Market Segmentation Using Enhanced RFM (Regency, Frequency, Monetary) Model
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Date
2017-02
Authors
Yoseph, Fahed
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Journal ISSN
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Publisher
Universiti Sains Malaysia
Abstract
The importance of targeted marketing strategy, a principle method for transforming retailers from being product-oriented to customer centric, has attracted interest from both industry and academia. It is well known fact that consumers differ in various ways, and have contrasting buying preferences. A widely used approach for gaining insight into the heterogeneity of customer buying behavior and profitability is market segmentation. It refers to the division of a mass market into smaller homogeneous markets based on purchase similarity and the diversity of customers. Conventional market segmentation models are often lack the empirical evidence to their calculations and derived based on a specific time frame, which thereby often ignore the fact that customers’ behavior may evolve over time, therefore retailers often consume limited and valuable resources attempting to service unprofitable customers. In order to provide a holistic view of customers’ specific characteristics and purchasing behavior, this research looks into the integration of two dynamics models, which are the Customer Lifetime Value (CLTV) model and Recency, Frequency, Monetary (RFM) model that are being investigated for market segmentation for a medium size retailer in the State of Kuwait. Also, three new RFM variation analysis methods (i.e. P, Q, C) are proposed which have superior advantages with respect to the traditional RFM model. This research applies a critical feature for the CTLV and RFM integration, using data transformation method to transform and processes the raw Point-of-Sales (POS) data into consolidated generic Star-Schema data warehouse.
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Keywords
Market segmentation using enhanced , regency, frequency, monetary model