Revenue Modeler Expert revenue forecasting agent that builds driver-based revenue models, projects growth scenarios, optimizes pricing strategies, and forecasts subscription metrics. Specializes in SaaS revenue modeling, marketplace economics, and multi-stream revenue forecasting. This skill applies rigorous revenue modeling methodologies to create defensible projections, stress-test assumptions, and support strategic planning. Perfect for fundraising projections, board reporting, budgeting, and pricing decisions. Core Workflows Workflow 1: SaaS Revenue Model Objective: Build comprehensive SaaS/subscription revenue model Steps: Current State Analysis Current MRR/ARR Customer count by segment ARPU by segment Growth trends (MoM, YoY) Cohort retention data Revenue Driver Identification Customer Acquisition: New customer growth rate Lead generation capacity Conversion rates by channel Sales capacity and productivity CAC and payback period Customer Retention: Gross churn rate (customer count) Net revenue retention (NRR) Churn by segment/cohort Contraction rate Expansion: Upsell rate Cross-sell rate Seat expansion Tier upgrades Model Architecture Beginning MRR + New MRR (new customers × ARPU) + Expansion MRR (existing customer upgrades) - Contraction MRR (downgrades) - Churned MRR (lost customers) = Ending MRR ARR = MRR × 12 Cohort-Based Modeling Track each cohort separately Apply cohort-specific retention curves Model degradation over time Account for seasonality Scenario Development Base Case: Current trend continuation Realistic growth assumptions Upside Case: Improved conversion Lower churn Higher expansion Downside Case: Slower acquisition Higher churn Economic headwinds Key Metrics Output MRR/ARR projections by month Customer count projections Net Revenue Retention LTV/CAC ratio evolution Payback period Gross margin projections Deliverable: Monthly MRR model with 12-36 month projections Workflow 2: Marketplace Revenue Model Objective: Build revenue model for marketplace businesses Steps: Marketplace Metrics Setup Supply Side: Active sellers/providers Listings per seller Average order value Supply growth rate Demand Side: Active buyers Transactions per buyer Buyer frequency Demand growth rate Marketplace Metrics: Gross Merchandise Value (GMV) Take rate percentage Net revenue = GMV × Take rate GMV Driver Model GMV = Active Buyers × Transactions/Buyer × Average Order Value OR GMV = Active Sellers × Listings/Seller × Sell-Through Rate × Price Take Rate Analysis Current take rate Take rate by category Take rate optimization potential Competitive benchmarking Additional revenue streams (ads, premium, fulfillment) Liquidity Modeling Match rate projections Supply/demand balance Geographic coverage Category depth Revenue Streams Transaction fees (primary) Subscription fees (seller SaaS) Advertising revenue Fulfillment/logistics fees Premium placement fees Data/analytics fees Deliverable: Marketplace revenue model with GMV and take rate projections Workflow 3: Usage-Based Revenue Model Objective: Model revenue for consumption-based pricing Steps: Usage Metrics Identification Primary usage unit (API calls, storage, compute hours) Average usage per customer Usage distribution (heavy vs. light users) Seasonal patterns Pricing Structure Per-unit pricing tiers Volume discounts Minimum commitments Overage pricing Platform fees Customer Segmentation Segment by usage level Different growth rates by segment Segment-specific retention Enterprise vs. SMB patterns Model Components Revenue = Σ (Customers per segment × Usage per customer × Price per unit) Account for: - Customer growth - Usage growth per customer - Price changes - Volume discount impact Predictability Enhancement Committed vs. overage revenue Minimum revenue guarantees Prepaid usage credits Annual contract values Scenario Modeling Usage growth scenarios Customer mix changes Pricing optimization Enterprise contract impact Deliverable: Usage-based revenue model with consumption projections Workflow 4: Multi-Product Revenue Model Objective: Model revenue across multiple products and revenue streams Steps: Product Portfolio Mapping Product 1: Type, pricing, target market Product 2: Type, pricing, target market Product 3: Type, pricing, target market Cross-sell relationships Individual Product Models Build sub-model for each product Apply appropriate methodology: Subscription → SaaS model Transaction → Marketplace model Usage → Consumption model One-time → Pipeline model Cross-Sell Modeling Attach rate assumptions Timing of cross-sell Bundle discount impact Cannibalization effects Revenue Mix Analysis Current revenue mix Target revenue mix Mix shift assumptions Profitability by product Consolidation Sum of product revenues Eliminate double-counting Bundle revenue allocation Total company revenue Scenario Development Product-specific scenarios Portfolio-level scenarios New product launch impact Sunset product impact Deliverable: Consolidated multi-product revenue model Workflow 5: Pricing Optimization Model Objective: Analyze and optimize pricing strategy Steps: Current Pricing Analysis Current price points Discount frequency and depth ARPU analysis Price sensitivity observed Competitive Benchmarking Competitor pricing Feature comparison Value-based positioning Market standard pricing Value-Based Pricing Analysis Customer value delivered ROI for customer Willingness to pay research Price anchoring opportunities Price Elasticity Modeling Historical price change impact Segment-specific elasticity Volume vs. price trade-off Revenue optimization point Pricing Scenarios Price increase impact: Revenue gain from price Volume loss from churn Net revenue impact Price decrease impact: Revenue loss from price Volume gain from conversion Net revenue impact Pricing Structure Options Per-seat vs. per-company Usage-based vs. flat Tiered pricing design Freemium conversion Annual discount strategy Implementation Plan Grandfathering strategy Rollout timeline Customer communication Monitoring metrics Deliverable: Pricing analysis with optimization recommendations Quick Reference Action Command/Trigger SaaS model "Build MRR/ARR revenue model" Marketplace "Model marketplace GMV and revenue" Usage-based "Create consumption-based revenue model" Multi-product "Model revenue across products" Pricing "Analyze pricing optimization" Scenarios "Model revenue scenarios" SaaS Metrics Reference Core Metrics Metric Formula Healthy Benchmark MRR Sum of monthly recurring revenue Growing ARR MRR × 12 Growing ARPU MRR / Customers Stable or growing Net Revenue Retention (Start MRR + Expansion - Contraction - Churn) / Start MRR

100% Gross Revenue Retention (Start MRR - Contraction - Churn) / Start MRR 85% LTV ARPU × Gross Margin / Churn Rate 3× CAC CAC Payback CAC / (ARPU × Gross Margin) < 12 months MRR Movement Types Type Definition New MRR Revenue from new customers this month Expansion MRR Revenue increase from existing customers (upsells) Contraction MRR Revenue decrease from existing customers (downgrades) Churned MRR Revenue from customers who cancelled Reactivation MRR Revenue from customers who returned SaaS Benchmarks Metric Good Great Best-in-Class MRR Growth (MoM) 5-7% 10-15% 20%+ Net Revenue Retention 100-110% 110-130% 130%+ Gross Churn (monthly) 3-5% 1-3% < 1% LTV/CAC 3:1 5:1 10:1 CAC Payback 12-18 mo 6-12 mo < 6 mo Revenue Model Template

Revenue Model: [Company Name] ** Model Period: ** [Start] - [End] ** Last Updated: ** [Date]

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Key Assumptions & Risks 1. [Assumption 1] - [Risk if wrong] 2. [Assumption 2] - [Risk if wrong] Best Practices Model Building Start with driver-based approach Document all assumptions Make assumptions adjustable Build scenario capability Test edge cases Assumption Setting Ground in historical data Benchmark to industry Be realistic, not optimistic Explain reasoning Sensitivity test key drivers Presentation Executive summary first Visualize key trends Show assumption sensitivity Include scenario comparison Highlight risks Integration with Other Skills Use with budget-planner : Link revenue to expense budget Use with cash-flow-forecaster : Convert revenue to cash Use with unit-economics-calculator : Validate profitability Use with financial-analyst : Historical performance analysis Use with investment-analyzer : Support fundraising projections Common Pitfalls to Avoid Hockey stick projections: Ground in reality Ignoring churn: Even small churn compounds Overestimating new customers: Harder than it looks Ignoring seasonality: Build in monthly patterns Linear assumptions: Growth often S-curve Ignoring capacity constraints: Sales, product, support Static pricing: Build in price evolution No segmentation: Different customers behave differently

revenue modeler

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