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: adobe analytics
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 […]
Customer Journey Analytics and R: How to Escape SQL Hell With cjar
In my last post, I illustrated how to use R with the Adobe Experience Platform (AEP) Query Service to query your raw data with analysis-supercharging tools like dbplyr without having to know any SQL. While I’m a big fanboy of R and dbplyr, if I’m honest, there are some things that SQL and dbplyr just […]
Visualizing the Customer Journey with R and Adobe Analytics Data Feeds
Follow @trevorwithdata 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 […]
How to Setup a Data Lake and Start Making SQL Queries with Adobe Analytics, AWS S3, and Athena
Follow @BikerJaredThe phrase “big data” is used so often it’s almost trite. These days, nearly all large enterprises have established a data science or data integration practice that is used for analysis projects. In my experience, however, many smaller companies (or often smaller teams within large enterprises) have yet to adopt any sort of big data […]
Build Your Own Cross-Device Marketing Attribution with Apache Spark and R
Follow @trevorwithdata 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 @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 […]
Importing Statistical Models from R into Adobe Analytics Using Customer Attributes
Follow @trevorwithdata 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 […]