Saturday, March 15, 2008

Exploring Web Analytics #1

Number of subscribers to Making A Mark - it's a long haul up that incline!

I confess - I actually LIKE looking at numbers. Which is why I'm surprised that I am only now sitting down to try and understand more about web analytics and, in particular Google Analytics.

As ever, for those of you who didn't click straight to another page at the sight of the word 'numbers', I'm going to record the journey and what I find out.

This seems to herald the return of the "Techie Saturday" posts. Three on the trot - is this a trend? ;)

Web analytics: Why I use statistics

Web analytics is the study of the behaviour of visitors to websites/blogs. I study my stats because I like to know:
  • how many people visit my blog and when - that helps me gear posts which are likely to be more popular to days on which I get lots of visitors. Do you you know the days on which you get the most and least visitors over time?
  • whether I can change the trend in visitor numbers. The answer is 'Yes' - I've done it deliberately a few times now which means that for the 'blockbuster' post it probably doesn't matter when I post.
  • what changes the trend in subscribers - like spending less time in forums and more time on developing my blog and understanding its audience!
  • which subjects are the most popular - which tells me whether I'm writing for a wide audience or a serious niche. That then influences how I write.
  • which keywords are the most popular - You'd never ever guess at least two of the terms which regularly turn up in the top spots. Well - a couple of my readers might - because my guess is that they experience the same phenomenon.
  • which sites send me the most visitors - I'm not sucking up to those sites - but I'm certainly not setting out to annoy them! Interestingly I find niche sites can generate big numbers whereas (some) big sites don't.
It's always fascinating to hear your stories about what happened to your statistics and blog after your blog or website got a mention on this blog. So far I've got lots of people who said their stats went through the roof and some people who've even sold work as a direct result!

Web analytics: Which statistics packages I use

I've tried out various statistics packages on this blog. I currently use
Web analytics: Why I want to know more

First, I only installed Google Analytics on this blog just over a month ago. I spent the first 48 hours after installation racing around the site - but, of course, it had negligible statistics so didn't have any 'interesting' reports. A month later I looked again - and it's a completely different story! Now I just have to try and find out what it all means!

Second, I'm currently developing publications and building a new website and which will draw on material on this blog and elsewhere. It's a major project so understanding more about the popularity or otherwise of topic areas enables me to direct my efforts in a logical way. I also need to decide which webware to use for my stats for that project.

Third - because I'm eternally curious and like to know more than I do right now!

Web analytics: What do all those terms mean?

So let's ease our way slowly into web analytics by starting off with the definitions of the technical terms used in web analytics. What follows is the Wikipedia definition as there isn't industry wide agreement about what the terms mean.

Note in particular the ones where it's easy to misunderstand what they mean. It's worth making an effort to know a bit more - otherwise you'll be confusing your reach with your bounces! ;)
Key definitions

There are no globally agreed definitions within web analytics as the industry bodies have been trying to agree definitions that are useful and definitive for some time. The main bodies who have had input in this area have been Jicwebs(Industry Committee for Web Standards)/ABCe (Auditing Bureau of Circulations electronic, UK and Europe), The WAA (Web Analytics Association, US) and to a lesser extent the IAB (Interactive Advertising Bureau). This does not prevent the following list from being a useful guide, suffering only slightly from ambiguity. Both the WAA and the ABCe provide more definitive lists for those who are declaring their statistics using the metrics defined by either.

  • Hit - A request for a file from the web server. Available only in log analysis. The number of hits received by a website is frequently cited to assert its popularity, but this number is extremely misleading and dramatically over-estimates popularity. A single web-page typically consists of multiple (often dozens) of discrete files, each of which is counted as a hit as the page is downloaded, so the number of hits is really an arbitrary number more reflective of the complexity of individual pages on the website than the website's actual popularity. The total number of visitors or page views provides a more realistic and accurate assessment of popularity.
  • Page View - A request for a file whose type is defined as a page in log analysis. An occurrence of the script being run in page tagging. In log analysis, a single page view may generate multiple hits as all the resources required to view the page (images, .js and .css files) are also requested from the web server.
  • Visit / Session - A series of requests from the same uniquely identified client with a set timeout. A visit is expected to contain multiple hits (in log analysis) and page views.
  • First Visit / First Session - A visit from a visitor who has not made any previous visits.
  • Visitor / Unique Visitor / Unique User - The uniquely identified client generating requests on the web server (log analysis) or viewing pages (page tagging) within a defined time period (i.e. day, week or month). A Unique Visitor counts once within the timescale. A visitor can make multiple visits. The Unique User is now the only mandatory metric for an ABCe audit [[3]].
  • Repeat Visitor - A visitor that has made at least one previous visit. The period between the last and current visit is called visitor recency and is measured in days.
  • New Visitor - A visitor that has not made any previous visits. This definition creates a certain amount of confusion (see common confusions below), and is sometimes substituted with analysis of first visits.
  • Impression - An impression is each time an advertisement loads on a user's screen. Anytime you see a banner, that is an impression.
  • Singletons - The number of visits where only a single page is viewed. While not a useful metric in and of itself the number of singletons is indicative of various forms of "Click Fraud" as well as being used to calculate bounce rate and in some cases to identify automatons ("bots").
  • Bounce Rate / % Exit - The percentage of visits where the visitor enters and exits at the same page without visiting any other pages on the site in between.
  • Visibility time - The time a single page (or a blog, Ad Banner...) is viewed.
Wikipedia - Web Analytics - Key Definitions
The advertising industry seem to have a very specific set of terms
The Express Guide to the Industry Agreed Metrics:
  1. How many - the 'audience reach' metric = Unique Users
  2. How busy - the 'volume' metric = Page Impressions
  3. How often - the 'frequency' metric = Visits
  4. What see - the 'opportunity to see' metric = Ad Impressions
  5. What do - the 'response' metric = Ad Clicks
What I'm now looking for are some perspectives on this topic. I aim to I link in future posts to places where you can read more about different aspects of web analytics.

So who out there is already a Google Analytic Techie - and have you written any useful posts on this topic?