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Analytics Agent

The analytics agent helps you understand your product data through natural language. Ask a question, and the agent will search your workspace, explore your data catalog, and create the right analysis for you.

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Where to access the agent​

You can start a conversation with the agent from several places:

  • Home page — type your question directly in the input area.
  • Sidebar navigation — click Mitzu Agent in the left sidebar to start a new conversation in a full-screen interface.
  • Floating button — the agent button in the bottom-right corner is available on every page. Click it to open the agent in sidebar mode without leaving your current view.
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The floating button opens the agent in sidebar mode, letting you chat while keeping your current page visible. You can switch between sidebar and full-screen at any time using the Expand and Minimize buttons.

What you can ask​

The agent supports several types of analysis. Here are examples for each.

Segmentation​

Count events, unique users, trends over time, and breakdowns by properties.

  • "How many users signed up this week?"
  • "Show me daily active users over the last 3 months"
  • "Compare signups by country"
  • "What percentage of active users made a purchase?"

Funnels​

Track conversion rates through sequential steps.

  • "What's the conversion rate from signup to first purchase?"
  • "Which campaigns drive the best conversion?"
  • "How long does it take users to go from trial to paid?"

Retention​

Measure whether users return after an initial action.

  • "What's our day 1, day 7, day 30 retention?"
  • "Show me retention by signup source"
  • "Are users who signed up last month coming back?"

Discovery​

Explore existing insights and your data catalog.

  • "What insights do we have about engagement?"
  • "What events do we track?"
  • "Show me the top insights"

How the agent works​

When you ask a question, the agent follows a structured workflow:

  1. Searches your workspace for existing saved insights that match your question. If a relevant insight exists, the agent runs it and shows you fresh results rather than creating a duplicate.
  2. Explores your data catalog if no existing insight matches. The agent discovers the right events, properties, and dimension tables to answer your question.
  3. Creates an analysis — a segmentation, funnel, or retention insight — and runs it to generate a chart and key findings.
  4. Presents the results with a summary highlighting the most important numbers, along with a chart visualization.

Working with results​

When the agent creates an insight, you can:

  • Click the insight link to open it in the full explore interface
  • Edit the metric — change filters, time windows, breakdowns, or aggregation types
  • Save it as a workspace insight for future use
  • Add it to a dashboard to track alongside other metrics

Conversations​

The agent supports multi-turn conversations. You can ask follow-up questions in the same thread, and the agent will maintain context from previous messages.

  • Start a new conversation anytime using the "New conversation" button in the header
  • Switch views between full-screen and minimized sidebar mode
  • Find past conversations — recent chats are shown in the sidebar agent panel. Click View all to see your full conversation history on the All Content page.
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AI settings​

Configure the agent's behavior in Settings → Insight Settings → AI Settings.

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Model selection​

Choose which AI model powers the agent:

  • Auto (recommended) — intelligently selects between models based on query complexity
  • Claude Sonnet — best for complex analyses that require deeper reasoning
  • Claude Haiku — faster responses for straightforward questions

Custom instructions​

Add workspace-specific context that the agent uses for every query. This is useful for:

  • Domain-specific terminology (e.g., "a 'conversion' means a completed purchase")
  • Default conventions (e.g., "always use weekly time groups" or "our conversion window is 7 days")
  • Business context (e.g., "our fiscal year starts in April")
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Custom instructions apply to all agent queries in the workspace. Keep them concise and focused on context that would help the agent give better answers for your specific product and data.

Getting better results​

The agent discovers events, properties, and dimensions from your configured data catalog. The quality of its answers depends directly on how well-organized your analytics data is — better naming, organization, and completeness means better insights.

Here are actionable ways to improve the agent's output:

  • Use descriptive display names — if your raw column names are cryptic (e.g., evt_pg_vw), add clear display names (e.g., "Page View") so the agent can find the right events
  • Create custom events for key business actions — this gives the agent clean, meaningful concepts to work with instead of raw event table names
  • Configure dimension tables for user attributes you frequently analyze — the agent uses these for breakdowns like "by country" or "by plan"
  • Add property descriptions — descriptions help the agent understand what a property means and when to use it for filters and breakdowns
  • Keep your catalog up to date — re-index after adding new tables or columns so the agent has access to your latest data
  • Use custom instructions (see above) to give the agent domain context it can't infer from the data alone