In Ghana, businesses and organizations often struggle with effectively handling customer support inquiries due to the high volume and diverse nature of the messages received. Support teams face challenges in promptly identifying the intent behind each inquiry, leading to delays and customer dissatisfaction.
The lack of an efficient intent classification system hinders businesses’ ability to provide timely and personalized customer support. Manual processing of customer inquiries is time-consuming and prone to errors, resulting in longer response times, misrouted tickets, and frustrated customers
By developing an intent classification model specifically designed for customer support in Ghana, we aim to revolutionize the way businesses handle customer inquiries. The automated classification system will accurately categorize intents such as product queries, technical issues, and account-related concerns, enabling faster ticket routing and response times. This will lead to improved customer satisfaction, increased operational efficiency, and enhanced brand reputation for businesses in Ghana.
Project Setup and Data Collection
Data preparation and Annotation
Model Development and training
Model Optimization and Validation
NLP techniques , Text processing , model training and evaluation, feature engineering , Pytorch