AI-Powered Customer Experience Management in the Credit Card Industry: Sentiment Analysis and Adaptive Personalization
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P105Keywords:
Artificial Intelligence, Customer Experience Management, Credit Card Industry, Sentiment Analysis, Adaptive Personalization, Natural Language Processing, Reinforcement LearningAbstract
The blistering development of the sphere of Artificial Intelligence (AI) and Natural Language Processing (NLP) has developed the Customer Experience Management (CEM), especially in the sphere of a steeply competitive credit card industry. Customers have moved beyond the traditional, clumsy modes of customer service, which could not meet the dynamic and complex nature of the contemporary customer. Contrastingly, AI-based technologies such as sentiment analysis and intelligent personalization offer scalable, real-time, and customer-behaviour and preference intelligence. The current paper is an in-depth exploration of artificial intelligence-powered sentiment analysis and how it can be applied in adaptive personalization models of the credit card industry. We find a discussion of the impacts of emotion detection, language models, and machine learning algorithms on customer satisfaction, customer loyalty, and customer lifetime value. Our approach involves collecting data through user reviews, in-app support chats and then preprocessing it through the application of NLP algorithms, scoring sentiment based on either a lexicon or a machine learning based model and coming up with adaptive strategies based on reinforcement learning and recommendation systems. The outcomes have shown that the Net Promoter Scores (NPS) improvement can be measured, and that the churn rates significantly decreased and the level of engagement grew among the clients who experienced the personalized services. Moreover, feedback loops enable constant AI model development, leading to a proactive rather than a reactive approach to service. The discussion also provides the ethical and operational concerns of the large-scale deployment of such systems. Having provided a literature synthesis, experimental analysis, and practical suggestions, this paper will reveal how AI can change the concept of CEM for credit card issuers
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