--- sourceDocument: Australia Conversational Interfaces sourceDocumentLink: https://www.servicenow.com/docs/r/conversational-interfaces Release : - australia ft:locale : - en-US ft:publication_title : - Australia Conversational Interfaces ft:clusterId : - convint bundleId : - convint workflow : - Platform --- # Voice page # Voice page in assistant analytics {#ariaid-title1} * Release version: Australia * * Updated June 6, 2026 * * ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 11 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Voice page in assistant analytics The Voice page in Assistant analytics within Assistant Designer enables ServiceNow customers to monitor and analyze the performance of their voice assistants. It provides comprehensive metrics organized into four tabs---Overview, Performance, Insights, and Assist Consumption---allowing customers to track conversation volume, resolution rates, tool usage, authentication metrics, conversation quality signals, and AI agent assist activity. Filters by voice assistant, language, communication channel, and date range help refine data views for targeted insights. Show full answer Show less ## Key Features * **Overview tab:** Displays high-level metrics such as total voice conversations, resolution rates (AI inferred via LLM transcript analysis), live agent transfer rates, average handle duration, average conversational turns, and customer satisfaction (CSAT) scores. It also includes AI voice agent-specific performance data to identify strong and weak agents. * **Performance tab:** Focuses on tool execution metrics (counts, success rates, and execution times at various percentiles), guest authentication performance, and voice assistant response times. This helps identify tool efficiency, authentication speed, and system responsiveness. * **Insights tab:** Provides detailed conversation outcomes beyond resolution, including immediate transfers, disconnects, session expirations, and ticket creations. It also measures user effort, agent empathy, user-agent confusion, and user frustration through LLM transcript analysis to gauge conversation quality and user experience. * **Assist Consumption tab:** Tracks AI agent assist usage by showing total assists consumed, trends over time, breakdown by assist tiers (Small, Medium, Large based on number of actions), and assists per AI voice agent. This data supports understanding AI usage patterns and operational scale but is informational and not for billing. ## Practical Benefits for ServiceNow Customers * **Performance Monitoring:** Quickly assess how voice assistants are handling conversations, their resolution effectiveness, and when escalations to live agents occur, enabling workflow optimization. * **Quality Improvement:** Use conversation quality signals such as user effort, empathy, confusion, and frustration to improve AI agent interactions and user satisfaction. * **Operational Insights:** Analyze tool execution and authentication times to detect bottlenecks and enhance technical performance. * **Usage Tracking:** Monitor AI action usage per assistant and over time to manage resource allocation and plan for capacity. * **Data-Driven Decisions:** Leverage AI inferred metrics for informed tuning of voice assistants but review these metrics carefully due to potential variability in accuracy. Overall, the Voice page empowers ServiceNow customers to gain actionable insights into their voice assistant deployments, optimize conversational workflows, improve user experience, and manage AI resource consumption effectively. Monitor the performance of voice assistants from the Voice page of Assistant analytics in Assistant Designer. The Voice page shows performance metrics for your voice assistants, organised across four tabs: Overview, Performance, Insights, and Assist consumption. Use these tabs to monitor conversation volume, resolution rates, tool execution, authentication performance, conversation quality signals, and AI agent assist usage. Figure 1. Voice page in Assistant analytics You can filter the data on all tabs using the following options: * Filter by voice assistant: View metrics for specific voice assistants. * Filter by language: View metrics by conversation language, such as English, German, Spanish, and so on. * Filter by communication channel type: View metrics by channel, such as phone, mobile app - iOS, mobile app - Android, or web browser. * Filter by date range: View metrics for a predefined period, such as last 7 days or last 30 days, or select a custom start and end date using the date picker. {#voice-assistant-analytics__ul_rdf_dwv_j3c} Scorecard widgets display a trend indicator below the metric value, showing the change in value compared to the equivalent previous period. The indicator includes the absolute change, the percentage change, and the comparison date range. Note: Metrics marked with the AI Inferred tag are calculated through large language model (LLM) transcript analysis. Results may vary and may not be fully accurate. Review AI Inferred metrics before acting on them. ## Overview tab {#voice-assistant-analytics__section_overview_tab} The Overview tab shows high-level conversation volume, resolution performance, and AI voice agent activity for the selected date range. Total voice conversations : This area of the dashboard shows the total number of conversations with voice assistants in the selected date range. Use this metric to track growth in voice interactions and set benchmarks for assistant performance. Select Related records to view the underlying records. Figure 2. Total voice conversations Total voice conversations over time : This area of the dashboard shows how conversation volume has changed over the selected date range. Use this chart to identify patterns such as peaks and dips in usage and correlate them with changes to your assistant configuration. Hover over a date to view the total number of conversations for that date. Figure 3. Total voice conversations over time Resolution rate (AI Inferred) : This area of the dashboard shows the percentage of conversations resolved by the voice AI, with no human follow-up needed. This is measured through large language model (LLM) transcript analysis. Select Related records to view the underlying records. Figure 4. Resolution rate Resolution rate over time (AI Inferred) : This area of the dashboard shows how the resolution rate has changed over the selected date range. Use this chart to track the impact of assistant updates and configuration changes on resolution performance. Hover over a date to view the resolution rate percentage for that date. Figure 5. Resolution rate over time Live agent transfer rate : This area of the dashboard shows the percentage of conversations transferred from the voice assistant to a live agent in the selected date range. Use this metric to identify common escalation triggers and optimise assistant workflows to reduce unnecessary transfers. Select Related records to view the underlying records. Figure 6. Live agent transfer rate Live agent transfer rate over time : This area of the dashboard shows how the live agent transfer rate has changed over the selected date range. Use this chart to identify periods of increased escalation and correlate them with conversation patterns or assistant configuration changes. Hover over a date to view the transfer rate percentage for that date. Figure 7. Live agent transfer rate over time Average handle duration (with voice assistant) : This area of the dashboard shows the average duration of the AI-handled portion of voice conversations, excluding time spent with a live agent after transfer. Use this metric to identify opportunities to streamline conversations and reduce resolution time. Figure 8. Average handle duration (with voice assistant) Average handle duration (with voice assistant) over time : This area of the dashboard shows how the average handle duration has changed over the selected date range. Use this chart to track whether workflow optimisations are reducing the time the voice assistant spends handling conversations. Hover over a date to view the average handle duration in seconds for that date. Figure 9. Average handle duration (with voice assistant) over time Average turns : This area of the dashboard shows the average number of turns taken by the voice assistant per voice conversation in the selected date range. Use this metric to assess how efficiently the assistant resolves user requests. Figure 10. Average turns Average turns over time : This area of the dashboard shows how the average number of conversational turns has changed over the selected date range. Use this chart to identify whether conversations are becoming more or less efficient over time. Hover over a date to view the average turn count for that date. Figure 11. Average turns over time Average CSAT score : This area of the dashboard shows the average customer satisfaction (CSAT) score for voice conversations in the selected date range. CSAT scores are captured through your own post-conversation survey solution. Select Related records to view the underlying records. Figure 12. Average CSAT score Average CSAT score over time : This area of the dashboard shows how the average CSAT score has changed over the selected date range. Use this chart to evaluate the impact of assistant updates on user satisfaction over time. Hover over a date to view the average CSAT score for that date. Figure 13. Average CSAT score over time AI voice agent performance : This area of the dashboard shows the conversation count and resolution rate for each AI voice agent invoked during conversations. The resolution rate column is AI Inferred. Use this table to identify high-performing agents and improve underperforming ones.The table includes the following columns: * Voice AI agent --- name of the AI voice agent. * Conversations --- total number of conversations handled by the agent. * Conversation change --- change in conversation count compared to the previous period. * Resolution rate (%) --- percentage of conversations resolved by the agent, measured through LLM transcript analysis (AI Inferred). {#voice-assistant-analytics__ul_aivap_cols} Figure 14. AI voice agent performance ## Performance tab {#voice-assistant-analytics__section_performance_tab} The Performance tab shows tool execution metrics, authentication performance, and response time data. Execution count by tool type : This area of the dashboard shows the number of tool executions categorised by type, including flow actions and RAG-based search, for the selected date range. Use this metric to understand which tools are most frequently invoked during voice conversations. See [Add tools and information to an AI agent](https://www.servicenow.com/docs/access?context=add-tool-aia&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US) for information on tool types. Figure 15. Execution count by tool type Tool execution time (50th percentile) : This area of the dashboard shows the tool execution time within which 50% of tool executions were completed. Tool time is the time required for the voice agent to complete actions using tools. Select Related records to view the underlying records. Figure 16. Tool execution time (50th percentile) Tool execution time (90th percentile) : This area of the dashboard shows the tool execution time within which 90% of tool executions were completed. Only 10% of executions took longer than this time. Select Related records to view the underlying records. Figure 17. Tool execution time (90th percentile) Tool execution time (99th percentile) : This area of the dashboard shows the tool execution time within which 99% of tool executions were completed. Only 1% of executions took longer than this time. Select Related records to view the underlying records. Figure 18. Tool execution time (99th percentile) Tool Performance : This area of the dashboard shows performance broken down by individual tool. Success rate reflects the share of executions that completed without error. P50, P90, and P99 columns represent execution time percentiles in seconds.The table includes the following columns: * Type --- the tool type, such as Flow actions or RAG-based search. * Tool --- the name of the specific tool invoked. * Success rate --- the percentage of executions that completed without error. * P50 Time (s) --- median execution time in seconds. * P90 Time (s) --- 90th percentile execution time in seconds. * P99 Time (s) --- 99th percentile execution time in seconds. {#voice-assistant-analytics__ul_tool_perf_cols} Figure 19. Tool Performance Guest authentication time (50th percentile) : This area of the dashboard shows the time within which 50% of guest authentication sequences were completed, measured from the first voice AI identification question until the authentication API call response. Select Related records to view the underlying records. Figure 20. Guest authentication time (50th percentile) Guest authentication time (90th percentile) : This area of the dashboard shows the time within which 90% of guest authentication sequences were completed. Only 10% took longer than this time. Select Related records to view the underlying records. Figure 21. Guest authentication time (90th percentile) Guest authentication time (99th percentile) : This area of the dashboard shows the time within which 99% of guest authentication sequences were completed. Only 1% took longer than this time. Select Related records to view the underlying records. Figure 22. Guest authentication time (99th percentile) Guest Authentication Outcomes : This area of the dashboard shows the number of interactions by authentication outcome. Successful means the caller was authenticated at any point during the interaction. Failed means every authentication attempt was unsuccessful. Figure 23. Guest Authentication Outcomes 50th percentile response time : This area of the dashboard shows the response time within which 50% of voice assistant responses were completed, measured from when the user finishes speaking to when the voice assistant responds. Only 50% of responses took longer than this time. Figure 24. 50th percentile response time 90th percentile response time : This area of the dashboard shows the response time within which 90% of voice assistant responses were completed. Only 10% of responses took longer than this time. Figure 25. 90th percentile response time 99th percentile response time : This area of the dashboard shows the response time within which 99% of voice assistant responses were completed. Only 1% of responses took longer than this time. Figure 26. 99th percentile response time ## Insights tab {#voice-assistant-analytics__section_insights_tab} The Insights tab shows conversation outcome data and key sentiment signals measured through large language model (LLM) transcript analysis. Additional conversation outcomes : This area of the dashboard shows conversation outcomes beyond resolution and live agent transfer. Immediate outcomes refer to events occurring within the first 30 seconds of the call.The table includes the following columns: Outcome, Conversation count, Conversation change, and Percent of total conversations. Outcomes tracked include: * Immediate live transfers --- conversations where the caller requested transfer to a live agent within the first 30 seconds. * Immediate disconnects --- conversations that disconnected within the first 30 seconds. * Session expiration --- conversations that ended due to session timeout. * Ticket created --- conversations that resulted in a ticket, such as an incident or case record, created for follow-up. {#voice-assistant-analytics__ul_conv_outcomes} Figure 27. Additional conversation outcomes User effort required with AI agents : This area of the dashboard tracks how much effort a user had to put in during a conversation, based on signals like transfers, wait times, and escalations. Scored as Low, Medium, or High. This is measured through large language model (LLM) transcript analysis. Select Related records to view the underlying records. Figure 28. User effort required with AI agents AI agent empathy : This area of the dashboard measures how politely and attentively the agent acknowledged the user's needs and concerns throughout the conversation. Scored as Low, Medium, or High. This is measured through large language model (LLM) transcript analysis. Select Related records to view the underlying records. Figure 29. AI agent empathy User / AI agent confusion : This area of the dashboard indicates whether the user and agent misunderstood each other at any point in the conversation. Scored as Yes or No. This is measured through large language model (LLM) transcript analysis. Select Related records to view the underlying records. Figure 30. User / AI agent confusion User frustration with AI agents : This area of the dashboard indicates whether the user expressed frustration, through complaints, sarcasm, or dissatisfaction, during the conversation. Scored as Yes or No. This is measured through large language model (LLM) transcript analysis. Select Related records to view the underlying records. Figure 31. User frustration with AI agents ## Assist consumption tab {#voice-assistant-analytics__section_assist_consumption_tab} Note: The data on this tab is for informational purposes only and should not be relied upon as a definitive statement of your AI usage for billing purposes. The Assist consumption tab shows AI agent assist usage metrics for the selected date range. An assist is recorded each time an AI voice agent completes an action during a conversation. Assists are categorised into three tiers based on the number of actions taken by the voice agent: Small, Medium, and Large. Total assists consumed : This area of the dashboard shows the total number of assists consumed by AI voice agents in the selected date range. Select Related records to view the underlying records. Figure 32. Total assists consumed Total assists consumed over time : This area of the dashboard shows how the total number of assists consumed by AI voice agents has changed over the selected date range. Hover over a date to view the number of assists consumed for that date. Figure 33. Total assists consumed over time Total assists consumed by tier : This area of the dashboard shows the total assists consumed, broken down by tier: Small, Medium, and Large. Figure 34. Total assists consumed by tier Assist consumption by agent : This area of the dashboard shows the average actions per call and total assists consumed, broken down by AI voice agent. Assist tier (small, medium, large) is based on the number of actions taken by the voice agent.The table includes the following columns: * AI voice agent --- name of the AI voice agent. * Average actions per call --- average number of actions the agent took per conversation. * Assists Consumed --- total number of assists consumed by the agent. {#voice-assistant-analytics__ul_assist_agent_cols} Figure 35. Assist consumption by agent