding content to cover missed thematic areas identified in the portfolio can strengthen domain authority and increase the chances of being cited in future AI responses, an increasingly important ranking factor.

For marketers seeking comprehensive solutions, exploring platforms like Adsroid’s suite of SEO and AI tools offers robust support in tracking, analyzing, and capitalizing on these new AI-driven opportunities.

Share the post

X
Facebook
LinkedIn

About the author

Picture of Danny Da Rocha - Founder of Adsroid
Danny Da Rocha - Founder of Adsroid
Danny Da Rocha is a digital marketing and automation expert with over 10 years of experience at the intersection of performance advertising, AI, and large-scale automation. He has designed and deployed advanced systems combining Google Ads, data pipelines, and AI-driven decision-making for startups, agencies, and large advertisers. His work has been recognized through multiple industry distinctions for innovation in marketing automation and AI-powered advertising systems. Danny focuses on building practical AI tools that augment human decision-making rather than replacing it.

Table of Contents

Your Google and Meta Ads on Autopilot

Let AI handle the work.

Adsroid analyzes your campaigns, finds opportunities and takes action to improve performance, while you stay in control.

Latest posts

How AI Shopping Agents Determine Product Recommendations

Learn how AI shopping agents use product details and shopper language to recommend relevant products. Discover strategies to enhance product pages for better AI-driven ecommerce discovery.

Understanding Bing’s Topics Portfolio Beta in AI Performance Reporting

Bing's Topics Portfolio beta groups AI-cited queries into broader topics, revealing content gaps and opportunities to improve site presence in AI-generated search answers.

Chrome Enhances Core Web Vitals with Soft Navigation Tracking

Chrome now tracks soft navigations in Core Web Vitals, providing detailed metrics for single-page applications. This update refines performance measurement for modern web experiences.