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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Clustering Your Customers Using Adobe Analytics Data Feeds and R

Follow @TrevorHPaulsen Theodore Levitt was a famous Harvard economist who is famous for his definition of corporate purpose, which he proposed was not merely making a profit, but instead creating and keeping customers.  One of my favorite quotes comes from his book, The Marketing Imagination, in which Levitt says, “If you’re not thinking segments, you’re not thinking.” […]

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Visitor Level Aggregations Using R and Adobe Analytics Data Feeds

Follow @TrevorHPaulsen Visitor level aggregations (or as I like to call them, “visitor rollups”) are one of the most useful and meaningful things you can do with an Adobe Analytics data feed.  If you ever want to do cluster analysis to find interesting marketing segments, propensity modeling to find likely converters, or product affinity analysis for cross […]

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