Purpose The main purpose of this research is to allocate marketing budgets in complex environments, where data is scarce and management judgment is available. In this research, marketing budgets are allocated, in order to maximize customer equity as a long-term profitability measure. Design/methodology/approach The researchers provide a model for allocation of marketing budgets based on both decision calculus and econometric models and combine it with the concept of Markov chain model to cope with data scarcity. Dynamic programming is used to find the optimal solution. Findings We examine the model in telecommunication industry. Applicability of the model is supported by an illustrative example. To allocate marketing budgets researchers consider three strategies for each period: do nothing, retention-focused strategy, and acquisition-focused strategy. The results show the applicability and effectiveness of the model to find the best strategy. Research limitations/implications Since the suggested approach is based on management judgment, then it is useful in situations we have experts or experienced managers to achieve reliable data. In situations which we don’t have access to experienced managers the results may be unreliable. Practical implications The suggested approach is useful in situations of data scarcity, where experienced managers are accessible. The researchers have focused on telecommunication industry cases; however, the model is useful in other industries like the insurance industry. Originality/value The main contribution of the research lies in the suggestion of a new approach to allocate marketing budgets in data scarcity situations in multi-period planning horizons. The researchers use both decision calculus and econometric tools to find the transition matrices of marketing plans.

Keywords