Bob Mitchell

bob-o-rama: The Art of Slack.

Axis change

Simple data visualisation

7th July 2008 - 8:50 - bob

There is a very simple trick that, while obvious once you know it is something that may not be obvious at first.

Many reports, not just from web analytics products look like this:

analytics axis change chart before - Click to enlarge.
Click to enlarge.

In this case we are looking at a 'Most Frequent Referrers' report, with a classic bar chart. Don't worry about the data (it happens to be from this site), what I want you to pay attention to is the chart and how pointless it is.

All it's telling us is that the most frequent referrer (the leftmost bar) is sending us most traffic (by definition (duh!)) and the second-most frequent referrer is sending us a bit less (and so on).

Whenever we see a chart like this we are looking at:

analytics axis change diagram before

...where the x-axis is showing 'rank' and thus volume and the y-axis is also showing volume (both 'Visits' in this case). With a little thought we will see that we are wasting an axis.

What we really ought to have is something more like:

analytics axis change diagram after

...where there is rank/volume on the x-axis and some form of 'quality' (not volume based) measurement on the y-axis.

In NetInsight we would use this button to change the dataset to be shown on the y-axis:

analytics axis change change axis

Here we are selecting the 'Bounce Rate' metric (the percentage of people that land on the site and only view one page - lower is usually better)

We then see:

analytics axis change chart after - Click to enlarge.
Click to enlarge.

Which is actually useful - we can instantly see the high volume referrers on the left, with not unreasonable bounce rates, but in ranks 3, 4 and 6 (wikipedia, iwantmymum and linusm) we see referrers that have even better (remember, lower is better) bounce rates.

If we start building the volume of traffic from these sources then we should hopefully see increasing volume while maintaining the higher quality.

This tactic should work with any volume-based x-axis such as Views, Visits or Visitors and any quality-based metric on the y-axis, bounce rate, conversion rate, average order value, cost per acquisition etc.

Know this is useful for someone, hope it's been useful for you.

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