What the Cohort retention and behavioural segmentation research prompt does

Act as a SaaS retention researcher and behavioural segmentation lead.

The prompt will, at minimum:

  • Validate datasets, definitions, time windows, market scope and source-of-truth ownership before assessing cohort retention and behavioural segmentation research
  • Examine cohort entry, retention event, account and user levels, observation windows, censoring, reactivation, survival curves, behaviour sequences, frequency and intensity, plan and market differences, seasonality, clustering stability and actionability; preserve original identifiers and show the derivation of every finding
  • Segment only when evidence supports the split. Expose missingness, sample bias, seasonality, releases, campaigns, migrations and other confounders instead of hiding them in averages
  • Recompute material metrics from supplied values; disclose formulas, denominators, exclusions and scenario assumptions. Never invent benchmarks, market sizes or competitor performance
  • Turn evidence into a reproducible cohort framework, interpretable segments and prioritised retention hypotheses; assign owner, priority, dependency, expected signal, verification method and human-approval point to each action

Who it is for

Gökhan Güzel's SaaS prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Research brief and evidence-quality assessment
  • Cohort retention and behavioural segmentation research research framework
  • Segmented findings and comparable evidence map
  • Opportunity hypotheses prioritised by evidence and uncertainty
  • Next-research plan, sources, limitations, confidence and QA report

Variables

PlaceholderPurpose
{{account_master}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{analysis_period}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period
{{cohort_definition}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{company_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{customer_segments}}Target audience, segment, persona, customer/player or industry group
{{data_quality_notes}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{market_scope}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{product_event_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{product_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{reactivation_rules}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{retention_event}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{subscription_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{success_metrics}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{user_master}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run Cohort retention and behavioural segmentation research in ChatGPT

Open a new ChatGPT chat, paste the filled-in Cohort retention and behavioural segmentation research prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: