Prospective sales policies are one of the essential components of short- and medium-term planning in any business. The correct and accurate formulation of sales policies can play an effective role in managing cash flows and allocating resources. In general, the above statement indicates the fact that in today's competitive world, customer satisfaction and increased market share is vital, estimating the issues about customer buying behavior and decision making is the main theme of any organization that this can be improved by using advanced prospective analysis in the field of sales policy. The purpose of this study is to provide a model for customer clustering, extract the product portfolio of each cluster and allocate the appropriate sales policies for them. Finally, the results were confirmed by experts. Apart from current customers and with the entrance of new customers, using clustering algorithms, the appropriate policies for different categories of these customers are provided to improve their loyalties.

Keywords: Sales policy Making, Clustering, Product portfolio, Distribution Industry, Predictive Analytics.

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