Most MMMs now claim to use experiment results. Far fewer can show that those experiments actually shaped what the model concluded. This report from Haus Staff Applied Scientist Ittai Shacham, PhD, gives marketers and analysts a clearer way to judge the models behind their budget decisions.
Inside the report:
- Better questions for vendors: how to tell a model that lists your tests as inputs from one whose channel estimates actually agree with them
- Blind spots a good fit can hide: why a model that matches your sales history can still steer budget to the wrong channels
- More value from past tests: how experiments run in different seasons and conditions can keep informing planning, instead of looking out of date
- A way to judge any model: a simple standard for whether a model has learned real cause and effect, not just past patterns
- A clearer view of the tradeoffs: why a slightly looser fit to historical sales can be the better choice when budget is on the line
