In this age of ubiquitous connectivity there is very little we do which isn’t tracked and stored in some form or another be it active (something we request) or passive (something which is happens automatically behind the scenes). This data is used for a variety of reasons; for marketing, personalisation, recommendation, law enforcement, research, capacity planning, trend analysis, performance enhancement… – the list is almost endless. It spans both our online and offline lives, whether we like it or not, and is becoming evermore sophisticated in its reach and depth.

Being a bit of an analytics junkie I decided to take a look at what all my favourite applications/services offer by way of being able to visualise some of this data –

WordPress Blog Stats Graph

WordPress blog stats for randomwire.com showing slow but steady traffic increase month-on-month (actual numbers obfuscated). The two mini traffic spikes were caused by exceptionally popular posts (1 / 2).

WordPress Akismet Spam Stats Graph

WordPress comment spam being tracked and auto-deleted by Akismet. Spikes show a targeted attack/flood. 40,683 spams caught and an overall accuracy rate of 99.855%. Petty impressive.

Feedburner RSS Feed Stats Graph

Feedburner RSS stats showing the number of subscribers and reach of the syndication feed (actual numbers removed). Because of the way feeds are ingested and used these stats should only be taken as a guideline at best.

Flickr Stats Graph

Flickr photo view stats tracking 3,404 items / 13,251 views to date. Difficult to infer anything here but generally I’ve noticed the more metadata you add (especially titles) the more hits you can expect.

Google Reader Trends Graph

Google Reader trends – “From your 86 subscriptions, over the last 30 days you read 4,858 items, starred 15 items, shared 16 items and emailed 2 items.” Saturday – Monday clearly slow news days in the blogosphere.

FriendFeed Stats Pie Charts

FriendFeed activity stats showing a breakdown of top sites from the past 30 days of online activity. Twitter dominant in this group at least but with the ability to re-share and re-tweet these stats may be incestuous.

Wakoopa Applications Stats Pie Chart

Wakoopa applications stats showing application usage over the past week equating to an average of 10 hours per day – I really must cut down! Interesting how I’m now using Google Chrome more than Firefox these days.

Google Analytics China Map Overlay

Google Analytics map overlay showing visitors to the blog from China – most were from Beijing or Shenzhen (where I live) clustered in the more developed east of the country. Unfortunately no readers in North Korea!

Last.fm Top Artists Stats

Last.fm top artists list artists by the number of times I’ve played their tracks since installing the “audioscrobbler” tracking application. If someone asks me what sort of music I like I just point them here.

Whilst this is all fairly rudimentary it provides some basic insight into some of the data we generate. Already many services provide semi-open interfaces to allow other applications to take data and create mashups and this is likely become more pervasive and easier to do. Personally I just like looking at pretty graphs!

Comments

  1. Rebecca says:

    Finally I think I understand this article means haha:p
    It really took time to read,haha

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