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Experimentation Week '24: July 15-19.
Statsig has been working on a suite of new, advanced experimentation and statistical methods over the past months. July 15th-19th, we'll annouce a new one each day. Tune into our LinkedIn and Twitter to be the first to see what we launch.
Monday: Meta-Analysis
Learn more by analyzing your experiments on a team or company-level, across a timeline or metric view.
Tuesday: Stratified Sampling
Increase the reliability of your tests when some users or customers contribute disproportionately to a certain metric, by intelligently assigning them to test and control groups.
Wednesday: Differential Impact Detection
Identify cases where some user groups are impacted disproportionately by an experiment, helping you find bugs or understand when the takeaway from an experiment might be different for a sub-population.
Thursday: Interaction Detection
Know when the impact of users being exposed to two concurrent experiments could be different than exposure to one or the other.
Friday: Collaboration
Collaborate on your experiment setup, enforce best practices across your experiments, save experiment notes, and export the takeaways to share across the team.
What builders love about us
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering