An analysis of over 400 Google Ads accounts found no discernible shift toward longer search queries, revealing a structural gap in how the platform reports traffic from AI search assistants.
The finding matters because longer, conversational queries typically signal AI-driven search activity. Users formulate questions differently in ChatGPT, Gemini or Perplexity than they do in traditional search—more context, more specificity. If AI traffic were properly captured in search terms reports, the average query length would show growth. It does not, suggesting either that AI-sourced clicks go unattributed or that Google aggregates and obscures them.
Google Ads has long withheld individual search queries below a significance threshold, grouping them instead as 'Other searches.' As AI search grows, this blind spot widens. For a context marketer, the practical problem is immediate: clicks arrive from sources you cannot see. Optimizing negative keywords, adjusting bids, understanding intent—all demand data the report does not contain.
The gap is structural rather than technical. Google aggregates queries to protect user privacy, the company says. But aggregation also masks the patterns AI search is now creating. Without a standard for attributing traffic from AI assistants, accounts will continue running partly blind. The analysis of 400+ accounts confirms it: AI search leaves no systematic trace in search terms reports.
