Product Updates

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Kaz Haruna
Product Manager, Statsig
10/24/2025
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⏰ Schedule Experiment Start

You no longer need to manually start your experiments. This is especially helpful when coordinating launches with other activities, like email campaigns, or when organizing experiment start times across your organization.

You can find this feature today in the "Start Experiment" dialogue.

schedule start dialogue
10/24/2025
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💪 Power Analysis Enhancements

We’ve rolled out several updates to make Statsig’s Power Analysis Calculator more powerful and easier to use when planning experiments.

You can now:

  • Review multiple metrics side-by-side to see how power and duration vary across key metrics in one view.

  • Set a target MDE across your metrics to clearly see the optimal experiment duration across your metrics.

  • Share results with saved configurations, so your team sees the same inputs and assumptions when reviewing analysis.

new_power_analysis

For Statsig Cloud users, Power Analysis now supports multiple qualifying events and event parameter filters, allowing more precise reflection of your experiment setup and traffic definitions.

With these updates, users can plan well-powered experiments and better align on timelines with your.

Akin Olugbade
Product Manager, Statsig
10/22/2025
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🔎 Warehouse Events

All events across your multi-event metric sources can now be found in one place. No more digging through different metric sources to find the event you want. Just search for the event and use it.

What You Can Do Now

  • Search across all events from multi-event metric sources in a single view.

  • Add events to your metrics without opening individual metric sources.

  • Search by event name or by metric source name to keep related events together.

How It Works

  • This unified view includes events only from metric sources that are explicitly configured as multi-event.

  • A multi-event metric source contains multiple event types, for example page_view and checkout. It is not a single computed metric, and it is not a single-event source.

  • To make a source multi-event, go to the metric source page and set Configure for Metrics Explorer to Multi-event.

  • The unified view supports search by event name and by metric source name.

  • This view is optional and does not replace existing create or edit flows. If you prefer working from Metric Sources, those flows are unchanged.

Impact on Your Analysis

  • Faster event discovery when you do not remember which source an event belongs to.

  • Less context switching while building metrics in Metrics Explorer.

  • Better visibility across similar events from different sources in large warehouses.

Warehouse Native users can use the unified event view to quickly find, add, and work with events across your multi-event metric sources.

Akin Olugbade
Product Manager, Statsig
10/21/2025
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🚪Feature Gate Exposures in Metrics Explorer

You can now treat Feature Gate exposure events like any other event in Metric Drilldown and Funnel analyses. This capability is available on both Cloud and Warehouse-Native and currently includes first exposures for each user.

What You Can Do Now

  • Use Feature Gate exposure events in Drilldown charts to track exposure trends over time

  • Add a gate exposure as the first step of a funnel to measure post-exposure conversion paths

  • Group or filter by gate-related properties, such as gate name, pass/fail result, or environment

  • Compare user behavior across gate conditions to understand the impact of gated rollouts

How It Works

Exposure logging When a user is evaluated against a gate, a first-exposure event is recorded with relevant gate properties and user context.

Event selection In both Drilldown and Funnel charts, gate exposures appear in the same event picker you already use for other events.

Property handling Exposure events include gate metadata and user properties, enabling the same group-by and filter controls available for other event types.

Impact on Your Analysis

Drilldown

  • Validate rollout health by visualizing exposure volume and distribution over time

  • Debug exposure logging by spotting spikes, drops, or unexpected gaps

  • Align exposure activity with key metrics to confirm rollout timing and behavior

Funnels

  • Measure user journeys starting from a user’s first gate evaluation

  • Identify conversion differences between users who passed or failed a gate

  • Attribute downstream changes to specific gated experiences

This brings Feature Gate exposure analysis into Metrics Explorer, helping you debug, validate, and measure the real-world effects of gated rollouts across both Cloud and Warehouse-Native environments.

Brock Lumbard
Product Manager, Statsig
10/20/2025
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👨‍⚕️ Docs v2

Following 4.5 years in our previous codebase and infrastructure, we're excited to announce the second iteration of the Statsig Documentation!

New UI/UX

Docs v2 comes with a vastly updated UI, including revamped codeblocks, tabs and dropdowns, and tidied-up navigation and page structure.

New Features

Docs v2 features some new features that make it easy to pull Statsig's docs into your LLMs' context, get answers with AI, and more. We also have a brand new API playground for our Console API and HTTP API, making it easy to grab code snippets in your language of choice or get a sample cURL.

As always, our docs remain open source and free for the community to contribute to. We make our docs better every day, if you find anything that needs some love, let us know in Slack!

Docs v2
Shubham Singhal
Product Manager, Statsig
10/17/2025
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📈 Autocapture Updates

Statsig Autocapture allows you to track events on your website such as page views, clicks, scroll depth, etc. with just one line of code. Today, we are excited to announce 4 major updates that will help you measure and provide more context around user behavior and site performance.

🔗 To start using Autocapture, refer to the setup guide in our docs:

1. Expanded Autocapture Events

Autocapture now tracks additional user actions, including:

  • Form changes

  • Clicks across more element types

  • Text input

  • Rage clicks (repeated clicks in frustration)

  • Dead clicks (clicks that lead to no action or broken links)

  • Copy/paste actions

2. UTM Parameters

UTM tags are now automatically captured, allowing teams to understand where traffic is coming from. Captured parameters include source, campaign, medium, content, and term.

3. Web Vitals

You can now track key performance metrics directly through Autocapture:

  • Cumulative Layout Shift (CLS)

  • First Contentful Paint (FCP)

  • Last Contentful Paint (LCP)

  • Time to First Byte (TTFB)

4. Web Analytics Dashboard

A refreshed Web Analytics Dashboard is now generated when you set up autocapture. It provides visibility into traffic trends, channel breakdowns, visitor demographics, and performance metrics. Each chart is customizable for filtering and segmentation.

Web-analytics-dash
Brock Lumbard
Product Manager, Statsig
10/14/2025
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📝 Statsig Visual Editor

Following two previous iterations under the "Sidecar" title, Statsig's third-generation visual editor is here, simply called the Statsig Visual Editor. The Visual Editor, like Sidecar before it, lets you start experiments without writing code but still use Statsig's powerful Stats Engine to get results faster. The Visual Editor experience is centered around the Statsig console (instead of in a Chrome Extension), meaning your Visual Editor experiments sit alongside your product experiments in the console. Alongside the in-console experience, the Statsig Visual Editor is designed to be vastly simpler to use vs. previous iterations, and have fewer hiccups going from idea-to-experiment.

The Editor is in an open beta, you can get started by reading the docs or choosing the "Visual Editor" experiment type when creating an experiment in the console!

Akin Olugbade
Product Manager, Statsig
10/11/2025
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💰 Rich Text Widgets on Dashboards

Overview

You can now add rich text widgets to any dashboard. This is a new option in addition to existing header text widgets, which remain for simple dividers.

What You Can Do Now

  • Write context directly on dashboards with formatted text

  • Use headings, bold, italics, lists, and links

  • Format with Markdown or the widget’s built-in controls

How It Works

  1. On a dashboard, add a widget and choose Rich Text.

  2. Enter your content.

  3. Format using Markdown or the toolbar, then save.

Impact on Your Analysis

  • Make dashboards self-explanatory with metric definitions, scope, and caveats next to the charts

  • Reduce back-and-forth by capturing conclusions, decisions, and next steps inline after reviews

  • Speed up onboarding by explaining how to read the dashboard and why certain cuts or filters are used

  • Link out to specs, tickets, or experiments so readers can get more context without leaving the page

Available now on all dashboards. Try adding a Rich Text widget to provide context where it’s most useful.

Laurel Chan
Product Manager, Statsig
9/29/2025
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📈 Change Alerts

You can now set Change Alerts to track relative shifts in your metrics. Instead of relying on fixed thresholds, these alerts notify you when a metric moves up or down by the percentage or amount you choose.

What You Can Do Now

  • Create alerts that trigger on % increases or decreases

  • Catch major swings like a 20% drop in signups or a 50% jump in errors

  • Use Change Alerts with Threshold Alerts to cover both relative and topline changes

Getting Started

  1. In the left product menu, open Topline Alerts.

  2. Create a new alert and choose your desired Condition Type.

When to Use Each Alert Type

  • Threshold - use to monitor against a fixed limit. ("Alert me when total daily signups drops below 1000")

  • Change - use to monitor absolute shifts. ("Alert me when daily signups drop by 200 compared to yesterday")

  • Change (%) - use to monitor percentage shifts ("Alert me when daily signups drop 20% compared to yesterday")

change-alerts
Akin Olugbade
Product Manager, Statsig
9/24/2025
Permalink ›

🧪 Exposure Imbalance / Sample Ratio Mismatch (SRM) Debugging in Metrics Explorer

What is SRM?

Sample Ratio Mismatch (SRM) happens when the share of users in experiment groups is different from what you expected. For example, if you set up a 50/50 split between control and treatment but the actual traffic is 60/40, that’s an SRM.

What is the SRM p-value?

The SRM p-value is a statistical measure that tells you whether the observed imbalance could have happened by chance.

  • A p-value above 0.01 generally means the imbalance is within expected random variation.

  • A p-value below 0.01 suggests the imbalance is unlikely due to chance and may warrant investigation.

What You Can Do Now

  • View SRM results and p-values across experiment groups in Metrics Explorer

  • Group results by different properties to identify potential causes of imbalance

  • Start from experiment exposure diagnostics and click on suggested properties to pre-apply them as group-bys in Metrics Explorer

How It Works

Metrics Explorer applies the SRM formula across experiment groups and shows the resulting p-value. From there, you can add group-bys (such as country, platform, or custom properties) to spot where imbalance is happening.

Experiment diagnostics also highlight properties that may be driving the imbalance. Clicking the icon next to one of these properties takes you into Metrics Explorer with that property already grouped, so you can continue the investigation seamlessly.

Impact on Your Analysis

This workflow makes it faster to detect and understand exposure imbalances. By moving directly from diagnostics to group-by analysis, you save time and get clearer visibility into which properties are linked to the imbalance.

Sample Ratio Mismatch debugging is available now across Cloud and Warehouse Native.

Loved by customers at every stage of growth

See what our users have to say about building with Statsig
OpenAI
"Statsig's experimentation capabilities stand apart from other platforms we've evaluated. The ease of use, simplicity of integration help us efficiently get insight from every experiment we run. Statsig's infrastructure and experimentation workflows have also been crucial in helping us scale to hundreds of experiments across hundreds of millions of users."
Paul Ellwood
Head of Data Engineering
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
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
"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
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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
OpenAI
"Statsig has been an amazing collaborator as we've scaled. Our product and engineering team have worked on everything from advanced release management to custom workflows to new experimentation features. The Statsig team is fast and incredibly focused on customer needs - mirroring OpenAI so much that they feel like an extension of our team."
Chris Beaumont
Data Scientist
"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
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 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
"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
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
OpenAI
"Statsig has helped accelerate the speed at which we release new features. It enables us to launch new features quickly & turn every release into an A/B test."
Andy Glover
Engineer
"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
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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