Visualizing the Customer Journey with R and Adobe Analytics Data Feeds

Follow @TrevorHPaulsen Much has been said regarding the benefits of multi-touch or algorithmic attribution models to understanding your customers’ conversion paths, but running analyses merely looking at some numbers in a table doesn’t quite inspire insight in the same way that a well-constructed visualization can. So, in this post, I’m going to give you two great ways […]

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Build Your Own Cross-Device Marketing Attribution with Apache Spark and R

Follow @TrevorHPaulsen Over my last few posts I’ve been focusing on how to do better marketing attribution using Adobe Analytics Data Feeds and Apache Spark coupled with R. You can read all about those attribution techniques here: Multi-Touch Attribution Using Adobe Analytics Data Feeds and R The Two Best Models for Algorithmic Marketing Attribution That said, […]

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Attribution Theory: The Two Best Models for Algorithmic Marketing Attribution – Implemented in Apache Spark and R

Follow @TrevorHPaulsen In my last post, I illustrated methods for implementing rules-based multi-touch attribution models (such as first touch, last touch, linear, half-life time decay, and U-shaped) using Adobe Analytics Data Feeds, Apache Spark, and R. These models are indeed useful and appealing for analyzing the contribution any marketing channel has to overall conversions. However, they […]

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Multi-Touch Attribution Using Adobe Analytics Data Feeds and R

Follow @TrevorHPaulsen One of the hottest topics in the digital marketing space has always been marketing attribution. If you’re unfamiliar with this problem space, (I’d be surprised, but) there are lots of excellent explanations out there including this one. In a nutshell, companies have a lot of marketing outlets – search, display ads, social networks, email, […]

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