Build an NLP Model for Customer Intent Classification

Intent classification is a machine learning process used to identify and classify user intent automatically. It helps in business operations by enabling faster responses to queries and allowing for a more customer-centric support service.

In this project, we will build a natural language processing (NLP) model using TensorFlow for intent classification in a customer support context. The model will be fed with textual data comprising 13,083 customer service queries labeled with 77 intents in a banking domain. The trained NLP model will identify customer intent from questions and automatically categorize them into one of several severity levels (e.g., high, medium, or low). This can help business owners prioritize urgent and high-priority cases, serving as an early warning system to identify potential risks to customer retention. With this information, they can devise timely strategies to win back customers.