What happened to the Google Analytics benchmarking reports? In this article we look at this legacy report from UA and explore whether this data will come to GA4.

This is a repost of an article originally written and published by Peter Borden, and which was published on the blog of the now defunct social analytics company, SumAll. I came across this article back when Peter wrote it in 2014, and I found it to be an absolutely essential part of the discourse in the A/B testing industry. And so I wanted to re-publish the original article, since the original link is now dead, to help preserve its educational value for anyone interested in learning about A/B testing.

In my latest post I look at a recent article published on LinkedIn that claimed to have found the secret sauce for understanding how content goes viral on LinkedIn. The article featured some rather questionable math, and in this post I break down exactly what went wrong and why.

Over the weekend a friend and former colleague of mine tagged me in a LinkedIn post titled 5 bullshit metrics you need to stop using to measure content marketing success. In it, the author details 5 digital metrics he thinks content marketing folks need to chuck out the window. Here's my response.

We rely on data analytics software and tools to answer key business questions. But sometimes, those tools can lie. In this post I like at examples of how some reports in Google Analytics can be misleading.

As someone who works in the private sector, or more specifically, in marketing, I’ve seen data applied in some pretty manipulative ways to make a point or validate an untested hypothesis. if you're working in the field of marketing analytics and you care about being truthful you'll always struggle to find the right balance between time, cost and rigour. But not everyone understands the importance of rigour when it comes to truthful interpretation of data, and worse, some don’t care.

The objectives and needs of your measurement practice are unique, complex, and vary not only on your business context, but the personnel within your organization that use your marketing data to make decisions. So why do we measure? This is the first of two articles where I explore why we  invest time, money and resources into measuring marketing performance.