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Ryko1141
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subscription-analytics

Analyze SaaS subscription metrics with cohort and churn analysis.

Updated Feb 15, 2026
Search Tags:#analytics#retention#saas#subscription#cac#churn#lvt
One-click install
npx skills add https://github.com/Ryko1141/Hedge-Edge-agentic --skill subscription-analytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: subscription-analytics
Source: https://github.com/Ryko1141/Hedge-Edge-agentic/tree/main/Finance%20Agent/.agents/skills/subscription-analytics
Command: npx skills add https://github.com/Ryko1141/Hedge-Edge-agentic --skill subscription-analytics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms raw subscription data into actionable business intelligence, enabling data-driven decisions to optimize revenue, reduce churn, and improve customer retention.

Core Features & Use Cases

  • Cohort Analysis: Understand user behavior and retention patterns across different signup groups.
  • Churn Decomposition: Identify the root causes of customer churn (voluntary vs. involuntary, specific reasons).
  • Conversion Funnel Optimization: Analyze trial-to-paid conversion rates and identify bottlenecks.
  • Unit Economics: Calculate LTV, CAC, and LTV:CAC ratios to guide growth investments.
  • Use Case: A monthly deep-dive into subscription metrics reveals that users who don't link a broker account within 7 days have a 50% higher churn rate. This insight prompts a targeted in-app onboarding flow to encourage immediate broker linking.

Quick Start

Run a comprehensive subscription analysis for the last quarter, focusing on cohort retention by signup month.

Frequently Asked Questions about subscription-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze SaaS subscription metrics like churn and retention?▼

SaaS subscription metrics like churn and retention are analyzed by cross-referencing billing data with user behavior to identify revenue optimization opportunities and predict churn risk across different signup cohorts.

What is churn decomposition and how does it identify root causes of customer loss?▼

Churn decomposition identifies root causes of customer loss by separating voluntary and involuntary churn factors, cross-referencing billing data with user behavior to pinpoint specific actions or bottlenecks driving cancellation.

How do I calculate unit economics like LTV and CAC for a subscription business?▼

Unit economics for a subscription business calculates LTV, CAC, and LTV:CAC ratios by analyzing trial-to-paid conversion rates and cohort retention, guiding data-driven decisions for growth investments and revenue optimization.

Do I need Creem.io and Supabase APIs to run cohort analysis on subscription data?▼

Yes, comprehensive cohort analysis and cross-referencing of billing data with user behavior requires access to Creem.io and Supabase APIs to integrate the raw subscription data needed for retention pattern evaluation.

Can I optimize trial-to-paid conversion rates using subscription analytics?▼

Yes, trial-to-paid conversion rates are optimized by analyzing the conversion funnel to identify bottlenecks, then cross-referencing user behavior data to prompt targeted interventions like in-app onboarding flows.

What's the best way to predict churn risk using SaaS subscription data?▼

Predicting churn risk is best achieved by cross-referencing billing data with user behavior, analyzing cohort retention curves, and decomposing churn to identify high-risk patterns such as delayed account linking within the first week.

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