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
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 |
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| Q2 |
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| Q3 |
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| Q4 |
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Growth Decomposition
Break total revenue growth into its components:
| Growth Component |
$ Contribution |
% of Total Growth |
Description |
| New Customer Acquisition |
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Revenue from first-time customers |
| Expansion (Upsell) |
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Existing customers buying more |
| Expansion (Cross-sell) |
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Existing customers buying new products |
| Price Increases |
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Same usage at higher price |
| Contraction |
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Existing customers downsizing |
| Churn |
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Lost customers |
| Net Growth |
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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 |
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| Jul 2024 |
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| Oct 2024 |
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| Jan 2025 |
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| Apr 2025 |
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Values can be expressed as % of M0 revenue retained (gross retention) or including expansion (net retention).
Cohort Analysis Questions
- Are newer cohorts retaining better or worse than older ones?
- Is there a consistent drop-off point (e.g., M3 cliff)?
- Do cohorts expand over time (net retention > 100%)?
- Are there seasonal patterns in cohort quality?
- 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 |
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> 90% |
| Net Dollar Retention (NDR) |
(Beginning ARR + Expansion - Churn - Contraction) / Beg. ARR |
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> 110% |
| Logo Retention Rate |
(Beginning Customers - Churned) / Beginning Customers |
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> 85% |
| Monthly Churn Rate |
Churned MRR / Beginning MRR |
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< 2% |
| Average Revenue per Account |
Total ARR / Total Customers |
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Growing |
| Customer Lifetime (months) |
1 / Monthly Churn Rate |
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> 36 |
| LTV |
ARPA x Gross Margin x Customer Lifetime |
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Churn Root Cause Analysis
| Churn Reason |
# Customers |
Lost ARR |
% of Total Churn |
Preventable? |
| Product fit / feature gaps |
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Yes |
| Competitive displacement |
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Partially |
| Budget cuts / downsizing |
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No |
| Poor onboarding / support |
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Yes |
| Champion departure |
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Partially |
| Acquired / merged |
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No |
| Non-payment / collections |
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Partially |
| Other / unknown |
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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 |
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Revenue change from price changes, holding volume constant |
| Volume Effect |
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Revenue change from volume changes, holding price constant |
| Mix Effect |
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Revenue change from shift in product/plan mix |
| FX Effect |
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Revenue change from currency movements |
| Total Change |
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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 |
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| Segment B |
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| Segment C |
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| Segment D |
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| Total |
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100% |
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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
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 |
ashutoshsrivastava17