Statsig vs. Split

Split is a legacy feature flagging solution, but many users are looking for an advanced platform with modern experimentation, analytics, and more.

Statsig's key advantages over Split are:
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Most advanced experimentation, trusted by OpenAI & Notion
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'Unscalable' customer obsession & support
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Product optimization as a first-class product
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Better for teams
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Warehouse-Native Experimentation & Analytics

Key Differences

Statsig and Split both offer feature flagging and experimentation platforms that help builders ship better products.
01

Most advanced experimentation, Trusted by OpenAI & Notion

Statsig's experimentation, based on best practices from Facebook, is trusted as the most advanced and battle-tested experimentation platform available. With functionality like CUPED, Meta Analysis, A/A Testing, Stratified Sampling and more, Statsig has all of the bells and whistles for those who need them.
02

'Unscalable' customer obsession & support

Rather than a regular support system with tickets and SLAs, support is the responsibility of the whole company, with a community Slack channel free for everyone, and dedicated Slack channels included for each Enterprise customer.
03

Product optimization as a first-class product

We've prioritized tooling to analyze user behavior and iteratively improve products as much as tooling to ship features throughout our entire experience. Our world-class experimentation and product analytics solutions are unparalleled in their feature sets, and are a fraction of the cost of competitors.
04

Better for teams

One of our core tenets is that we believe building products is a team sport. This is why we don’t charge based on seats: we believe everyone in the company should be in the Statsig Console, looking at dashboards, playing with data, and opting themselves in and out of new features to ensure they’re experiencing beta versions of the product.
05

Warehouse-Native experimentation & analytics

Using Warehouse Native Statsig means that you can define the metrics that back your experiments, feature flags and product analytics (beta) directly on top of your warehouse data, with support for Snowflake, Bigquery, Redshift, Databricks, and Athena. You can also use Statsig's infrastructure to track events, metrics and exposures, and store them in your own warehouse.

Feature Comparison

Basic experimentation

The basic features you need to measure feature impact.
Primary Metrics
Track core metric performance across variants
Experiment Templates
Pre-defined templates for experiments
Team-based Experiment Defaults
Default settings for teams in experiments
Bayesian
Support for Bayesian experimentation methods
Frequentist
Support for Frequentist experimentation methods
Recommended Run Times
Recommended durations for running experiments
Holdouts
Ability to create holdout groups not exposed to any experiment treatments
Mutually Exclusive Experiments
Ensure experiments do not interfere with each other
Cloud Hosted Option
Cloud-hosted experimentation supported
Warehouse Native Experimentation
Support for experimentation directly in your data warehouse
No-code experiments
Create experiments without coding

Advanced experimentation

Advanced features for more complex experimentation needs.
CUPED
Method to reduce experiment runtime and increase accuracy with historical data
Switchback Tests
Testing method when traditional A/B testing is not possible due to implementation or Network effects
Stratified Sampling
Assign experiment subjects intelligently across groups
Sequential Testing
Method to prevent early-peeking on A/B test results
Multi-armed Bandit
Explore and Exploit models for optimization
Winsorization
Reduce the influence of outliers
Bonferroni Correction
Adjust for multiple comparisons
A/A Tests
Run tests assessing if your experimentation program is set up correctly

Flag & experiment platform

Comprehensive features for flag and experiment management.
Unlimited Seats
Support for unlimited seats
Unlimited MAU
Support for unlimited MAU
Basic Feature Flags
Basic feature flag support
Unlimited Free Feature Flags
Unlimited free feature flags
Percentage Rollouts
Support for percentage rollouts
Scheduled Rollouts
Support for scheduled rollouts
Environments
Support for multiple environments (dev, staging, prod)
Metric Alerts
Alerting for metrics
Flag Lifecycle Management
Manage the lifecycle of flags
In-Console Collaboration
Out-of-the-box collaboration features in the console
Approval Flows
Support for approval workflows
SDKs for all Major Languages
Support for SDKs in all major programming languages
Edge SDKs
Support for edge SDKs
No-code Dynamic Configs
Support for no-code dynamic configurations
Impact Measurement/Analyses
Measurement and analysis of impact
Feature Gate Rollout Analysis
Analysis of feature gate rollouts
Change Logs History with Revert
Change logs history with revert option

Warehouse-native experimentation

Native support for popular data warehouses.
Snowflake Support
Support for Snowflake data warehouse
Bigquery Support
Support for Bigquery data warehouse
Redshift Support
Support for Redshift data warehouse
Databricks Support
Support for Databricks data warehouse
Athena Support
Support for Athena data warehouse
Define Metrics with SQL Queries
Ability to define metrics using SQL queries
Flexible Hybrid Cloud/Warehouse Solutions
Support for hybrid cloud and warehouse solutions
Compatibility with Other Assignment Sources
Compatible with other assignment sources
* This comparison data is based on research that was conducted in June 2024.
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Loved by customers at every stage of growth

See what our users have to say about building with Statsig
OpenAI
"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
SoundCloud
"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
Recroom
"Statsig has been a game changer for how we combine product development and A/B testing. It's made it a breeze to implement experiments with complex targeting logic and feel confident that we're getting back trusted results. It's the first commercially available A/B testing tool that feels like it was built by people who really get product experimentation."
Joel Witten
Head of Data
"We knew upon seeing Statsig's user interface that it was something a lot of teams could use."
Laura Spencer
Chief of Staff
"The beauty is that Statsig allows us to both run experiments, but also track the impact of feature releases."
Evelina Achilli
Product Growth Manager
"Statsig is my most recommended product for PMs."
Erez Naveh
VP of Product
"Statsig helps us identify where we can have the most impact and quickly iterate on those areas."
John Lahr
Growth Product Manager
"The ability to easily slice test results by different dimensions has enabled Product Managers to self-serve and uncover valuable insights."
Preethi Ramani
Chief Product Officer
"We decreased our average time to decision made for A/B tests by 7 days compared to our in-house platform."
Berengere Pohr
Team Lead - Experimentation
"Statsig is a powerful tool for experimentation that helped us go from 0 to 1."
Brooks Taylor
Data Science Lead
"We've processed over a billion events in the past year and gained amazing insights about our users using Statsig's analytics."
Ahmed Muneeb
Co-founder & CTO
SoundCloud
"Leveraging experimentation with Statsig helped us reach profitability for the first time in our 16-year history."
Zachary Zaranka
Director of Product
"Statsig enabled us to test our ideas rather than rely on guesswork. This unlocked new learnings and wins for the team."
David Sepulveda
Head of Data
Brex
"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
President
Ancestry
"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
"Statsig has enabled us to quickly understand the impact of the features we ship."
Shannon Priem
Lead PM
Ancestry
"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
"Working with the Statsig team feels like we're working with a team within our own company."
Jeff To
Engineering Manager
"[Statsig] enables shipping software 10x faster, each feature can be in production from day 0 and no big bang releases are needed."
Matteo Hertel
Founder
"We use Statsig's analytics to bring rigor to the decision-making process across every team at Wizehire."
Nick Carneiro
CTO
Notion
"We've successfully launched over 600 features behind Statsig feature flags, enabling us to ship at an impressive pace with confidence."
Wendy Jiao
Staff Software Engineer
"We chose Statsig because it offers a complete solution, from basic gradual rollouts to advanced experimentation techniques."
Carlos Augusto Zorrilla
Product Analytics Lead
"We have around 25 dashboards that have been built in Statsig, with about a third being built by non-technical stakeholders."
Alessio Maffeis
Engineering Manager
"Statsig beats any other tool in the market. Experimentation serves as the gateway to gaining a deeper understanding of our customers."
Toney Wen
Co-founder & CTO
"We finally had a tool we could rely on, and which enabled us to gather data intelligently."
Michael Koch
Engineering Manager
Notion
"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
Whatnot
"Excited to bring Statsig to Whatnot! We finally found a product that moves just as fast as we do and have been super impressed with how closely our teams collaborate."
Rami Khalaf
Product Engineering Manager
"We realized that Statsig was investing in the right areas that will benefit us in the long-term."
Omar Guenena
Engineering Manager
"Having a dedicated Slack channel and support was really helpful for ramping up quickly."
Michael Sheldon
Head of Data
"Statsig takes away all the pre-work of doing experiments. It's really easy to setup, also it does all the analysis."
Elaine Tiburske
Data Scientist
"We thought we didn't have the resources for an A/B testing framework, but Statsig made it achievable for a small team."
Paul Frazee
CTO
Whatnot
"With Warehouse Native, we add things on the fly, so if you mess up something during set up, there aren't any consequences."
Jared Bauman
Engineering Manager - Core ML
"In my decades of experience working with vendors, Statsig is one of the best."
Laura Spencer
Technical Program Manager
"Statsig is a one-stop shop for product, engineering, and data teams to come together."
Duncan Wang
Manager - Data Analytics & Experimentation
Whatnot
"Engineers started to realize: I can measure the magnitude of change in user behavior that happened because of something I did!"
Todd Rudak
Director, Data Science & Product Analytics
"For every feature we launch, Statsig saves us about 3-5 days of extra work."
Rafael Blay
Data Scientist
"I appreciate how easy it is to set up experiments and have all our business metrics in one place."
Paulo Mann
Senior Product Manager
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