A. Strategic Context Assessment Business Objective Validate whether an AI customer support platform can achieve product-market fit before significant investment. Initiative Scope Product development Market launch Pricing validation Customer acquisition Operational scalability Current Evidence Moderate customer interest Limited pilot data Financial assumptions based mainly on industry benchmarks Decision Urgency High. Product roadmap and hiring decisions depend on validation within 90 days. Strategic Dependencies AI model performance Platform integrations Customer acquisition efficiency Funding availability Strategic Assumption Summary The business shows promising early signals but relies on several unvalidated assumptions regarding pricing, automation quality, and customer acquisition economics. B. Assumption Inventory Category Assumption Why It Matters Evidence Level Customer Customers will pay $99/month Revenue model Moderate Market SMB demand is growing Market size Strong Product AI resolves 70% of tickets Core value proposition Weak Financial CAC under $250 Profitability Weak Operational Small team can support 200 customers Scalability Moderate Technology AI uptime above 99.5% Reliability Moderate Competitive Competitors won't react quickly Market position Weak Regulatory No major AI compliance barriers Expansion Moderate C. Assumption Risk Matrix Assumption Importance Uncertainty Business Impact Evidence Risk Priority AI resolves 70% of tickets High High High Weak #1 CAC below $250 High High High Weak #2 Customers pay $99/month High Medium High Moderate #3 Customer retention above 90% High High High Weak #4 Competitor response Medium High Medium Weak #5 D. Validation Experiment Design Experiment 1 Hypothesis Customers will pay $99/month. Validation Method Pricing A/B test. Required Data Trial conversion rate Purchase rate Customer feedback Success Criteria ≥15% of trial users convert to paid plans. Failure Criteria <5% conversion. Estimated Cost $1,500 Estimated Duration 2 weeks Smallest Practical Experiment Offer two pricing options to 100 qualified prospects. Experiment 2 Hypothesis AI resolves 70% of customer support requests. Validation Method Pilot deployment. Required Data Resolution rate Escalation rate Customer satisfaction (CSAT) Success Criteria ≥70% autonomous resolution CSAT ≥4.5/5 Failure Criteria Resolution <50% Estimated Cost $2,000 Estimated Duration 3 weeks E. Evidence Quality Assessment Evidence Type Rating Customer Evidence Moderate Financial Evidence Weak Market Evidence Strong Operational Evidence Moderate Competitive Evidence Weak F. Decision Readiness Analysis Recommendation Proceed with Safeguards Reasoning Market demand appears promising. Pricing has partial validation. AI performance remains uncertain. Customer acquisition economics require additional testing before scaling marketing spend. G. Assumption Monitoring Dashboard Metric Target Trigger Trial Conversion >15% Below 8% CAC <$250 Above $300 Monthly Churn <5% Above 8% AI Resolution Rate >70% Below 60% Customer Satisfaction >4.5/5 Below 4.0 Review Cadence Weekly experiment review Monthly executive review Pivot Criteria Three consecutive weeks below target conversion or AI performance. Escalation Threshold CAC exceeds $350 or churn exceeds 10%. H. Strategy Confidence Scorecard Dimension Score Evidence Strength 7/10 Assumption Quality 8/10 Experiment Design 9/10 Risk Management 8/10 Decision Readiness 7/10 Learning Agility 9/10 Strategic Confidence 8/10 Overall Strategy Confidence Score 56/70 (80/100) I. 90-Day Validation Roadmap Phase 1 (Weeks 1–2): Assumption Mapping Objective: Identify and prioritize critical assumptions. Milestone: Complete assumption inventory. KPI: 100% of high-impact assumptions documented. Phase 2 (Weeks 3–6): Experiment Execution Objective: Run pricing, AI performance, and acquisition experiments. Milestone: Three experiments completed. KPI: Minimum sample size achieved for each test. Phase 3 (Weeks 7–10): Evidence Review Objective: Analyze experiment outcomes. Milestone: Executive evidence review. KPI: At least 80% of assumptions validated or invalidated. Phase 4 (Weeks 11–13): Strategic Decision Objective: Decide whether to scale, pivot, or pause. Milestone: Board decision completed. KPI: Final investment recommendation documented. J. Executive Strategy Validation Report Strategic Assumption Summary The initiative has encouraging market signals but depends on validating pricing, AI effectiveness, and customer acquisition economics before scaling. Top 10 Critical Assumptions Customers will pay $99/month. AI resolves 70% of support tickets. CAC remains below $250. Monthly churn stays below 5%. AI accuracy is consistently high. Integrations satisfy customer needs. Customer onboarding takes less than one day. Infrastructure scales without major cost increases. Competitors do not significantly reduce prices. Regulatory changes do not materially impact AI operations. Top 5 High-Risk Assumptions AI resolves 70% of support requests. CAC remains below $250. Customer retention exceeds 90%. Customers accept the proposed pricing. Competitor reactions remain manageable. Top 5 Validation Experiments Pricing A/B test. AI support pilot with real customers. Customer acquisition channel test. Retention cohort analysis. Competitive positioning interviews. Top 5 Decision Triggers Trial conversion below 8%. CAC exceeds $300. AI resolution below 60%. Monthly churn above 8%. Customer satisfaction below 4.0/5. Strategy Confidence Score 80/100 Most Important Assumption to Test First Whether the AI can autonomously resolve at least 70% of customer support requests while maintaining high customer satisfaction. One Rule for All Future Strategic Decisions Never commit significant resources until the highest-risk assumption has been validated with measurable evidence.