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)?
A post to clarify a common misunderstood problem when setting permissions to enable the linking of your Google Analytics account with your AdWords account.
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.
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?
As you can see in Figure 2, we are not tweaking the edges here!
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…
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?
Let me explain the story…
A global white-goods brand, lets call them GlobalBrandlux.com, sent me a survey asking what I thought about my recent website experience. Here’s my response – I wanted to be honest and constructive:
Online privacy is a complex subject. Hence I use this slide to neatly sum up the issue by analogy. Essentially, to illustrate the different levels of privacy I use the scenario of an organisation wishing to understand the impact of traffic on their community.
When speaking at events I am sometimes accused (light heartedly) of drinking too much of the Google Koolade – meaning I endorse the good parts and skip/skim the pitfalls. However this post is a criticism of Google for what I consider to be a flawed thinking with their recently announced support of multiple currencies in Google Analytics.
SEO is getting harder! If you are active with search engine optimisation (SEO), then you will be aware of the issue of not provided showing in your Google Analytics reports for organic visits. This post updates the situation plotting the growing impact over time and the differentiation of tech-savvy versus tech-savvy web users.