Design And Implementation Of Enterprise Customer Service System

With the continuous increase of enterprise business,the number of users has also increased exponentially,and the number of enterprise customer service online services and traffic volume has increased,and the workload of customer service has further increased.At the same time,the quality inspection of customer service calls requires a lot of human resources.And the company staff have heavy work.Enterprise customer service system can improve customer service efficiency,help enterprises reduce labor costs,reduce customer harassment through differentiated services,and improve customer service quality.The thesis comes from practical applications,mainly based on the actual problems faced by enterprises in the process of customer service,through research,analyzes the pain points and difficulties of customer service personnel in the service process,and designs and develops the enterprise customer service system.The enterprise customer service system includes five main functional modules,namely knowledge base management,work order management,labeling quality inspection center,model training center and intelligent robot management module.Work order management provides customer service with functions such as work order creation,work order circulation and work order processing;knowledge base management provides data support for customer service personnel and intelligent robots to improve customer service efficiency;Mark Quality Inspection Center provides customer service services for quality inspectors Quality inspection function,and unified quality inspection and labeling platform to label files;model training center uses speech recognition algorithm to repeatedly train existing speech recognition models to improve the accuracy of speech recognition and reduce customer service workload;intelligent robot management as a system The administrator provides robot management and configuration functions,and the intelligent robot can answer user questions according to the content in the knowledge base.The whole system is developed with Java Web,the main technical architecture is developed with Spring Boot framework,and the system adopts the MVC design pattern:presentation layer,business logic layer and data access layer.The model training center uses speech recognition technology to train basic speech models and improve the accuracy of speech recognition in customer service systems.At present,the system has completed the development of all functions,and has undergone complete testing.The system has been launched and can meet the needs of target users.According to the statistical data of the system,the system is running normally,providing stable services for enterprises and achieving the expected results.