A customer portfolio model based on multi-phase marketing strategy and particle swarm optimization

The rational enterprise decision makers tradeoff between returns and risks. Customer portfolio paradigm is a favorable tools to increase the value of customer base and reduce its risks. After analyzing the similarities and differences of the financial assets and customer equity, a customer portfolio optimization model is proposed. In this model, semi-variance is employed as the risk metrics considering the risk characteristics of the customer equity; multi-phase marketing strategy is its output because of the liquidity characteristics of the customer equity. A particle swarm optimization algorithm is proposed to find the solution for the NP-hard computational feature of customer portfolio model. The empirical tests from a futures company show that, given the company´s risk tolerance, a multi-phase acquisition and retention strategy can be found to maximize the long term revenue of the customer equity with this model and its PSO algorithm.