Product owners working on web projects need to understand about web analytics for two interlinked reasons.
First so that they can understand which parts of their site are most used, which are less used, which bring in most revenue, which cause confusion in users – and in what order users visit pages.
The second reason is so that they can specify what analytics are required for their own needs and for the needs of other people responsible for the site.
Avinash Kaushik’s brilliant Occam’s Razor blog delivers a fast and deep introduction to what’s what in analytics. Many of the best articles are a year or two old, but they bring wisdom and experience that is still very relevant.
Start with ‘Web Analytics 101: Definitions: Goals, Metrics, KPIs, Dimensions, Targets’ and have your analytics tool ready while you read so you can try out the ideas. Avinash recommends using the free Google Analytics tool. Or, if your organisation has already bought and configured a more costly and complex tool then you should stick with that.
By the time you’ve finished working through Avinash’s Web Analytics 101 you should feel that you have a good initial grip on how your tool works. Avinash recommends just getting stuck in and trying things out. After a little of that, you may feel that you have some understanding of what you can do with analytics.
Now is the time to read Avinash’s ‘Beginner’s Guide To Web Data Analysis: Ten Steps To Love & Success’, where he helps you to take a step back for a more strategic view of how well your site achieves what you want it to achieve. The ten steps are what Avinash might complete in a day’s analysis of a site. If you’re new to this, it’s likely to take you a week or more – so ask for help from a technical expert if you have access to one. The page is a couple of years old so some of the reference links are broken and you’ll need to search for the information referred to instead. It’s worth the effort because after you have completed these ten steps (and followed some new paths that your investigations will have lead you to) you will have a good knowledge of how to find out how your users are actually using your site.
By now, you will probably have insights about the usage of your site that no one else has – and almost certainly not your management. Such knowledge is very hard to communicate clearly – partly because we all have strong preconceptions about how a site is used, based mostly on our own limited use of it. Avinash’s ‘Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories’ explains how to create compelling and accessible arguments from analytics data. Be warned though that there’s no simple formula, and you will have to work your data hard and think carefully to ensure that you’re presenting a useful and truthful picture.
Bang up-to-date for 2013, Avinash has published his illuminating ‘10 Data Analysis Strategies That Pay Off Big!‘, giving you some straightforward techniques for unlocking the value in your analytics data.
To complete your introduction, read Avinash’s ‘Web Analytics Segmentation: Do Or Die, There Is No Try!’. ‘Segmentation’ refers to the way you split up analytics figures to give meaningful information. For example, looking at the total site visitor count for a month doesn’t really give you much actionable information. However, splitting that into subtotals according to the route the visitors took to get to your site or according to how long they spent on your site or according to how much money they spent – now that is information that can be used.