IECT: A methodology for identifying critical products using purchase transactions

Ping Yu Hsu, Chen Wan Huang

Research output: Contribution to journalArticlepeer-review

Abstract

Identifying critical products and key customers to strengthen company performance is vitally important in the digital transformation era. Critical products are the itemsets that are preferred by vip customers and yet not popular among ordinary customers. As a result, critical products should be kept on the shelf despite its sales volumes may be lower than other popular items. However, few studies have considered identifying critical products or their potentially valuable patterns. Therefore an innovative algorithm taking advantage of vertical databases to identify critical products was designed. The proposed algorithm is applied to a transaction database of a midsize supermarket to verify the performance. The result showed that precision can reach 80.55% and 82.15% for two different filtering criteria. To the best of our knowledge, this study is the first to apply the concept of critical products to real retail industry transaction records.

Original languageEnglish
Article number106420
JournalApplied Soft Computing Journal
Volume94
DOIs
StatePublished - Sep 2020

Keywords

  • Critical products
  • Data mining
  • Frequent itemsets
  • RFM
  • Vertical database

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