The Intent Insights chart offers a focused lens into your AI agent’s performance at the intent level— revealing how effectively it understands, recommends, and fulfills user needs. Drawing from best practices in conversational analytics, this dashboard compiles multiple intent-focused metrics into a single view, helping you to measure quality and optimize outcomes. 1. Intent Fulfillment Friction (IFF) : Measures the level of friction encountered by the AI agent when resolving user intents. Higher friction may indicate prolonged dialogues or delays in achieving intent resolution. 2. Intent Fulfillment Rate (IFR): Represents the percentage of user intents successfully fulfilled by the AI agent. A higher rate signifies better agent performance in meeting user needs. 3. Intent Fulfillment Sentiment: Evaluates the sentiment expressed by users during the process of intent fulfillment. This metric provides insights into user satisfaction and emotional tone while fulfilling user need. 4. Intent Acceptance Rate (IAR) : Assesses the frequency at which users accept intent recommendations proposed by the AI agent. This metric reflects the relevance and accuracy of the agent’s suggestions. 5. Attribute Acceptance Rate (AAR) : Measures the rate at which users accept attribute recommendations (e.g., missing information) provided by the AI agent during intent fulfillment. A higher rate indicates effective guidance by the agent. 6. Intent Fulfillment Efficiency: Evaluates the efficiency of the AI agent in resolving user intents, considering factors like the number of interactions and time taken. This metric is inversely related to Intent Fulfillment Friction.