Marketing Mix Modeling
Statistical models for estimating channel impact, saturation, adstock, and budget response.
About Marketing Science & Insights
A practical home for marketing data science.
This site bridges analytical methods and day-to-day marketing decisions through concise articles, reproducible examples, and applied measurement frameworks.
Mission
Make advanced measurement easier to understand and easier to use.
The goal is to help practitioners, analysts, and decision-makers connect statistical thinking with marketing reality: imperfect data, channel overlap, organizational constraints, and decisions that need to happen on schedule.
Each piece aims to lead with the business question, show the method clearly, and explain what the output means for action.
Areas of Focus
6 domainsAttribution & Measurement
Frameworks for interpreting customer journeys when platform and user-level signals are incomplete.
Causal Inference
Experiments, geo-holdouts, difference-in-differences, and other methods for incrementality.
Customer Analytics
Lifetime value, cohort behavior, retention, and predictive analytics for growth decisions.
Marketing Technology
Data pipelines, dashboards, and tooling that make measurement repeatable for teams.
Strategic Analytics
Translating models into decisions, operating cadence, and clear business recommendations.
Approach
Working principlesEvidence-based
Methods should be grounded in statistical reasoning and tested against real business behavior.
Reproducible
Examples and workflows should be clear enough to inspect, rerun, and adapt.
Decision-focused
Analysis earns its place by improving choices, not only by improving reports.
Iterative
Measurement systems should evolve as channels, data quality, and business questions change.
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