Insights on expert networks, market research, UX research, and AI training from the CleverX team.
Creating a category means proving demand exists and shaping how buyers frame the problem. This guide covers both: bottom-up demand sizing with real buyers and the research that shapes the category narrative.
Most churn research never reaches the people who left. This guide covers how enterprise teams source churned buyers, interview them candidly, and build a win-back program from what they learn.
Most market entry decisions rest on a desk-research spreadsheet and optimism. This guide covers how enterprise teams validate a new geography or segment with real local buyers before committing.
Most enterprise launch research stops at the launch date. This guide covers the full loop: pre-launch demand validation with real buyers and the post-launch tracking that tells you whether the launch actually worked.
A guide to win-theme research: how to systematically mine won and lost deals for the recurring reasons buyers choose or reject you, and how to turn those themes into messaging and enablement the whole revenue team can repeat.
Teams guess at how buyers choose, then lose on reasons they never saw. This guide covers how enterprise teams research switching triggers, evaluation criteria, and committee dynamics with real buyers.
A guide to running enterprise B2B usability and product testing with the real practitioners who use complex software, covering why generic testers produce misleading results and how to recruit and verify domain professionals at the seniority your product requires.
A practical guide to enterprise willingness-to-pay research: how to measure what buyers will really pay, how to defend that price through procurement and renewals, and how to recruit verified decision-makers instead of unqualified panel traffic.
Insurance expert data is the evaluations, rubrics, benchmarks, and demonstrations that verified underwriters, actuaries, and claims adjusters produce so AI models and agents meet the standards a practitioner would apply. This guide covers what it looks like, who makes it, and how AI teams buy it.
Operations and supply chain expert data is the evaluations, rubrics, benchmarks, and demonstrations that verified procurement, logistics, and ops professionals produce so AI models and agents make the tradeoffs a practitioner would. This guide covers what it looks like, who makes it, and how AI teams buy it.
A practical guide to preference data for AI: what it is, where quality breaks down, and how to source expert human feedback for alignment.
A comparison of Prolific alternatives for expert and B2B professional research, scored on verification, seniority reach, data quality, and cost per completed study.