A measured approach

As has become traditional, I’m posting again in February after a long break in the second half of last year. Hopefully in 2015 I can break my bad habit and actually continue with regular blog content all the way through the year.

I’ve spent much of the last few months obsessing over stats and analytics from the Boroondara library websites, as I developed a brief for developers to help us with a major overhaul. The experience has reinforced the advice from Matthew Reidsma to regularly analyse the way people use your website, and test and make changes immediately and incrementally. A lot of the recommendations I’ve made at Boroondara are as much about the way we produce website content as they are about the design of the sites. For example, I’ve discovered that visitors using mobile devices are most likely to visit on weekends, whilst visitors on desktop are most likely to visit on Monday and least likely to visit on Sunday. Do we need to change our posting schedules? Does this difference reflect different users or just the same visitors using different devices across the week? These are questions we would not have even thought to ask until we saw the data - and this is just one simple example. Something more intriguing (and hindsight obvious) was my discovery that visitors to our Storytimes page were more than 50% more likely to come from mobiles (about 46% compared to 30% for visits to all pages). It’s pretty easy to construct a story of busy parents checking their phone from the local park to check if the library has a storytime today - but we hadn’t really considered this behaviour until now (and of course, there could be any number of alternative explanations for why there is this difference).

What became quite clear is that we should have been doing more than simply look at total hits and visits each month and really looked deeply into our analytics on both our catalogue and our general website. I won’t be doing this at Boroondara, because I finished up there last week, but if anyone at Brimbank Libraries is reading this - be prepared to become obsessed with user tracking and analytics!

Coincidentally, I recently read John O’Nolan’s post about onboarding stats at Ghost. I’ve read lots of stuff from UX experts and library website experts emphasising the usefulness of things like A/B testing and ongoing analysis of usage data, but until now I’ve never fully appreciated what they’re saying. Perhaps it’s because the Ghost Foundation is a non-profit, but I found O’Nolan’s post helped me to see how we can (carefully) use usage data to help library members get more from us. That is, libraries have the ability to actually use analytics to ‘improve the user experience’. Using data to manipulate users to act against their own best interests, as too many commercial services seem to do, isn’t the only possibility.

A couple of simple examples

Email notices

Pretty much every library sends notifications to members in one form or another. Mostly these are emails. Whilst I am stunned by the fact that several major library management systems are still only capable of sending plaintext emails and not HMTL formatted emails, at this point I am going to assume you are sending HTML formatted email notices.

Ever wondered whether the wording of your notices is effective? Perhaps if you used a different subject heading or made your email text more friendly members would have less overdue loans. Wouldn’t it be great to test your theory scientifically? A/B testing is the way to do this. Web companies do this all the time. True A/B testing is random - on a given day a website might randomly show different users different configurations on the front page, for example. They can then test which configuration (‘configuration A’ or ‘configuration B’) resulted in more sales, or newsletter sign-ups, or whatever.

It all sounds very hard and complicated, but you can fairly easily use an analytics program like Piwik to create ‘campaigns’ and associated tracking codes. All this does is add some extra code to the URLs you use, which is identified by your analytics system when visitors use a URL with that code. You could use campaign tracking codes by sending out two batches of email notices (perhaps on two consecutive Tuesdays, for example) with a link to ‘click here to renew these items’. By comparing the number of hits on your login page from that tracking code to the number of notices sent out using it, you can measure the effectiveness of different types of approaches to subject headings, wording and layout.

What do mobile visitors want to do?

An even simpler example comes from some of the analysis I’ve recently been doing. I had a feeling that visitors on mobile devices might show different browsing behaviour to those on desktops, but I didn’t really know. Because browsers tend to broad