Platform
Resources
Statsig vs. Adobe (Target + Analytics)
Statsig is the leading experimentation platform that empowers teams to ship faster, automate a/b testing, and make data-driven decisions at scale.
Adobe Target and Analytics are tailored for web-based applications, specializing in website personalization and marketing campaigns, but with a more limited scope compared to a comprehensive experimentation platform.
Statsig's four main advantages over Adobe Target and Analytics are:
Unification under one platform
Flexible targeting and near-time analysis of all metrics
Advanced statistical capabilities
Scalability and reliability
Statsig vs. Adobe (Target + Analytics)
Feature Comparison
Feature flags
Enable or disable functionality in your app without deploying new code, allowing for safer rollouts and quicker iterations.
A/B testing
Compare different versions of a feature to determine which performs better, driving data-informed product decisions.
Analytics
Provides comprehensive data analysis tools to gain deeper insights into user behavior and feature performance.
Single snapshot view of all metrics for a feature rollout
Provides a consolidated dashboard to view key metrics impacted by a feature release, enabling quick assessment of performance.
Mutually exclusive experiments (without custom scripts)
Ensures that users are only in one experiment at a time, eliminating cross-experiment contamination and providing cleaner data.
Variance reduction (CUPED)
Utilize pre-experiment data to reduce variability in experiments, enhancing the accuracy and efficiency of results.
Holdouts
Reserve a control group that is not exposed to the feature, serving as a benchmark to measure true impact.
Custom ID support
Allows the use of unique identifiers for users or entities in experiments, offering flexibility in data segmentation and analysis.
Multi-armed bandit experiments
Continuously optimize and allocate more traffic to winning variations, even as the experiment is still running.
Sequential testing
Continuously monitors experiment results, enabling early stopping for success or failure, thus saving time and resources.
Switchback testing
Alternate between control and treatment states over time, ideal for environments with network effects or shared resources.
* This comparison data is based on research that was conducted in November 2023.
Why the best build with us
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