Leading Bank
Auto Dispatch / Complaint Classification
Problem
The client needed an automated solution to classify customer feedback and complaints, enabling efficient routing to the appropriate departments for timely resolution of issues.
Solution
State-of-the-art deep learning models were fine-tuned to classify customer feedback accurately. The system also provided automated responses, directing customers based on the model’s classifications, ensuring a seamless communication flow.
Outcome
The enhanced categorization of customer feedback led to a significant improvement in the complaint resolution rate, while simultaneously reducing manual effort, optimizing workflows, and ensuring faster response times.
Automating Customer Feedback Classification for Improved Efficiency and Satisfaction
The client sought to develop a predictive model to automate the classification of customer feedback and complaints. The goal was to enhance customer service by efficiently redirecting complaints to the appropriate department. To achieve this, customer feedback data from various sources within the banking industry was leveraged to fine-tune deep learning models. Additionally, an SMTP system was implemented to send timely, relevant replies to customers based on the model’s classification.
The AI-driven model successfully achieved an accuracy range of 80-90% in classifying customer feedback and complaints. As a result, the complaint resolution rate improved by 50%, and manual efforts were reduced by 60%, significantly increasing operational efficiency. This automation not only streamlined complaint handling but also led to faster response times and enhanced customer satisfaction.
Faster Resolutions, Less Effort
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