Marketing Mix Modeling, Three Ways

Bayesian, Ridge, and Ensemble modeling approaches with response curves, 13-week forecasts, and a budget optimizer that pushes directly to your ad platforms. All computed in your browser.

Modeling Approaches

Three Modeling Approaches

Choose the approach that suits your data and goals. Each method brings a different statistical perspective. Results are produced in seconds, not hours.

  • Bayesian: Uncertainty-aware estimates with credible intervals for statistically rigorous results
  • Ridge: Multi-objective optimization balancing model fit and stability
  • Miqs Ensemble: A proprietary method combining multiple approaches for the strongest signal
  • Results in seconds, no overnight batch processing or waiting
  • Compare outputs across approaches to validate findings
Marketing Mix Modeling page with Bayesian, Ridge, and Miqs ensemble approaches

Response Curves and Forecasts

Response Curves and 13-Week Forecasts

Visualize the diminishing returns curve for each channel and project revenue over the next quarter. Know exactly when additional spend stops generating proportional returns.

Per-channel response curves show saturation points clearly
Identify the point of diminishing returns before you over-invest
13-week forward revenue projections under current and optimized spend
Compare forecast scenarios side-by-side to evaluate trade-offs

Budget Optimizer

Budget Optimizer with Ad Platform Push

The optimizer recommends the ideal spend allocation across channels to maximize total revenue. Adjustable spend multipliers let you model what-if scenarios, and you can push the results directly to your connected ad platforms.

Optimal allocation recommendation with projected revenue impact
Adjustable spend multipliers for scenario planning per channel
Push optimized budgets to Google Ads and LinkedIn Ads with full preview
Amazon Ads push coming soon
Complete audit trail of every budget push and mutation

Model Your Marketing Mix

Contact us to discuss how Attriqs fits your attribution needs.

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