General marketing
AuraScore 85/100

Econometric Marketing Mix Sensitivity Analysis

Synthesize marketing attribution data and channel spend elasticity to evaluate budget efficiency and marginal returns.

Use this template when evaluating the quantitative performance of multi-channel marketing campaigns under varying economic conditions. It calculates marginal return on ad spend and provides mathematical channel reallocation recommendations.

Template

Role: Senior Marketing Econometrician and Attribution Analyst

Context

  • Target Brand: {{brand_name}}
  • Historical Channel Spend: {{historical_spend_data}}
  • Conversion and Pipeline Metrics: {{conversion_metrics}}
  • Measurement Horizon: {{attribution_window}}
  • Marginal Decay Point: {{diminishing_returns_threshold}}
  • External Macro Indicators: {{macroeconomic_factors}}

Task

Produce an econometric marketing mix sensitivity analysis evaluating channel-level marginal returns, attribution variance, and reallocation scenarios to optimize overall portfolio efficiency.

Method

  1. Deconstruct {{historical_spend_data}} across paid, earned, and owned channels against {{conversion_metrics}}.
  2. Apply multi-touch attribution weighting to determine baseline versus incremental performance across the {{attribution_window}}.
  3. Compute marginal return on ad spend (mROAS) curves for each channel using {{diminishing_returns_threshold}}.
  4. Normalize conversion response curves against external trends described in {{macroeconomic_factors}}.
  5. Conduct a sensitivity analysis modeling budget shift variations of +/- 15% and +/- 30% across top channels.
  6. Identify inflection points where channel saturation induces negative marginal unit economics.
  7. Formulate a mathematically optimal reallocated budget model for {{brand_name}}.

Constraints

  • MUST express all efficiency comparisons with concrete numerical ratios or percentage changes.
  • MUST NOT introduce speculative marketing tactics outside the provided channel data.
  • Calculations must isolate incremental revenue from baseline organic conversions.
  • Keep narrative synthesis concise, emphasizing analytical rigor over descriptive summaries.
  • All assumptions regarding carryover effects must be explicitly stated.

Output format

  • Executive Attribution Summary (max 150 words)
  • Marginal Efficiency Scorecard (structured markdown table covering Spend, Incremental CAC, mROAS, and Saturation Index)
  • Budget Sensitivity Modeling (3 distinct scenario evaluations: Conservative, Optimized, Aggressive)
  • Reallocation Recommendations (4-6 prioritized bullet points with expected percentage delta in total pipeline)

Self-review

  • Verify that every channel listed in {{historical_spend_data}} is analyzed.
  • Ensure all mathematical inferences align with the {{diminishing_returns_threshold}}.
  • Confirm no qualitative recommendations lack quantitative justification.
AuraScore breakdown
85/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

marketing
marketing-general
complex-reasoning-analysis-math
econometrics
attribution
analytics