cohort-analyzer
SolidAnalyzes revenue cohorts, retention curves, LTV/CAC trends over time
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Quality Score: 96/100
Skill Content
Details
- Author
- a5c-ai
- Repository
- a5c-ai/babysitter
- Created
- 4 months ago
- Last Updated
- today
- Language
- JavaScript
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
saas-cohort-analyzer
Performs rigorous Software as a Service (SaaS) cohort analysis: retention curves, Lifetime Value (LTV), Customer Acquisition Cost (CAC) payback, Net Revenue Retention (NRR), Gross Revenue Retention (GRR), and expansion versus churn decomposition with dollar-weighted and logo-weighted views. Use when diagnosing retention problems, forecasting Annual Recurring Revenue (ARR), evaluating pricing changes, segmenting customer health, validating product-market fit, or preparing board and investor key-performance-indicator reports.
cohort-analysis
Use when the user needs customer cohort analysis — acquisition cohorts, retention curves, LTV by cohort, behavioral cohorts, or time-based cohort comparison to understand customer lifecycle patterns.
cohort-analysis
Structure a cohort analysis for retention, LTV, or behavioural patterns. Use when asked to run a cohort analysis, analyse retention by cohort, segment users by behaviour over time, or calculate lifetime value by acquisition period. Produces a complete cohort analysis framework with methodology, cohort definitions, retention curves, and prioritised interventions.
cohort-analysis-specialist
Track customer behavior over time by grouping customers based on shared characteristics or experiences. Use when measuring retention rates, understanding how customers evolve over time, comparing new vs old user behavior, evaluating product changes by cohort, identifying at-risk cohorts early, or calculating LTV by cohort. Essential for understanding retention, lifecycle patterns, and how product changes affect different user vintages.
cohort-analysis
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.