Learn Topic-Based AI Visibility With Bing Topics Portfolio

Learning AI visibility becomes more practical when you study themes instead of isolated searches. Bing's Topics Portfolio beta groups grounding queries into topic clusters, so you can practice finding patterns, gaps, and useful content improvements.

The report is available inside Bing Webmaster Tools' AI Performance area when a site has sufficient data. It includes topic groups, citation concentration, estimated demand, competition, and opportunity queries where other sites appear but yours does not.

What Topics Portfolio Helps You Learn

AI visibility work requires more than checking whether one page appears in one answer. You need to recognize the subjects that connect related questions and determine whether your published information supports those subjects clearly.

Topics Portfolio gives learners a structured starting point. Instead of reviewing every grounding query separately, you can examine broader clusters and then inspect the searches inside each cluster.

• See the main themes associated with your site's AI Search presence.
• Review where citations already concentrate.
• Compare topic demand with the level of competition.
• Find opportunity queries where other sites appear and yours does not.
• Study a one-, two-, or three-month reporting window.

The report uses AI-generated classification and ecosystem aggregates, so treat its topic labels and estimates as study signals rather than exact measurements. Your next step should always include reviewing the underlying queries and pages.

A Four-Session Practice Plan

Session One: Choose One Topic

Open the AI Performance report and select the Topics tab. Start with a topic where your site already receives citations, because existing evidence gives you material to examine before you study gaps.

Record the topic name, reporting period, visible demand estimate, competition indicator, and number of related queries shown. Do not copy conclusions without recording the date and selected time window.

1. Select one topic with existing citation activity.
2. Write down the reporting window.
3. Record the topic's demand and competition indicators.
4. List several grounding queries associated with the topic.

This exercise teaches careful observation. It also prevents a common learning error: treating one impressive answer as proof of broad visibility.

Session Two: Group the Questions

Place the related queries in a simple worksheet. Add columns for the searcher's likely task, the information needed, your relevant page, and the page or pages cited in the answer.

Look for repeated needs. Several queries may ask for definitions, comparisons, instructions, requirements, or examples even when their wording differs.

• Definition questions ask what a term means.
• Comparison questions ask how two choices differ.
• Instruction questions ask how to complete a task.
• Requirement questions ask what a person must provide or follow.
• Example questions ask what a useful result looks like.

Do not create a new page for every wording variation. First check whether one well-organized page can answer the shared need with clear sections and supporting details.

Session Three: Compare Evidence

Choose two or three queries from the topic and inspect the pages associated with your site and the pages cited in AI answers. Compare the information, organization, clarity, and evidence without copying another publisher's wording.

Use a comparison worksheet with four columns: claim, supporting detail, source quality, and missing explanation. This makes the review concrete and keeps the exercise focused on reader value.

Ask these questions for each query:

• Does your page answer the question near the beginning?
• Does it define important terms before using them?
• Does each important factual claim have suitable support?
• Does the page explain limits, conditions, or exceptions?
• Can a reader identify the next practical step?

If a cited page contains information your page lacks, verify the claim with a primary source before adding it. If the claim cannot be confirmed, leave it out rather than filling the gap with an assumption.

Session Four: Study an Opportunity Query

Open the topic's opportunity queries and choose one that matches your site's actual subject. An opportunity is a practice lead, not proof that you should publish a page or that visibility will follow.

Classify the query before changing content. Decide whether it fits an existing page, needs a new page, or falls outside your site's purpose.

1. Read the query exactly as displayed.
2. Identify the task behind the wording.
3. Find the current page that best serves that task.
4. Check primary sources for accurate supporting facts.
5. Improve the existing page if the topic fits.
6. Record the change and its reason.

Use a small change whenever possible. For example, clarify a definition, add a missing step, or separate two commonly confused concepts. A focused edit makes your practice easier to evaluate later.

How to Keep a Practice Log

Maintain one row for each tested topic or query. Include the date, reporting window, topic, query, page reviewed, evidence checked, change made, and result observed in a later review.

Do not treat the report as a promise of traffic or business results. Microsoft describes Topics Portfolio as a beta report, and the feature does not provide referral-click data. Use it to study AI presence and content patterns, then evaluate important outcomes through separate records.

Use this short review format:

• Observation: What did the topic or query show?
• Evidence: Which primary source supports the information?
• Decision: What will you change, keep, or leave alone?
• Check: When will you review the same topic again?

Write the decision before making the edit. This separates analysis from guesswork and creates a useful record for future study.

Limits Learners Should Understand

Topics Portfolio does not replace query-level review. A broad topic can contain questions with different purposes, audiences, and evidence needs, so inspect individual queries before drawing conclusions.

The report may not appear for every site because Microsoft says sufficient data is required. If the tab is unavailable, use a manual worksheet based on questions your audience asks, then review whether your pages answer those questions clearly and accurately.

Topic labels and demand estimates are also approximate because the report relies on automated classification and aggregated ecosystem data. Record the report's values as directional clues, not exact market size or guaranteed opportunity.

What Good Practice Looks Like

A strong learner finishes with more than a list of topics. The learner can explain which questions belong together, which page serves each need, what evidence supports the answer, and why a specific content change is justified.

Repeat the process with one topic at a time. Over several review cycles, your log can show which questions remain difficult, which explanations need work, and where your site has a clear reason to provide better information.