Notus Media Mix Modeling (MMM) uses sophisticated statistical analysis to measure the true impact of your marketing campaigns, guiding budget allocation and maximizing effectiveness without relying on user-level data.
Visualization of Marketing Channel ROI
In a privacy-first world, understanding the effectiveness of your marketing channels is more critical than ever. Our MMM framework provides clear answers to key questions:
Leverage a highly customizable, Bayesian causal inference model designed for large-scale data, providing robust insights for strategic marketing decisions.
Our platform offers advanced methodologies to accurately model and optimize your media investments.
Utilize granular geo-level marketing data for richer insights and regional effectiveness analysis. Supports national-level modeling if geo-data isn't available.
Our Bayesian model allows incorporating existing knowledge (experiments, past results, benchmarks) via ROI priors, improving accuracy, especially with weak signals.
Model diminishing returns (saturation) and carryover effects (adstock) using sophisticated parametric functions for realistic media impact assessment.
Optionally use reach and frequency data as inputs for deeper insights into campaign performance and frequency optimization.
Built on causal inference theory with transparent assumptions. Includes options for control variables (like search query volume) for channels like paid search.
Determine optimal budget allocation across channels based on your goals, or let the system suggest an optimal overall budget. Includes frequency optimization.
Estimate ROI under hypothetical media scenarios (e.g., budget shifts, spending increases/decreases) using your fitted model.
Comprehensive reporting on model fit statistics (in-sample and out-of-sample) to compare different configurations and ensure reliability.
Optionally incorporate non-media factors like price changes and promotions to estimate their impact alongside media efforts.
We guide you through a structured process to unlock actionable media insights.
Aggregate your marketing spend, performance data (revenue/KPIs), and optional inputs like geo-data, reach/frequency, search volume, and non-media factors.
Configure the model based on available data (geo vs. national), incorporate priors, define saturation/lag parameters, and train the Bayesian model using advanced sampling methods.
Analyze results (ROI, marginal ROI, parameter uncertainty), run budget optimizations, explore "what-if" scenarios, and evaluate model fit for confident decision-making.
Discover how Notus' advanced Media Mix Modeling can provide the clarity you need to maximize ROI. Request a personalized demo today.