- Intent Classification
- The AI task of identifying what a customer is trying to do or resolve in a conversation.
Why CX and AI teams search for this
Teams search for this when they need AI to understand customer requests reliably enough to route, automate, or analyze support conversations.
Intent Classification is the process of identifying the customer's goal in a conversation. In CX operations, intent classification helps route interactions, trigger workflows, measure demand, and evaluate whether AI or human agents understood the customer correctly.
Examples of Customer Intents: - Check order status - Request refund - Cancel subscription - Report product defect - Update billing details - Ask for technical support - Escalate complaint
Why It Matters: Accurate intent classification is foundational for automation. If an AI agent misclassifies intent, it may use the wrong workflow, provide irrelevant information, or fail to escalate an important issue.
In VoC and QA programs, intent classification also helps leaders understand why customers contact support and where operational demand is coming from.
Examples
- A WhatsApp message saying "where is my package?" is classified as order status.
- A chat saying "I was charged twice" is classified as billing issue.
- A call transcript about a broken product is classified as product defect.
FAQs
Why is intent classification important for AI agents?
AI agents need accurate intent classification to choose the right answer, workflow, policy, or escalation path.
How is intent classification used in VoC?
It groups conversations by customer need so teams can measure demand, detect trends, and prioritize operational fixes.