Introduction to Product Analytics
Altertable Product Analytics lets you send events and identity updates from your application, then query that data in the same lakehouse as the rest of your business data.
That means product questions do not live in a separate analytics silo. You can join feature usage with revenue, support activity, billing state, or any other data already available in Altertable.
How it works
Most teams use Product Analytics in a simple flow:
- Enable Product Analytics for the environment from Catalogs.
- Authenticate an SDK or direct API client with a Product Analytics API key.
- Identify users once you know who they are so future analysis can connect activity across sessions and devices.
- Track events for the moments that matter in your product, such as sign-up, activation, conversion, and retention.
- Query the resulting tables with SQL or use them in dashboards and insights.
The ingestion flow is straightforward, but the important difference is where the data lands: once enabled, raw events, identities, and session-derived tables are written directly into a managed Altertable catalog for that environment.
Built-in Product Analytics Catalog
When you enable Product Analytics, Altertable creates a read-only product_analytics catalog in that environment. Altertable manages this catalog for you. As your application sends events and identity updates through the Product Analytics API, Altertable writes the resulting data into these tables:
Table | Description |
|---|---|
main.events | Raw events (everything /track receives) |
main.identities | Raw identities (everything /identify receives) |
main.identity_distinct_ids | Raw distinct IDs mapping |
main.identity_distinct_id_overrides | Raw distinct ID overrides (impacted by /alias) |
analytics.events | Identity-resolved events |
analytics.identities | Alias & anonymous-resolved identities |
analytics.web_sessions | Aggregated session data |
analytics.web_pageviews | Page-level analytics |
The main.events and the main.identities tables are the raw building blocks. The analytics.web_sessions and analytics.web_pageviews tables are derived views that make common web analytics questions easier to answer.
Enabling Product Analytics also provisions the related built-in models and product analytics workflows for that environment. If Product Analytics is not enabled, the related navigation and product-behavior insight types stay hidden.
Why this model is useful
Because product analytics data lives in the same lakehouse as your other data sources, you can:
- Join product events with business data: Combine behavioral data with revenue, margins, or support data to answer questions like "which feature drives higher LTV?"
- Query across all data sources: Use SQL to query product events alongside data from your external catalogs in your lakehouse
- Build unified dashboards: Create visualizations that combine product analytics with business metrics in a single view
- Use AI assistance: Use Altertable's AI agents to surface insights across both product and business data
New to insights? Learn about the insight types and when to use them in our Insights guide.
Typical setup flow
- Set up authentication so each environment can send data with the correct API key.
- Install an SDK for your client or server runtime.
- Identify users after login or account creation so behavior is tied to a stable user ID.
- Track product events for the actions you want to measure.
Product analytics data is queryable via SQL as soon as events and identities are ingested, so it fits naturally into existing warehouse-style analytics workflows.