Eppo

Name: Eppo
Author: Eppo

Warehouse-native experimentation platform for data-driven teams.

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About Eppo

Eppo is a warehouse-native experimentation platform designed to help product and data teams conduct statistically rigorous A/B tests directly within their existing data infrastructure. By connecting to a company's data warehouse, it eliminates the need for complex data pipelines or proprietary SDKs, ensuring data integrity and consistency across the organization. Its primary differentiator is its ability to provide self-serve, trustworthy experimentation insights that leverage a company's single source of truth, enabling teams to make faster, evidence-based product decisions without compromising on analytical depth.

Type:SaaS

API:Available

Pros & Cons

Pros

Connects directly to existing data warehouses to maintain a single source of truth.
Provides statistically rigorous analysis that reduces false positives in A/B testing.
Enables self-serve experimentation for non-technical product managers and designers.
Eliminates the need for maintaining custom data pipelines or external tracking SDKs.
Supports complex metric definitions directly from SQL-based warehouse models.

Cons

Requires a mature data warehouse setup to function effectively.
Lacks a public free tier for small startups or individual developers.
Steeper implementation curve for teams without existing SQL-based analytics workflows.

Who Is This For?

Best For

Product Managers

Allows for rapid, data-backed feature iteration without constant dependency on data engineering teams.

Data Scientists

Provides a robust, statistically sound framework for managing complex experiments at scale.

Growth Teams

Facilitates high-velocity testing cycles by leveraging existing warehouse data for immediate insights.

Not Ideal For

Early-stage startups

The reliance on a mature data warehouse infrastructure may be overkill for teams without established data stacks.

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IndustriesData & Analytics Marketing

CategoriesAnalytics

Pricing

Eppo utilizes a custom enterprise pricing model tailored to the scale of data usage and experimentation volume, positioning itself as a premium solution for data-mature organizations.