Frequently Asked Questions

A curated summary of the top questions asked on our Slack community, often relating to implementation, functionality, and building better products generally.
Statsig FAQs

Can I get sticky results for an A/B test based on IP address?

Statsig does not support sticky results for A/B tests based on IP address. The primary identifiers used for consistency in experiments are the User ID and the Stable ID. The User ID is used for signed-in users, ensuring consistency across different platforms like mobile and desktop. For anonymous users, a Stable ID is generated and stored in local storage.

While the IP address can be included in the user object, it's not used as a primary identifier for experiments. The main reason is that multiple users might share the same IP address (for example, users on the same network), and a single user might have different IP addresses (for example, when they connect from different networks). Therefore, using the IP address for sticky results in A/B tests could lead to inconsistent experiences for users.

If you want to maintain consistency across a user's devices, you might consider using a method to identify the user across these devices, such as a sign-in system, and then use the User ID for your experiments.

For scenarios where users revisit the site multiple times without logging in, there are two potential options:

1. Run the test sequentially, only control at first, then only test group. This is known as Switchback testing. You can learn more about it in this blog post and the technical documentation.

2. Offer a way to switch between control/test group visually for the user so they can bounce back to the behavior they'd expect from being on another device.

However, if there's a lengthy effect duration, Switchback may not be ideal. If you are able to infer the IP address, you can use this as the user identifier (maybe even as a custom identifier) and randomize on this. But be aware that skew in the number of users per IP address may introduce a significant amount of noise. You may want to exclude certain IP addresses from the experiment to get around this.

The skew comes from IP addresses that represent dozens if not hundreds of users. This can skew some of the stats when we try to infer confidence intervals. For example, instead of a conversion rate of 0/1, or 1/1, this metric looks like 36/85. This overweights both the numerator and denominator for this "user" which can skew the results.

Join the #1 Community for Product Experimentation

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.
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.
Karandeep Anand
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.
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.
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.
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy