Marketing mix modeling
Methods and validation
Bayesian Modeling for Modern Marketing: Solving Real-World Attribution & CLV ChallengesCookie deprecation and shrinking first-party tracking have made channel attribution harder to trust.
Methods and validation
When a Forecasted-Control MMM Can (and Can't) Answer a Budget QuestionA forecasted-control MMM can answer a budget question about known dynamics under expected future conditions, but it cannot tell a team whether an action its historical…
Comparisons
PyMC-Marketing vs. Meridian: What a Baseline-Modeling Benchmark Shows About MMM AttributionA marketing mix model can hit a strong R² and still get channel attribution wrong.
Methods and validation
Why a Frozen CAC Number Misleads Your Next Budget ReallocationThe decision this affects
Methods and validation
Why a Media Mix Model Number Needs a Controlled Test Before It Moves BudgetA media mix model can tell a VP of Marketing Analytics that paid social drove 18% of last quarter's revenue.
Use cases
An AI Agent's Budget Recommendation Looks Confident. Is It Correct?A marketing leader gets a channel-reallocation recommendation from an AI analytics agent: shift budget toward the channel with the strongest apparent lift.
Methods and validation
Agency vs. in-house marketing measurement: where causal action testing fitsA marketing analytics or data-science leader deciding how to measure effectiveness usually frames the choice as agency versus in-house.
Comparisons
PyMC-Marketing vs. Google Meridian: What to Check Before a Benchmark Moves Your BudgetA marketing analytics team choosing between PyMC-Marketing and Google's Meridian will find a published benchmark claiming one library is faster and more accurate than the other.
Methods and validation
Why a Bayesian Marketing Mix Model Still Needs Calibration Before You Reallocate BudgetA Bayesian Marketing Mix Model (MMM) can tell you which channel looks most effective.
Methods and validation
Marketing Mix Modeling: A Complete GuideMarketing mix modeling is a statistical technique that decomposes historical sales into a base level and the estimated incremental lift attributed to each marketing channel, using…
Case studies
When Last-Touch Attribution Breaks: A Funnel-Aware MMM ReadA marketing leader reallocating budget under GDPR-constrained tracking faces a specific question: which channels actually cause leads, when user-level attribution can no longer…
Methods and validation
Bayesian Marketing Measurement When Individual Tracking WeakensWhen individual-level attribution loses coverage, marketing teams should not treat the remaining tracked journeys as the whole market.
Methods and validation
Bayesian Media Mix Modeling for Marketing OptimizationA marketing analytics team allocating budget across TV, paid social, and direct mail usually starts from last-touch attribution or a spend-to-revenue heuristic.
Methods and validation
Funnel-Aware MMM: A Bayesian Architecture for Full-Funnel Marketing OptimizationA standard marketing mix model (MMM) treats every channel as independent: spend goes in, conversions come out, and each channel gets its own response curve.
For buyers
When Your MMM Gets the Channel Ranking BackwardsA marketing mix model can rank two channels by ROAS and get the order exactly wrong, not close, inverted.
Methods and validation
An Automated MMM Says Shift Budget. Should You Act on It?A marketing mix model (MMM) fits historical spend and outcome data to estimate each channel's contribution, then automates the data prep and Bayesian modeling choices behind that…
Methods and validation
When a Marketing Mix Model Recommends a Budget Shift, Test the Claim Before You Move the MoneyA production Bayesian marketing mix model (MMM) can trace spend through a real funnel: upper-funnel spend shapes lower-funnel demand, demand runs into budget caps, caps shape…
Methods and validation
From Uncertainty to Insight: What Bayesian Reasoning Means for a Business DecisionA marketing or analytics leader deciding how much stock to buy, how to price a product, or when to worry about churn usually has a forecast in hand.
Methods and validation
Is Your Marketing Model's Answer Data-Driven, or Just Your Priors Talking Back?A statistical model hands a marketing team a channel-attribution number, and the team has to decide: act on it now, or check it first.
Methods and validation
Why a Confounder Can Make a Marketing Channel Look Effective When It Isn'tA marketing team sees sales rise whenever Google Ads run. The obvious read is that the ads work. The obvious read can be wrong, and a worked Bayesian example shows exactly how.
Methods and validation
A Faster MMM Pipeline Doesn't Answer Whether the Numbers Are CausalMarketing Mix Modeling teams spend most of their time wrangling data: pulling spend, impressions, and conversions from a dozen ad platforms into one schema before a model ever…
Methods and validation
When an AI-Accelerated Marketing Mix Model Is TrustworthyA marketing mix model can now be configured in hours instead of months. That speed changes how often a team can rebuild the model.
Use cases
Marketing Mix Models, Attribution, or Experiments: Which One Should Decide Your Next Budget Move?A CMO deciding where to move next quarter's media budget usually has three kinds of evidence on the table: a marketing mix model, an attribution report, and maybe a handful of A/B…