1 Teesside University International Business School, Middlesbrough United Kingdom.
2 Department of Corporate Services, Gelose Marine Services Nig. Ltd, Port Harcourt, Rivers State, Nigeria.
3 Independent Researcher, Lagos Nigeria.
4 One Advanced, UK.
World Journal of Advanced Research and Reviews, 2024, 23(03), 923–933
Article DOI: 10.30574/wjarr.2024.23.3.2733
DOI url: https://doi.org/10.30574/wjarr.2024.23.3.2733
Received on 28 July 2024; revised on 04 September 2024; accepted on 06 September 2024
This paper explores the significant correlation between employee engagement and customer service quality, emphasizing the role of data-driven strategies in enhancing organizational outcomes. The paper highlights the importance of using data analytics to understand and improve employee engagement by analyzing key theories that link engagement to customer satisfaction. It discusses the critical metrics used to measure engagement and how data-driven insights can inform HR strategies, leading to superior customer service. The paper also examines the implications of implementing these strategies, addressing potential challenges such as data privacy, misinterpretation, and cultural resistance. Finally, it suggests future research directions, particularly in integrating emerging technologies like AI and machine learning, to refine engagement strategies further and adapt them to diverse work environments. This review underscores the evolving role of data analytics in HR and its potential to transform employee engagement into a key driver of business success.
Employee Engagement; Data-Driven HR; Customer Service Quality; Data Analytics; Organizational Performance; HR Strategies
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Olufunke Anne Alabi, Funmilayo Aribidesi Ajayi, Chioma Ann Udeh and Christianah Pelumi Efunniyi. Data-driven employee engagement: A pathway to superior customer service. World Journal of Advanced Research and Reviews, 2024, 23(03), 923–933. Article DOI: https://doi.org/10.30574/wjarr.2024.23.3.2733
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0