Apache Superset for Product Analytics 2026

Apache Superset, combined with a well-designed event schema, is a solid alternative to Mixpanel or Amplitude for product analytics. With a bit of initial modeling, you get the same funnel, cohort, and feature adoption analysis capabilities, with sovereignty over your data. This guide details the stack and essential dashboards in 2026.

1. Why Superset for product analytics?

• Cost: Mixpanel/Amplitude bill by event volume, quickly very expensive at scale;
• Sovereignty: your data stays in your warehouse;
• Flexibility: free SQL, custom modeling;
• Integration: same tool for business, marketing, product.

If you want to start immediately, TVL Managed Superset offers a preconfigured product analytics dashboard on Pro+ instances.

2. Product analytics data stack

1. Tracking: Snowplow, Segment, RudderStack, or homemade tracking;
2. Storage: ClickHouse (best fit for events), BigQuery, Snowflake;
3. Modeling: dbt in layers events → sessions → metrics;
4. BI: Apache Superset connected to marts.

3. Typical event schema

CREATE TABLE fct_events (
  event_id UUID PRIMARY KEY,
  user_id INT,
  session_id UUID,
  tenant_id VARCHAR,
  event_name VARCHAR,
  event_at TIMESTAMP,
  properties JSON,
  page_url VARCHAR,
  referrer VARCHAR
);

4. Essential dashboards

Dashboard 1 — Product overview

• DAU / WAU / MAU;
• Stickiness (DAU/MAU);
• Sessions per user;
• Time spent per session;
• Top 10 features used.

Dashboard 2 — Activation funnel

From signup to first value, step by step. See funnel analysis.

Dashboard 3 — Feature adoption

• % users having used each feature;
• Adoption by segment (free / paid);
• Adoption evolution month over month;
• Time to first use of a feature.

Dashboard 4 — Cohort retention

See cohort analysis.

This configuration is applied by default on TVL Managed Superset, which follows community best practices.

5. Key product KPIs

KPI	Formula
DAU	Distinct active users today
WAU	Distinct active users over 7 rolling days
MAU	Distinct active users over 30 rolling days
Stickiness	DAU / MAU (target > 20% B2C, 50% B2B)
Activation rate	% signups having reached the value moment
Time to value	Median delay signup → activation

6. Advanced patterns

• Behavioral cohorts: users having used feature X within 7 days following signup;
• Power user definition: users performing critical action 3+ times a week;
• Churn prediction: engagement drop, pre-churn signal;
• A/B test analysis: compare cohorts by variant.

7. Limits vs Mixpanel/Amplitude

• UI: Mixpanel has a UI optimized for non-tech; Superset requires SQL;
• Funnel definitions: more straightforward in Mixpanel;
• Notebook analytics: Amplitude excels, Superset less so;
• Maintenance: Mixpanel is SaaS, Superset requires infra.

For a very non-technical product team, Mixpanel remains more accessible. For a data-mature team, Superset offers unbeatable flexibility and cost.

8. Conclusion

Apache Superset for product analytics requires an initial investment (event modeling, dbt) but pays back quickly in flexibility and savings. For a B2B SaaS with a data team in place, it's typically the right choice.

Want the benefits of Apache Superset without the friction of installation and maintenance? Deploy your instance in 3 clicks with TVL Managed Superset, hosted in Europe (OVHcloud, Roubaix, France).

For more: SaaS metrics, cohort analysis, funnel analysis.