利用从企业到客户零售市场的大数据,基于位置和时间维度的消费者细分。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Fatemeh Ehsani, Monireh Hosseini
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引用次数: 0

摘要

消费者细分是一种电子营销实践,包括将消费者分为具有相似特征的群体,以发现他们的偏好。在企业对客户(B2C)零售业中,营销人员探索大数据,根据不同维度对消费者进行细分。然而,在这些维度中,购物地点和时间的动机受到的关注相对较少。在这项研究中,我们使用最近度、频率、货币和保有权(RFMT)方法,根据消费者的时间和地理特征将其分为10组。为了探索地点,我们调查了市场分布、收入分布和消费者分布。地理坐标和特性是根据消费者密度估计的。关于时间探索,我们评估产品交付的准确性和促销时间。为了准确定位目标消费者,我们在分销热图上显示了主要热点。此外,我们确定了有利消费者的最佳购买时间和人口最密集的地点。此外,我们评估产品分布,以确定最受欢迎的产品类别。基于RFMT细分和产品受欢迎程度,我们开发了一个产品推荐系统,以帮助营销人员吸引和吸引潜在消费者。通过使用大规模B2C零售数据的案例研究,我们得出结论,所提出的细分提供了对消费者行为的卓越见解,并提高了产品推荐性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consumer Segmentation Based on Location and Timing Dimensions Using Big Data from Business-to-Customer Retailing Marketplaces.

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 explore big data to segment consumers based on various dimensions. However, among these dimensions, the motives 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 consumer 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 pinpoint 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 segmentation and product popularity, we have developed a product recommender system to assist marketers in attracting 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.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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