AI Conversation Turn Analysis

Turn counts vary across search, support, education, and social AI. The analysis uses session length and resolution metrics to explain why one average cannot represent every interaction.

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Standardizes samples and addresses bots, caps, censoring, and bias.

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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.

Focus on voice assistants

Changes application class and session rules.

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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.

Measure resolution, not length

Changes outcome from length to resolution.

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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 Research

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.