iDigiChat: intelligent digital marketing service chatbot for providing efficient customer services using artificial intelligence

Due to the increasing demand for intelligent customer service in the financial sector, the use of AI-powered chatbots is becoming unavoidable. Existing chatbot systems lack sufficient knowledge of complex language patterns, which limits their ability to handle intricate customer queries effectively. This study introduces an advanced AI-based customer service framework called iDigiChat, which integrates a knowledge graph (KG) and artificial neural network (ANN) techniques for more precise and responsive interactions. The system converts customers' queries into a structured graph format using Text-to-Graphql. It then applies Knowledge Graph Completion models to extract relational insights, which are classified and refined through a multi-layered ANN framework (KG-ANN). The simulation was conducted using a large-scale dataset consisting of 34,089 chatbot logs and 317,438 customer service call logs from a leading Korean bank, collected over a three-year period (2018-2020). The results show that the system achieves 90% R² and significantly reduces both mean absolute error and mean squared error by 25%, enabling faster and more reliable customer interactions.