Key Drivers of E-Commerce Platform Customer Service Satisfaction: A Big-Data Analytics Approach

DOI

10.2991/978-94-6239-642-5_113How to use a DOI?

Keywords

CSAT; e-commerce; regression analysis; customer service; price sensitivity

Abstract

This study investigates the key determinants of Customer Satisfaction (CSAT) within an e-commerce customer service context. Using over 85,000 customer interaction records, we applied descriptive statistics and multiple linear regression to quantify how operational, managerial, and product-related factors influence customer satisfaction. Results show that issue category and product price are the most influential predictors, while variables such as agent shift, and response lag have limited impact. The findings offer insights for optimizing customer service scheduling, product communication strategies, and pricing perceptions.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yahui Li
PY  - 2026
DA  - 2026/04/29
TI  - Key Drivers of E-Commerce Platform Customer Service Satisfaction: A Big-Data Analytics Approach
BT  - Proceedings of the 2026 11th International Conference on Financial Innovation and Economic Development (ICFIED 2026)
PB  - Atlantis Press
SP  - 1074
EP  - 1084
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-642-5_113
DO  - 10.2991/978-94-6239-642-5_113
ID  - Li2026
ER  -