  Customer retention or churn prevention is a challenging task of a telecom
operator. One of the effective approaches is to offer some attractive incentive
or additional services or money to the subscribers for keeping them engaged and
make sure they stay in the operator's network for longer time. Often, operators
allocate certain amount of monetary budget to carry out the offer campaign. The
difficult part of this campaign is the selection of a set of customers from a
large subscriber-base and deciding the amount that should be offered to an
individual so that operator's objective is achieved. There may be multiple
objectives (e.g., maximizing revenue, minimizing number of churns) for
selection of subscriber and selection of an offer to the selected subscriber.
Apart from monetary benefit, offers may include additional data, SMS, hots-spot
tethering, and many more. This problem is known as offer optimization. In this
paper, we propose a novel combinatorial algorithm for solving offer
optimization under heterogeneous offers by maximizing expected revenue under
the scenario of subscriber churn, which is, in general, seen in telecom domain.
The proposed algorithm is efficient and accurate even for a very large
subscriber-base.
