Product analytics

Understand how people use your product, how that behavior turns into revenue, and what changed before the business notices — all from the same governed lakehouse.

How teams adopt product analytics

Capture trustworthy events, connect behavior to business outcomes, then operate dashboards and agents from the same source of truth.

Diagram: product events flowing into the lakehouse for analysis

Capture events you can trust

Product analytics only works when the event stream is clean enough to trust. Altertable captures product behavior directly into the lakehouse, where it can be queried next to the rest of the business.

Start with decision-grade events
Track the moments that actually explain growth: sign-up, activation, conversion, retention, and the product actions that move them.
Keep identity from drifting
Tie anonymous and known behavior together early so cohorts, journeys, and revenue views follow the same customer across devices and sessions.
Use the data while it is fresh
Events become available for SQL, dashboards, and follow-up analysis quickly, without waiting on a separate analytics warehouse to catch up.

What product and growth teams get

Clean instrumentation, live joins with the business, fast exploration, and governed metrics that work for humans and agents.

One truth for product and revenue

Behavior, billing, margin, and support can be analyzed together in the same lakehouse, without reverse-ETL stitching or duplicate metric logic.

Instrumentation you can trust

SDKs in major languages and stable identity keep events useful as the product evolves, instead of creating a stream of free-form properties teams have to clean later.

Exploration stays fast

Cohort, funnel, and retention analysis should invite the next question, not punish it. Keep drill-downs responsive even as event volume grows.

Controls every surface inherits

Set permissions, residency, and auditability once at the lakehouse layer, then let SQL, dashboards, APIs, and agents inherit the same guardrails.

Core product analytics capabilities

Clean event capture, identity-aware analysis, business joins, and shared definitions in the same operational lakehouse.

Events live with the business

Product events land in the same lakehouse as revenue, support, and operational data, so activation, retention, and conversion can be analyzed against the rest of the company.

Clean events from day one

SDKs in the major languages your team already uses make clean event capture easy. Anonymous and known behavior can still be tied together as users move across sessions and devices.

Behavior meets revenue

Answer questions like which features drive LTV, margin, or expansion without stitching product analytics to finance data after the fact.

Same metrics for every surface

Funnels, segments, dashboards, SQL, and agents can all read from the same definitions, so teams stop reconciling why every tool counts the product differently.

Your language, your stack

SDKs and adapters in the languages your team already uses,
so you ship without changing how you work.

Product Analytics API

import { altertable } from '@altertable/altertable-js';

// Initialize with your API key
altertable.init('YOUR_API_KEY', {
  environment: 'production',
});

// Track a user event
altertable.track('checkout_completed', {
  revenue: 49.99,
  plan: 'pro',
  currency: 'USD',
});

// Identify a user
altertable.identify('user_abc123', {
  email: '[email protected]',
  plan: 'pro',
});

Explore more use cases

Other workloads that share the same engine and governance.

Analytical Database

Store data in Altertable or connect the systems you already have, then query everything through one fast SQL engine across product, business, and operational data.

Self-Serve BI

Build dashboards and visualizations on the same live engine used for SQL, then expose trusted metrics and insights to AI agents and collaboration tools through MCP.