Discover how integrating ChatGPT and R for automating analytics data quality checks can streamline your analytics process, ensuring reliable insights for informed decision-making. Follow this step-by-step guide to improve data quality and save time with this innovative approach.
Tag: machine learning
How to Create Alerts for Adobe Analytics Using R and Slack
Intelligent alerting has been one of the most popular features of Adobe Analytics since its release years ago. It’s impossible to keep an eye on your data 24/7, and alerts are an excellent way to prevent missing out on important trends in your metrics over time. And while there are lots of amazing things you […]
Attribution Theory: The Two Best Models for Algorithmic Marketing Attribution – Implemented in Apache Spark and R
Follow @trevorwithdata 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 […]
Propensity Scoring in Adobe Analytics Using Data Feeds and R
Follow @trevorwithdata 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 @trevorwithdata 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 […]
Clustering Your Customers Using Adobe Analytics Data Feeds and R
Follow @trevorwithdata 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.” […]
Visitor Level Aggregations Using R and Adobe Analytics Data Feeds
Follow @trevorwithdata 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 […]