About the Guidebook
Marketing attribution has been around for many years, and as the number of available advertising channels continues to shift and expand, so do the strategies employed by teams to leverage those channels. This guidebook is not intended to be an overview of every possible strategy, but a deep dive specifically into using machine learning models as opposed to heuristic models for marketing attribution across digital channels (both the why and the how).
By the end, readers should have an understanding of:
- What it means to use data science for marketing attribution.
- How it can make the difference in scaling efforts to reach customers with more customized targeting (whether in a business-to-consumer or business-to-business enterprise).
For those completely unfamiliar with data science in the context of marketing attribution, this guide will provide a short introduction to the topic and walk through the core aspects. But on top of that, for those already familiar, the guide includes some code and practical examples for execution