With the telecommunications industry analytics is about understanding the customer, and telcos have richer data than just about any other company when it comes to customer behaviour. The following are just some of the types of analysis that modern telcos should be performing on a regular basis.

Segmentation. The most fundamental activity for telcos is segmenting the customer base into groups that can be treated similarly, and can be reported on in terms of growth and ARPU. There are many ways that customers can be grouped, and often multiple segmentations make sense for different purposes. Value is one of the most obvious of these, since it makes sense to know your best customers. However "value" can go beyond simple annual revenue, and should be based on lifetime value, which takes into account probablity of churn, and cost to serve. Understanding the customer life-cycle is important to controlling churn; warning signs can be identified and appropriate action taken in time. For example, how often do customers change plans, and how do their usage patterns transition?

Behaviour is another good way to segment customers, and this can include simple things like call frequency, local/international ratios, data usage, etc. It can also be more advanced, and incorporate link analysis, call circles, etc. Identifying customers who are "communication hubs", or early adopters in their personal network can enable very targeted marketing.

Marketing is the lifeblood of a telco, and there are many aspects to this. The most basic building block of an analytical approach to campaigns is the propensity model, estimating the individual likelihood of customer response. Just as important is tracking the success of past campaigns, to gradually improve the methodology, which involves carefully designed control groups.

In addition to propensity, contact rules should be implemented to ensure that the best customers aren't spammed constantly, and the next tier down ignored. A proper campaign management tool makes this much easier to manage. The next step for advanced companies is marketing optimization. This is a way of combining all the propensity scores and contact rules, along with other constraints such as channel limits, budgets, targets, etc, into a mathematical model that optimally assigns customers to campaigns over a planning horizon. It is quite dramatic how much improvement can be made over what seem like smart manual strategies. There are just too many factors involved for humans to pick the best combinations.

Beyond even optimization is real-time. The most advanced telcos are starting to implement models that update instantly with every customer interaction, and can highlight to a customer service representative, or on the internet, an appropriate offer tailored to that customer at that time. This can prevent churn (when desired - some customers cost more than they are worth), and increase up-sell, cross-sell, and customer satisfaction dramtically.