I have spent the last few weeks helping my partners in Europe with a project involving one of the largest mobile operators where we are looking at how to improve the handset strategy.
This is another striking difference between Europe and the ME in how companies operate. In the ME people are used to pay fully for their mobile phones, in Europe handsets were subsidized almost from the beginning. That means that operators make a substantial investment (up to 100 euros) upfront to capture a new customer and expect to recover the cost of the handset over the next months. The whole thing has grown, just do the maths: 100 euros per subscriber times 10 million handsets per year (or 60 million if you look at the whole operation) and you are quickly talking serious money here.
As operators face an increasing pressure on voice tariffs they are starting to look more and more into content related services to provide an extra revenue. New services (games, music, video...) require handsets with more advanced capabilities that are, not surprisingly, more expensive. Mobile operators need to understand how these new features translate into additional revenue through the consumption of these content-rich services.
One way of doing this would be asking people what they want and why and then tailor the offer to meet their needs. The problem with this approach is that people are not good at forecasting their own consumption (that is why we spend so much effort designing pricing plans that will give the perception of low tariffs while protecting the revenue of the operator).
The way we prefer is to look at the actual data patterns. We have extracted a quite large sample of their historical usage data and we have crossed it with the information regarding the handset used. This involves processing a large volume de data on relatively sophisticated ways (at least for what consultants usually do).
In the past we used SAS for this but I have never been happy about that as the syntax is horrible, the licencing process totally unfriendly and there is a serious scarcity of qualified programmers. So this time I decided to give a go to some alternative software. So far we are using MySQL and R running of course on my Mac.
I will post a more detailed assessment once the project is over but so far I am quite happy.