Eppo is an AB experimentation platform designed to drive metrics and reliably learn. Whether running product, growth, or machine learning experiments, Eppo centralizes reports and automates all analytical workflows.
Rigor, visibility, and transparency. That is Eppo. Eppo puts everyone on the same page. Everyone is using the same picture and the same numbers to understand experiment results. It is no longer a game of telephone where a data scientist analyses an experiment, writes something up, shares it with the product owner, and then the product owner crafts their narrative and shares it with executives. Now, executives have very simple, easy access to look at the result of an experiment, which all use the same standardized definitions for metrics.
Our team is very happy with the way we're running experiments with Eppo across front-end, back-end and Machine Learning use cases. Our business stakeholders now utilize the experiment results without questioning it, and our data team can self-serve using Eppo’s intuitive interface. I'm confident that Eppo is going to be the leader in the experimentation and product analytics space.
Switching to Eppo has led to a massive improvement in the quality of our experimentation analysis. With Eppo, our Product team is confident that their tests are bug-free and they are making decisions based on true metric impact, not noise. Product Managers are spending 50% less time making dashboards and debugging issues, which leaves more time to develop the features our users want.
Before learning about Eppo, we weren't aware of how much analyst time we could save. Now that all of our growth experimentation runs through Eppo, we're gaining at least half an FTE worth of product analyst time. This is time that our analysts can be spending uncovering insights rather than checking on experiments. Integrating Eppo into our systems and workflow was straightforward — we went from discussions to value in less than a month.
Eppo is designed to centralize experimentation across your entire organization. Our differentiated architecture unites feature flags and experiments, and integrates with your existing data infrastructure and engineering workflows.
Run experiment scenarios with self-serve power analysis. Centralize and coordinate experiment sequences across teams.
Easily integrate with existing feature flags, or use Eppo’s feature flag SDK to confidently launch, remotely configure, and rollout experiments from a common UI
Trust that experiments are healthy with automated Slack alerts for traffic imbalances, anomalous metric drops, instrumentation gaps, and data pipeline errors.
Bring teams together with beautiful, accessible reports. Grow a scientific culture with centralized, consistent scorecards built around core business metrics.
Go deeper on experiment results and understand root causes. Slice results
by core subject segmentations using warehouse data.
Eppo applies bleeding edge statistical methods to warehouse-based business metrics, controlling false positive and false negative rates.
No reconciling of results against black box tools
Native workflows for eng to implement, data to measure, product to run the operation
On-cloud compute means no egressing user data
Any experiment use case, one trusted process
Innovation comes with wide participation in product science
Scale analytical power without high expertise headcount
Some ways in which Eppo can help you:
Turn power users into net promoters with shareable experiences
Activate new users by helping them see value, quickly
Reduce friction and increase focus across core workflows
Don’t need experimentation quite yet? Eppo includes a complete and reliable feature flagging toolkit out of the box for your engineering workflow: SDKs for your stack, feature gates, advanced targeting, kill switches, manual opt-ins. Use these features to decouple deploys from releases, and add on experimentation independently any time you want.