Choose useful improvements

How to Turn Bing AI Visibility Topics and Intents Into Content Priorities

Conceptual illustration for How to Turn Bing AI Visibility Topics and Intents Into Content Priorities: A topic label is a prompt, not a content brief.
A visual explanation of A topic label is a prompt, not a content brief.View full-size illustration

A topic label is a prompt, not a content brief

Bing Webmaster Tools’ AI Performance reporting adds context to citation activity. Intent categories classify grounding queries into broader types, such as Commercial, Informational, Local, Research, and Learn and Solve. Topics group related queries into wider subject clusters. Together, they can help a team notice the kinds of audience questions associated with the pages appearing as sources in supported AI experiences.

If Topics Portfolio is available for a site with sufficient data, use its additional context to choose what to inspect: topic size, sites cited, and query counts are approximate, while opportunity queries highlight queries where other sites appear and your site does not. Treat these as directional prompts, not verified gaps. Check each opportunity query against the target audience, offer, and existing pages. Branded queries can also appear as opportunities, so confirm the fit before commissioning work. If a topic or opportunity query is clearly off target, use the available feedback control to flag the mismatch as well as noting it in your planning; that is a useful response without turning the signal into a content task.

That is useful campaign intelligence, but it is not a publishing recommendation. A Commercial label does not prove that a particular audience is ready to buy, that a page is converting, or that a commercial landing page is missing. A topic cluster does not show that your site needs a new article simply because the subject appears in the report.

The useful question is not, “What should we publish for this label?” It is, “What does this signal suggest we should check about the audience, the page and the work already planned?”

Bing describes these intent and topic labels as outputs of evolving AI and machine-learning classification systems. During preview, a label may be broad, particularly for a specialized or niche subject, and its precision may change. The grounding queries shown are sampled rather than a complete record of citation activity. Citation counts and cited pages show observed activity; they do not establish placement in an individual answer or page ranking.

So use the report to open an investigation, not to skip one. A defensible content decision connects the signal to a real audience need and a business priority, then identifies the best existing or new destination for that need.

Sources: AI Performance in Bing Webmaster Tools; AI visibility insights: intent, topics and citation share; Introducing Topics Portfolio (Beta) in AI Performance

Read the query and page together

A broad topic name can compress several different jobs a visitor is trying to do. The cited page helps you understand which of those jobs your content may actually be serving. Look at the available grounding queries, the intent category and the cited URL as one piece of context, then compare that picture with the campaign’s audience and offer.

For each signal worth reviewing, ask:

  • What is the person trying to decide or accomplish? Read the available query wording, not just the intent label. Does it suggest learning a basic concept, comparing options, solving a problem, finding a local provider, or something else?

  • Which page is being cited, and what job is it designed to do? An explainer, product page, service page and comparison guide have different purposes. A citation to one does not prove that another is needed.

  • Does the page address the decision criteria that matter to this audience? For a commercial question, that may mean checking whether the relevant page makes the offer and its distinctions clear and answers the evaluation questions the client actually wants to serve. The label alone does not tell you which criteria those are.

  • Is this need already covered elsewhere? Check the campaign’s existing pages and planned work before proposing a new URL. A content gap is a missing or poorly served audience need, not merely a subject that can support another headline.

  • Would addressing it help the business or campaign? Connect the task to a relevant objective, audience or offer. If that connection is absent, the signal may be interesting without deserving production time.

This check also guards against planning around a classification that is too coarse. A topic could include several query types while the cited page only addresses one. Conversely, a page may be useful to the campaign even if the displayed label does not neatly match the team’s internal funnel or campaign naming. Prioritize the audience’s actual need and the page’s usefulness, not a forced one-to-one match between a dashboard category and a campaign taxonomy.

Sources: AI Performance in Bing Webmaster Tools; AI visibility insights: intent, topics and citation share; Introducing Topics Portfolio (Beta) in AI Performance; How ChatGPT Does Query Fan-Out (15 Million Queries Studied)

Choose among four sensible next moves

Once the query, cited page, audience need and campaign objective are in view, the action is usually clearer. You do not need to turn every observed topic into a new content brief. Choose the smallest useful move that addresses the evidence you have.

Improve the page that already fits

Update an existing page when it is the right destination for the audience need but does not answer it well enough. The work might be to clarify the page’s scope, make an important explanation easier to find, address a missing decision criterion, correct out-of-date information, or distinguish the offer more clearly. Make a change because the page has a real usefulness or positioning problem, not simply because it has fewer citations than another URL.

Create content when the gap is real

A new page makes sense when a valuable audience need is not adequately served by the existing site and cannot be handled clearly within an appropriate existing destination. Define the intended reader, the question they need answered, how the answer supports the offer or campaign, and why an existing page is not the better home. If that brief is difficult to write without repeating another page, the proposal may be a restructuring or update rather than a new article.

Investigate or monitor when the signal is unclear

If a label is unusually broad, the available query sample is thin, or the cited page’s relationship to the audience need is uncertain, record the question and look for more context before committing production resources. You might review other available queries or cited URLs, compare the pattern across a later reporting period, or discuss whether the topic aligns with current campaign priorities. A monitor decision is an active choice to wait for a more useful basis, not a failure to act.

Leave it alone when there is no useful fit

Some citation activity will be outside the client’s target audience, service area, product scope or current business priorities. Some pages may already be doing their intended job. If there is no meaningful audience need to address and no page problem to fix, do not manufacture a content task to make a dashboard signal look actionable. Keep the observation in reporting if it is useful, then move on.

Sources: AI Performance in Bing Webmaster Tools; AI visibility insights: intent, topics and citation share; Introducing Topics Portfolio (Beta) in AI Performance; How ChatGPT Does Query Fan-Out (15 Million Queries Studied)

A comparison topic does not automatically call for another article

Imagine an agency sees a client cited for a broad topic that includes product-comparison queries. The page appearing as a source is an introductory explainer. That combination is a useful reason to inspect the client’s content, but it does not tell the agency to commission a comparison article.

First, look at the actual query examples available and consider whether they reflect the client’s target buyers and offer. Then review the cited explainer: does it help with the kind of comparison suggested by the queries, or is it only designed to introduce the subject? Next, check whether the client already has a comparison or product page. If one exists, ask whether it clearly answers the buyers’ decision criteria and whether it is the appropriate destination for this need.

The right outcome could be to improve the existing comparison page, make the explainer’s scope clearer, propose a new page if a distinct and valuable decision need is genuinely uncovered, or do nothing if the queries are too broad or do not fit the campaign. Each is a more grounded response than treating a topic label as proof that another article will help.

The lesson applies beyond commercial topics. A Learn and Solve classification does not automatically mean “write a how-to guide,” and a Local label does not automatically mean “create another location page.” Use the label to ask a better question about the visitor’s task. Use the query and page context to determine whether that task deserves a content change.

Sources: AI Performance in Bing Webmaster Tools; AI visibility insights: intent, topics and citation share; Introducing Topics Portfolio (Beta) in AI Performance

Make the decision usable in campaign planning

A useful content-priority note should let the client or editorial team understand why a task exists and what decision it is meant to support. Keep the record compact enough to use in planning, but specific enough that “AI visibility opportunity” is not the entire rationale.

For each proposed action, capture:

  1. The signal: the relevant intent or topic, the available grounding query context and the cited URL.

  2. The audience need: what the person appears to be trying to learn, solve or decide, and why that audience matters to the campaign.

  3. The page assessment: what the cited or existing destination already does well, what it does not address, and whether another page already serves the need.

  4. The recommended move: update a page, create a page for a distinct verified need, investigate or monitor, or make no change.

  5. The reason to prioritize it: the client objective, offer, audience or planned campaign work that makes the action worthwhile.

  6. The next step and owner: who will take the action and, for an investigation or monitor decision, what additional context or reporting change would prompt a decision to act.

This keeps reporting honest and briefs focused. The observation is that Bing reports citation activity and classifies or clusters some of its query context. The interpretation is your assessment of how that context relates to a target audience and page. The recommendation is the work you believe is justified. Keeping those steps distinct makes it easier to explain a decision without presenting a classification as proof of demand or a citation as a conversion result.

If a team later makes a page change, it can keep observing the relevant reporting context and evaluate business outcomes using the client’s own analytics and conversion reporting. A subsequent change in citation activity can be noted, but it does not by itself establish that the edit caused the change or delivered a business result. The value of the workflow is better prioritization: work that answers a meaningful audience need, and fewer pages created just to fill a dashboard-shaped content calendar.

When a topic does not neatly match the campaign plan, that mismatch is not a problem to solve by force. It is a cue to inspect what the data groups together, what the cited page actually contributes, and whether the audience need deserves attention now. If it does, choose the most useful page action. If it does not, leave the signal where it belongs: as context, not a mandate.

Sources: AI Performance in Bing Webmaster Tools; AI visibility insights: intent, topics and citation share; Introducing Topics Portfolio (Beta) in AI Performance; How ChatGPT Does Query Fan-Out (15 Million Queries Studied)

Sources

Read the JSON companion

Read next