Case Study: Forecasting Subscriber
A major mobile phone service provider was anxious
to move from reacting to sudden spikes in customer
attrition to managing customer attrition proactively.
Data Miners developed a churn forecasting system
that predicts the number of active subscribers
there will be on a daily basis for a year or
more into the future. Unlike aggregate level
forecasts based on historic churn rates, the
system developed by Data Miners uses the specific
attributes of each customer segments (or even
individual customers) to calculate survival curves.
Many variables affect the expected lifetime of
a customer: credit class, rate plan, acquisition
channel, calling behavior, payment behavior,
to name a few. At any given time, the active
subscriber base contains a mix of customers with
different values for these explanatory variables.
Our forecast takes all these factors into account
along with the characteristics of newly acquired
customers and the expected characteristics of
planned future additions to the customer base.
One consequence is that the forecasting tool
is also useful for "what if" analysis.
Managers can use the tool to forecast the future
effects of alternate customer acquisition strategies
that might be adopted.
The chart shows the survival curves associated
with customers from four different acquisition
channels. All the curves show an acceleration
in cancellations at a tenure of one year when
subscribers typically come off contract. The
effect is much stronger in the red line that
represents customers acquired through independent
dealers. Hence, the company could reduce "anniversary
churn" by reducing its reliance on this
Since building our first survival-based forecast
for this mobile phone service provider, we have
built several more for telephone companies, internet
service providers, newspapers, and other subscription-based