Microsoft Advertising this week published its first monthly product newsletter on LinkedIn, bundling several reporting and measurement updates into a single release. The most significant addition is Topic Insights inside Microsoft Clarity, which organizes AI citation data by subject, not just by individual query. For brands tracking how they appear in AI-generated answers, the shift from individual data points to topic-level patterns is a meaningful one.
What Is Microsoft Clarity’s Topic Insights, and What Does It Actually Show?
Topic Insights groups AI citation data by subject area rather than listing every individual grounding query (the behind-the-scenes searches that AI systems run before producing an answer). According to the Microsoft Clarity blog published August 2026, the tool automatically classifies these queries into related clusters. A site in the outdoor sports space, for example, might see a broad cluster labeled “Sports” subdivided into more specific themes like “Winter Skiing.”
The August 2026 Clarity update introduces two complementary views:
- Query Topics: Automatically groups grounding queries already driving citations on your site. It answers: “Where is my content earning AI visibility right now?”
- Topic Insights: Lets you define topics proactively and evaluate competitive standing within them. It answers: “Where are the gaps I should be targeting?”
The Microsoft Advertising August 2026 newsletter also defines the three key metrics advertisers will see in these reports:
- Grounding queries: The retrieval searches AI systems generate before producing an answer.
- Citation share: How frequently your domain appears as a cited source.
- Share of authority: How often your domain is cited compared to competing sources on the same topic.
Topic-level data can be exported for external reporting or analysis. As of August 2026, Query Topics is available in beta.
Microsoft also recommends using grounding query data directly in paid search strategy: comparing grounding queries against existing search terms to find keyword gaps, identifying negative keyword opportunities, and adjusting landing pages based on competitive AI citation data, per the August 2026 newsletter.
How Do the New Performance Max Experiment Types Work?
Performance Max (an AI-powered campaign type that automatically places ads across Microsoft properties) now has two structured experiment types, both highlighted in the August 2026 newsletter as recently released:
- Uplift experiments: Measure the incremental impact of adding Performance Max alongside your existing campaigns.
- Upgrade experiments: Compare existing Search or Shopping campaigns directly against Performance Max after migration.
Microsoft continues to cite an average 8% increase in incremental conversions from Performance Max campaigns (per the August 2026 Microsoft Advertising newsletter). The experiment types give advertisers a way to verify that figure against their own account data before committing to broader changes.
Microsoft’s setup guidance, per the August 2026 newsletter:
- Have at least 30 conversions in the previous 30 days before starting an experiment.
- Keep bidding targets, product groups, and campaign settings consistent between test and control groups.
- Allow 4 to 12 weeks before evaluating results, depending on conversion volume and typical conversion lag.
What Changed in Ad Preview Hub?
Ad Preview Hub previously let advertisers preview Audience ads before launch. The August 2026 update extends that functionality to Performance Max and adds Bing Search results page (SERP) previews. Teams can now generate shareable preview links showing how ads may render before campaigns go live, rather than capturing screenshots after ads begin serving.
Because Performance Max automatically assembles and serves ads across multiple placements, being able to review creative before launch can help catch formatting issues, messaging inconsistencies, or stakeholder concerns early, particularly for agencies and teams with legal or brand approval workflows.
What This Means for AI-Search Visibility
Think of AI visibility like share of voice in a conversation, except the conversation is happening inside an AI assistant. The core question is: when a user asks an AI about your category, does your brand get mentioned or cited? Until now, most brands had no structured way to track this by topic. Topic Insights is one of the first tools to make that measurement usable at scale.
Here is a concrete example. Say you run a financial planning service. You might discover through Query Topics that your site earns strong citation share on “retirement savings calculators” but near-zero visibility on “first-home buyer grants,” even though you publish content on both. That gap, visible in a single dashboard view, gives a content team a specific brief rather than a vague instruction to “do more AI optimization.”
A few observations that neither source explicitly flags, offered here as Hingewise’s editorial assessment:
The combination of grounding query data and share of authority mirrors how search practitioners have used keyword rankings and backlink share for years. That is potentially good news for teams already fluent in search measurement, because the analytical muscle transfers. But the same blind spots apply: citation volume does not automatically equal business impact. A topic where you earn high AI citation share but low conversion value may not be worth defending.
The cross-channel use case Microsoft is promoting, applying grounding query data to paid keyword strategy, is worth watching carefully. If AI citation data starts influencing paid search keyword decisions at scale, it could reshape how keyword research is conducted for Microsoft Ads accounts. That is a material shift in how the two channels inform each other, not just a reporting add-on.
In Hingewise’s assessment, brands most likely to benefit near-term are those with established content libraries that AI systems are already drawing from. Topic-level citation data shows where you already hold authority. The gap view shows where to build it. Both require a content base worth measuring in the first place, which is the less glamorous prerequisite the tools assume you have solved.
Before You Act on Topic Insights Data: A Quick Checklist
- Confirm Query Topics is active in your Clarity project (in beta as of August 2026; not all accounts may have access yet).
- Cross-reference your top cited topics against your actual business priorities. High citation volume in an off-target topic is informative but not necessarily actionable.
- Compare grounding queries in Clarity against your Microsoft Ads search terms report to identify paid keyword gaps.
- Check share of authority per topic to see where competitors are consistently outpacing you.
- Flag pages with strong citation counts but low on-site conversion rates; AI visibility and revenue impact do not always align.
- Before running Performance Max experiments, verify your account meets the 30-conversion minimum from the previous 30 days.
- Set a review cadence for Topic Insights data. Tracking changes over time reveals trends; a single snapshot rarely tells the full story.
What to Watch Next
Microsoft’s August 2026 newsletter signals a consistent direction: adding measurement, experimentation, and review layers on top of existing AI-powered features rather than introducing new campaign types. The open question is whether Topic Insights data becomes a routine input into content and keyword planning workflows, similar to how organic keyword data is used today. That depends on how reliably grounding query data maps to actual user intent over time. As the feature moves out of beta and as Microsoft expands AI Visibility reporting, that correlation will become clearer.
Sources: Search Engine Journal (August 2026) microsoft-advertising-adds-ai-visibility-insights-pmax-testing-and-creative-preview-updates; Microsoft Clarity Blog (August 2026) analyze-ai-citation-queries-by-topic
Lam Nguyen · Hingewise