Statsig
Statsig consolidates feature flags, A/B testing, and product analytics into a single platform with warehouse-native architecture, enabling product teams to ship faster and experiment with the rigor of top-tier tech companies.
Last updated May 11, 2026 by ATDb automated enrichment · Connections updated May 14, 2026
- Industry
- Experimentation & Feature Management / MarTech
- Business Model
- SaaS
- Target Market
- Mid-Market and Enterprise
- Employee Count
- 51-200
- Funding
- $43.5M
- Revenue Range
- $10M-$50M ARR
- API Available
- Yes
Emerging challenger to legacy experimentation platforms, positioned as the all-in-one modern alternative with warehouse-native capabilities and strong statistical rigor
Statsig is a feature management and product experimentation platform founded in 2021 by former Facebook engineers, including CEO Vijaye Raji. The company was built to democratize the kind of sophisticated experimentation infrastructure that only large tech companies like Facebook, Google, and Microsoft had previously been able to build internally. Statsig's unified platform combines feature flags, A/B testing, product analytics, session replay, and a data warehouse-native architecture into a single cohesive environment, eliminating the need for teams to stitch together multiple disparate tools. The platform is designed for high-velocity product teams that need to move fast without sacrificing statistical rigor. Statsig's warehouse-native offering allows companies to run experiments directly on top of their existing data infrastructure (Snowflake, BigQuery, Databricks, etc.), giving them full data ownership and eliminating data duplication concerns. Its CUPED and sequential testing methodologies provide enterprise-grade statistical accuracy, while its real-time analytics layer enables teams to monitor experiment results and feature rollouts as they happen. Statsig has gained significant traction among technology companies ranging from fast-growing startups to large enterprises, positioning itself as a credible alternative to legacy tools like Optimizely and LaunchDarkly, as well as homegrown experimentation systems. The company competes in the broader experimentation and feature management market, which is increasingly seen as critical infrastructure for product-led growth organizations. Statsig's strong engineering pedigree, competitive pricing, and all-in-one platform approach have made it a notable player in the MarTech and product analytics ecosystem.
Feature Flags
Gradual rollouts, targeted feature gating, and kill switches with real-time control over feature exposure across user segments
A/B Testing & Experimentation
Rigorous experiment framework with CUPED variance reduction, sequential testing, and Bayesian/frequentist statistical methodologies
Product Analytics
Real-time event-based analytics with funnels, retention, and user journey analysis tied directly to feature and experiment data
Session Replay
Visual session recording and playback to understand user behavior in context of feature rollouts and experiments
Statsig Warehouse Native
Run experiments and compute metrics directly on top of existing data warehouses like Snowflake, BigQuery, and Databricks without data leaving the customer environment
Autotune
Multi-armed bandit optimization that automatically allocates traffic to winning variants in real time
Metrics Catalog
Centralized metric definitions and a shared metrics layer ensuring consistency across experiments and analytics
Holdouts
Global holdout groups to measure the cumulative impact of all shipped features over time
Dynamic Config
Remote configuration management allowing teams to change app behavior without code deployments