Find and Act On More AI Search Signals with Query Fan-Out Analysis

TABLE OF CONTENTS

    AI search isn't about single questions, requests, or interactions.

    When a prompt is given, LLMs deconstruct it into multiple related searches, evaluate what ranks in search engines for these, and synthesize the results into a single answer.

    This process is known as query fan-out. It's an incredibly important shift in how search visibility is earned and a new point of strategy for brands.

    With new Query Fan-Out Analysis capabilities in Semrush Enterprise AI Optimization (AIO), teams can now easily see, track, and act on these previously hidden search signals.

    By understanding the fan-out queries for individual prompts, you can target these searches with keywords and content. It's an extension of your approach to SEO that can yield big visibility gains across both forms of search.

    Why Query Fan-Out Matters

    Query fan-out forms the basis of how AI platforms like ChatGPT generate search responses. Instead of running a single query, the model:

    • Breaks the initial prompt into multiple related queries
    • Runs those queries across Google
    • Evaluates what ranks
    • Synthesizes the results into an answer

    This means that even with targeting of the specific prompt, you could be less visible than competitors if they own adjacent or supporting queries.

    As Google results are used in the process, query fan-out also demonstrates how crucial SEO remains. Think of it as a key link between AI search results and SEO execution.

    Targeting fan-out queries improves AI search performance

    In a controlled Semrush experiment, we optimized the content of four articles to specifically target fan-out queries. The outcome was measurable gains in AI citations and brand visibility, as citations of these content pieces more than doubled.

    The takeaway is clear: AI systems reward brands that provide comprehensive information, with context that spans across multiple supporting questions.

    Introducing Query Fan-Out Analysis

    Query Fan-Out Analysis reveals the Google searches that ChatGPT relies on to generate responses for the prompts being tracked and reveals the domains that rank for each of them.

    Instead of only seeing the final answer, teams gain visibility into:

    • Each underlying Google query used in forming the response
    • The domains ranking for each of these query
    • Gaps where competitors repeatedly surface
    • Which SERP results matter most for your brand
    Query Fan-Out Analysis UI

    This gives teams a direct line to action. Search and content improvements can be prioritized based on the fan-out queries with the highest potential impact on AI visibility.

    These new capabilities connect AI performance directly to SEO levers that teams already control.

    Align AI Visibility With SEO

    Use fan-out insights to understand which Google queries actually influence AI responses, so optimization efforts can be directed where it counts most.

    Identify competitive gaps

    Discover competitor content that shapes AI answers while your brand is absent, even if your core keywords perform well.

    Prioritize content efforts

    Not all content creation is equally impactful. Fan-out analysis highlights the queries that disproportionately affect AI output, helping teams allocate resources with confidence.

    Build unified performance tracking

    Paired with the AI vs SEO Comparison, Query Fan-Out Analysis enables teams to track improvements in Google rankings holistically alongside their AI visibility gains, reinforcing a comprehensive search strategy.

    Tips for Targeting Fan-Out Queries

    It's not necessary to include the exact queries in your content, as long as it answers the question or provides the information that's being requested. Your goal should always be to naturally include what readers are looking for.

    Start by reviewing your existing sections. In many cases, these can be tweaked to include to cover any new topics, or new subsections can be embedded within the flow.

    If your content seems disjointed and the new topics aren't easily added, consider adding an FAQ, "next steps", or "other considerations" section. The direct answer structure is simple for AI to parse and this can often allow multiple fan-out queries to be included.

    When a lengthier rewrite is needed, Semrush Enterprise provides targeted content optimization capabilities, including an AI-powered Smart Writer option, that includes any target keywords or phrases in the draft copy.

    Add any queries outside the article's scope to your content creation backlog. Semrush Enterprise can also support in creating a content brief, then prioritize what to work on next based on the projected visibility gains.

    Fuel Your AI Visibility and SEO Tactics

    Query fan-out is another example of the intrinsic link between AI search and SEO.

    It's also another strategic lever (and advantage) that's available to teams seeking to build their brand visibility, provided they have the capabilities to identify the right queries to target.

    Semrush Enterprise AIO's new Query Fan-Out Analysis empowers teams to build a more comprehensive and holistic strategy. Ensuring that as search expands, your capabilities, and brand visibility grow alongside it.

    Ready to get started? Request a demo now.

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