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Documentation Index

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The AI Agent Analytics dashboard surfaces the operational quality of your AI agent: how quickly it responds, how often it resolves tickets on its own, how satisfied customers are, and the commerce impact of AI-driven conversations.

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Where to find it

  • Open the Analytics entry in the main sidebar.
  • Select the AI Agent tab from the apps row at the top of the Analytics page.
  • Set the date range and (optionally) the channel filter at the top of the dashboard.
AI Agent is one of the analytics apps alongside bitLink, bitCRM, bitChat, bitLogin, and Commerce. The page is reached from the platform-wide Analytics surface, not from the AI Studio sidebar.

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What’s on the dashboard

The page is composed of an 8-card statistics grid followed by four chart sections:
  • Stat cards (2 rows × 4 cards) — headline metrics with a period-over-period delta on each card.
  • AI Resolution — pie chart breaking down conversations into Resolved, Handed-off, and Takeover.
  • Resolution rate by agent type — bar chart comparing AI agent vs. human agent resolution rates.
  • Customer satisfaction — semicircle chart of customer ratings, with a satisfied-percentage figure.
  • Intention — distribution of detected customer intentions across the period.
  • Top AI Tags — time-series of the most-generated AI tags.

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Stat cards inventory

RowCardWhat it measures
1Ticket handled by AITotal tickets where the AI agent was involved.
1AI ResponsesTotal replies sent by the AI agent (includes a See details link to the AI token usage history).
1First response timeTime between the customer’s first message in a ticket and the AI agent’s first reply.
1Avg. response timeAverage time between any customer message and the AI agent’s next reply across the period.
2Resolution rate(Tickets resolved by AI agent / Total tickets handled by AI) × 100.
2Hand-off rate(Tickets handed off by AI / Total tickets handled by AI) × 100.
2Order conversion rate(Orders created by AI / Tickets with purchase intention) × 100.
2Order value created by AITotal value of draft orders the AI agent generated, in your workspace currency.
Each stat card also shows a period-over-period delta beneath the value — for percentage and count cards this is a percentage change; for the response-time cards it is a duration (for example, −12s). The delta is an inline indicator on the card, not a separate card.

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Response time metrics

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First response time

The time between the customer’s first message in a ticket and the AI agent’s first reply.
  • Lower is better. Use this card to spot regressions after a prompt or skill change — a sudden increase usually means the agent is taking longer to retrieve context or is blocked on tool calls.
  • The delta beneath the value shows movement against the previous comparable window (for example, this week vs. last week). A downward arrow is an improvement; an upward arrow is a regression.

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Avg. response time

The average time between any customer message and the AI agent’s next reply in the same ticket across the period.
  • Lower is better. This complements First response time because it accounts for the entire conversation, not just the opening reply.
  • Like First response time, the delta is shown beneath the value as a duration vs. the prior comparable window.

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Customer satisfaction (CSAT)

The Customer satisfaction section sits below the stat-card grid as its own card. It shows:
  • A semicircle chart of the rating distribution (1–5 stars).
  • A satisfied % figure — the share of ratings of 4 or 5 out of all ratings in the period. The backend returns this as satisfiedPercentage; the UI falls back to computing it client-side if the backend value is null.
  • A See details link that opens the bitChat ticket performance breakdown filtered to handler=ai_agent for the same date range.
Only tickets where the customer submitted a rating contribute to CSAT. The set of tickets attributed to the AI agent for CSAT purposes is determined by the handler=ai_agent filter on the underlying ticket-performance endpoint.
Needs verification (Brandon): confirm the following behaviors so we can document them concretely instead of inferring from code:
  • Whether the “handler = ai_agent” attribution counts tickets that the AI agent handed off to a human agent before the customer left a rating.
  • The comparison window used for the period-over-period delta on each card (rolling N days vs. matched calendar period).
  • Any minimum sample size below which CSAT is shown as empty rather than a low percentage.

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Other metrics on the page

These sit below the stat-card grid and round out the same dashboard. They are mentioned here so the page maps cleanly to what you see in product; deeper guides for each can be added separately.
  • AI Resolution — pie chart of ticket outcomes split into Resolved (AI closed the ticket), Handed-off (AI explicitly transferred to a human), and Takeover (a human intervened mid-ticket).
  • Resolution rate by agent type — bar comparison of AI agent vs. human agent resolution percentages over the same period.
  • Intention — distribution of detected customer intentions (for example, purchase, support, browsing).
  • Top AI Tags — time-series view of the AI tags generated across the period, with totals and an average-per-day figure.

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Filtering by channel

The dashboard supports a channel filter at the top of the page. The default is your most-connected channel; switching to All removes the channel filter and aggregates across every connected channel.