A Comparative Study of Deterministic and Stochastic Programming Approaches to Optimise Marketing Campaigns

• C. Bisset School of Industrial Engineering, North-West University, South Africa https://orcid.org/0000-0001-5296-5945
• M.F. Alberts School of Industrial Engineering, North-West University, South Africa https://orcid.org/0009-0000-0368-5082

DOI:

https://doi.org/10.7166/36-3-3327

Abstract

Many factors continually influence customer behavioural patterns, leading to complex and uncertain decision-making. Traditional deterministic approaches, while useful, do not account for uncertainty, potentially causing suboptimal decisions and reduced profitability. Retailers should adopt models that incorporate uncertainty while maximising profitability to address this. This paper proposes a two-stage stochastic programming model, referred to as a recourse model, to optimise a marketing campaign’s profitability while providing solutions that hedge against uncertainty. A deterministic counterpart is also proposed, based on two existing deterministic models from the literature. The main contribution of this study involves the formulation of the recourse model and the added value of a stochastic approach in handling uncertainty more effectively. The proposed recourse model opens up new frontiers for marketing campaign optimisation by incorporating demand uncertainty and providing decisions that hedge against uncertainty.