Clustering Customers Using Their In-Depth Buying Behavior: A Pet Food Manufacturing Company Case Study

Nowadays pet ownership in Thailand is on the rise. Pet related industries have been boosted and expanded significantly. The pet food industry competition, as a result, has been higher and tougher.The aim of this research istoapply K-means clustering method tosegment customers ofamanufacturing petfood company using the data from January 2018toSeptember 2020including the total of588business customers. This research employs15variables:purchasingamount in 2020, growth rate from 2018-2019, growth rate from 2019-2020, distance from distribution center to store districts, number of transactionsin 2018-2020, number of returns in 2018-2020, consistency of monthlypurchasing amountfrom 2018-2020, the percentage of return frequency and the percentage of the returnvalue.The customershave been clustered into 8groupswhich can be characterized as follow: “Rarely return customers” (56.4%), “Regular customers with high swing” (15.7%), “Suburbanand ruralcustomers” (13.2%), "Frequently return customers" (6.0%), "Frequentlypurchasecustomers" (5.9%), "High volume customers" (1.3%), "Prospective customers" (0.8%) and "Irregular customers" (0.79%). By understanding the customer behavior ineach group, the results benefit the manufacturing company inoptimal sale strategyplanning.