There’s a lot of confusion from marketers about the right way to use lift tests or incrementality experiments to calibrate the results of a media mix model (MMM). We see questions like: Should I use experimental results from other brands or products to calibrate my MMM? What if I have multiple different experiments, how do I choose which one to use? Won’t experiments just bias the MMM’s results? You need to be thoughtful when incorporating information from incrementality experiments into an MMM, so in this post we’ll: Talk a little bit about the theoretical relationship between incrementality experiments and MMMs. Answer commonly asked questions. Then share some guidelines for the appropriate way to do calibration. Why Calibrate? The goal of…
One of the ever-present problems with marketing mix modeling is that you always have to choose some start date. And since you always need to choose a start date, there’s always some period before the start date that’s impacting your results. Here's how Recast handles these carry-over effects.
Mockingbird empowers parents with premium, well-designed baby gear like their signature Single-to-Double Stroller. With a complex buyer’s journey and an…
With digital tracking breaking, consumer brands that relied on multi-touch attribution are now looking for alternatives to measure marketing effectiveness.…
There are three main ways that consumer brands measure marketing effectiveness: digital tracking (MTA), marketing mix modeling (MMM), and testing/conversion…
Business environments are messy; people with different responsibilities need to work together on decisions quickly and without perfect information. That…
In the context of marketing measurement, marketing analysts and marketing scientists use the term “incrementality” to refer to causality. Incrementality…