# Revenue Analysis > Analyze revenue streams including growth trends, cohort analysis, churn and retention metrics, pricing impact assessment, and segment performance breakdown. TRIGGER when: user says /revenue-analysis, "analyze revenue", "revenue breakdown", "churn analysis", "retention metrics", "revenue growth", "pricing analysis". - Skill: `ashutoshsrivastava17/revenue-analysis` (Agent Skill) - Install (CLI): `npx skillmds@latest add ashutoshsrivastava17/revenue-analysis` - Raw SKILL.md: https://api.skillmd.com/api/skills/ashutoshsrivastava17/revenue-analysis/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: ashutoshsrivastava17 (https://skillmd.com/u/ashutoshsrivastava17) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ashutoshsrivastava17/revenue-analysis --- # Revenue Analysis Perform a deep analysis of revenue streams to understand growth drivers, retention dynamics, pricing effectiveness, and segment performance. This skill produces actionable insights for leadership and go-to-market teams. --- ## Step 1 — Define Analysis Scope Establish the boundaries and objectives of the revenue analysis. | Parameter | Description | Example | |------------------------|----------------------------------------------------|----------------------------------| | Business / Product | Which entity or product line to analyze | Acme SaaS Platform | | Time Period | Analysis window | Jan 2025 – Dec 2025 (12 months) | | Comparison Period | Benchmark period | Jan 2024 – Dec 2024 | | Revenue Model | Subscription, transactional, hybrid, usage-based | Subscription (annual + monthly) | | Segmentation Axes | How to slice the data | Plan tier, geography, company size| | Data Sources | Billing system, CRM, data warehouse | Stripe + Salesforce + Snowflake | ### Checklist - [ ] Revenue data reconciles to GL / financial statements - [ ] Customer master data is clean (no duplicates, correct segments) - [ ] Contract dates and terms are accurate (start, end, renewal) - [ ] Revenue recognition rules are understood (ASC 606 implications) - [ ] FX rates available for multi-currency analysis --- ## Step 2 — Revenue Growth Trends Analyze the trajectory of revenue over time. ### Revenue Summary Table | Period | Total Revenue | MRR / ARR | QoQ Growth | YoY Growth | Organic Growth | Inorganic | |----------|---------------|------------|------------|------------|----------------|-----------| | Q1 | | | | | | | | Q2 | | | | | | | | Q3 | | | | | | | | Q4 | | | | | | | | **FY** | | | | | | | ### Growth Decomposition Break total revenue growth into its components: | Growth Component | $ Contribution | % of Total Growth | Description | |--------------------------|----------------|-------------------|-------------------------------------| | New Customer Acquisition | | | Revenue from first-time customers | | Expansion (Upsell) | | | Existing customers buying more | | Expansion (Cross-sell) | | | Existing customers buying new products| | Price Increases | | | Same usage at higher price | | Contraction | | | Existing customers downsizing | | Churn | | | Lost customers | | **Net Growth** | | | | ### Revenue Waterfall ``` Beginning ARR → + New → + Expansion → - Contraction → - Churn → Ending ARR ``` --- ## Step 3 — Cohort Analysis Understand how revenue from each customer cohort evolves over time. ### Monthly Cohort Retention Table | Cohort | M0 (Starting) | M3 | M6 | M9 | M12 | M18 | M24 | |-----------|----------------|--------|--------|--------|--------|--------|--------| | Jan 2024 | | | | | | | | | Apr 2024 | | | | | | | | | Jul 2024 | | | | | | | | | Oct 2024 | | | | | | | | | Jan 2025 | | | | | | | | | Apr 2025 | | | | | | | | *Values can be expressed as % of M0 revenue retained (gross retention) or including expansion (net retention).* ### Cohort Analysis Questions 1. Are newer cohorts retaining better or worse than older ones? 2. Is there a consistent drop-off point (e.g., M3 cliff)? 3. Do cohorts expand over time (net retention > 100%)? 4. Are there seasonal patterns in cohort quality? 5. Which acquisition channel produces the highest-LTV cohorts? --- ## Step 4 — Churn and Retention Metrics Calculate and analyze the key retention KPIs. ### Retention Metrics Dashboard | Metric | Formula | Current | Prior | Benchmark | |--------------------------------|--------------------------------------------------------------|---------|--------|-----------| | Gross Revenue Retention (GRR) | (Beginning ARR - Churn - Contraction) / Beginning ARR | | | > 90% | | Net Dollar Retention (NDR) | (Beginning ARR + Expansion - Churn - Contraction) / Beg. ARR | | | > 110% | | Logo Retention Rate | (Beginning Customers - Churned) / Beginning Customers | | | > 85% | | Monthly Churn Rate | Churned MRR / Beginning MRR | | | < 2% | | Average Revenue per Account | Total ARR / Total Customers | | | Growing | | Customer Lifetime (months) | 1 / Monthly Churn Rate | | | > 36 | | LTV | ARPA x Gross Margin x Customer Lifetime | | | | ### Churn Root Cause Analysis | Churn Reason | # Customers | Lost ARR | % of Total Churn | Preventable? | |----------------------------|-------------|-------------|-------------------|--------------| | Product fit / feature gaps | | | | Yes | | Competitive displacement | | | | Partially | | Budget cuts / downsizing | | | | No | | Poor onboarding / support | | | | Yes | | Champion departure | | | | Partially | | Acquired / merged | | | | No | | Non-payment / collections | | | | Partially | | Other / unknown | | | | | --- ## Step 5 — Pricing Impact Assessment Evaluate how pricing changes have affected revenue. ### Pricing Analysis Framework | Dimension | Analysis | |-----------------------------|-------------------------------------------------------------| | Price Realization | Actual revenue per unit vs. list price (discount depth) | | Discount Distribution | Histogram of discount % across deals | | Price Increase Adoption | % of renewals accepting price increases vs. churning | | Plan Mix Shift | Movement from lower to higher tiers (or vice versa) | | Usage vs. Seat Economics | Revenue per seat vs. revenue per unit of usage | | Competitive Price Position | Where your pricing sits relative to alternatives | ### Price-Volume Decomposition | Component | $ Impact | Description | |-------------------|--------------|------------------------------------------------------| | Price Effect | | Revenue change from price changes, holding volume constant | | Volume Effect | | Revenue change from volume changes, holding price constant | | Mix Effect | | Revenue change from shift in product/plan mix | | FX Effect | | Revenue change from currency movements | | **Total Change** | | | --- ## Step 6 — Segment Performance Break down revenue by the most meaningful dimensions. ### Segment Breakdown Template *Repeat for each segmentation axis (geography, plan tier, company size, industry, channel).* | Segment | Revenue | % of Total | Growth (%) | GRR | NDR | ARPA | # Customers | |--------------------|------------|------------|------------|--------|--------|--------|-------------| | Segment A | | | | | | | | | Segment B | | | | | | | | | Segment C | | | | | | | | | Segment D | | | | | | | | | **Total** | | 100% | | | | | | ### Segment Health Assessment | Segment | Revenue Trend | Retention Trend | Profitability | Strategic Priority | Action | |-----------|---------------|-----------------|---------------|--------------------|------------------| | Segment A | Growing | Stable | High | Core | Invest & expand | | Segment B | Growing | Declining | Medium | Watch | Fix retention | | Segment C | Flat | Stable | Low | Evaluate | Improve margins | | Segment D | Declining | Declining | Negative | Sunset | Manage exit | --- ## Output Format ``` ## Revenue Analysis — [Business/Product] — [Period] ### 1. Executive Summary - Total revenue and growth rate - Key driver of growth (or decline) - Retention headline (NDR, GRR) - Top opportunity and top risk ### 2. Growth Trends [Revenue summary with growth decomposition] ### 3. Cohort Analysis [Cohort retention table with key observations] ### 4. Churn & Retention [Retention metrics dashboard; churn root cause analysis] ### 5. Pricing Analysis [Price-volume decomposition; discount analysis] ### 6. Segment Performance [Segment breakdown with health assessment] ### 7. Recommendations [Prioritized actions to accelerate growth and reduce churn] ### 8. Appendix - Monthly revenue detail - Customer-level top accounts analysis - Methodology notes ``` --- ## Quality Checklist - [ ] Revenue figures reconcile to audited financial statements - [ ] Cohort definitions are consistent and documented - [ ] Retention metrics use consistent numerator/denominator definitions - [ ] Churn reasons are based on actual exit interview data, not assumptions - [ ] Pricing analysis accounts for discounts, credits, and free periods - [ ] Segment classifications are mutually exclusive and collectively exhaustive - [ ] Growth decomposition sums to actual total growth - [ ] Recommendations are specific, measurable, and assigned --- ## Edge Cases | Scenario | Handling Approach | |-----------------------------------------|----------------------------------------------------------------------------------| | Usage-based revenue model | Analyze revenue per unit of consumption; cohort by usage tier, not just time | | Multi-product company | Analyze each product separately then show cross-sell dynamics between them | | Free-to-paid conversion funnel | Track conversion rates by cohort; include freemium in funnel, not in ARR | | Large enterprise deals with custom terms| Normalize to standard terms for comparison; flag outliers | | Revenue recognized over time (ASC 606) | Analyze both bookings (TCV/ACV) and recognized revenue separately | | Marketplace or platform revenue | Separate take rate analysis from GMV growth; track both sides of marketplace |