A New Approach to Market Segmentation Based on 2-Dimensional Tables

In a competitive market, market segmentation is essential for building effective marketing strategies. In this study, we propose two approaches to classify entities of a market into four segments which can be interpreted in advance without arbitrariness, using two quantifiable indicators. One is "FlexBound-Seg," which flexibly constructs the boundaries of each region by solving a combinatorial optimization problem, and the other is "PercentSquare-Seg," which revises the classical method in Pareto analysis to satisfy an upper bound on the number of elements in the heavy region. By applying real data of e-shopping usage, the results showed that "FlexBound-Seg," "PercentSquare-Seg," and the classical method "Pareto-Seg" in that order, provided more accurate segmentation for heavy users, and were useful methods that could cope with fluctuations in user usage over time. In this case study, it was also found that all the methods were effective in increasing the number of users through sales campaigns, and that the extraction of heavy users during the entire period was a classification method that can also look at heavy users classified into heavy region frequently. Although there are effective cases at the current stage, further application of the method to data from other industries is an issue for the future to measure its versatility. In addition, we also need to improve the method to expand the number of indicators, such as three indicators, to enable more complex segmentation.

• Publication year

  2024

• Venue

  International Conferences on Computing and Data Engineering

• Publication date

  2024-01-15

• Fields of study

  Mathematics, Business, Computer Science

• Identifiers
  DOI 10.1145/3641181.3641194
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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