Evaluate feature investments using revenue impact, cost structure, ROI, and strategy. Use when deciding whether a feature deserves investment.

Purpose Guide product managers through evaluating whether to build a feature based on financial impact analysis. Use this to make data driven prioritization decisions by assessing revenue connection (direct or indirect), cost structure (dev + COGS + OpEx), ROI calculation, and strategic value—then deliver actionable build/don't build recommendations with supporting math. This is not a generic prioritization framework—it's a financial lens for feature decisions that complements other prioritization methods (RICE, value vs. effort, user research). Use when financial impact is a key decision factor. Input Works best with: The feature you're deciding on, in a sentence or two. Also useful: Revenue connection (direct or indirect), rough cost inputs (dev time, COGS, ongoing OpEx), and the strategic argument being made for it. Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re ask. Arriving empty handed? That works too. The advisor opens by asking what the feature is and how it's supposed to make or save money. Example invocation: Should we build SSO/SAML? Enterprise deals keep stalling on it; est. 2 engineer months plus ongoing support burden. Key Concepts The Feature Investment Framework A systematic approach to evaluate features financially: 1. Revenue Connection — How does this feature impact revenue? Direct monetization (new tier, add on, usage charges) Indirect monetization (retention, conversion, expansion enablement) 2. Cost Structure — What does it cost to build and run? Development cost (one time investment) COGS impact (ongoing infrastructure, processing) OpEx impact (ongoing support, maintenance) 3. ROI Calculation — Is the return worth the investment? Direct monetization: Revenue impact / Development cost Retention features: LTV impact across customer base / Development cost Factor in gross margin, not just revenue 4. Strategic Value — Non financial value that might override pure ROI Competitive moat (prevents churn to competitor) Platform enabler (unlocks future features) Market positioning (needed for enterprise deals) Risk reduction (compliance, security) Anti Patterns (What This Is NOT) Not feature scoring alone: Combines financial analysis with strategic judgment Not revenue only thinking: Considers margins, costs, and ROI, not just top line revenue Not ignoring retention: Indirect revenue impact (churn reduction) is equally valid Not building without validation: Assumes you've done discovery; this is the financial lens When to Use This Framework Use this when: Prioritizing between features with quantifiable revenue/retention impact Evaluating expensive features ( 1 engineer month of work) Making build/buy/partner decisions Defending feature prioritization to stakeholders or leadership Choosing between direct monetization (add on) vs. indirect (retention) Don't use this when: Feature is table stakes (must have for competitive parity) Impact is purely qualitative (brand, UX delight without measurable retention effect) You haven't validated the problem (do discovery first) Feature is < 1 week of work (just build it) Facilitation Source of Truth Use [ workshop facilitation ](../workshop facilitation/SKILL.md) as the default interaction protocol for this skill. It defines: session heads up + entry mode (Guided, Context dump, Best guess) one question turns with plain language prompts progress labels (for example, Context Qx/8 and Scoring Qx/5) interruption handling and pause/resume behavior numbered recommendations at decision points quick select numbered response options for regular questions (include Other (specify) when useful) This file defines the domain specific assessment content. If there is a conflict, follow this file's domain logic. Application This interactive skill asks up to 4 adaptive questions , offering 3 5 enumerated options at decision points. Step 0: Gather Context Agent asks: "Let's evaluate the financial impact of this feature investment. Please provide: Feature description: What's the feature? (1 2 sentences) Target customer segment (SMB, mid market, enterprise, all) Current business context: Current MRR/ARR (or customer count if pre revenue) Current ARPU/ARPA Current monthly churn rate Gross margin % Constraints: Development cost estimate (team size × time) Any ongoing COGS or OpEx implications? You can provide estimates if you don't have exact numbers." Step 1: Identify Revenue Connection Agent asks: "How does this feature impact revenue? Choose the option that best describes the revenue connection: 1. Direct monetization (new revenue stream) — We'll charge for this (new pricing tier, paid add on, usage based fee) 2. Retention improvement (reduce churn) — Addresses key churn reason; keeps customers from leaving 3. Conversion improvement (trial to paid) — Helps convert free/trial users to paid customers 4. Expansion enabler (upsell/cross sell) — Creates upsell path or drives usage based expansion 5. No direct revenue impact — Table stakes, platform improvement, or strategic value only Choose a number, or describe a custom revenue connection." Based on selection, agent adapts: If 1 (Direct monetization): "What pricing are you considering?" "What % of customers do you expect to adopt this?" (conservative, base, optimistic) Calculate: Potential Monthly Revenue = Customer Base × Adoption Rate × Price If 2 (Retention improvement): "What % of churn does this feature address?" (e.g., "30% of churned customers cited this gap") "What churn reduction do you expect?" (e.g., "5% → 4% monthly churn") Calculate: LTV Impact = Increase in Customer Lifetime × Customer Base × ARPU × Margin If 3 (Conversion improvement): "Current trial to paid conversion rate?" "Expected conversion lift?" (e.g., "20% → 25% conversion") Calculate: Additional MRR = Trial Users × Conversion Lift × ARPU If 4 (Expansion enabler): "What expansion opportunity does this create?" (upsell tier, usage growth, add on) "What % of customers will expand?" Calculate: Expansion MRR = Customer Base × Expansion Rate × ARPU Increase If 5 (No direct revenue impact): Skip to strategic value assessment Step 2: Assess Cost Structure Agent asks: "What's the cost structure for this feature? Development cost (one time): Team size: engineers Time estimate: weeks/months Estimated dev cost: $ Ongoing costs (if any): COGS impact: $ /month (hosting, infrastructure, processing) OpEx impact: $ /month (support, maintenance) If no ongoing costs, enter $0." Agent calculates: One time investment: Development cost Ongoing monthly cost: COGS + OpEx Contribution margin impact: (Revenue COGS) / Revenue Agent flags: If COGS is 20% of projected revenue: "⚠️ This feature significantly dilutes margins" If ongoing costs are high relative to revenue: "⚠️ Consider if this is sustainable" Step 3: Evaluate Constraints and Timing Agent asks: "What constraints or timing considerations apply? 1. Time sensitive competitive threat — Competitor launched this; we're losing deals 2. Limited budget/team capacity — We can only build one major feature this quarter 3. Dependencies on other work — Requires platform improvements or other features first 4. No major constraints — We have capacity and flexibility Choose a number, or describe your constraints." Based on selection: If 1 (Competitive threat): Strategic value increases (churn prevention) Urgency factor in recommendation If 2 (Limited capacity): Compare ROI against other features in backlog Recommend stack ranking If 3 (Dependencies): Flag dependency risk Suggest sequencing If 4 (No constraints): Proceed to recommendations Step 4: Deliver Recommendations Agent synthesizes: Revenue impact (from Step 1) Cost structure (from Step 2) Constraints (from Step 3) ROI calculation Strategic value assessment Agent offers 3 4 recommendations: Recommendation Pattern 1: Strong Financial Case When: ROI 3:1 (direct monetization) or LTV impact 10:1 (retention/expansion) Positive contribution margin No major red flags Recommendation: " Build now — Strong financial case Revenue Impact: [Direct/Indirect revenue impact calculation] Conservative estimate: $ /month Optimistic estimate: $ /month Cost: Development: $ Ongoing COGS/OpEx: $ /month Net margin impact: % ROI: Year 1 ROI: :1 Payback period: months Why this makes sense: [Specific reasoning based on numbers] Next steps: 1. Validate pricing/adoption assumptions with customer research 2. Build MVP to test core value prop 3. Monitor [specific metric] to measure impact" Recommendation Pattern 2: Weak Financial Case, Build Anyway (Strategic) When: ROI <2:1 or marginal financial impact But high strategic value (competitive, platform, compliance) Recommendation: " Build for strategic reasons (financial case is marginal) Financial Reality: Revenue impact: $ /month (modest) Development cost: $ ROI: :1 (below 3:1 threshold) Strategic Value: [Competitive moat / Platform enabler / Market requirement] Prevents churn to competitor X Required for enterprise segment (30% of pipeline) Recommendation: Build, but monitor closely: 1. Track adoption vs. projections 2. Measure churn impact (target: reduce churn by %) 3. Re evaluate after 6 months if adoption is low Risk: Opportunity cost—other features may have better ROI" Recommendation Pattern 3: Don't Build (Poor ROI) When: ROI <1:1 (direct monetization) or negative LTV impact Margin diluting No compelling strategic value Recommendation: " Don't build — Financial case doesn't support investment Why: Revenue impact: $ /month Development cost: $ ROI: :1 (below breakeven) Margin impact: Dilutes gross margin from % to % Alternative approaches: 1. Reduce scope — Can we build a simpler version at 50% cost? 2. Change monetization — Can we charge more or differently? 3. Deprioritize — Focus on higher ROI features like [alternative] What would need to change: If adoption rate increases from % to %, ROI becomes viable If we can reduce dev cost to $ , payback becomes acceptable" Recommendation Pattern 4: Build Later / Need More Data When: Assumptions are highly uncertain Revenue impact depends on unvalidated hypotheses Medium strategic value Recommendation: " Build later — Validate assumptions first Current uncertainty: Adoption rate assumption: % (needs validation) Churn impact: % reduction (hypothesis, not proven) Pricing unknown What to validate: 1. Run feature demand survey with 50+ customers 2. Prototype and test willingness to pay 3. Interview churned customers to confirm this addresses churn reason Decision criteria: If % of customers say they'd pay $ , build If churn interviews confirm this is top 3 reason, build Otherwise, deprioritize Timeline: Spend 2 4 weeks validating Re evaluate with real data" Step 5: Allow Follow Up Questions Agent offers: "Do you want to: 1. See the detailed math breakdown 2. Compare this to another feature 3. Adjust assumptions (pricing, adoption, cost) 4. Export recommendation summary Or, ask any follow up questions." Agent can: Show detailed calculations Sensitivity analysis (what if adoption is 2x? 0.5x?) Compare multiple features side by side Export summary for stakeholders Examples See examples/ folder for sample conversation flows. Mini examples below: Example 1: Direct Monetization (Time

feature-investment-advisor