Statsig Developer Tier
StatsigReviews from AWS customer
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using statsig main features
What do you like best about the product?
Statsig excels at providing granular control over feature releases with excellent safety mechanisms. The ability to instantly roll back features, target specific user segments, and gradually ramp up releases gives us confidence to deploy changes without fear of widespread issues.
What do you dislike about the product?
While powerful, the dashboard can feel cluttered when managing multiple experiments and feature flags simultaneously. Navigation between different sections isn't always intuitive, and finding specific configurations can be time-consuming in larger projects.
What problems is the product solving and how is that benefiting you?
The platform addresses both feature management complexity and the need for data-driven product decisions. We can safely test new features, measure their impact on key metrics, and make quick adjustments without additional development cycles. This has accelerated our product iteration speed and reduced time-to-market.
Probably need more document on SDK, especially for ASGI integration
What do you like best about the product?
UI, easy to use, easy to check logs, debug ability is good.
What do you dislike about the product?
I think the support is less for free tier user. Asked question in slack. after one day, still no response except auto AI one
What problems is the product solving and how is that benefiting you?
easy UI to create and config feature flag
Reliable, Real-Time Experimentation Platform That Powers Our Growth
What do you like best about the product?
Statsig was super easy to add via the v0 native integration. We’ve been able to run high-velocity experiments on our main B2C funnel with reliable, real-time data. It handles both A/B and multivariate tests smoothly, and it feels like we’ve only scratched the surface of what’s possible.
What do you dislike about the product?
Some of the more advanced setups take a bit more upfront time to configure and deploy. It’s not a dealbreaker, but there’s a learning curve when you move beyond the basics.
What problems is the product solving and how is that benefiting you?
Statsig helps us experiment with confidence. Before, it was hard to run multiple tests quickly and trust the data. Now we can launch A/B and multivariate experiments across our B2C funnel, track results in real time, and know the insights are credible. This has sped up our learning cycle, improved funnel performance, and given us a clear view of what actually drives growth.
Experimentation built for analysts
What do you like best about the product?
The ability to customise metrics from whatever data we have and leverage our whole data warehouse rather than just events. The statistical depth and options on Statsig is also unmatched to any other A/B testing tool we have used.
What do you dislike about the product?
There are some nuances with a new product such as how users are including in experiment results.
What problems is the product solving and how is that benefiting you?
Running experiments and understanding how they are impacting our metrics.
StatSig helps us make product improvements faster, and with confidence
What do you like best about the product?
I like that StatSig offers a very clear picture into how experiment variants are performing compared to control. It's not difficult to use for someone like me who had previously limited experience with experimentation.
What do you dislike about the product?
Perhaps some elements of the UI. For example, there are a lot of tabs when analyzing a test and it could be streamlined a bit.
What problems is the product solving and how is that benefiting you?
StatSig helps my product team validate experimentation success and impact on our key metrics. It helps us tell a clear story to the business with confidence.
StatSig accelerated our experimentation/learning velocity
What do you like best about the product?
Recently, our team began using a StatSig feature called "Parameter Stores". Parameter stores can be leveraged as server driven UI to power experimentation. As long as my team is thoughtful about how we are designing a new component or a new experience, we can enable ourselves to endlessly optimize that experience through A/B experimentation using StatSig parameter stores without additional engineering work. This has multiplied our experiment velocity while helping us ensure that we don't ship something new without optimizing it.
What do you dislike about the product?
The only downside of StatSig is with their Sidecar feature. Sidecar allows you to ship no-code / low-code experiments on a websites through an editor that is available as a google chrome plugin. I had high hopes for this feature, but was unable to use it with a single page web application.
What problems is the product solving and how is that benefiting you?
Statsig is helping our business learn more about the product experiences we are shipping while accelerating our testing velocity.
Collaborative, quick, and always improving
What do you like best about the product?
A responsive partner that ships improvements fast
I’m a Product Analytics Manager and I’ve been genuinely impressed with how Statsig works with us. The collaboration model between our Internal Experimentation Hub and the Statsig team feels like a tight feedback loop, not a vendor relationship. We share casual feedback and they translate it into changes quickly. The product has improved visibly quarter after quarter, which has made our experimentation smoother and our decisions faster. Support is quick, thoughtful, and pragmatic. If you care about momentum and a team that actually listens, Statsig is a great choice.
I’m a Product Analytics Manager and I’ve been genuinely impressed with how Statsig works with us. The collaboration model between our Internal Experimentation Hub and the Statsig team feels like a tight feedback loop, not a vendor relationship. We share casual feedback and they translate it into changes quickly. The product has improved visibly quarter after quarter, which has made our experimentation smoother and our decisions faster. Support is quick, thoughtful, and pragmatic. If you care about momentum and a team that actually listens, Statsig is a great choice.
What do you dislike about the product?
Governance is still a team sport, it is too easy for different groups to spin up the same metric under different names. I’d love stronger guardrails like a global registry, aliasing, and approval workflows.
This is a common challenge across platforms, not a Statsig issue.
This is a common challenge across platforms, not a Statsig issue.
What problems is the product solving and how is that benefiting you?
Statsig gives us one single place to run, read and analyze experiments, which solves some big problems:
- Speed - we now have much clearerreadouts thanks to the ability to breakdown metrics in valuable segments within the same tool and whitout needing to have SQL skills, now product-teams can move from launch to decision faster.
- Trust- Consistent metrics (which could be better handled in the tool) and disgnostics reduce the usual questions about results being real. It also allows make results comparable across teams overtime
-Scale - the collaboration model between Product Teams -> Experimentation Hub <-> Statsig allows for more concurrent tests being supported and Statsig is quick to ship improvements based on our feedback
The benefit for Product Analytics is: clearer reads on domain main. KPIs, fewer bespoke analyses (meaning more time for analysts to focus on more complex, higher value analysis), and faster, safer iteration on features that improve our customer experiences
- Speed - we now have much clearerreadouts thanks to the ability to breakdown metrics in valuable segments within the same tool and whitout needing to have SQL skills, now product-teams can move from launch to decision faster.
- Trust- Consistent metrics (which could be better handled in the tool) and disgnostics reduce the usual questions about results being real. It also allows make results comparable across teams overtime
-Scale - the collaboration model between Product Teams -> Experimentation Hub <-> Statsig allows for more concurrent tests being supported and Statsig is quick to ship improvements based on our feedback
The benefit for Product Analytics is: clearer reads on domain main. KPIs, fewer bespoke analyses (meaning more time for analysts to focus on more complex, higher value analysis), and faster, safer iteration on features that improve our customer experiences
STATSIG and SampleApp.ai are killing the game!
What do you like best about the product?
I've been testing a lot of different no code (vibe code) builders lately, and I think that SampleApp.ai is one of the best ones I've used thus far!
What do you dislike about the product?
I think it's brand new, so the only thing I noticed was a slight hallucination when using SampleApp.ai that I'm sure is an easy fix. Other than that, I was VERY impressed with the speed and quality that it build my app. Some of these no code builders do a crappy job and the end product looks trashy. With these guys, my app had a much more modern and sleek look that matched up with the times (Sept. 3, 2025). Highly recommended. Don't sleep on this one! : -)
What problems is the product solving and how is that benefiting you?
It's helping me bring my ideas to life FAST and run A/B tests to determine the optimal way to create and deploy my applications. I come from a pay-per-click (PPC) advertising background, so A/B testing is something I think that should be in EVERY product online (SaaS, Web Apps, Websites, etc.).
Best experimentation platform
What do you like best about the product?
It is super easy to set up experiments, track them and get insights. It’s an excellent experimentation platform!
What do you dislike about the product?
Honestly nothing. I can do almost anything needed for my experiments
What problems is the product solving and how is that benefiting you?
It’s allowing us to conduct A/B test. It is making us more efficient and helping us to take scientific decisions.
Feature flags, experiments, and impact in one place
What do you like best about the product?
It’s the tight join between shipping and learning. We plan rollouts, define success metrics once, then let Statsig run trustworthy analysis (including CUPED and switchbacks) and Autotune traffic. Results are clear, decisions are auditable, and the warehouse-native mode means our source of truth stays in Snowflake/BigQuery. We’ve genuinely cut time to insight while increasing confidence in product decisions.
What do you dislike about the product?
There’s a mild learning curve when you first set up metrics, guardrails, and experiment taxonomy. Event-based pricing is fair, but you do need to watch noisy clients and background events. The UI is dense in places, though it pays off once your team’s rhythm is set.
What problems is the product solving and how is that benefiting you?
We needed to move quickly without breaking things. Statsig lets us ramp features safely, prove impact with clear dashboards, and automatically steer traffic to winners. Pricing scales sensibly, SDKs are robust, and the UI is powerful once you learn the basics. It’s materially improved release safety, experiment velocity, and confidence in product decisions.
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