TY - JOUR
T1 - Maximizing customers' lifetime value using limited marketing resources
AU - Marmol, Mage
AU - Goyal, Anita
AU - Copado-Mendez, Pedro Jesus
AU - Panadero, Javier
AU - Juan, Angel A.
N1 - Publisher Copyright:
© 2021, Emerald Publishing Limited.
PY - 2021/10/25
Y1 - 2021/10/25
N2 - Purpose: For any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), which are usually expensive. Design/methodology/approach: This paper proposes a formal model of the Customer Life Value problem inspired by the uncapacitated facility location problem. Findings: The computational experiments conducted by the authors illustrate the potential of the approach when compared with a standard (non-algorithm-supported) one. Originality/value: The approach leads up to the economic trade-off between the volume of the employed resources and the aggregated CLV, i.e. the higher the number of resources utilized, but also the higher the cost of achieving this level of lifetime value. Hence, the number of resources to be “activated” has to be decided, and the effect of each of these resources on each CLV will depend upon how “close” the resource is from the corresponding customer (i.e. how large will the impact of the active resource on the customer).
AB - Purpose: For any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), which are usually expensive. Design/methodology/approach: This paper proposes a formal model of the Customer Life Value problem inspired by the uncapacitated facility location problem. Findings: The computational experiments conducted by the authors illustrate the potential of the approach when compared with a standard (non-algorithm-supported) one. Originality/value: The approach leads up to the economic trade-off between the volume of the employed resources and the aggregated CLV, i.e. the higher the number of resources utilized, but also the higher the cost of achieving this level of lifetime value. Hence, the number of resources to be “activated” has to be decided, and the effect of each of these resources on each CLV will depend upon how “close” the resource is from the corresponding customer (i.e. how large will the impact of the active resource on the customer).
KW - Artificial intelligence
KW - Biased-randomized algorithms
KW - Customer lifetime
KW - Customer loyalty
KW - Marketing intelligence
UR - http://www.scopus.com/inward/record.url?scp=85112254603&partnerID=8YFLogxK
U2 - 10.1108/MIP-02-2021-0050
DO - 10.1108/MIP-02-2021-0050
M3 - Article
AN - SCOPUS:85112254603
SN - 0263-4503
VL - 39
SP - 1058
EP - 1072
JO - Marketing Intelligence and Planning
JF - Marketing Intelligence and Planning
IS - 8
ER -