Abstract
Customer Equity (CE) is an important concept for marketers in managing
their customers. It allows them to better evaluate the contribution of existing
customers and the potential purchases of new customers to their overall
value. Such valuation provides better segmentation schemes that eventually
lead to better financial performance. Various models in the literature aim at
modeling CE with different structural forms and assumptions but most
commonly are based on evaluating the value of current, active customers.
This paper introduces a different approach for evaluating CE that consider
current and future (potential) customers by developing a two-stage model
that is based on stochastic and actuarial calculations. In the first stage, we
consider the value of current customers and relate it to their remaining
potential consumption lifetime. In the second stage, we use stochastic arrival
and departure processes to account for potential new customers using
stochastic calculations of remaining purchasing lifetime. As a result, the
model can better predict current and future value of customers compared
with current approaches.
their customers. It allows them to better evaluate the contribution of existing
customers and the potential purchases of new customers to their overall
value. Such valuation provides better segmentation schemes that eventually
lead to better financial performance. Various models in the literature aim at
modeling CE with different structural forms and assumptions but most
commonly are based on evaluating the value of current, active customers.
This paper introduces a different approach for evaluating CE that consider
current and future (potential) customers by developing a two-stage model
that is based on stochastic and actuarial calculations. In the first stage, we
consider the value of current customers and relate it to their remaining
potential consumption lifetime. In the second stage, we use stochastic arrival
and departure processes to account for potential new customers using
stochastic calculations of remaining purchasing lifetime. As a result, the
model can better predict current and future value of customers compared
with current approaches.
Original language | English GB |
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Pages (from-to) | 167-182 |
Journal | Journal of Business and Management |
Volume | 13 |
Issue number | 2 |
State | Published - 2007 |