We are reminded constantly that Web 2.0 is a “conversation” and that the difference with social media is that communication is two way. Yet it is still easy to fall into the trap of putting up communications (blog posts, tweets etc.) and thinking that is the end of it. Tracking and analytical tools can disrupt that thinking. After Damon Ellis kindly sent me his paper on using Google Analytics to inform develop of the Massey University APA interactive referencing tool, I looked at the Moodle statistics for our Whitireia NZ online resources and was able to present an eloquent argument to our team about the need for change – without writing a word. The data spoke very clearly for itself, challenging our ideas of what is useful to students.

It is interesting, then, to look at my Thinking about Ideas blog statistics. Who reads my words, and how do they find me? What are my readers interested in? Some data I have found:
• 407 people have viewed my blog (I wonder how many times that has been me?).
• My best ever day was 22 Sept with 48 views – which, coincidently (not really), happened to be the day that I posted on Facebook that I was starting a blog.
• Facebook and Twitter are major referrers to my blog (this is obviously where people find out that I’ve posted something).
• My posts are most viewed within a couple of days of being published.
• Earlier posts were mostly viewed ‘on site’, whereas views are now trending towards ‘syndicated views’ – I assume this means most of the people reading my blog now are following the blog rather than being first time visitors. This is reinforced by the fact that no new posts = no visits.
• The top post is my ‘starting ideas’ – it does seem that novelty creates interest, but the trick would be to maintain people’s interest over time.
• There is not a lot of commenting that goes on (yet).

What does this mean for me if I want to continue the blog? I think that I need to:
• Post regularly.
• Continue to advertise my blog posts in a range of different forums.
• Make personal suggestions to people I meet face to face (I know that has resulted in people ‘following’ me.

When it comes to looking at my Moodle statistics for 23 Things for Research, I get a pretty graph:
[Moodle usage graph

This makes it obvious that I have done most of this course during my employed work days, Mon-Wed (it’s been quiet, and I consider this to be relevant PD for employment as well) and it could show that I am good at working on my PhD on the other days… but it doesn’t really show that, just that I don’t go on 23 Things on those days. So this graph has no surprises for me, but does tell whoever else looks at it something about me. I think that is a relevant consideration – what can be discovered about oneself if there is someone who has the time and skills to analyse the data.