◆ Insights
Straight talk on what makes a model actually work
Most writing about modeling is either a sales pitch or a math lecture. This isn’t. I write for the people who buy, commission, and act on models — about the difference between a model that looks impressive and one that improves the decision in front of you.
A recurring theme: a model can fit your history beautifully and still be wrong about what happens when you make a change. Knowing how to tell the difference is worth more than any accuracy statistic — and it’s what separates a model you can bet a budget on from one that just makes a nice slide.
Featured series: Getting your money’s worth from an MMM
A practitioner’s guide to hiring firms to build Marketing Mix Models — what to demand, how to validate what you get, and why the usual success metrics can pass a model that would steer your budget the wrong way.
Is Your Marketing Mix Model a Waste of Money?
You don’t need to know how to build a model to know how to buy one. Five brutal questions to ask an MMM firm before you sign the contract.
Good Fit, Wrong Direction
Four increasingly sophisticated models, one flaw in the data — and every one of them got the budget call backwards. What it costs when nobody asks question #1.
Latest
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Is Your Marketing Mix Model a Waste of Money?
Is your marketing mix model (MMM) a waste of money? If you don’t know how to build a model yourself, it’s almost impossible to spot a firm that’s just blowing smoke. But you don’t need to know how to build a model to know how to buy one. Here are 5 brutal questions to ask…
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Good Fit, Wrong Direction
In my last post I laid out five questions to ask an MMM firm before you sign the contract. Question #1 was about uneven data precision. Here’s what it costs when nobody asks it. I built a simulated world where I know the ground truth: direct mail generates 30 leads per $1K, digital generates 25.…
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Stop Hiring Analysts for Their Skills
SQL, R, Python — none of it is what makes a good analyst. I’ve hired and managed many data scientists and analysts, and the strongest predictor of who’d actually be great at the job was never their skill set. It was their talent: the stuff that comes naturally to a person and doesn’t for most…
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