Statsig
Feature flags, experiments and product analytics together
1/2Statsig ships feature flags, experimentation, product analytics and session replay as one platform, so the flag that gates a feature is also the experiment that measures it and the event stream that explains the result. Experiments support A/B/n and multivariate designs with both Bayesian and frequentist readouts, flags and dynamic config are checked without limit on every plan, and analytics cover funnels, retention and user journeys against the same events. More than thirty open-source SDKs cover the usual languages and platforms, and Enterprise can run warehouse native, executing against your own data warehouse instead of sending events out. The free tier is unusually large - two million events a month, fifty thousand session replays and unlimited seats - and Pro is $150 a month including five million events, then five cents per thousand.
- Feature flags and dynamic config, checked without limit
- A/B/n and multivariate experiments on the same flags
- Bayesian and frequentist statistical readouts
- Product and web analytics on the same event stream
- Session replay, 50,000 a month on the free plan
- More than thirty open-source SDKs
- Warehouse native deployment on Enterprise
- Unlimited seats, including on the free plan
Based on what people have said
Every answer links back to the mentions it came fromWhat are the primary use cases for Statsig?
Users primarily utilize the platform for feature flagging, feature gating, and running A/B experiments. Some also leverage it for product analytics, though opinions on its depth in that area vary.
5 mentions · Hacker News · r/ProductManagement · Hacker News · @GergelyOrosz · May 2025 – Sep 2026
How does Statsig perform regarding data latency and reliability?
Experiences are mixed. While some users describe the platform as polished and robust, others have reported significant concerns regarding data latency, with some noting delays of several days for data to populate. There are also reports of critical technical issues and documentation gaps.
3 mentions · r/ProductManagement · Hacker News · May 2026 – Jun 2026
Is Statsig considered a strong choice for product analytics?
There is disagreement on this point. Some users find it to be a well-rounded tool that consolidates experimentation and analytics effectively. Others argue that its capabilities for funnel exploration and user event tracking are limited compared to dedicated analytics platforms.
3 mentions · r/ProductManagement · Nov 2025
How does the warehouse-native feature work?
The platform is noted for its warehouse-native architecture, which allows teams to execute experiments and analytics directly against their own data warehouses, such as BigQuery, rather than relying solely on external event ingestion.
3 mentions · r/dataanalytics · r/ProductManagement · Jun 2026 – Jul 2026
What is the sentiment regarding the company's recent acquisition?
The acquisition has generated uncertainty among the user base. Some express concern about the future of the product, the departure of key personnel, and whether the platform will continue to be maintained effectively, while others hope the new ownership will focus on experimentation development.
6 mentions · r/ProductManagement · Hacker News · Hacker News · Sep 2025 – Jun 2026
These summarise counts and dates only. Read the quotes themselves under what people are saying.
What people are saying about Statsig
50% positive“Configure and control the triggers with Statsig.”
“Launchdarkly and Statsig are both well-established companies that basically do feature flags+add-ons.”
“statsig has documentation that explains a lot of this.”
“I work a lot with the outputs of that, like was this new product feature statsig in generating the incremental causal lift we wanted etc.”
“if warehouse-native is a must, statsig is what you want, its built for that exact thing...”
“Our top choice currently would be to start pushing our core events into BigQuery and then use a warehouse-native analytics platform (maybe Statsig?) as the interface for Product teams. Also, having this data in BigQuery is super useful for our data science projects (e.g.”
“As we've been getting up to speed with Statsig's code base, they do a lot well, even better than Amplitude: experimentation, warehouse native, a more modern architecture, and there's a few places where they're behind: ingestion, data latency. There's a bunch of work we're doing to make it robust and I want to make sure we're hitting what you're running into.”
“Anyone else having real statsig performance and latency issues, since the acquisition? We are routinely waiting 2+ days for data to fill in”
“Statsig is a half-baked product bought out by OpenAI for data harvesting. We already reported 2 documentation issues and 1 critical technical issue, and we're barely using it.”
“Statsig has worked great at my work, really polished and rich feature set. Their tooling to identify unused flags as candidates for removal is neat.The per-seat billing we have in our agreement is a bit rough but it's workable.”
“It’s funny that you think Statsig is a product still being maintained and cared about by OpenAI.”
“My company is a (mostly) happy customer of Statsig and dissatisfied Amplitude customer. I’m not optimistic that Amplitude will do a good job of carrying the product forward.”
“Think it’s probably a good thing for the development of statsig with a parent more focused on experimentation than AI.”
“Seems like an amazing move for Amplitude since Statsig was best in class at experimentation and can help modernize the brand and platform for the more technical engineering and data science audience that is growing a lot due to agentic coding tools.”
“Yeah, having everything consolidated with saved us from managing separate tools, so props to Statsig. You're right that the upfront investment in setup definitely pays off once you're tracking meaningful experiments.”
“For the use case you described, Statsig is great. You may try other A/B testing tools as well such as Growthbook (Open Source), launchdarkly, optimizely, etc.”
“So with the 4 capabilities in one, it’s at least 3x cheaper when consolidated and much easier for everyone to use because it’s under one platform.”
“They have released more (funnel style) analytics fairly recently - https://www.statsig.com/analytics - though their bread and butter is definitely A/B testing.”
“Statsig is not the go to product for product analytics. It's a great product for runninga/b experiments and feature gating(you know enable/disable features at run time). It has very limited capabilities when it comes to funnel exploration or just user even tracking.”
“Statsig is really an analytics tool - not sure there's much overlap with how you'd use Jira!”
“I’ve seen some really good feedback about Statsig but I haven’t used it myself and was hoping if others can make a recommendation on if it’s a well-rounded (but also user friendly) tool for product development and analytics?”
“Statsig doesn't really offer much to the core product of OpenAI. Sure, it may support their efforts.”
“Experimentation platforms like Statsig exist to lower the high cost of experimenting.”
“Have implemented Statsig in two companies as alternatives to LaunchDarkly and loved it both times. Going to be interesting how their other big customer deals with this purchase i.e.”
“Statsig is big enough that its acquisition is interesting in its own right. Or maybe I'm biased because I spent quite some time setting up a Statsig integration at $FORMER_EMPLOYER.”