Client-Side Testing

Client-side testing refers to the process of testing the performance and functionality of a web application or software in the client's environment. This type of testing is typically performed on client-side applications like mobile apps and websites.

Characteristics of Client-Side Applications

Client-side applications usually have the following common characteristics:

  1. Serves a Single User at a Time: The user object is provided to the application at initialization time. For example, in the case of Statsig, the SDK makes a single network request to the Statsig server to fetch all the feature gates and experiment values for the given user. This way, checking feature gates or experiments uses local values rather than issuing more network requests, and every event log is associated with the same user implicitly.

  2. Not in a Secure Environment: Client-side applications operate under the assumption that everything is public. For instance, Statsig provides client API keys for use in client SDKs, and the values their server returns about your features and experiments are all public.

Device-Level Experiments

Statsig takes advantage of the single-user characteristic and provides experiments at the device level. This ensures that users get a consistent experience before and after sign-in/up, as well as getting events generated post-sign-in/up attributed correctly. Many customers find this feature useful when running experiments on improving their apps’ sign-up flow.


Let's say you're running an experiment to test a new landing page design. You can use Statsig's client-side SDK to check if the feature gate for the new design is on for a particular user. If it is, you show the new landing page; if not, you show the old one. This allows you to test the new design with a subset of your users, gather data on its performance, and make informed decisions based on the results.

Remember, client-side testing is crucial for ensuring that your application provides a seamless and enjoyable user experience across different environments.

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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
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