Understanding branded and non-branded queries is crucial for marketers leveraging AI citations data from platforms like Microsoft Clarity. These distinctions aid in evaluating how AI systems reference your brand specifically or more general topics that surround your industry.

Microsoft Clarity’s New Branded and Non-Branded Query Features

Recently, Microsoft Clarity enhanced its AI Citations dashboard by adding labels and filters that categorize grounding queries as either branded or non-branded. This update enables marketing executives to discern whether AI systems accessed their content through direct brand mentions or broader topical research.

Branded retrievals occur when the AI system’s search query explicitly includes a company or product name. Conversely, non-branded retrievals involve queries targeting broader categories or problems without direct brand mention.

Such granular data empowers marketers to measure AI visibility trends precisely and benchmark their Share of Authority against competitors within both contexts.

Share of Authority Explained

Microsoft defines Share of Authority as the proportion of AI citations your domain earns compared to other domains cited for the same set of queries. This measure is calculated daily and reflects your visibility within queries where your site is cited, not the entire AI search ecosystem.

Share of Authority offers a competitive signal reflecting your brand’s citation prominence in AI grounding queries, separating brand-specific and general topic exposure.

Characteristics of Branded and Non-Branded Grounding Queries

Branded Grounding Queries

Branded queries explicitly mention your brand or company name. These queries tend to surface your product documentation, pricing pages, support articles, detailed specifications, and customer reviews.

Tracking citations from branded queries helps marketers assess their brand presence within AI-driven content and evaluate if their direct information is utilized more than third-party sources. A high branded Share of Authority indicates dominant citation shares for branded research.

Non-Branded Grounding Queries

Non-branded queries encompass broader subject matters relevant to industry categories or customer problems without brand mention. Examples include searches for “enterprise analytics platforms” or “email marketing tools for retailers.”

Citations in this area reflect your content’s ability to contribute expert insights within broader topical AI research. Monitoring non-branded Share of Authority provides competitive intelligence about your visibility alongside peer companies in category-level queries.

For content strategy, weak non-branded visibility signals a need for stronger category content, original research, or digital PR efforts to increase authoritative signals across wider topics.

How Grounding Queries Differ From User Prompts

It is important to understand that grounding queries are formulated internally by AI systems to retrieve relevant content and may differ from the original user prompt. For instance, a user asking, “Which tools help understand website visitor behavior?” might prompt an AI to search for specific branded tools by name as part of its research process.

This distinction means branded grounding query data represents AI retrieval behavior rather than the explicit intent or awareness of the user. Marketers should therefore view these insights as a layer of AI search behavior, supplementing it with traditional web analytics, surveys, and sales data to understand customer intent.

Separating Citations, Referral Traffic, and Business Results

Microsoft Clarity tracks citations separately from AI referral traffic. Citations indicate how often an AI-generated answer referenced your content, but this does not guarantee user visits. Referral traffic measures actual site sessions from AI assistants.

It is possible to earn many citations without corresponding visits if the AI answer fully satisfies the user or links to your site are not prominently presented. Therefore, marketing teams should segment their analysis into three stages: citation visibility, referral traffic, and business outcomes such as lead generation or revenue.

Accurate performance measurement requires connecting AI referral data with CRM or analytics platforms to attribute conversions properly. This methodology avoids conflating citation growth with proven business impact.

Applying the AI Visibility Scorecard

The addition of branded and non-branded query filters allows marketers to develop a nuanced AI visibility scorecard incorporating:

Branded citations, branded Share of Authority, non-branded citations, non-branded Share of Authority, AI referral traffic, and AI-referred conversions.

By regularly monitoring these metrics by topic and page, companies can uncover content gaps or competitive pressures and adjust strategies accordingly. For example, weak branded citations might highlight product page deficiencies, while low non-branded visibility could justify investing in category leadership content.

Implementing a monthly review cycle that compares these indicators and hyperlinks with competitive landscape enables marketers to focus efforts where AI-enhanced search drives the most strategic value.

For practical steps, consult resources on adapting SEO strategy for AI search to gain actionable insights on gaining positive brand citations in AI-driven answers.

Limitations and Best Practices for Using Clarity Data

Microsoft notes several important caveats about the Clarity Citations dashboard. The data is representative but may exclude very low-volume activities or fail to capture all citations across platforms using Bing’s retrieval.

The classification of branded queries can be complex, especially with common words or multiple brand mentions. Therefore, marketers should carefully contextualize findings and avoid overinterpretation.

Clear labeling of reports as “Microsoft Clarity AI citation data” helps temper expectations and ensures transparency about the data scope.

Strategic Insights for CMOs and Marketing Leaders

Chief marketing officers should consider the following action points:

Separate branded from non-branded citations to analyze distinct visibility types; use Share of Authority to benchmark competitively; interpret grounding queries as AI retrieval signals rather than direct consumer intent; monitor citations, referrals, and conversions as distinct performance layers; and translate data into focused content and distribution decisions.

Starting with a baseline measurement and conducting monthly trend analyses allows marketing teams to optimize content investment and expand authority in AI-powered search environments.

Marketers interested in exploring in-depth AI visibility strategies can evaluate comprehensive plans such as the 90-day AI visibility boost that combines entity recognition and earned media approaches.

Finally, utilizing platforms like Adsroid’s AI-powered tools for monitoring and optimizing AI citation presence can provide a competitive advantage by automating data collection and insight generation.