Understanding the ROI across all of your paid marketing channels is a top priority for senior-level executives across every industry and every geographical market. Getting a clear sense of the ROI on each channel allows companies to answer really important questions. For example: What will happen if I increase my Email spend by 20%? What […]
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 […]
Using Adobe Analytics Data Feeds and SQL for Basic Reporting
Three DB SQL’s walk into a NOSQL bar. A little while later… they all walked out, because they couldn’t find a TABLE… Joking aside, online marketers frequently use analytics tools like Adobe Analytics, but find that the granularity and accessibility of the data in the tool doesn’t meet their needs. A few examples: Loading Adobe Analytics […]
Parsing Products and Events in ClickStream Data Feeds
A lot of companies that I’ve worked with are initially confused when processing Adobe Analytics Data Feeds. The data comes out of Adobe Analytics in TSV format and you’d naturally expect that the data is ‘flat’ (meaning just rows and columns). Unfortunately, this isn’t the case. Columns like ‘post_product_list’ and ‘event_list’ are lists of data that […]
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 […]
Dealing with Special Characters When Parsing Adobe Analytics Data Feeds
Adobe Clickstream Data Feeds are the most granular way to view your analytics data. They effectively contain all the information that Adobe Analytics needs to build its reports. Having a good understanding of how to use these feeds will allow you to use Analytics data in ways that aren’t possible through LiveStream, the Web Services […]
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 […]
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.” […]
Use R to Statistically Pick Your March Madness Bracket!
Follow @trevorwithdata March Madness is upon us! I’ve been using statistical models to predict my March Madness bracket for about 6 years (sometimes fairly successfully), and this year I’ve decided to post the statistical tool online for anyone to use for any last minute bracket adjustments. Click here for the full screen version. Here’s how […]
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 […]