Skill: 1kalin/afrexai-revenue-forecasting (version 1.0.0)

# Revenue Forecasting Engine Build accurate, data-driven revenue forecasts your board and investors actually trust. ## What This Does Generates a complete revenue forecasting model covering: 1. **Pipeline-Weighted Forecast** — Apply stage-specific close rates to your current pipeline 2. **Cohort Analysis** — Track revenue by customer cohort with expansion/contraction/churn 3. **Scenario Modeling** — Bear/base/bull projections with probability weighting 4. **Seasonality Adjustments** — Monthly coefficients based on your historical patterns 5. **Leading Indicators** — Track signals that predict revenue 60-90 days out ## Instructions When the user asks for a revenue forecast, follow this framework: ### Step 1: Gather Inputs Ask for (or use available data): - Current MRR/ARR - Pipeline by stage with deal values - Historical close rates by stage - Average sales cycle length - Net revenue retention rate - Expansion revenue % ### Step 2: Build the Pipeline Forecast **Stage-Weighted Model:** | Stage | Probability | Weighted Value | |-------|------------|----------------| | Discovery | 10% | Deal × 0.10 | | Demo/Eval | 25% | Deal × 0.25 | | Proposal Sent | 50% | Deal × 0.50 | | Negotiation | 75% | Deal × 0.75 | | Verbal Commit | 90% | Deal × 0.90 | | Closed Won | 100% | Deal × 1.00 | **Adjustment factors:** - Deal age penalty: -5% per month past avg cycle - Champion risk: -20% if no identified champion - Budget confirmed: +10% if budget is allocated - Competitive deal: -15% if competitor identified ### Step 3: Cohort Revenue Model Track each monthly cohort: ``` Month 0: New MRR from cohort Month 1: Retained MRR × (1 - monthly churn rate) Month 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS) Month 6: Steady-state retention rate applies Month 12: Mature cohort — use net revenue retention ``` **Benchmarks by company stage:** | Metric | Seed | Series A | Series B+ | |--------|------|----------|-----------| | Gross Churn | 3-5%/mo | 2-3%/mo | 1-2%/mo | | Net Retention | 90-100% | 100-110% | 110-130% | | Expansion % | 5-10% | 10-20% | 20-40% | | CAC Payback | 18-24 mo | 12-18 mo | 6-12 mo | ### Step 4: Scenario Analysis **Bear Case (20% probability):** - Pipeline closes at 60% of weighted value - Churn increases 50% - No expansion revenue - 1 key deal slips each quarter **Base Case (60% probability):** - Pipeline closes at weighted value - Current retention rates hold - Historical expansion rate - Normal seasonality **Bull Case (20% probability):** - Pipeline closes at 120% of weighted value - Retention improves 10% - Expansion accelerates 25% - 1 surprise large deal per quarter **Expected Value = (Bear × 0.2) + (Base × 0.6) + (Bull × 0.2)** ### Step 5: Seasonality Coefficients Apply monthly adjustment factors: | Month | B2B SaaS | Ecommerce | Professional Services | |-------|----------|-----------|---------------------| | Jan | 0.85 | 0.70 | 0.90 | | Feb | 0.90 | 0.75 | 0.95 | | Mar | 1.05 | 0.85 | 1.10 | | Apr | 1.00 | 0.90 | 1.00 | | May | 0.95 | 0.90 | 0.95 | | Jun | 1.10 | 0.95 | 1.05 | | Jul | 0.85 | 0.85 | 0.85 | | Aug | 0.80 | 0.90 | 0.80 | | Sep | 1.10 | 1.00 | 1.10 | | Oct | 1.05 | 1.05 | 1.05 | | Nov | 1.15 | 1.40 | 1.10 | | Dec | 1.20 | 1.75 | 1.15 | ### Step 6: Leading Indicators Dashboard Track these weekly — they predict revenue 60-90 days out: | Indicator | Weight | Signal | |-----------|--------|--------| | Qualified pipeline created | 25% | New opps entering Stage 2+ | | Demo-to-proposal rate | 20% | Conversion velocity | | Average deal size trend | 15% | Moving up or down? | | Sales cycle length | 15% | Getting longer = red flag | | Inbound lead volume | 10% | Marketing effectiveness | | Website trial signups | 10% | Self-serve demand | | Customer NPS/CSAT | 5% | Retention predictor | ### Step 7: Output Format Present the forecast as: ``` REVENUE FORECAST — [Period] ================================ Current ARR: $X Pipeline (Weighted): $X Expected New ARR: $X 12-Month Projection: Bear: $X (20%) Base: $X (60%) Bull: $X (20%) Expected: $X Key Risks: 1. [Risk] — [Mitigation] 2. [Risk] — [Mitigation] Leading Indicators: 🟢 [Healthy metric] 🟡 [Watch metric] 🔴 [Concerning metric] Next Month Actions: 1. [Specific action] 2. [Specific action] ``` ## Red Flags to Call Out - Pipeline coverage < 3x target = high risk - >40% of forecast from 1-2 deals = concentration risk - Average deal age exceeding 1.5x normal cycle = stalling - Declining demo-to-close rate = product-market fit erosion - Rising CAC payback period = unit economics degrading ## Revenue Recognition Notes - SaaS: Recognize ratably over contract term - Services: Recognize on delivery/milestones - Usage-based: Recognize on consumption - Annual prepay: Deferred revenue, recognize monthly --- *Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI context packs for business operators who ship.* **Get the full toolkit:** - [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find where you're losing money - [Context Packs](https://afrexai-cto.github.io/context-packs/) — Industry-specific AI agent configs ($47/pack) - [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Deploy your first AI agent in 15 minutes **Bundles:** Playbook $27 | Pick 3 for $97 | All 10 for $197 | Everything Bundle $247


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