Old SEO Tactic Foresaw AI Search Behavior, New Queries Persist

Image credit: Search Engine Journal

A press release optimization strategy developed in 2003, which involved nesting phrases to capture both short and long search queries, anticipated modern artificial intelligence (AI) search behavior and the persistent 15 percent of daily new queries, according to industry analysis.

This early approach, dubbed the ‘Russian nesting doll’ strategy by its developer, focused on what is now known as ‘query fan-out’ before the term gained widespread recognition, underscoring the enduring relevance of detailed content optimization.

Google reported in 2019, with the introduction of its BERT algorithm, that 15 percent of daily search queries were entirely new and had never been encountered before. This figure has remained constant even with the subsequent rise of large language models, indicating a persistent user need for novel information.

Recent data from Google in May 2026 showed that AI Mode queries in the U.S. are now three times longer than traditional search queries, emphasizing that query length has become a critical factor in AI-driven search.

A 2024 dataset study by MJ Cachón found that branded ChatGPT prompts generated an average of seven-word sub-queries. The study also observed a 25-fold increase in the use of quotation marks between the first and last search within a single query run, suggesting AI systems are narrowing their searches inward.

Content strategies should now prioritize identifying nested phrases and regularly checking Search Console for long-variant queries that show high impressions but low click-through rates, according to experts.

To optimize for current search behavior, content creators should publish information at the speed of news and craft literal, quotable answers, industry observers noted.

John Mueller, a Google Search Advocate, has previously discussed the importance of understanding how users formulate queries, particularly as search engines evolve.

The consistent percentage of new queries, combined with the increasing length of AI-generated searches, highlights a continuous demand for content that can address highly specific and evolving user information needs.

Source: Search Engine Journal