Web Analytics Primer from an "Evangelist"
This is a great new article by Avinash Kaushik, the “Analytics Evangelist” for Google. I have posted a few other articles that touch on the topic of web analytics because I consider this a relatively untapped, but potentially rich source of information.
This is a very good primer for web analytics. Kaushik describes basic concepts in how website usage, or “visit” data, has utility. These concepts are fundamental, but certainly are still the most widely used in website analytics.
The applications for analysis for the six basic measures mentioned:
■ Visits
■ Page views
■ Pages/visit
■ Bounce rate
■ Average time on site
■ % new visits
These are universal in creating core metrics for a website—you need to have some place to start to know where you are going.
Basic ideas off the top of my head for these simple applications include:
1) Basic web stats for an online donations page—what is the “close” rate of those who visit?
2) Tracking sourcing from online pages—what are the most effective and least effective “links” sending people to your online donations page?
3) Identifying other interest areas through usage stats—are there other surprising sources on your site that have generated strong interest? Special events, news, messages? Possible affinities or, at the very least, interests may lie undetected.
And this is just a start. Obviously, as you layer and link pages, data, etc., the specificity of the analysis can increase sharply. This is a basic start.
Try it out. Show a colleague—see if they are interested…
New to Web Analytics? Confused about Web Analytics? Think it is too hard? Scared of tools and consultants?
This post is for you, its goal: Web Analytics Demystified! Yeah!
Web Analytics is complex. That is what it is. Complex.
Get the nuance? Complex. Mysterious. Inviting. Come in. Sit down. See what’s there. No free rides. You’ll do your part, your efforts will have a rich payback.
Complex holds the promise that you’ll get it. Nay, you can get it. Come in, welcome.
Start with this post.
Labels: Analytics concepts, General Development and Metrics, online behavior
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