AI Conversation Turn Analysis
Search, support, education and social-companion systems count turns differently, so it reports medians, quantiles and uncertainty instead of one pooled mean.
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Start with this prompt
Standardizes samples and addresses bots, caps, censoring, and bias.
Compare turns per AI conversation across search, support, education, and social-companion systems using accessible datasets or published aggregates. Define turn, message, exchange, conversation, and session; never imply access to private platform-wide logs. Record platform, version/period, application, geography, population, inclusion rules, sample size, unit, timeout, cap, and counted messages. Convert only compatible metrics. Report distributions, medians, quantiles, uncertainty, and denominators, not one pooled mean. Address bots, retries, multi-user threads, gaps, caps, censoring, survivorship, opt-in telemetry, vendor incentives, and selection bias. Label inaccessible platform-wide data unavailable. Compare length with complexity, completion, escalation, satisfaction, and intent without assuming more or fewer is better. Deliver comparability table, harmonization, estimates, sensitivity analysis, reproducible calculations, and exact source versions.
Compare turns per AI conversation across search, support, education, and social-companion systems using accessible datasets or published aggregates. Define turn, message, exchange, conversation, and session; never imply access to private platform-wide logs. Record platform, version/period, application, geography, population, inclusion rules, sample size, unit, timeout, cap, and counted messages. Convert only compatible metrics. Report distributions, medians, quantiles, uncertainty, and denominators, not one pooled mean. Address bots, retries, multi-user threads, gaps, caps, censoring, survivorship, opt-in telemetry, vendor incentives, and selection bias. Label inaccessible platform-wide data unavailable. Compare length with complexity, completion, escalation, satisfaction, and intent without assuming more or fewer is better. Deliver comparability table, harmonization, estimates, sensitivity analysis, reproducible calculations, and exact source versions.
Analyze censored session lengths
Adds a distributional time-to-termination analysis with explicit administrative censoring, dropout handling, assumptions, and sensitivity tests.
Try Deep ResearchCompare turns per AI conversation across search, support, education, and social-companion systems using accessible datasets or published aggregates. Define turn, message, exchange, conversation, and session; never imply access to private platform-wide logs. Record platform, version/period, application, geography, population, inclusion rules, sample size, unit, timeout, cap, and counted messages. Convert only compatible metrics. Report distributions, medians, quantiles, uncertainty, and denominators, not one pooled mean. Address bots, retries, multi-user threads, gaps, caps, censoring, survivorship, opt-in telemetry, vendor incentives, and selection bias. Label inaccessible platform-wide data unavailable. Compare length with complexity, completion, escalation, satisfaction, and intent without assuming more or fewer is better. Deliver comparability table, harmonization, estimates, sensitivity analysis, reproducible calculations, and exact source versions.
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