Evaluating consumer satisfaction by using chatbots and traditional customer relationship management tools: a comparative study

Zeina Alaa Elrefaie, Abeer Ezzi, Hanan Youssef, Jihan Yehia

Abstract


 This study investigates consumer satisfaction with Artificial Intelligence (AI) driven chatbots compared to traditional Customer Relationship Management (CRM) tools within the Egyptian market. Grounded in Social Information Processing (SIP) Theory and the Technology Acceptance Model (TAM). the study explores how efficiency, personalization, and perceived usefulness shape consumer experiences. A mixed-method approach was employed, combining survey data from 200 Egyptian consumers mainly Gen Z and Millennials with expert interviews from marketing professionals and system developers. Findings reveal that while chatbots excel in cost-effectiveness, speed, scalability, and 24/7 availability, they fall short in empathy, contextual adaptation, and trust-building, areas where traditional CRM continues to better. The study highlights that Egyptian consumers prefer hybrid approaches, integrating both chatbots and human agents depending on service needs. Ultimately, the research underscores that AI-enabled chatbots significantly enhance operational efficiency and data-driven personalization. traditional CRM remains indispensable for fostering long-term trust and loyalty, these insights provide both theoretical contributions to communication and adoption models, as well as practical guidance for businesses seeking to balance automation with human-centered service strategies.

Key words: Artificial Intelligence, Consumer Satisfaction, Consumer Awareness, Chatbots, Digital Applications, Marketing Development and Traditional Customer Relationship Management.

 

Received on: 31 October 2025

Accepted on: 30 November 2025

Published on: 28 December 2025



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References


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DOI: https://dx.doi.org/10.21622/ILCC.2025.05.2.1760

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Copyright (c) 2025 Zeina Alaa Elrefaie, Abeer Ezzi, Hanan Youssef, Jihan Yehia

Insights into Language, Culture and Communication

E-ISSN: 2812-491X

P-ISSN: 2812-4901

 

Published by:

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Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

ilcc@aast.edu