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
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GENERAL

Can I use an IntersectionObserver with Statsig's `getExperiment` function to control user exposure timing and ensure accurate experiment metrics?

Date of slack thread: 6/13/24

Anonymous: Can I use an IntersectionObserver in combination with the getExperiment function from Statsig to control when a user is exposed to a variant of an experiment, and will this approach affect the assignment of users to the experiment or the calculation of experiment metrics?

Anonymous: getExperiment doesn’t determine the variant or triggers the experiment, it just gets the variant value for the experiment specified, which has been set by Statsig when initialising the app.

Anonymous: Metrics are calculated based on exposure stream. and that gets logged only when getExperiment is called so the combination of IntersectionObserver and getExperiment makes sense?

Anonymous: Not sure how you plan to use IntersectionObserver, but it sounds fine to me. Your understanding also sounds correct to me, “assignment” is done beforehand. getExperiment will trigger exposure events, and we use exposure events to calculate pulse result in our data pipeline.

Anonymous: I have a component that renders at the bottom of the page. So I wanted to enroll users into the experiment when they see the component (when it’s visible in the viewport). (To do this I am doing lazy rendering using IntersectionObserver). I do not want our metrics to be distorted by users who do not interact with the component.

Anonymous: So making use of getExperiment inside my component makes sense right?

Tore (Statsig): When you call getExperiment, an exposure is going to be logged - if you want to manually control exposure logging, you have to call getExperimentWithExposureLoggingDisabled or the equivalent for the SDK you are using. If it is not called until the component is rendered, then you should be good.

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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
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