Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Valuing customer portfolios with endogenous mass-and-direct-marketing interventions using a Stochastic Dynamic Programming Decomposition
AU - Esteban-Bravo, Mercedes
AU - Vidal-Sanz, Jose M.
AU - Yildirim, Gokhan
PY - 2014
Y1 - 2014
N2 - The CRM allocation of marketing budget is potentially misleading when it uses individual CLV estimations from historical data. Planned marketing interventions would change the purchasing behavior of different customers and history- based decisions would thus be sub-optimal. To cope with this inherent endogeneity, we model the optimal allocation of the marketing mix by accounting simultaneously for mass interventions and direct marketing interventions on each customer. This is a large stochastic dynamic problem that, in general, is computationally rather intractable due to the “curse of dimensionality”. We present an algorithm to derive the optimal marketing policies (how the firm should allocate its marketing resources), and the expected present value of those decisions which maximize the long-term profitability of firms. This allows the firm to value customers/segments and helps the firm to target the customers/segments that maximize long-term profitability given the optimal marketing resources allocation. We apply the proposed approach in the context of a manufacturer of kitchen appliances. The results identify the most effective marketing policies and the endogenous customer values. It is in this context that we also dynamically identify the most-profitable customer and the short- and long-term effects of marketing activities on each customer.
AB - The CRM allocation of marketing budget is potentially misleading when it uses individual CLV estimations from historical data. Planned marketing interventions would change the purchasing behavior of different customers and history- based decisions would thus be sub-optimal. To cope with this inherent endogeneity, we model the optimal allocation of the marketing mix by accounting simultaneously for mass interventions and direct marketing interventions on each customer. This is a large stochastic dynamic problem that, in general, is computationally rather intractable due to the “curse of dimensionality”. We present an algorithm to derive the optimal marketing policies (how the firm should allocate its marketing resources), and the expected present value of those decisions which maximize the long-term profitability of firms. This allows the firm to value customers/segments and helps the firm to target the customers/segments that maximize long-term profitability given the optimal marketing resources allocation. We apply the proposed approach in the context of a manufacturer of kitchen appliances. The results identify the most effective marketing policies and the endogenous customer values. It is in this context that we also dynamically identify the most-profitable customer and the short- and long-term effects of marketing activities on each customer.
KW - CRM
KW - marketing resource allocation
KW - long-term effect of marketing activities
KW - stochastic dynamic programming
KW - dynamic panel-data models
U2 - 10.1287/mksc.2014.0848
DO - 10.1287/mksc.2014.0848
M3 - Journal article
VL - 33
SP - 621
EP - 640
JO - Marketing Science
JF - Marketing Science
SN - 0732-2399
IS - 5
ER -