> ## Documentation Index > Fetch the complete documentation index at: https://docs.conduit.ai/llms.txt > Use this file to discover all available pages before exploring further. # Metrics > Understanding how Conduit calculates your team's performance metrics ## Overview Conduit tracks key performance metrics to help you understand how your team and AI are handling customer conversations. This guide explains how these metrics are calculated. Every metric card on the dashboard has an info icon (ℹ) that shows the formula when you hover over it. ## Response Time The **Median response time by user** chart measures the time between a customer's message and a human reply that directly follows it. It does not measure time from an AI hand-off. ### How It's Calculated * **Attribution:** Response time is attributed to whoever sends the reply, not who the conversation is assigned to * **Median calculation:** The chart shows a separate median for each person across their qualifying replies in the selected time period * **Exclusions:** Response times over 48 hours are excluded from the calculation to prevent outliers from skewing results * **AI replies:** If the AI has already replied to the customer, a later human follow-up is not recorded in this chart * **AI Agent bar:** This bar is an estimate derived from the configured AI response delay plus a fixed buffer, not a measured median of AI replies ### Common Scenarios | Scenario | Who gets the response time? | | - | - | | Staff A replies to Staff B's conversation | Staff A's response time is counted | | Multiple people reply to an unassigned conversation | Only the person whose reply directly follows the customer message gets a response time recorded | ### Things to Keep in Mind * **Quick responders:** Someone who frequently jumps in to quickly handle others' conversations will naturally have a lower median response time * **Complex conversations:** Team members who handle more complex conversations requiring research or investigation may have a higher median response time This chart describes replies directly after customer messages. Use the separate hand-off card to assess how quickly the team answers escalated conversations. ### Human Hand-off Response Time The **Human hand-off response time** card measures wall-clock time from when a chat conversation is escalated to the first customer-visible human reply to that contact, in any conversation. An AI reply does not stop this clock, so a human reply after an AI answer is included. Escalations for the same contact before the first human reply count as one hand-off, even across conversations. Messages sent from the PMS (`issentfromplatform = false`) do not stop the clock because the available data cannot distinguish staff replies from PMS automations. The card shows the average across all answered hand-offs for the team, the team median, and an average for each first responder. The team average is calculated from all answered hand-offs together, not from an average of the per-person figures. It also shows answered hand-offs and hand-offs with no human reply. The latter have no response time and are excluded from the averages, even if an escalation was reviewed or dismissed. The selected date range is based on when the hand-off happened; a hand-off without a reply can later become answered in that same period. This metric does not apply the 48-hour exclusion used by the older median chart. The report considers earlier escalations and human replies before applying the selected date range to each hand-off's first escalation. A later escalation cannot restart an unanswered hand-off from an earlier period. The export includes one row per hand-off with its escalation time, first human reply time if present, responder, elapsed minutes, and answered or no-human-reply status. Only chat escalations with a reliable conversation link are included. ## Automation Rate Automation rate measures the percentage of countable agent decisions that produced an AI send. ### Formula ```text theme={null} Automation Rate = (Sent agent decisions / Total countable agent decisions) × 100 ``` Answer-and-escalate decisions count as successful AI sends in this headline metric. Use the disposition breakdown to distinguish fully answered decisions from sends that also escalated. ### What Counts as an Escalation The AI escalates a conversation when: * A topic is marked as urgent * The AI needs confirmation or authorization to complete an action * There isn't enough information to provide an adequate response * The message contains attachments the AI can't process ### Improving Your Automation Rate To increase your automation rate: * Add more knowledge to your AI agent about common questions * Create skills for repetitive tasks * Review escalation patterns to identify gaps in AI training For more details on escalation types and how to address them, see the [AI Automation Dashboard](/insights/ai-automation-dashboard). ## Resolution Rate Resolution rate measures the share of eligible conversation threads resolved with a sent agent response during the selected period. The overall rate includes threads with human-in-the-loop involvement or escalation; it is not the fully autonomous rate. ### Formula ```text theme={null} Resolution Rate = (Resolved and sent threads / Threads with an actual autopilot decision) × 100 ``` For each real provider conversation thread, Conduit deterministically selects the latest qualifying actual-autopilot decision. The thread counts toward resolution when the final disposition is `resolved` and the final response was sent. The secondary **Fully autonomous** series uses the same denominator and shows the stricter subset with no known teammate outbound and no escalation or answer-and-escalate during the selected date range. The difference between the overall and fully autonomous rates is the share resolved with a teammate outbound message or escalation (human-in-the-loop or escalated). An escalation does not necessarily mean a teammate replied. ### What Counts * **Included:** Completed, inbound-triggered, non-proactive actual-autopilot decisions linked to a real conversation thread * **Excluded:** Sandbox, copilot, inactive, proactive-only, `no_op`, and unlinked runs * **Inbox filters:** When an inbox type is selected, only conversations in that inbox type are included * **Comparison periods:** The same formula is applied to the comparison date range, then aligned with the selected period on the chart ### Chart Buckets vs. Headline Number The line chart groups conversations by the time of each conversation's latest qualifying AI run. Depending on the selected range, buckets are hourly or daily in the workspace timezone. The headline percentage is calculated from the full selected period: ```text theme={null} Headline Resolution Rate = Total resolved conversations / Total qualifying conversations × 100 ``` It is not an average of the visible chart buckets. ## Hours Saved Hours saved estimates the total time your AI agent has saved your team by handling messages and calls autonomously. ### Formula ```text theme={null} Hours Saved = Message Hours + Call Hours Message Hours = (AI messages × Minutes per response) / 60 Call Hours = Total connected call duration (minutes) / 60 ``` * **Minutes per response** defaults to 3 minutes but can be customized in dashboard settings * **Call duration** includes only connected calls (answered or transferred), not missed calls ## Est. Labor Saved Estimated labor saved converts the hours saved into a dollar value based on your configured hourly wage. ### Formula ```text theme={null} Est. Labor Saved = Hours Saved × Hourly Wage ``` * **Hourly wage** defaults to \$25/hr and can be customized in dashboard settings ## Triage & Context Switch Savings This metric estimates the cost savings from AI handling your inbox, eliminating the overhead of reading, categorizing, and switching between conversations. ### Formula ```text theme={null} Triage Hours = (Total incoming messages × 1 min per message) / 60 Context Switch Hours = (AI-handled messages × 2 min per switch) / 60 Total Hours = Triage Hours + Context Switch Hours Triage & Context Switch Savings = Total Hours × Hourly Wage ``` * **1 min per message** represents the estimated time to read, categorize, and route an incoming message * **2 min per switch** represents the cognitive overhead of switching between conversations ## Booking Conversion Booking conversion measures the percentage of contacts that resulted in a booked appointment or meeting. ### Formula ```text theme={null} Booking Conversion = (Contacts with bookings / Total contacts) × 100 ``` ## Booking & Transfer Rate When no custom aggregation attributes are configured, the headline metric on the Capture tab shows the combined booking and transfer rate. ### Formula ```text theme={null} Booking & Transfer Rate = Booking Conversion Rate + Transfer Rate ``` ## Phone Connection Rate Phone connection rate measures how effectively your outbound calling efforts are reaching contacts. ### Formula ```text theme={null} Phone Connection Rate = (Contacts who answered or called back / Total contacts called) × 100 ``` A contact is considered "connected" if they answered an outbound call, were transferred, or called back after receiving an outbound call. ## Text Connection Rate Text connection rate measures how effectively your outbound messaging efforts are generating responses. ### Formula ```text theme={null} Text Connection Rate = (Contacts who responded / Total contacts messaged) × 100 ``` A contact is considered "connected" if they sent at least one incoming message after receiving an outbound message during the selected period. ## Transfer Rate Transfer rate measures the percentage of calls that were escalated to a human agent. ### Formula ```text theme={null} Transfer Rate = (Calls transferred to humans / Total calls) × 100 ``` ## After-Hours Coverage After-hours coverage measures the percentage of conversations (calls and messages) that occurred outside your configured business hours. ### Formula ```text theme={null} After-Hours Coverage = (Conversations outside business hours / Total conversations) × 100 ``` * Conversations include both incoming calls and incoming messages * Business hours are configured in your workspace settings * If business hours are not configured, this metric will not be available ## AI Responses A simple count of all outbound messages sent by AI agents (autopilot) during the selected period. ## Escalations Total count of conversations escalated to human agents during the selected period. Escalations include: * Topics marked as urgent * AI needs confirmation or authorization * Insufficient information to respond * Messages with unprocessable attachments *** ## Conversation Insights The conversation insights tab shows per-user and per-conversation metrics. These are the formulas behind each column. ### Positive Conversation Rate Measures the percentage of conversations where the customer had a positive experience. ```text theme={null} Positive Conversation Rate = (Conversations with CX score ≥ 3.0 / Total conversations with CX scores) × 100 ``` ### CX Score An AI-generated customer experience score on a 1-5 scale, based on conversation sentiment analysis. * **Green (≥ 4.0):** Positive experience * **Amber (≥ 3.0, \< 4.0):** Neutral experience * **Red (\< 3.0):** Negative experience ### AI % The percentage of outgoing messages in a conversation that were sent by AI. ```text theme={null} AI % = (AI messages / Total outgoing messages) × 100 ``` ### Escalations (per conversation) Count of AI escalation events within a single conversation. Escalations are triggered by: * Topics marked as urgent * AI needs confirmation or authorization * Insufficient information to respond * Messages with unprocessable attachments ### Messages (per conversation) Total count of all messages (incoming + outgoing) in a conversation during the selected period. *** ## Configurable Settings Several metrics depend on configurable values that you can adjust in the dashboard settings: | Setting | Default | Affects | | - | - | - | | Hourly wage | \$25/hr | Est. Labor Saved, Triage & Context Switch Savings | | Minutes per response | 3 min | Hours Saved, Est. Labor Saved | | After-hours multiplier | 1.5× | After-hours calculations | This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.