
What happened
Itera's LLMO Cheki now offers "AI question suggestions": users pick a site URL and a goal, and AI proposes prompts by funnel stage with sourced-versus-hypothesis labels, for 20 credits per site analysis.
Why it matters
Measurement quality hinges on asking the questions buyers actually use, so auto-designed prompts could cut setup work and reduce blind spots from biased prompt choices, though users must still vet each suggestion.
WHO IT HITSMarketing and SEO teams at companies tracking how often they appear in ChatGPT or Google AI search results stand to benefit most, since they can register suggested prompts in bulk instead of designing them by hand.
Summaries like this, every morning.
Itera frames the problem behind the launch in a simple way: measuring how a company appears in AI search only works if the questions being tested match what buyers actually ask. If the prompts drift from real consideration behavior, the numbers stop reflecting reality — but designing good prompts takes industry knowledge and trial and error, which is where the setup burden and blind spots come from.
The feature addresses that by reading a company's public pages and organizing its product, target customers, and pain points, then proposing question candidates across awareness, comparison, verification, and naming stages. Each candidate is tagged as backed by the site or as containing a hypothesis, with the reason for the suggestion shown, so users can decide what to adopt rather than mixing what the AI inferred with what the site states. The cost estimate comes before registration because more questions mean more daily measurement volume.
The company says it plans to keep refining suggestion accuracy and to propose replacing prompts based on how the registered questions actually perform, suggesting the tool is meant to become a recurring loop rather than a one-time setup.
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