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 @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 […]
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 @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.” […]
Use R to Statistically Pick Your March Madness Bracket!
Follow @TrevorHPaulsen 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 @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 […]
How to Setup Adobe Analytics Data Feeds
Follow @TrevorHPaulsen As of February 16 of this year, you can now setup and manage Adobe Analytics’ data feeds right in the UI. This is super helpful, because you no longer have to rely on Adobe Customer Care to help you set this up! If you don’t know what data feeds are, they’re basically the log […]
How to Setup sparklyr: An R Interface for Apache Spark
Follow @TrevorHPaulsen If you haven’t heard of Apache Spark yet, I’d be pretty surprised. It’s an amazing open source project that’s changing the way people think about processing big data. That said, in my opinion it has never been super accessible to those of us data enthusiasts who aren’t Java application engineers – that is until […]