Feature Rollout

A feature rollout is the structured process you use in software development to introduce new features or improvements. This method involves a phased and controlled release, enabling you to manage the deployment effectively. Here’s why this matters:

  • Incremental testing: You can test new features with a small group of users to catch and fix bugs before a full release.

  • Optimization based on feedback: By gathering input from initial users, you can refine the feature based on real-world use.

  • Reduced risk: Gradual rollouts help prevent widespread issues, contributing to a more stable product launch.

This approach not only enhances the stability of new features but also ensures that they meet user expectations and business objectives efficiently.

Examples of feature rollout

Let's look at how different companies apply feature rollouts in real-world scenarios:

  • Tech Company A tests a new user interface by initially releasing it to 10% of their user base. This allows them to collect feedback and fine-tune the interface, ensuring it meets user expectations before a broader deployment.

  • E-commerce Platform B introduces a streamlined payment system, starting with a regional test. This strategy helps them understand regional acceptance and iron out any operational kinks.

  • Social Media Platform C experiments with a new content algorithm on a select group of users. Monitoring engagement and system performance helps them ensure the algorithm performs well across diverse user groups before a global launch.

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