Mixed Modelling - What's the Best of Both Worlds?

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Mixed modelling is taking your historical data, including incorporating time series and other factors. And then anywhere where you runin experiment, there might be an overlap period. So let's say part of your year of data that you modelled has whatever, you know, a recent month in it. And tot myt meet me month whre yu had an experiment. It totally did. Anyone who was relying on a mixed model kanta just had a bit ofa in their heart drop to their stomachs when they realized what a change in the dynamic that just happened. In our case, anywhere where we had live experiments, we didn't have to think about it too much. We had

Multi-touch attribution, media mix modeling, matched market testing. Are these the three Ms of marketing measurement (Egad! The alliteration continues!)? Seriously. What's with all the Ms here? Has anyone ever used experimentation to build a diminishing return curve for the impact of a media measurement technique based on how far along in the alphabet the letter of that technique is? Is "M" optimal?! Trust us. You will look back on this description after listening to this episode with John Wallace from LiftLab and find it… at least mildly amusing. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.