Open camera or QR reader and scan code to access this article and other resources online. Consumer Segmentation Based on Location and Timing Dimensions Using Big Data from Business-to-Customer Retailing Marketplaces Fatemeh Ehsani and Monireh Hosseini * Abstract Consumer segmentation is an electronic marketing practice that involves dividing consumers into groups with similar features to discover their preferences. In the business-to-customer (B2C) retailing industry, marketers ex- plore big data to segment consumers based on various dimensions. However, among these dimensions, the mo- tives of location and time of shopping have received relatively less attention. In this study, we use the recency, frequency, monetary, and tenure (RFMT) method to segment consumers into 10 groups based on their time and geographical features. To explore location, we investigate market distribution, revenue distribution, and con- sumer distribution. Geographical coordinates and peculiarities are estimated based on consumer density. Regarding time exploration, we evaluate the accuracy of product delivery and the timing of promotions. To pin- point the target consumers, we display the main hotspots on the distribution heatmap. Furthermore, we identify the optimal time for purchase and the most densely populated locations of beneficial consumers. In addition, we evaluate product distribution to determine the most popular product categories. Based on the RFMT segmen- tation and product popularity, we have developed a product recommender system to assist marketers in attract- ing and engaging potential consumers. Through a case study using data from massive B2C retailing, we conclude that the proposed segmentation provides superior insights into consumer behavior and improves product recommendation performance. Keywords: B2C retailing; big data; consumer segmentation; RFMT model; recommender system Introduction Electronic marketing (e-marketing) has emerged as an exciting new concept. It involves the execution of business strategies related to product perception, promotion, and pricing using electronic devices, appli- cations, and big data. The primary objectives of e-marketing are to achieve marketing goals and gener- ate revenue for organizations. 1 Business-to-customer (B2C) has become the most prevalent type of e-marketing, indicating the process of buying or selling products, services, and information through an online platform to end consumers. 2 In a B2C environment, consumers are often inclined to explore diverse infor- mation, products, and services that they have never encountered before. 3 Over time, the diversity of con- sumer demands has increased, posing a challenge for suppliers to meet their customers’ desired products. 4 Such behavior is typically observed in B2C retailing marketplaces, where consumers purchase inexpensive and frequently consumed goods. 5 Electronic retailing (e-retailing or e-tailing) is the most pervasive and independent model of B2C e-marketing. It involves the retailing of products, ser- vices, and information. 6,7 The success and survival of a market in a dynamic atmosphere are closely linked to the massive data generated from e-retailing sales. Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran. *Address correspondence to: Monireh Hosseini, Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran, E-mail: hosseini@kntu.ac.ir Correction added on November 17, 2023 after first online publication of October 30, 2023: The correspondence has been changed from Fatemeh Ehsani to Monireh Hosseini. Big Data Volume 11, Number 5, 2023 ª Mary Ann Liebert, Inc. DOI: 10.1089/big.2022.0307 1 Downloaded by 159.65.125.149 from www.liebertpub.com at 12/02/23. For personal use only.