Statsig
Product experimentation platform combining feature flags, A/B testing, analytics, and session replay on one event pipeline.
Used by OpenAI, Notion, Atlassian; acquired by OpenAI in 2025 with the platform continuing to operate.
Ownership
- Sold to Amplitude · closed May 2026 · source · In the Martech Market Report
On 5 May 2026 OpenAI handed the Statsig platform, brand and customers to Amplitude, which now runs and develops Statsig while the original team stays at OpenAI.
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Statsig Pros & Cons
Key strengths and limitations to consider, drafted by an AI model from public sources
Strengths
- Combines feature flags, experimentation, analytics, and replay on one event model
- Supports warehouse-native analysis on Snowflake, BigQuery, Databricks, and more
- Offers free usage for 2 million metered events per month
- SDKs support deterministic assignment for experiments, layers, gates, and configs
- Exports experiment exposures to tools including Braze and Datadog
Limitations
- Pro pricing applies separately to each Statsig project
- Cloud projects support only one outbound data connection at a time
- Warehouse Native requires warehouse write access for staging tables
- Usage pricing can rise with high event volume and event dimensions
- Standalone product analytics is limited to Enterprise contracts
Ideal For
Who benefits most from Statsig, drafted by an AI model from public sources
Quick Analysis
Statsig competes in the product experimentation and feature-management market, rather than in web-only conversion-rate optimization. It provides SDK-based assignment, feature gates, dynamic configuration, experiment analysis, metrics, product analytics, and session replay on shared event infrastructure. Since May 5, 2026, Statsig's product, brand, and customers have been part of Amplitude, while the platform continues to operate across hosted and warehouse-native deployments.
Its strongest fit is technically mature digital-product organizations that want to connect release controls to causal measurement, rather than operate feature flags and analytics as separate tools. Compared with LaunchDarkly and Split, Statsig has deeper built-in experimentation and product analytics; compared with Optimizely, it is better aligned to SDK-led product releases and warehouse data; compared with Eppo and GrowthBook, it offers a more complete hosted feature-management and analytics stack. Warehouse Native is a meaningful differentiator for teams that need experiment computation against Snowflake, BigQuery, Databricks, Redshift, or Athena data.
Evaluate Statsig when experimentation velocity depends on engineering-owned flags, reliable exposure logging, and data-warehouse measurement. Buyers already standardized on Amplitude should assess roadmap and commercial alignment following the acquisition; buyers preferring independent, open-source, or self-hosted control should compare GrowthBook and PostHog. Validate event-volume economics, warehouse query costs and permissions, identity design, metric governance, and whether a single outbound data connection meets integration needs.
A SaaS product team rolls out a new AI workflow to 5% of users while tracking retention and errors.
A mobile app team runs an A/B test on onboarding steps using iOS and Android SDK assignment.
A marketplace computes experiment lift from Snowflake revenue tables without exporting raw metrics.
An engineering team links Datadog alerts to automatic feature-gate shutdown during a production incident.
A lifecycle team sends Statsig experiment exposure attributes to Braze for treatment-specific campaigns.
A product analyst reviews sessions from an experiment cohort to explain a conversion-rate decline.
Capabilities
Core Capabilities
Also Supports
Pricing
The free Developer plan includes 2M metered events per month, unlimited flag and config checks, 50,000 session replays per month, 1-year analytics retention and unlimited seats.
Checked and not offered
One capability that other experimentation tools are built around, which Statsig does not appear to cover. Each was checked against Statsig's own documentation in three separate AI passes, and only a majority verdict is recorded — the count is on each row.
A gap is not a fault — a product that does one job well is a reasonable thing to buy. It is only expensive when you find out after signing.
Statsig Overview documents analytics and experimentation but no survey or feedback collection module.
Checked: https://docs.statsig.com/welcome· 3 of 3 passes agreed it is absent
Read from public documentation, and documentation lags shipping. If you work at Statsig and this is out of date, and we will record the correction against your name.
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