Measuring Content Success with GTM

by on 6th April 2017

The questions that marketers know how to answer with Google Analytics are typically things it will tell you out of the box:

  • How many sessions were driven by the organic channel last month?
  • What are my top sources of referral traffic?
  • Which pages are doing well socially?

These are important questions which absolutely need to be answered. However, GA is also capable of answering more complex, behavioural questions; it can be invaluable tool in scenarios like these:

  • Newsletter sign-ups are an important step in my sales funnel – what pathways do people take to that goal?
  • My blog is central to my content strategy. Which authors and categories are collectively driving the most visits to my sales pages?
  • I value engagement – it correlates with higher lifetime value. How are the commenters on my blog behaving differently from other users?

The best way to get answers to questions like these is with a smart implementation of Google Tag Manager. By using GTM to deploy GA, and by coupling your reporting setup with a Data Layer, it becomes far easier to answer complex behavioural questions at short notice. It can also enable you to sidestep your congested development queue when you need to rollout changes to your reporting, allowing you to work more efficiently.

For more detail on this, take a look at the slides I presented at BrightonSEO earlier today. You can watch the livestream here, download the original slides here, or alternatively – if you prefer your slides butchered and pixelated – an embedded Slideshare is available below.

Any questions, you can reach me on Twitter @tomcbennet. Thanks for reading!


Google Analytics: A Guide for Beginners – Builtvisible
Getting Started with Content Grouping in Google Analytics – Builtvisible
The Data Layer – Simo Ahava
Developers Guide to the Data Layer – Google Developers
Understanding Scope in Google Analytics – LunaMetrics

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  1. This may be off-topic, but wanted to know if you guys track articles that are shared through any referring channels and able to follow one sharer to another, through all the downstream visits, even across social networks.
    Instead of just seeing that this article was shared 1k on FB and 200 on Twitter. You would see the tree structure of network diffusion of social content that are passed on from one sharer to another.

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