Robust Optimization for Maximizing Customer Equity under Uncertainty: The Impact of Discounts

The allocation of marketing budgets has always been one of the main issues in marketing as well as budgeting. In fact, executives are looking how to divide marketing budgets between customer acquisition and retention activities, such that the profit created by the customer is maximized. To do this, we require a mathematical modeling. Unfortunately, any model which is not consider uncertainty may arise questions in its applicability. Here, we have proposed a robust optimization model to cope with the uncertainty in the model parameters. This research tries to provide a rigor model in allocating customer relationship budgets to customer acquisition and retention activities, taking into account the uncertainty in the estimation of uncertain parameters, in order to maximize the customer equity. In fact, taking into account the conditions of the real world, which is unstable in practice, and due to uncertainty in the estimation of some parameters, a robust optimization approach is proposed. By using Malvey s scenario-based approach, the budget allocation model is presented. The comparison of the results obtained from the use of deterministic and robust models shows that the solution of the robust model remains stable in all examined conditions. Also, in the comparison of all the examined scenarios, the robust optimal solution is better than the deterministic optimal solution. The findings of this research can be used by organizations to increase long-term profits, increase the rate of customer acquisition and retention, target marketing programs and ultimately increase market share.