Use of Artificial Intelligence as a Mechanism to Evaluate Costumer Experience. Literature Review

Silva-Aravena, F; Morales, J.; Sáez, P; Jorquera J.; Cornide-Reyes H.

Keywords: literature review, ethical principles, Customer experience, AI Strategies

Abstract

In the contemporary era marked by the explosion of data, the widespread adoption of Artificial Intelligence (AI) technologies has become essential for companies and researchers exploring various phenomena across industries. An important focus lies on evaluating and improving customer experience (CX) through technologies such as chatbots powered by AI strategies, such as natural language processing (NLP), through the use of chatbots, voice assistants, among others. This not only optimizes CX efficiency but also contributes to improving organizations' processes. The convergence of AI and CX is evident in several sectors; highlighting smart retail, CX in the hospitality sector, and service customization in the banking sector. Additionally, the COVID-19 pandemic has further highlighted the importance of these technologies, catalyzing their accelerated integration. We propose a literature review, employing a five-stage protocol to explore key questions: How can the use of AI improve the CX? Which fields of AI are most frequently used to evaluate CX? What are the aspects of CX in which AI is most frequently used? Five databases were surveyed, yielding insights into AI strategies (e.g., NLP, Decision Trees, Naive Bayes), and evaluation methods, such as user tests and ethical considerations. Despite progress, gaps still remain that require more research, empirical studies, and success stories to solidify the effectiveness of AI in CX. For responsible development, we suggest organizations develop implementation guides when putting into practice commercial strategies for the use of AI, which ensure ethical standards and regulate machine-client interaction.

Más información

Título según WOS: Use of Artificial Intelligence as a Mechanism to Evaluate Costumer Experience. Literature Review
Título de la Revista: LEARNING AND INTELLIGENT OPTIMIZATION, LION 18
Volumen: 14704
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2024
Página de inicio: 338
Página final: 354
Idioma: English
DOI:

10.1007/978-3-031-61305-0_24

Notas: ISI