Handle customer inquiries and complaints to improve service efficiency
Optimize customer interactions through data-driven insights and AI-powered support systems.
Data Collection
Gather a diverse dataset of customer inquiries, complaints, and corresponding resolutions from various industries, including e-commerce, telecommunications, and financial services.
Model Fine-Tuning
Fine-tune GPT-4 on the customer service dataset to optimize its ability to understand and respond to customer queries and complaints accurately and efficiently.
System Development
Develop an AI-powered customer service system that integrates the fine-tuned model to handle customer interactions in real-time.
User Testing
Conduct user testing with real customers and customer service representatives to validate the system’s usability and performance.
Performance Evaluation
Use metrics such as response accuracy, resolution time, and customer satisfaction scores to assess the system’s effectiveness.
Expected Outcomes
This research aims to demonstrate that fine-tuning GPT-4 can significantly enhance its ability to handle customer inquiries and complaints efficiently and effectively. The outcomes will contribute to a deeper understanding of how advanced AI models can be adapted for customer service applications. Additionally, the study will highlight the societal impact of AI in improving customer satisfaction, reducing operational costs for businesses, and advancing the field of intelligent customer service.