Web Analytics in Europe, Part VII (Interview with Sean Burton, Foviance)

Interview with Sean Burton, Senior Consultant, Foviance.

How do you think the market for web analytics in Europe differs from the rest of the world?

We are a UK based company, and as such our client base is predominantly in the UK (although we do have clients in other countries), so my take on the differences between Europe and the rest of the world, is therefore obviously UK centric. This said, the UK Web Analytics market is still quite technical nature, although this is rapidly switching to more marketing focused activities.

Is web analytics adoption more widespread in some European nations than others?

I’m obviously more familiar with the UK market, in which Web Analytics is well established. From my perspective France also seems a key market.

What is the number one challenge for web analytics in Europe 2007?

There are various challenges within Web Analytics at the moment, but the key challenges broadly fall into either technical or education. There are technical considerations for new technologies such as AJAX, but most of these have been now been overcome. From a technical standpoint, we are seeing an increasing need for integration with other systems, which are often propriety to the client. This is obviously a challenge, and we are seeing an increasing trend within Europe towards adoption of open standards to ensure interoperability. The second category relates to education and training. Currently Web Analytics can be quite technically complex especially when combined with other data sources. The key questions tend to be why is metric X different to metric Y, which has be derived from a different source. I think we will see Web Analytics move away from traffic analysis to a more more targeted behavioural analysis, which are two very different things. The Web Analytics market at the moment is trying to services the needs of an increasingly polarised market. On the one hand, we have the technical audience, and on the other we have a marketing audience. Both groups have been brought closer together in recent years, which has led to tools trying to answer question from both groups - often leading to confusion or over simplification. The UK is still heavier invested in out-sourced ASP based solutions, although, as with the US, there appears to be a move back to in-house solutions as the requirement for an integrated data centric approach increases.

In-house solutions are often considered to be the more scalable and future proof solution, but they require an internal resource to ensure that the tool is providing value. At the end of the day no piece of software can provide all the answers to all possible problems. This holds true of Web Analytics. To get the most out of Web Analytic data, time and resource must be spent to ensure that it is a true reflection. Web Analytics is a complex area, and although tools are doing an extremely good job in reducing this complexity, the downside is that this simplification can easily result in mis-interpretation. For example, a common metric is ‘Average number of Pages per Visit’. On the face of it, this is very simple, but there are various kinds of average, the most common of which is the ‘Mean’ (cumulative total divided by the number of items). So, the ‘Average number of Pages per Visit’ is calculated as ‘Total Page Impressions / Total number of Visits’ - straight forward enough, until you consider automated traffic which can dramatically inflate the total number of Page Impressions, and thus skew the ‘Average number of Pages per Visit’.

This is a very common query regarding Web Analytics, especially when moving from one tool to another - how is automated traffic excluded?

There has also been quite a lot of press coverage regarding Cookie churn, but that’s another story! In general, I think we will see a continuing trend to ‘in-house’ solutions - following the US trend - with an increasing focus on integrating data from various sources to provide a centralised, behavioural analytics based, profile including data from the web, call centre, survey, e-commerce platform, etc.

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