Probabilistic Customer Purchase Evolution Graph

• Published in: IEEE access Vol. 11; p. 1
• Main Authors: Lin, Yung-Tzu, Chang, Chuan-Yi, Cheng, Shein-Yung, Lin, Meng-Yun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-01-2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Behavioral sciences; Bioinformatics; Commodities; Consumer behavior; Consumption; Customer journey; Customers; Data points; Evolution; Evolution (biology); Evolution theory; Genes; Genomics; Repurchase; Retail transaction; Transaction databases; Urban areas
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3263729

Following the evolutionary theory, this paper defines the commodity consumption gene of the customer journey in the retail transaction, so as to discuss the distribution and evolution process of the consumer group. First of all, through relevant retail research, each transaction is defined as a data point in the SPC space (sales-product-customer). And the customer journey is a pivot transformation of transaction data points in the SPC space. Next, customer purchase products are defined as consumption genes in the customer journey, forming customer consumption species. Furthermore, evolutionary operations with probabilities between consumer species (genes) can analyze the evolution of each customer's purchase consumption over time in the retail database. And an algorithm for the Customer Purchase Evolution Graph (CPEG) is proposed. To prove the practicability, an one-year nearly 300,000 actual transactions from over 27,000 consumers is used to establishes the CPEGs with evolutionary probabilities of the overall customers and the CPEG of the SVIP. The CPEG of all customers can be used to see the main consumption distribution, the main consumption starting point (first purchase) behavior and repurchase behavior of overall customers and new customers. The CPEG of SVIP customers can further reveal the main consumption genes of mature customers (species) and the evolution process in their consumption journey. These findings can be of specific help to the company's commodity strategy and operational marketing.