scenario-engine

Board-level 'What If' simulator for strategic decisions.

Stop guessing. Use causal incrementality to measure exactly what works and what simply takes credit.

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This is exactly what you get when you run your data.

Scenario Engine: Aggressive Scale (+20% Spend)

Simulate potential futures. Compare baseline performance against modified spend and strategy assumptions.

Monte Carlo Simulation (10,000 Iterations)
Scenario
Aggressive Scale (+20% Spend)
Spend Change
+₹20.0k
Revenue Impact
+₹42.0k
Margin Impact
+₹22.0k
Risk Band
Medium

Confidence Level

Primary AnalysisLive Data
Main visualization of key metric drivers
Key Insights
  • Increasing spend by 20% yields ~₹{(currentSpend * 0.2 * 2.1).toLocaleString()} more revenue.
  • Risk is Medium because Meta scale relies on broader audience targeting.
  • Probability of positive ROI: 85%.
Logic Used
  • We run 10,000 simulations using channel volatility and historical betas.
  • Bounds: 95% Confidence Interval (VaR - Value at Risk).
  • Scenario: Adjusting input variables (Spend) to observe output distribution (Revenue).
Deep Dive

Change Drivers

Meta+20% Spend
Impact: ₹15,000Range: ₹12,000 - ₹18,000
Google+20% Spend
Impact: ₹8,000Range: ₹7,500 - ₹8,500
Data Transparency
Full breakdown of the underlying data points for verification.
Channel / DriverChangeRev ImpactConfidence Range
Meta+20%+15,00012,000 - ₹18,000
Google+20%+8,0007,500 - ₹8,500

Methodology

How SpendSignal calculates scenario-engine

The Logic

I need you to simulate and compare these 3 scenarios with confidence bands: 1. **Aggressive**: Increase total budget by 30%. 2. **Defensive**: Cut total budget by 20%. 3. **Reallocation**: Move 30% of spend from the worst performing channel to the best. Present the results as a decision slide: Revenue Impact, ROAD Impact, and Risk.

Input Data Required

  • Date Column
  • Spend per Channel
  • Revenue / Conversions

Output Deliverables

  • Executive Dashboard
  • Strategic Insights
  • Downloadable PDF

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