We need to start having more meaningful dialogue about measurement

We need to start having more meaningful dialogue about measurement

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.

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Your Web Analytics Data is Lying to You, so Fix it Already

Your Web Analytics Data is Lying to You, so Fix it Already

Yesterday I took part in a webinar discussion with Experian’s Simon Trilsbach on the topic of data quality (DQ). It was a great session and we received some good questions after the presso about how to go about addressing DQ within your business. I wanted to extend the discussion I had with Simon by looking at a practical example of DQ that many marketers probably face without even realizing it. 

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Benchmarking in Google Analytics: Using Relative vs Absolute Comparisons of Data

Benchmarking in Google Analytics: Using Relative vs Absolute Comparisons of Data

I love Google Analytics. It's one of the first tools I ever used when starting out my career in digital analytics and it’s the one tool I continue to use today. It’s beautifully designed, intuitive, customizable and easy to traverse layers of complexity in your data. But, for all the wonderful things Google does with Analytics, they occasionally get a few things wrong

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Meaningful Interpretation of Data: The Good, the Bad and the Ugly

Meaningful Interpretation of Data: The Good, the Bad and the Ugly

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.

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