Title: Modelling customer experience in digital services

Authors: Rohit Rawal; Suhas Hurli; Kai Wen Tien; Anita Woodman; Vittaldas Prabhu

Addresses: Penn State University, Industrial Engineering, PA 16802, USA ' Penn State University, Industrial Engineering, PA 16802, USA ' Penn State University, Industrial Engineering, PA 16802, USA ' Penn State University, Industrial Engineering, PA 16802, USA ' Penn State University, Industrial Engineering, PA 16802, USA

Abstract: Technology advancements allow customers the convenience of getting their desired products and services on demand. Digitisation of many of the services offers opportunities to collect data at various touchpoints of customer experience. However, appropriate data analytics and visualization are required to drive better decisions and enhance the customer experience. The modelling techniques developed in this paper can be used across the spectrum of services in which there is a process to capture the expectations and perceptions of the customers served. We apply this digital service modeling approach in a detailed case study to investigate customer experience using a large WiFi infrastructure and identify ways to improve the process. Future research could build on this work by performing text analysis using several machine learning and AI tools to identify improvement opportunities and conduct sentiment analysis periodically to track changes in customer perceptions and expectations.

Keywords: customer experience; digital services; data-driven models; visualisation; visualising lens; synthesising lens; sensing lens; net promoter score; customer satisfaction score; SERVQUAL.

DOI: 10.1504/IJSOI.2023.132348

International Journal of Services Operations and Informatics, 2023 Vol.12 No.3, pp.225 - 243

Accepted: 13 Feb 2023
Published online: 18 Jul 2023 *

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