Inferring Causal Impact Using Bayesian Structural Time-Series Models

the morning paper

Inferring Causal Impact Using Bayesian Structural Time-Series Models – Brodersen et al. (Google) 2015

Today’s paper comes from ‘The Annals of Applied Statistics’ – not one of my usual sources (!), and a good indication that I’m likely to be well out of my depth again for parts of it. Nevertheless, it addresses a really interesting and relevant question for companies of all shapes and sizes: how do I know whether a given marketing activity ‘worked’ or not? Or more precisely, how do I accurately measure the impact that a marketing activity had, so that I can figure out whether or not it had a good ROI and hence guide future actions. This also includes things like assessing the impact of the rollout of a new feature, so you can treat the word marketing fairly broadly in this context.

…we focus on measuring the impact of a discrete marketing event…

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