Eppo provides an end-to-end experimentation platform that integrates feature flagging, statistical analysis, and personalization capabilities. The platform enables data teams, engineers, marketers, and product managers to run trustworthy, self-serve A/B tests and controlled rollouts. Its warehouse-native architecture ensures data governance and rigorous measurement against core business metrics without data egress.
Funding
$51.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many organizations struggle to implement effective A/B testing due to complex data analysis, potential data integrity issues, and lengthy analysis cycles. Traditional experimentation platforms often lack seamless integration with existing data warehouses, leading to data silos and increased overhead. This can result in delayed insights, unreliable results, and ultimately, poor decision-making.
Solution
Eppo offers an experimentation and feature management platform designed to streamline A/B testing and ensure data-driven decision-making. By leveraging a warehouse-native architecture, Eppo automates experiment analysis, reduces analysis cycles, and maintains data integrity. The platform provides feature flags for controlled rollouts and out-of-the-box reporting, enabling organizations to easily implement and scale their experimentation programs. Eppo's statistical engine and metric governance tools help minimize the risk of false positives and ensure that experiments are aligned with key business objectives.
Target Audience
Eppo is designed for data scientists, product managers, and engineers in organizations of all sizes who are looking to implement a data-driven culture of experimentation.
Features
- Warehouse-native architecture for seamless integration with existing data infrastructure
- Automated experiment analysis with out-of-the-box reporting and slice-and-dice capabilities
- Feature flags for A/B testing, feature gates, controlled rollouts, and kill switches
- Advanced statistical engine with sequential, fixed sample, and Bayesian frameworks
- CUPED variance reduction for faster experiment duration
- Metric governance tools for defining and controlling key business metrics
- Role-based access control and data privacy features
- Integrations with popular data and analytics tools