Providing a Model of Customer Experience Management Based on Knowledge Management Models in the Field of Fintech Using Machine Learning

This study explores the role of machine learning in managing knowledge of customer experience. Given the importance of high-quality knowledge for organizational innovation, this research aim is to address existing research gaps and propose a novel model for leveraging customer experiences in the fintech sector using machine learning. The main research question is to identify the key components and effective elements in developing a knowledge management of customer experience model using machine learning. Two secondary questions focus on identifying the most relevant knowledge management model for developing the knowledge management of customer experience model and assessing the suitability of machine learning capabilities for interpreting customer perceptions.The research methodology is design science. Conceptual and structural equation models were developed, and hypotheses were tested and validated through model fitting. The findings led to the creation of a framework for future research and the development of the APO model into a seven-layer APO-CEM model, which includes preprocessing, coding, thematic categorization, and improved decision tree accuracy. The model was positioned and validated within the fintech ecosystem. Results confirm the model's effectiveness in enhancing growth, productivity, and customer satisfaction and demonstrate that machine learning can effectively measure and improve the quality of knowledge of customer experience through the cultivation of customer insights.