Cross-turn reasoning is the ability to interpret a conversation by connecting information across multiple turns between the customer and the agent. It accounts for references like “that,” “it,” or “as I said,” tracks changes in intent, and resolves meaning that only becomes clear when earlier and later turns are considered together.
Operationally, it matters because many contact-center signals depend on context over time: the real reason for contact, whether the agent followed required steps, if the customer’s problem was actually resolved, and what commitments were made. Without cross-turn reasoning, analytics can mislabel topics, miss compliance moments, and overstate resolution by treating isolated phrases as complete answers.
Using cross-turn reasoning helps produce more reliable call summaries, dispositioning, and QA findings by tying evidence to the full interaction. It also improves trend reporting by reducing false positives from single-turn keyword matches and by capturing the sequence of events that led to escalation, churn risk, or repeat contact.
