|A selection of homepage click analysis screenshots|
Most were link heavy, focusing on signposting content to the visitor, although 3 were text heavy with up to 400 words. Two included a gallery of images which change every few seconds.
Many usability and content management experts say the same:
- Steve Krug talks about satisficing behaviour - users choosing the first link they see that seems to have a reasonable chance of giving them what they want.
- Jared Spool talks about trigger words - the importance of learning what they are and getting them in the right locations.
- Jakob Nielsen has reported on numerous studies that highlight just how little website visitors read.
- Gerry McGovern talks about the importance of getting link and heading text right - succinct and meaningful and aligned to what the user wants to do.
In most cases, over 50% of visitors had clicked in under 10 seconds.
In all, over two thirds had left within 20 seconds.
|The vast majority of visitors have left within 30 seconds|
- The data analysed here has been collected over a range of time periods and had significantly different sample sizes - from 250 visits to 10 000.
- Where possible, the visits were filtered to include external or internal only audiences as appropriate, but in some cases the data is mixed. This is important because many key external audiences tend to visit the University's websites a small number of times, while internal audiences may well be frequent visitors.
- The data was collected using the Crazy Egg click analysis service which frustratingly changed the way they present time to click data about a year ago. This means I now only see the top 14 time intervals with all other clicks lumped into a category labelled 'other'. So sometimes there are gaps in the data. However, were the missing data present, it would only further accentuate the trends I've commented on.
- I've adopted the practice of cleansing the data, advocated by Jakob Nielsen, where I removed all excessively long periods of time to click. This is because the patterns would be skewed by visitors who haven't given the page their full attention - maybe it's their homepage on opening the browser, maybe they opened it in a background window or tab, or maybe they just wandered off to make a cup of coffee at that point. I looked at the number of words on the page, calculated how long it would take to read every one at 200 words per minute and then doubled this timeframe. Anything outside of this range I discarded.