Marketing Mix Modeling AI Prompt

Design and interpret a marketing mix model (MMM) for this business.

Business: {{business}}
Sales / conversion data: {{sales_data}} (weekly, 2+ years)
Marketing spend data: {{spend_data}} (by channel, same period)
External factors: {{external_factors}} (macroeconomic data, seasonality, competitor actions)

1. What MMM is and when to use it:
   - MMM uses regression to decompose total sales into: baseline (organic) + each marketing channel's contribution + external factors
   - Unlike attribution (which tracks individual user paths), MMM works at aggregate level
   - Best for: understanding the incremental contribution of each channel, including offline (TV, OOH)
   - Limitation: requires 2+ years of data, is backward-looking, and cannot measure within-campaign personalization

2. Data preparation:
   - Adstock transformation: marketing spend has a delayed and decaying effect
     Adstock_t = Spend_t + decay_rate x Adstock_{t-1}
   - Decay rates by channel: TV (~0.7), Digital display (~0.3), Paid search (~0.1)
   - Saturation curve: diminishing returns on increasing spend (log or S-curve transformation)
   - Control variables: seasonality (Fourier terms or dummy variables), price, distribution, promotions

3. Model specification:
   Sales_t = Baseline + sum(beta_i x Adstock_i_t) + beta_price x Price_t + Seasonal + Error
   - Estimate using Bayesian regression (allows priors on channel effectiveness)
   - Model diagnostics: R-squared, MAPE on holdout period, residual checks

4. Output interpretation:
   - Baseline %: share of sales occurring without any marketing
   - Contribution % per channel: what share of incremental sales each channel drove
   - mROAS (marginal ROAS): the return on the last dollar spent in each channel
   - Saturation point: at what spend level does each channel show diminishing returns?

5. Budget optimization:
   - Using the fitted saturation curves: what budget allocation maximizes total sales at the current total budget?
   - What is the revenue uplift from the optimal allocation vs current allocation?

Return: MMM methodology explanation, data preparation steps, model output interpretation, contribution table, mROAS by channel, and optimized budget allocation.