"I can get no e-satisfaction". What analytics say? Evidence using satisfaction data from e-commerce. (May 2022)

• Record Type: Journal Article
• Authors: Griva, Anastasia
• Is Part Of: Journal of retailing and consumer services. Volume 66(2022)
• Publication Date: 2022-05
• Subjects: Customer satisfaction -- Retail analytics -- e-commerce -- Customer segmentation -- Business analytics; Retail trade -- Periodicals; Service industries -- Periodicals; Customer services -- Periodicals; Commerce de détail -- Périodiques; Service à la clientèle -- Périodiques; Customer services; Retail trade; Periodicals; 658.87
• DOI: 10.1016/j.jretconser.2022.102954
• Languages: English
• ISSNs: 0969-6989

Abstract

Abstract: This study mines customer satisfaction (CS) segments using almost 270 thousand responses from a CS survey which ran in 140 e-commerce stores of a European country. To achieve this, it develops and applies a business analytics (BA)-informed framework. Then, it presents examples of how one e-commerce store exploited the extracted CS segments to build automated marketing actions for its customers, ranging from social media sharing strategies for the satisfied segments, to discounts for the less satisfied. This study contributes to customer satisfaction and segmentation literature. The extracted insights can be utilized to support decision making, ranging from targeted advertising for specific customer segments, to benchmarking for companies in similar industries. Highlights: Customer segmentation using customer satisfaction data. Development of a BA-informed framework to extract customer satisfaction segments. Application using e-commerce data from 140 e-commerce stores. Tailored automated marketing actions based on the satisfaction segments.