When a chatbot cannot recognize a reasonable request, it may send the user to a generic response, forcing repetition and increasing frustration, abandonment, or escalation. section 1.1.3 section 11.3.1
Intent classification assigns a user utterance to a predefined category representing the user’s goal. It gives the conversational system a practical answer to “What is this person trying to do?” so it can choose an appropriate route or response. section 4.0
Reliable classification depends on an improvement loop:
- Collect representative utterances from historical chat logs, call-center transcripts, or emails. section 1.1.3
- Balance and vary the training data so the classifier reflects the range of current user language. section 1.1.3 section 11.3.1
- Test classification accuracy and monitor signals such as declining understanding, abandonment, opt-outs, and unnecessary escalations. section 1.1.3 section 4.0
- Refresh training as user needs change, especially when an open-ended greeting implies that broad requests are supported. section 11.3.1
From missed intent to useful routing
A user asks for help with a reasonable business-related request after the assistant says, “How can I help you?” If the request falls outside the classifier’s prepared range, the assistant asks for a repeat or sends a generic reply. Representative training examples and ongoing tests help the system recognize more current user goals and reduce avoidable opt-outs. section 11.3.1 section 1.1.3
