Noise or Music? - The Insights Blog

Here I write about Google Analytics setup and usage; Online privacy; Data accuracy; Website usability; Conversion optimisation; and best practices for organisations wishing to achieve success online – the whole raison d’etre for measurement in the first place…!

I love to hear reader’s feedback, so please comment on my posts or share them.

Brian Clifton - Blog

New book: Successful Analytics

February 8, 2015 / Categories: Google Analytics specific, Metrics understanding / Comments: 4

  If you follow my tweets/posts/blog you know I have been writing my latest book these past 12 months. Happily that process is complete and the new book is launched – Successful Analytics: Gain Business Insights by Managing Google Analytics (both print and ebook versions). Note, if you have read my previous book series, this is […]

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Not Provided: Now impacting 80-90% of organic traffic

June 25, 2014 / Categories: Metrics understanding / Comments: 0

I have tracked this issue since the beginning – plotting the percentage of organic traffic impacted by not provided. First, only visitors logged into their Google account were effected and hence tech related websites (attracting a more tech savvy audience) were disproportionately impacted. However, Google has since applied this to pretty much all visitors using Google organic search.

The position now: Not provided impacts 80-90% of organic searches…

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10 Micro Goals for Tracking Content Engagement

March 20, 2014 / Categories: Metrics understanding / Comments: 0

Assuming you have no other “macro” drivers on your site – for example, no e-commerce facility, lead generation request from, store finder information, or advertisement click-throughs – how can you measure content engagement?

Here is my list of 10 tangible goals:

1. Show a snippet/summary first and then require a click to expand for more information
2. Use ratings e.g. rate this page/article, did this answer you question (y/n)?

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Google Content Experiments – A good or bad feature?

September 24, 2013 / Categories: Google Analytics specific, Metrics understanding / Comments: 10

Quote: [Google Analytics] “Content Experiments sucks and I will never use it for any of my clients….run away

The above snippet came from a post by Michael Whitaker (smart thinker, worth following) who asked for feedback on comments made at the Imagine 2013 conference earlier this year. My initial response was “hmmm – poor comments indeed. Whether you like a G product or not, to say that Google’s stats methods are unreliable, or reporting doesn’t work really is silly and lacks credibility.”

I am actually no big fan of the Google Analytics Content Experiments either, but I wish to put my views into context based on the following simple A/B test.

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Calculating your REAL ROI for AdWords

August 20, 2013 / Categories: Google Analytics specific, Metrics understanding / Comments: 2

Here’s the problem… The default Return on Investment (ROI) displayed by Google Analytics is misleading for two reasons.

Issue 1: Google Analytics combines revenue form your transactions and goals. That can lead to double counting, if for example, an add-to-cart click is a monetised goal.
Issue 2: Google Analytics has no idea about what profit margins you operate under – how can it? Google therefore has to assume that *ALL* revenue generated by your visitors is 100% profit.

In this post I show you how to avoid these issues and calculate your AdWords REAL ROI. Its purpose is to take you to the next level – allowing you to move beyond adjusting bids simply based on conversions. Instead, you can go after the “highest” value converters.

Figure 2 – How big a difference is the default ROI versus the REAL ROI?
real-roi-chart
As you can see in Figure 2, we are not tweaking the edges here!

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Multi-Channel Attribution Modelling – don’t write off the default models

August 15, 2013 / Categories: Google Analytics specific, Metrics understanding / Comments: 1

 

Avinash Kaushik is a great measurement thought provoker (up there with the likes of Tufte imho), all-round nice guy and friend of mine. I always come away from his posts challenged and simulated – quite a feat to achieve for your peers in a niche industry. The following post from him – Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models – is a great reference read, though I disagree on a couple of items. Once you have digested Avinash’s thoughts, here is my input…

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Why the Guardian is barking up the wrong tree with Prism

June 28, 2013 / Categories: Privacy and Accuracy / Comments: 3

My thoughts on why the Guardian and the Washington Post are barking up the wrong tree with their constant side-stories. It is disappointing to read the story degrading in this way.

“Analysing this type of meta-data is exactly what companies such as Google, Yahoo, Twitter, Facebook etc. openly do.”

Seriously… what is the problem with collecting and analysing meta-data?

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