Any keen observer of this blog may have noticed that I’ve been spending a lot of time on creative applications of R towards web analytics. While each individual application of R is interesting in itself, what I’ll present in this post is a vision for how integrating R into an analytics team can fundamentally alter how analysts work individually and collectively through code. This is a first step towards developing a set of broadly applicable principles and best practices I’m calling MeasureOps (akin to DevOps and DataOps.)Read More
When I send out weekly performance summaries to my clients, I often focus on just a few key take-aways and insights. For instance:
Campaign A is providing leads at $5/lead while Campaign B is converting at $15/lead. I’ve shifted most of the budget from Campaign B to Campaign A, but started an A/B test on Campaign B’s landing page to see if its performance can be improved.
These reports focus on what happened and what is about to happen. What’s missing in these emails, and discussions around measurement in general, is what didn’t happen. In other words, what mistakes did we avoid because we had data pointing us in another direction? Read More