USING RFM DATA TO OPTIMIZE DIRECT MARKETING CAMPAIGNS: A LINEAR PROGRAMMING APPROACH

The direct marketing framework that incorporates the recency, frequency, and monetary value (RFM) of customers' previous purchases is a useful analytical tool for companies that want to fine-tune their market segmentation strategies, design more effective database programs, improve customer relationship management, and allocate marketing resources more efficiently. The current research offers an optimization model that helps determine whether a company should continue or curtail its marketing spending on select customer segments given various budget constraints. The proposed linear programming model identifies the customer segments (based on RFM profile) that should be targeted in order to maximize profitability. At the same time, the method helps identify those RFM segments which are not worthy of pursuing either due to unprofitability or due to an insufficient campaign budget. The model is illustrated with a numerical example. Keywords: RFM; direct marketing; linear programming; customer lifetime value.

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