A multi-turn conversation involves multiple exchanges between the caller and AI agent, with each turn building on previous context. Managing multi-turn dialogue requires tracking what has been discussed and maintaining coherence across the interaction.
What makes multi-turn conversations challenging?
Each turn must consider everything that came before. The AI must remember what the caller said, what questions were answered, what commitments were made, and what remains unresolved. References like “that” and “it” require understanding of conversational context to interpret correctly.
Why do multi-turn conversations matter?
Real customer interactions rarely resolve in a single exchange. Scheduling requires discussing dates, times, and services. Troubleshooting involves describing problems, trying solutions, and verifying results. The ability to sustain coherent multi-turn dialogue determines what complexity of tasks a voice agent can handle.
Multi-turn conversation in practice
A caller requests an appointment, mentions they prefer mornings, asks about parking, inquires about cancellation policies, then confirms a Thursday 9am slot. The AI maintains context through all five turns, applying the morning preference when offering times and referencing “your Thursday appointment” in the confirmation without the caller needing to repeat details.