Discovering Specific Sales Patterns Among Different Market Segments

Cheng-Hsiung Weng and Cheng-Kui Huang
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Cheng-Hsiung Weng: Department of Management Information Systems, Central Taiwan University of Science and Technology, Taichung, Taiwan & Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
Cheng-Kui Huang: National Chung Cheng University, Taiwan

International Journal of Data Warehousing and Mining (IJDWM), 2020, vol. 16, issue 3, 37-59

Abstract: Formulating different marketing strategies to apply to various market segments is a noteworthy undertaking for marketing managers. Accordingly, marketing managers should identify sales patterns among different market segments. The study initially applies the concept of recency–frequency–monetary (RFM) scores to segment transaction datasets into several sub-datasets (market segments) and discovers RFM itemsets from these market segments. In addition, three sales features (unique, common, and particular sales patterns) are defined to identify various sales patterns in this study. In particular, a new criterion (contrast support) is also proposed to discover notable sales patterns among different market segments. This study develops an algorithm, called sales pattern mining (SPMING), for discovering RFM itemsets from several RFM-based market segments and then identifying unique, common, and particular sales patterns. The experimental results from two real datasets show that the SPMING algorithm can discover specific sales patterns in various market segments.

Date: 2020
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