AI Responses

Track and analyze how your AI chatbot performs and handles user questions

Understanding Response Categories

Every visitor message produces one AI turn. Each turn is grouped into one of three top-level buckets so you can read performance at a glance:

Successful

The AI answered from your knowledge base or a tool, connected the visitor to a human agent when they asked, or resolved the turn with an automated workflow.

Neutral

Simple interactions like greetings or small talk that don't require specific knowledge from your content.

Failed

The AI lacked enough information to answer, automatically handed off to a human, or hit a generation error.

The summary cards at the top of the page show each bucket's share of all turns — and because every turn is counted exactly once, the three percentages always add up to 100%.

Response Outcomes

Each row in the log carries a specific outcome badge that tells you exactly what happened. Use the outcome filter to drill into a single pattern.

Inspecting a Turn

Click the expand arrow on any row to open a full breakdown of how the AI produced that answer.

Conversation

The visitor's question and the AI's answer, shown exactly as they appeared in the chat — including any product carousel the AI added.

Details

A metadata strip summarizes the turn at a glance:

FieldMeaning
OutcomeThe result badge (see above).
ChannelWhere the turn happened — e.g. web chat or voice.
GroundedWhether the answer was based on content retrieved from your knowledge base.
ModelThe AI model that generated the answer.
TokensTotal tokens used for the turn.
LatencyHow long the answer took to generate.

Steps

A timeline of everything the AI did to reach its answer. Each step shows a status, and you can expand it for more detail:

  • Knowledge search — the search query the AI ran against your knowledge base, plus the results it matched. Each result lists its source and a relevance score; expand it to see the exact text the AI used.
  • API tool — an external API tool the AI called, with the data it sent and received.
  • Workflow — an automated workflow the AI triggered.
Retrieved context is shown live. If an article was edited or removed after the conversation, the step notes that the original text is no longer available.

How to Use This Data

Check Your Success Rate

Look at the percentage of successful turns to understand how well your AI is performing overall.

Identify Knowledge Gaps

Review Failed and Handoff (no context) turns to find questions your knowledge base doesn't cover yet.

Inspect the Steps

Expand a turn to see what the AI searched for and which content it retrieved — a fast way to spot when the wrong article is matching, or none at all.

Review Error Patterns

Look for recurring errors that might indicate a configuration issue.

Tips for Improvement

Low success rates? Add more content to your knowledge base, or set When the AI doesn't know the answer to Offer to connect with a human so unanswered questions can reach your team.
Many errors? Check your AI model settings or contact support if issues persist.
API tools failing? Verify your external service connections and API settings.