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The power of emotions: Leveraging user generated content for customer experience management

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Customer experience management (CEM) in the social media age finds itself needing to adapt to a rapidly changing digital environment and hence there is a need for innovative digital data analytical solutions. Drawing on an action case study of a large global automotive manufacturer, this study presents a digital innovation for enhanced emotion analytics on user generated content (UGC) and behaviour (UGB), to improve consumer insights for CEM. The digital innovation captures customer experience in real time, enabling measurement of a wide range of discrete emotions on the studied social media platform, which goes beyond traditional tools that capture positive or negative sentiment only. During the digital intervention, a substantial number of inauthentic and bot like behaviours was revealed, unbeknown to the case organisation. These accounts were found to be posting and amplifying highly emotional and potentially damaging content surrounding the case brand and its products. The study illustrates how emotion in the context of customer experience should go beyond typical categorisations, given the complexity of human emotion, while a distinction between bot and authentic users is imperative for CEM.

Funding

Advanced Propulsion Centre UK

History

School

  • Business and Economics

Department

  • Business

Published in

Journal of Business Research

Volume

144

Pages

997 - 1006

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2022-02-12

Publication date

2022-02-24

Copyright date

2022

ISSN

0148-2963

Language

  • en

Depositor

Dr Martin Sykora. Deposit date: 14 February 2022

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