% Percentile Metrics

Statsig Product Updates
< All updates
3/18/2024

Support for Percentile Metrics

We're excited to announce Percentile metrics on Statsig Warehouse Native! Percentiles are often used to optimize app performance, understand feature adoption or even manage resource utilization when experimenting on backend infra and AI models.

Percentiles are particularly useful when applied to metrics that exhibit large variances. They also help understand the distribution of a metric, and can be critical to understand outliers or unusual metric behaviors. Customers can now visualize understand impact (or even alert on) p90, p95, p99, p99.9 or any other percentile.

Reach out in Slack if you want to opt into this! If you're interested in the underlying math, we'll be writing about it but it's loosely patterned on the thinking here - Applying the Delta Method in Metric Analytics: A Practical Guide with Novel Ideas.

image

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
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
We use cookies to ensure you get the best experience on our website.
Privacy Policy