A method for fusion of customer caller appeal information based on a consistent clustering model

In recent years, the volume of customer incoming calls and demands has risen sharply, resulting in an increase in the word processing cost of power supply enterprises, which in turn leads to low processing efficiency of the demands and customer complaints, etc. This paper proposes a customer incoming call demand information fusion method based on the consistency clustering model to solve the fusion problem of customer incoming calls and demands information from different channels in this situation. Firstly, the method utilizes deep learning methods to analyze and extract the relevant data for collecting customer caller request information in a deeper way, secondly, it adopts the consistency clustering algorithm to cluster the similar request information, and finally, it integrates the caller request information of the same customer through the information fusion technology. This method can improve the efficiency and accuracy of customer service and provide a better customer service experience for enterprises.