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Multiperiod Multiproduct Advertising Budgeting: Stochastic Optimization Modeling

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  • Beltran-Royo, C.
  • Escudero, L.F.
  • Zhang, H.

Abstract

We propose a stochastic optimization model for the Multiperiod Multiproduct Advertising Budgeting problem, so that the expected profit of the advertising investment is maximized. The proposed model is a convex optimization problem that can readily be solved by plain use of standard optimization software. It has been tested in a case study derived from a real advertising campaign. In the case study, the expected profit of the stochastic approach has been favorably compared with the expected profit of the deterministic approach. This provides a quantitative argument in favor of the stochastic approach for managerial decision making in a data-driven framework.

Suggested Citation

  • Beltran-Royo, C. & Escudero, L.F. & Zhang, H., 2016. "Multiperiod Multiproduct Advertising Budgeting: Stochastic Optimization Modeling," Omega, Elsevier, vol. 59(PA), pages 26-39.
    • Handle: RePEc:eee:jomega:v:59:y:2016:i:pa:p:26-39
    DOI: 10.1016/j.omega.2015.02.013
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    References listed on IDEAS

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