Query fan-out: unprecedented revelations about search in the age of AI engines thanks to the analysis of 102,000 queries

For the past few years, online search has been undergoing a silent but profound revolution, shaped by the emergence of advanced AI engines like ChatGPT and Perplexity. These systems, fueled by an astronomical amount of big data, no longer simply query a single index, but break down the initial query into a multitude of subqueries, a phenomenon known as “query fan-out.” An in-depth analysis of 102,000 queries performed between 2025 and 2026 reveals unprecedented insights into how these new players are transforming our user behavior and, by extension, digital scraping/la-polyvalence-du-scraping-un-outil-mille-possibilites/">marketing and SEO.

Query fan-out: the hidden engine of search in the age of artificial intelligence

This mechanism, still relatively unknown just a few years ago, has become central to natural language processing and generative search. At the heart of the process, a simple query, such as “best smartphone 2026,” is split into several sub-queries: “best cheap phone 2026,” “top Android smartphones,” “Apple vs. Samsung comparison 2026,” and so on. The logic? To cover a broader range of information to provide the user with a more precise and comprehensive answer.

This massive deployment is not without consequences. With the technique ofquery fan-out

Discover the concept of query fan-out, a database querying technique that optimizes data retrieval by distributing queries across multiple sources simultaneously.

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The implications for SEO and digital marketing: Understanding search behavior from the perspective of query fan-out completely redefines SEO strategies. Previously, ranking for a primary keyword was enough to guarantee visibility. Now, appearing in multiple variations of the same query is essential to optimize your presence in these new search patterns. This requires adapting content, with increased segmentation and anticipation of the many possible variations.

Companies must also learn to leverage these sub-queries to position themselves in previously unexplored market niches. Monitoring these variations becomes essential and can strengthen both their authority and overall visibility. Finally, processing these fragmented queries presents a technical challenge, requiring SEO specialists to master new analysis and optimization methods adapted to these new models. An exclusive study: 102,000 queries decoded to understand AI behavior To better understand this phenomenon, the analysis conducted by the Qwairy platform is a key step. It leverages an unprecedented amount of data: no fewer than 102,018 queries from human-computer interactions, collected over a three-month period. This study highlights that not all AI engines apply the query fan-out technique in the same way. A significant disparity emerges between aggressive strategies like ChatGPT’s, which favors massive fan-outs, and more conservative systems like Perplexity, which generally limits itself to a single query. According to the study, this major difference directly influences each engine’s ability to generate a “multiplier effect” capable of increasing the visibility of multiple content types within a multivariate SEO framework.

What the analysis reveals is that certain words or phrases such as “list,” “top,” or “comparison” have an exceptional power to trigger a proliferation of subqueries. For example, a question like “top 10 restaurants Paris 2026” generates, on average, more than five different subqueries. This explosion of detail allows AI engines to explore a vast semantic field and a constantly evolving range of information, which can change rapidly depending on the context or geographic location.

Automatic enrichment: the unexpected effect of AI on query accuracy

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One of the most surprising aspects of this study concerns the automatic addition of keywords or parameters by AI, without the user’s awareness. For example, the current year or geographical signals like “Paris” or “France” are inserted into the query, thus increasing the accuracy and relevance of the results. While these enhancements promote better understanding, they also complicate content creation to remain competitive.

This phenomenon, also called “contextual amplification,” demonstrates the hybridization between human and automated search, allowing AI to produce more refined and relevant summaries. Furthermore, this leads to a reassessment of SEO strategy in this era of intelligent and personalized results. Discover the concept of query fan-out, a database querying technique that distributes a query across multiple sources to optimize performance and the relevance of results. Content Strategies in the Face of New Search Queries

Here is a checklist to optimize your presence in the face of this evolution:

🏆 Create varied content around the possible variations of a single theme 🔍 Monitor trigger keywords🌍 Integrate geographical parameters into your strategies

🛠️ Optimize for voice search and long-tail keywords

• 📊 Regularly analyze variations in sub-queries
• Impacts and challenges for SEO in 2026 following the study of massive search queries
• Are the transformations brought about by query fan-out synonymous with upheaval or opportunities? It all depends on the ability to adapt. Precise segmentation of topics with high fan-out becomes strategic, as each variation increases the probability of appearing in the AI ​​response. The main challenge remains the technical mastery of processing these complex queries to maintain visibility in this new era of search.
• Criterion

Observed Effect 🔍

Strategic Importance 🎯

How does query fan-out influence SEO?

This mechanism multiplies entry points for appearing in search results. It requires precise content segmentation and anticipation of possible query variations to increase website visibility.

Do all AI search engines use query fan-out in the same way?

No, the study shows a significant disparity: some, like ChatGPT, use this technique extensively, while others, like Perplexity, favor a more conservative approach.

What keywords and phrases trigger strong query fan-outs?

Terms like ‘list’, ‘top’, and ‘comparison’ trigger an explosion in the number of subqueries, reflecting a trend toward expanded exploration.

How can you optimize your strategy in the face of these new search methods? You need to segment your content, monitor the evolution of query variations, and enrich your pages with contextual parameters to remain competitive in this new generative search landscape.

Écrit par

Kevin Grillot

Consultant Webmarketing & Expert SEO.

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