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    "name": "Revenue Forecasting Engine",
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    "sections": [
      {
        "title": "Revenue Forecasting Engine",
        "body": "Build accurate, data-driven revenue forecasts your board and investors actually trust."
      },
      {
        "title": "What This Does",
        "body": "Generates a complete revenue forecasting model covering:\n\nPipeline-Weighted Forecast — Apply stage-specific close rates to your current pipeline\nCohort Analysis — Track revenue by customer cohort with expansion/contraction/churn\nScenario Modeling — Bear/base/bull projections with probability weighting\nSeasonality Adjustments — Monthly coefficients based on your historical patterns\nLeading Indicators — Track signals that predict revenue 60-90 days out"
      },
      {
        "title": "Instructions",
        "body": "When the user asks for a revenue forecast, follow this framework:"
      },
      {
        "title": "Step 1: Gather Inputs",
        "body": "Ask for (or use available data):\n\nCurrent MRR/ARR\nPipeline by stage with deal values\nHistorical close rates by stage\nAverage sales cycle length\nNet revenue retention rate\nExpansion revenue %"
      },
      {
        "title": "Step 2: Build the Pipeline Forecast",
        "body": "Stage-Weighted Model:\n\nStageProbabilityWeighted ValueDiscovery10%Deal × 0.10Demo/Eval25%Deal × 0.25Proposal Sent50%Deal × 0.50Negotiation75%Deal × 0.75Verbal Commit90%Deal × 0.90Closed Won100%Deal × 1.00\n\nAdjustment factors:\n\nDeal age penalty: -5% per month past avg cycle\nChampion risk: -20% if no identified champion\nBudget confirmed: +10% if budget is allocated\nCompetitive deal: -15% if competitor identified"
      },
      {
        "title": "Step 3: Cohort Revenue Model",
        "body": "Track each monthly cohort:\n\nMonth 0: New MRR from cohort\nMonth 1: Retained MRR × (1 - monthly churn rate)\nMonth 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS)\nMonth 6: Steady-state retention rate applies\nMonth 12: Mature cohort — use net revenue retention\n\nBenchmarks by company stage:\n\nMetricSeedSeries ASeries B+Gross Churn3-5%/mo2-3%/mo1-2%/moNet Retention90-100%100-110%110-130%Expansion %5-10%10-20%20-40%CAC Payback18-24 mo12-18 mo6-12 mo"
      },
      {
        "title": "Step 4: Scenario Analysis",
        "body": "Bear Case (20% probability):\n\nPipeline closes at 60% of weighted value\nChurn increases 50%\nNo expansion revenue\n1 key deal slips each quarter\n\nBase Case (60% probability):\n\nPipeline closes at weighted value\nCurrent retention rates hold\nHistorical expansion rate\nNormal seasonality\n\nBull Case (20% probability):\n\nPipeline closes at 120% of weighted value\nRetention improves 10%\nExpansion accelerates 25%\n1 surprise large deal per quarter\n\nExpected Value = (Bear × 0.2) + (Base × 0.6) + (Bull × 0.2)"
      },
      {
        "title": "Step 5: Seasonality Coefficients",
        "body": "Apply monthly adjustment factors:\n\nMonthB2B SaaSEcommerceProfessional ServicesJan0.850.700.90Feb0.900.750.95Mar1.050.851.10Apr1.000.901.00May0.950.900.95Jun1.100.951.05Jul0.850.850.85Aug0.800.900.80Sep1.101.001.10Oct1.051.051.05Nov1.151.401.10Dec1.201.751.15"
      },
      {
        "title": "Step 6: Leading Indicators Dashboard",
        "body": "Track these weekly — they predict revenue 60-90 days out:\n\nIndicatorWeightSignalQualified pipeline created25%New opps entering Stage 2+Demo-to-proposal rate20%Conversion velocityAverage deal size trend15%Moving up or down?Sales cycle length15%Getting longer = red flagInbound lead volume10%Marketing effectivenessWebsite trial signups10%Self-serve demandCustomer NPS/CSAT5%Retention predictor"
      },
      {
        "title": "Step 7: Output Format",
        "body": "Present the forecast as:\n\nREVENUE FORECAST — [Period]\n================================\nCurrent ARR: $X\nPipeline (Weighted): $X\nExpected New ARR: $X\n\n12-Month Projection:\n  Bear:  $X (20%)\n  Base:  $X (60%)\n  Bull:  $X (20%)\n  Expected: $X\n\nKey Risks:\n  1. [Risk] — [Mitigation]\n  2. [Risk] — [Mitigation]\n\nLeading Indicators:\n  🟢 [Healthy metric]\n  🟡 [Watch metric]\n  🔴 [Concerning metric]\n\nNext Month Actions:\n  1. [Specific action]\n  2. [Specific action]"
      },
      {
        "title": "Red Flags to Call Out",
        "body": "Pipeline coverage < 3x target = high risk\n\n\n40% of forecast from 1-2 deals = concentration risk\n\n\nAverage deal age exceeding 1.5x normal cycle = stalling\nDeclining demo-to-close rate = product-market fit erosion\nRising CAC payback period = unit economics degrading"
      },
      {
        "title": "Revenue Recognition Notes",
        "body": "SaaS: Recognize ratably over contract term\nServices: Recognize on delivery/milestones\nUsage-based: Recognize on consumption\nAnnual prepay: Deferred revenue, recognize monthly\n\nBuilt by AfrexAI — AI context packs for business operators who ship.\n\nGet the full toolkit:\n\nAI Revenue Leak Calculator — Find where you're losing money\nContext Packs — Industry-specific AI agent configs ($47/pack)\nAgent Setup Wizard — Deploy your first AI agent in 15 minutes\n\nBundles: Playbook $27 | Pick 3 for $97 | All 10 for $197 | Everything Bundle $247"
      }
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    "body": "Revenue Forecasting Engine\n\nBuild accurate, data-driven revenue forecasts your board and investors actually trust.\n\nWhat This Does\n\nGenerates a complete revenue forecasting model covering:\n\nPipeline-Weighted Forecast — Apply stage-specific close rates to your current pipeline\nCohort Analysis — Track revenue by customer cohort with expansion/contraction/churn\nScenario Modeling — Bear/base/bull projections with probability weighting\nSeasonality Adjustments — Monthly coefficients based on your historical patterns\nLeading Indicators — Track signals that predict revenue 60-90 days out\nInstructions\n\nWhen the user asks for a revenue forecast, follow this framework:\n\nStep 1: Gather Inputs\n\nAsk for (or use available data):\n\nCurrent MRR/ARR\nPipeline by stage with deal values\nHistorical close rates by stage\nAverage sales cycle length\nNet revenue retention rate\nExpansion revenue %\nStep 2: Build the Pipeline Forecast\n\nStage-Weighted Model:\n\nStage\tProbability\tWeighted Value\nDiscovery\t10%\tDeal × 0.10\nDemo/Eval\t25%\tDeal × 0.25\nProposal Sent\t50%\tDeal × 0.50\nNegotiation\t75%\tDeal × 0.75\nVerbal Commit\t90%\tDeal × 0.90\nClosed Won\t100%\tDeal × 1.00\n\nAdjustment factors:\n\nDeal age penalty: -5% per month past avg cycle\nChampion risk: -20% if no identified champion\nBudget confirmed: +10% if budget is allocated\nCompetitive deal: -15% if competitor identified\nStep 3: Cohort Revenue Model\n\nTrack each monthly cohort:\n\nMonth 0: New MRR from cohort\nMonth 1: Retained MRR × (1 - monthly churn rate)\nMonth 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS)\nMonth 6: Steady-state retention rate applies\nMonth 12: Mature cohort — use net revenue retention\n\n\nBenchmarks by company stage:\n\nMetric\tSeed\tSeries A\tSeries B+\nGross Churn\t3-5%/mo\t2-3%/mo\t1-2%/mo\nNet Retention\t90-100%\t100-110%\t110-130%\nExpansion %\t5-10%\t10-20%\t20-40%\nCAC Payback\t18-24 mo\t12-18 mo\t6-12 mo\nStep 4: Scenario Analysis\n\nBear Case (20% probability):\n\nPipeline closes at 60% of weighted value\nChurn increases 50%\nNo expansion revenue\n1 key deal slips each quarter\n\nBase Case (60% probability):\n\nPipeline closes at weighted value\nCurrent retention rates hold\nHistorical expansion rate\nNormal seasonality\n\nBull Case (20% probability):\n\nPipeline closes at 120% of weighted value\nRetention improves 10%\nExpansion accelerates 25%\n1 surprise large deal per quarter\n\nExpected Value = (Bear × 0.2) + (Base × 0.6) + (Bull × 0.2)\n\nStep 5: Seasonality Coefficients\n\nApply monthly adjustment factors:\n\nMonth\tB2B SaaS\tEcommerce\tProfessional Services\nJan\t0.85\t0.70\t0.90\nFeb\t0.90\t0.75\t0.95\nMar\t1.05\t0.85\t1.10\nApr\t1.00\t0.90\t1.00\nMay\t0.95\t0.90\t0.95\nJun\t1.10\t0.95\t1.05\nJul\t0.85\t0.85\t0.85\nAug\t0.80\t0.90\t0.80\nSep\t1.10\t1.00\t1.10\nOct\t1.05\t1.05\t1.05\nNov\t1.15\t1.40\t1.10\nDec\t1.20\t1.75\t1.15\nStep 6: Leading Indicators Dashboard\n\nTrack these weekly — they predict revenue 60-90 days out:\n\nIndicator\tWeight\tSignal\nQualified pipeline created\t25%\tNew opps entering Stage 2+\nDemo-to-proposal rate\t20%\tConversion velocity\nAverage deal size trend\t15%\tMoving up or down?\nSales cycle length\t15%\tGetting longer = red flag\nInbound lead volume\t10%\tMarketing effectiveness\nWebsite trial signups\t10%\tSelf-serve demand\nCustomer NPS/CSAT\t5%\tRetention predictor\nStep 7: Output Format\n\nPresent the forecast as:\n\nREVENUE FORECAST — [Period]\n================================\nCurrent ARR: $X\nPipeline (Weighted): $X\nExpected New ARR: $X\n\n12-Month Projection:\n  Bear:  $X (20%)\n  Base:  $X (60%)\n  Bull:  $X (20%)\n  Expected: $X\n\nKey Risks:\n  1. [Risk] — [Mitigation]\n  2. [Risk] — [Mitigation]\n\nLeading Indicators:\n  🟢 [Healthy metric]\n  🟡 [Watch metric]\n  🔴 [Concerning metric]\n\nNext Month Actions:\n  1. [Specific action]\n  2. [Specific action]\n\nRed Flags to Call Out\nPipeline coverage < 3x target = high risk\n\n40% of forecast from 1-2 deals = concentration risk\n\nAverage deal age exceeding 1.5x normal cycle = stalling\nDeclining demo-to-close rate = product-market fit erosion\nRising CAC payback period = unit economics degrading\nRevenue Recognition Notes\nSaaS: Recognize ratably over contract term\nServices: Recognize on delivery/milestones\nUsage-based: Recognize on consumption\nAnnual prepay: Deferred revenue, recognize monthly\n\nBuilt by AfrexAI — AI context packs for business operators who ship.\n\nGet the full toolkit:\n\nAI Revenue Leak Calculator — Find where you're losing money\nContext Packs — Industry-specific AI agent configs ($47/pack)\nAgent Setup Wizard — Deploy your first AI agent in 15 minutes\n\nBundles: Playbook $27 | Pick 3 for $97 | All 10 for $197 | Everything Bundle $247"
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    "owner": "1kalin",
    "version": "1.0.0",
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