Purpose

As e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns.

Design/methodology/approach

The authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase.

Findings

The authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume.

Originality/value

This is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division.

中文翻译：

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用于分析电子商务行业产品退货的数字化转型技术

目的

随着电子商务的迅速发展，在线购物平台在印度和世界各地变得普遍。产品退货对电子商务行业的经济和生态可持续发展产生负面影响，是在线交易大幅增长的情况下电子商务行业面临的最大挑战之一。作者分析了客户的购买模式，以更好地了解他们的产品购买和退货模式。

设计/方法论/途径

作者利用基于数字化转型技术的新近度、频率和货币模型来更好地了解和细分潜在客户，以便制定个性化策略来增加销量，并且作者使用 k 均值和层次聚类进行卖家聚类，以确定为什么一些卖家销量最高以及他们提供哪些产品来吸引客户购买。

发现

作者发现，通过将数字化转型模型应用于客户细分，超过 61.15% 的消费者可能会购买、成为忠诚客户并使用公司服务，而约 35% 的客户要么停止购买，要么支出相对较低。为了留住这些消费者群体，需要特殊的考虑和诱人的报价。随着作者对卖家聚类的深入研究，我们发现聚类的最大数量为六个，而某些聚类表明货物的及时交付对于客户反馈和高销量起着至关重要的作用。

原创性/价值

这是利用基于数字化转型的方法制定卖家细分策略以实现卖家群体划分的罕见研究之一。