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 […]
Author: Trevor Paulsen
Trevor comes from the world of aerospace engineering and robotics. He studied estimation theory and data mining techniques before leading Adobe’s data science consulting team. Trevor is currently a senior product manager for Adobe Analytics and loves doing big data projects and statistical analyses on the side whenever he can. He’s a father of three and a lover of bike rides & music. All views expressed are his own.
Amp Up Your A/B Testing Using Raw Analytics Data, Apache Spark, and R
Follow @TrevorHPaulsen Experimentation and testing (also known as A/B testing or split testing) is an essential tool in the digital information age. If you’re not sure what A/B testing is, it’s the process of comparing two versions of a web page or app screen to see which performs better. A/B testing tools such as Adobe Target, Optimizely, […]
Attribution Theory: 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, […]
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 […]
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, […]
How to Use Classifications With Adobe Analytics Data Feeds and R
Follow @TrevorHPaulsen Adobe Analytics Classifications is one of the most useful and popular features of Adobe Analytics, allowing you to upload meta-data to any eVar, prop, or campaign that you may be recording in Adobe Analytics. Classifications are useful when you need to do things like: Classify your marketing campaign tracking codes into their respective marketing […]
Propensity Scoring in Adobe Analytics Using Data Feeds and R
Follow @TrevorHPaulsen When I was a kid, my favorite TV gameshow was “The Price Is Right” – it’s flashy, fun, and to this day I still love watching it – that is except for one thing: the ads. I still find it obnoxious to be bombarded by annoying (and sometimes gross) TV ads about hemorrhoid […]
Algorithmic Bot Filtering in Adobe Analytics Using R
Follow @TrevorHPaulsen Over the last few years, I’ve noticed a marked increase in the number of companies that are worried about their analytics data becoming contaminated with non-human traffic – and with good reason. According to a fairly recent report from Imperva, websites that have more than 100k human visitors everyday should expect nearly one […]
Importing Statistical Models from R into Adobe Analytics Using Customer Attributes
Follow @TrevorHPaulsen One of the most common problems I hear from data scientists is that it’s incredibly difficult to make a statistical model useful to an entire organization. Oftentimes, a skilled data scientist will build an awesome model and do some amazing analysis, only to have it wind up in some Power Point presentation that […]
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.” […]