Revenue Analytics

Revenue Analytics (LADDER Framework)

Design a revenue analytics layer that answers where revenue is being created, where it's leaking, and which lever to pull next - not a dashboard of vanity totals. LADDER decomposes ARR, attributes it, diagnoses drivers, and turns analysis into named actions.

Core Principle

Revenue analytics fails when it stops at the totals. Reporting ARR up-and-to-the-right tells you nothing actionable. LADDER decomposes revenue into the components a leadership team can act on within a quarter.

The LADDER Framework

| Letter | Stage | The Question | |--------|-------|--------------| | L | Leading Indicators | Which forward-looking metrics predict ARR movement 1-2 quarters out? | | A | Attribution | Where does new ARR come from - channel, motion, segment, cohort? | | D | Drivers | Which 3-5 levers explain most of the variance in NRR and growth? | | D | Diagnosis | What's broken or accelerating, and what's the named hypothesis? | | E | Expansion Economics | What's the economics of expansion vs new logo by segment? | | R | Retention Decomposition | What's GRR, contraction, churn - by cohort and reason code? |

ARR Waterfall

The minimum decomposition every leader should be able to recite:

| Component | Definition | |-----------|------------| | Starting ARR | Beginning-of-period book | | New Logo ARR | Net-new customer ARR added | | Expansion ARR | Seat / module / price-up from existing customers | | Contraction ARR | Seat / module / price-down from existing customers (not churn) | | Churn ARR | Customers lost (logo or full) | | Ending ARR | Computed from the above | | NRR | (Ending − New Logo) / Starting | | GRR | (Starting − Contraction − Churn) / Starting |

Leading Indicators

Lagging metrics (ARR, NRR) confirm what already happened. Leading metrics let you act:

| Metric | Leads What | Lead Time | |--------|------------|-----------| | Qualified pipeline coverage (3x) | Bookings | 1-2 quarters | | Engagement score trajectory | Renewal / NRR | 2 quarters | | Health score distribution | GRR | 1-2 quarters | | MQL→SQL conversion | New logo bookings | 1 quarter | | Expansion pipeline coverage | Expansion ARR | 1 quarter | | Win-rate by segment | Booking productivity | 1 quarter |

Driver Decomposition

| Driver | Definition | Watch For | |--------|------------|-----------| | Acquisition | New logo ARR / period | Channel mix shift, win-rate change | | Expansion | Expansion / Starting ARR | Mix of seat vs module vs price | | Retention (GRR) | 1 − (Churn + Contraction) / Starting | Cohort drift, segment concentration | | Pricing | Realized ARPA trend | Discount creep, packaging drift | | Mix | Segment / motion share | Concentration risk, dilution risk |

Economics

| Metric | Formula | Why | |--------|---------|-----| | CAC Payback (months) | Fully loaded S&M / (New ARR × gross margin / 12) | Sustainability of acquisition | | LTV / CAC | Gross-margin LTV / CAC | Long-run profitability | | Magic Number | (Net New ARR × 4) / Prior-Q S&M spend | Efficiency of growth motion | | Net Magic Number | Same but using net new ARR (incl. churn) | Truer efficiency view | | Expansion ROI | Expansion ARR / (CS + Expansion S&M cost) | Cheaper growth lane usually |

Cohort Retention

Cohort retention surfaces what the totals hide:

| Lens | Insight | |------|---------| | Logo retention by acquisition cohort | When did the product stop retaining? | | NRR by ICP segment | Which segments compound, which decay? | | Channel-of-acquisition retention | Which channels deliver durable revenue? | | Use-case retention | Which use cases retain best? |

Output

Save to outputs/revenue-analytics-[scope]-[YYYY-MM-DD].md

| Artifact | Description | |----------|-------------| | ARR Waterfall | Period-over-period with segmentation | | Leading-Indicator Pack | 6-8 metrics with thresholds and trend | | Driver Decomposition | Top 3-5 drivers with quantified contribution to variance | | Cohort Retention Heatmap | Cohort × period with segment cuts | | Economics Pack | CAC payback, LTV/CAC, magic number, segment breakdown | | Diagnosis Memo | Anomalies + hypotheses + named owners | | Forecast Roll-Up | Bottoms-up vs tops-down with delta explanation |

Process

1. Lock the ARR waterfall definitions - one source of truth across finance, CS, and sales
2. Build the leading-indicator pack with named thresholds, not just charts
3. Decompose drivers with explicit attribution; refresh quarterly
4. Stand up cohort retention with segment cuts that match motion design
5. Wire economics into the operating cadence - not just board prep
6. Diagnose monthly: anomaly → hypothesis → owner → action

Tips

1. One ARR definition - every team must agree on what counts as ARR
2. Cohort > snapshot - retention totals lie; cohorts don't
3. Always reason-code churn and contraction; otherwise the diagnostic loop is closed
4. Leading indicators with no threshold are decoration
5. CAC payback is the most honest growth metric - easy to game, hard to fake

Pairs With

• customer-analytics - Engagement and behavioral cohorts feed NRR decomposition
• revenue-forecasting - Drivers and leading indicators inform the forecast
• customer-success - Health-score distribution is a top GRR driver
• budget-allocator - Economics inform reallocation decisions

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: varunk130
• Source: varunk130/ai-gtm-skill-library
• License: MIT

Install and usage instructions live in the source repository linked above.