Revenue Forecasting Engine

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

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*Built by AfrexAI — AI context packs for business operators who ship.*

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