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Statsig vs. Amplitude
While Amplitude is a strong tool for product analytics, Statsig is the platform of choice for companies looking for an all-in-one platform that connects data, decisions, and deployment.
Statsig's key advantages over Amplitude are:
Integration of analytics with experiments and flags
Unrivaled value
Customer obsession and hands-on support
Most advanced experimentation, trusted by OpenAI + Notion
Warehouse-native analytics + experimentation
Key Differences
01
Integration of analytics with experiments and flags
Statsig product analytics is built to work within the same platform as experiments and feature flags, allowing you to transform your product insights into action. Use flag/test ‘exposures’ as analytical metrics, breakdown other charts by flag and experiment group, and leverage product insights to decide what to build and test next.
02
Unrivaled value
Statsig offers the lowest unit rate and the most generous free tier in Product Analytics—without sacrificing features or performance. We never charge extra for group analytics or slicing and dicing by new criteria. By keeping costs low and analytics powerful, Statsig ensures that you get the best insights at the best price, every time.
03
Customer obsession and hands-on support
Our entire company takes responsibility for support. We offer a free community Slack channel, dedicated Slack for Enterprise customers, and direct access to senior leaders. We also provide flexible Proof-of-Concepts with no artificial deadlines.
04
Most advanced experimentation, trusted by OpenAI + Notion
Statsig’s platform—built by a team of ex-Facebook employees—features some of the most advanced capabilities on the market including CUPED, Meta Analysis, A/A Testing, Stratified Sampling, Switchback testing and more. You can also define metrics on your own warehouse data, unlocking powerful experimentation capabilities.
05
Warehouse-native analytics & experimentation
Using Statsig’s warehouse native model means that you can define the metrics that back your experiments, feature flags and product analytics 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
Product Analytics
Metric drilldown
Analyze key metrics and user behavior over time
Funnels
Track user progression through key conversion flows
User journeys
Analyze the various paths users take as they navigate your product
Cohort analysis
Define and reuse cohorts based on common properties
Retention charts
Analyze retention rate between any two events
Distribution charts
Visualize the range of user experiences across your product
Event Log Analysis
Perform segmentation analysis and quickly debug issues by viewing individual event logs
Dashboards with templates
Build custom dashboards to track performance or use pre-built templates
Analyze by Experiment and Feature Flag Group
Group metrics by experiment or feature flag group
Use Gate and Experiment exposures as metrics for analytics
Exposures for gates and experiments are automatically generated as metrics to use in analytics
Filter and drill down by user and event properties
Slice and dice your data in analytics by user and event properties
Autocapture
Capture user events automatically
Topline alerts
Alerts on a metric’s topline value, independent of any experiment or gate
Core Experimentation
Bayesian & Frequentists methods
Support for both Bayesian and Frequentist methods
Mutually exclusive experiments
Ensure concurrent experiments do not interfere with each other
Holdouts
Create holdout groups not exposed to any experiment treatment
Experiment templates and summaries
Save experiment templates and export formatted reports
No-code experiments
Create experiments with a visual editor
High level of metric flexibility
Percentile, ratio, first/latest value, capped, and more available out-of-the-box
In-platform collaboration
Support for team collaboration and discussions within the console
Built-in product analytics
Dive deeper into metrics and continuously develop new ideas to test
Bonferroni correction
A statistical method that reduces the probability of false positives by adjusting the significance level for multiple comparisons
CUPED
A technique which leverages user information from before an experiment to reduce variance, and increase confidence in metrics
Winsorization
A way of handling the impact of extreme values or outliers
Advanced Experimentation
Stratified sampling
Balance heterogeneous subjects across experiment groups
Switchback testing
Run tests when traditional randomization isn't feasible
Sequential testing
Prevent early-peeking on A/B test results
Multi-armed bandits
Continuously optimize allocation toward high-performing variant
Geo-based experiments
Measure the incremental impact from marketing initiatives
Interaction detection
Detect effects of overlapping experiment
Heterogeneous treatment effects
Identify classes of users that are differentially impacted
Benjamini-Hochberg procedure
Control the false discovery rate in multiple hypothesis tests
Meta-analysis views
Generate meta-level insights from your corpus of experiments
Knowledge base
Maintain a searchable repository of experiment learnings
Feature Flags
Feature flags
Decouple code deployment from releases, toggle features on and off
Dynamic configs
Replace hard coded values in your app with config values
Parameter stores
Store text parameters and call them in your app to change them on the fly
Advanced flexible user targeting
Attribute-based, segment-based, environment-based, and custom rules
Built-in metrics & impact measurement
Convert any change you make into a lightweight A/B test
Multi-environment support
Support across multiple environments: dev, staging, prod
Automated gradual rollouts
Percentage-based and scheduled rollouts
Approval workflows
Support for reviews and other team-level release management workflows
Automated metric alerts and rollbacks
Set alerts and automatically rollback features that have a negative impact
In-product collaboration
Support for team collaboration and discussions within the console
Feature flag lifecycle management
Unified cross-environment view, stale flag alerts, and code reference checks
Deployment Models
Fully-hosted (cloud) deployment
Warehouse-native deployment for Snowflake
Warehouse-native deployment for multiple data warehouses
Customer Support
Community slack channel for non-premium support customers
White glove onboarding for premium support
Dedicated customer slack channel for premium support with 4-hour response time
On-demand customer trainings for premium support
Occasional custom request features built for premium support customers
Pricing
Free group analytics
Unlimited free feature flag and config checks
No scaled-pricing for Monthly Tracked Users
* This comparison data is based on research conducted in April 2025.
Loved by customers at every stage of growth
See what our users have to say about building with Statsig
"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
"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
"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
"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'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
"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
"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
"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
"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
"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
"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
"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