Product Analytics

Product Analytics turns the data and metrics you’ve already configured in GrowthBook into a general-purpose analytics workspace. Visualize KPIs, explore raw events, run ad-hoc SQL, and share curated views with your team — without launching an experiment. Product Analytics is made up of two surfaces:

• Explorer — Build one-off charts from your metrics, fact tables, or raw warehouse tables. Ask questions in natural language, or configure explorations manually.
• Dashboards — Combine multiple explorations, SQL queries, and markdown into a single shareable view that auto-refreshes on a schedule.

Both surfaces read from the same data sources, fact tables, and metrics you already use for experimentation, so there’s no separate event pipeline or instrumentation to set up.

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Plan Availability

The Explorer is currently in Beta. We’re actively expanding the supported chart types, dimensions, and data sources.

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Getting Started

1. Connect a data source so GrowthBook can run queries against your warehouse. If you don’t have a warehouse yet, you can use a Managed Warehouse to get started without provisioning your own.
2. Define fact tables and metrics — these power the Metric and Fact Table explorers, and they’re what dashboard blocks visualize.
3. Open Product Analytics in the left sidebar to start exploring.

The first time you point an explorer at a data source, GrowthBook builds an information schema — an index of databases, schemas, tables, and columns — so the Fact Table and Data Source explorers can show you what’s available. This is a one-time, per-data-source step that runs in the background.

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What’s Next

• Build your first chart in the Explorer.
• Assemble a dashboard that combines multiple charts, SQL queries, and context.
• Connect Custom SQL Reports for analyses that don’t fit a structured explorer.