Marketing mix modeling

• 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…

• Comparisons

  PyMC-Marketing vs. Google Meridian: What to Check Before a Benchmark Moves Your Budget

  A 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

  When a Forecasted-Control MMM Can (and Can't) Answer a Budget Question

  A marketing analytics lead just allocated $30 million for next quarter's campaigns.

• Methods and validation

  When an AI-Accelerated Marketing Mix Model Is Trustworthy

  A marketing mix model can now be configured in hours instead of months. That speed changes how often a team can rebuild the model.

• Methods and validation

  Why a Media Mix Model Number Needs a Controlled Test Before It Moves Budget

  A media mix model can tell a VP of Marketing Analytics that paid social drove 18% of last quarter's revenue.

• Methods and validation

  Why a Bayesian Marketing Mix Model Still Needs Calibration Before You Reallocate Budget

  A Bayesian Marketing Mix Model (MMM) can tell you which channel looks most effective.

• For buyers

  When Your MMM Gets the Channel Ranking Backwards

  A marketing mix model can rank two channels by ROAS and get the order exactly wrong, not close, inverted.

• Methods and validation

  A Faster MMM Pipeline Doesn't Answer Whether the Numbers Are Causal

  Marketing 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…