Platform
Resources
Docs Blog Pricing
Sign In Book a Live Demo

🧲 Group-by in Retention Analysis

Statsig Product Updates
< All updates
10/18/2024

Akin Olugbade

Product Manager, Statsig

🧲 Group-by in Retention Analysis

We’ve added group-by functionality to retention charts, enabling you to break down your retention analysis by various properties and gain deeper insights into user behavior. This feature allows you to segment your retention data across event properties, user properties, feature gate groups, and experiment variants.

Group-By in retention charts is available for:

  • Event and User Properties: Break down retention based on event and user properties such as location, company or different context about an event or feature..

  • Feature Gate Groups: Understand retention among different user groups gated by feature flags.

  • Experiment Variants: Compare retention across experiment groups to see how different variants impact user retention.

Expanded support for group-by in retention charts is rolling out today.

Join the #1 experimentation community

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

Try Statsig Today

Get started for free. Add your whole team!
Sign up for Free Test Drive Now

Why the best build with 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