Eppo

Eppo is a next-generation experimentation platform that allows product and data teams to run A/B tests and feature flagging with scientific rigor and advanced analysis. Built as a data warehouse-native tool, Eppo leverages your existing analytics database (like Snowflake or BigQuery) so that all experiment data is centralized, and analysis is done on the raw data for accuracy.

With Eppo, setting up a test involves defining experiment groups, metrics you care about, and then pushing the experiment to your app via Eppo’s SDK or integrations with feature flag systems. What sets Eppo apart is its AI-driven analytical capabilities: for every experiment, Eppo doesn’t just show you the overall lift or decline for the primary metric, it also automatically digs into segments and secondary metrics to uncover insights (for example, “this new feature improved conversion overall by 5%, but the lift was 10% for new users while being neutral for returning users”).

It can identify interaction effects or anomalies that you might not think to check. Eppo provides thoughtful statistical guardrails (like cuped variance reduction, sequential testing corrections, etc.) to ensure results are trustworthy, and it presents findings in a clear dashboard. It’s also built to handle experiments on machine learning model variants (helpful in the age of AI features), allowing rapid iteration on model versions by comparing outcomes.

Eppo’s interface enables collaboration — PMs, data scientists, and engineers can all view results and even add notes or hypotheses. Since Eppo connects to existing data infrastructure, it fits nicely into modern data stacks, and it can trigger alerts or send results summaries to Slack/Email. Recently acquired by Datadog, Eppo is likely to become even more integrated into monitoring and product analytics workflows.

Pricing typically targets mid-to-large tech companies, often on a usage or seats basis, and they often provide a sandbox or trial for evaluation. Overall, Eppo helps companies move faster with experimentation by automating analysis and ensuring that no insight is missed when evaluating new product features or changes.