Currently, Analytics is definitely a buzz word in the
industry. As per my experience, almost each and every company in the industry
are talking about this and trying to understand what it will do or what can be
done with the data they have or what we can do for servicing the customers. As
pointed in my last blog, there is like huge requirement of knowledge
professionals for getting the insights from the data. As pointed by industry
experts, statisticians, data mining experts and from my experience, I can
certainly say that it all starts with
through understanding of the business problem in hand to be able to ascertain a
possible solution for it using data.
An analyst should focus on through understanding of the
problem before he thinks about the possible approach and the applicable
technique/algorithm for the problem. Actually, understanding of problem is half
way through for the analyst to decide upon the methodology and technique to be
followed. In this blog, I thought of sharing couple of observations on the
importance and how the steps would really change with a small difference in the
problem.
For example, if the overall problem is to predict Churn for
a Post-paid or a Pre-paid telecom customer then how it can be solved or what
type of assumptions an analyst should consider before-hand to start attacking
the problem. This particular problem statement raises 2 important questions,
which will have the impact on the approach/methodology.
Question 1 – Is the problem at hand is to identify the Customer
who will not recharge on the date of recharge in case of pre-paid or who will
not pay the current bill in case of post-paid?
Question 2 – Is the problem at hand is to identify the
Customer at Risk irrespective of his/her recharge date of bill due date?
We first need to understand the meaning of Churn – obviously
if the customer stops using it then it is a first check-point and if he is not
using it continuously then definitely a Churn case. It is this statement, which
raises above 2 outlined questions for the problem statement.
Let me explain now in detail,
‘Question 1’ is basically prediction of the customers who
will not recharge or pay the bill on the respective date of recharge or bill
due-date. Here we try to look at the customers who would not re-charge or pay
the bill based upon the various factors like usage, demographics, VAS, customer
profile, etc.
‘Question 2’ is actually the first thing to identify than
the Question 1. Here we are trying to identify customers who are going to end
the usage or who are going to get out of the system in the next month/next
quarter irrespective of his/her recharge date or bill due-date in the current
month. The approach/methodology to be followed for this problem will change as
compared to the above problem but the underlying data/factors remain same.
Both of them are really trying to solve the problem of Churn
but the way it is dealt in case of Question 1 and the way in case of Question 2
will definitely change. Question 2 is more like trying to predict the customers
who will not use his mobile but he will still be the customer of the service
provider but whereas Question 1 is trying to predict, who will not re-charge or
not pay the bill on the due-date.
It is a known fact in the telecom industry that, even if the
customer recharges or pay the bills on the due-date without being using the
services then he is treated as not a “good” customer. Revenues for telecom service
provider is a direct function of the usage and the company is really profitable
only if the customer recharges it continuously and uses it as well.
With the stiff competition in the market and with the Portability
in place, service providers are actually looking to solve the above 2 problems using
the Historical data combined with Data Mining Techniques.
To reiterate the point again that, it is the thorough
understanding of the business problem would lead the analyst for the right
approach/methodology to be followed for solving it.
Next question is having identified the customers at Risk,
what package or offer to be given to retain them?
