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Great Product
What do you like best about the product?
Great product for experimentation, reduces lot of manual effort, and very easy to use
What do you dislike about the product?
nothing specific, but could improve diagonstic tab perf.
What problems is the product solving and how is that benefiting you?
It reduces lot of manual effort requried in experiment step up and post analysis by reusing lot of existing metrics
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Most straight forward experimentation and flag SDK we've used
What do you like best about the product?
Implementing on our CDN edge and in our nextjs app was straight-forward and seamless.
What do you dislike about the product?
We could have used more code examples with various scenarios and use-cases demoed in code.
What problems is the product solving and how is that benefiting you?
A/B testing in our app and on the edge, answering user experience questions before we do mass releases.
Great Statistic First Experimentation Platform
What do you like best about the product?
I love the implementation of experimentation best practice. It has made my job taking colleagues on the journey of uplifting experimental practices very straightforward. The documentation Statsig provides also is super valuable.
What do you dislike about the product?
It can take a while to learn the key terminology used within the software
What problems is the product solving and how is that benefiting you?
Statsig is our experimentation platform
Fantastic consolidated experimentation platform
What do you like best about the product?
Statsig is an outstanding platform for product experimentation and analysis. Its intuitive A/B testing, real-time insights, and robust statistical methods gives confidence in experiment results.
I've struggled in the past with using multiple different products to achieve the same result and thankfully Statsig solves them all in one product
I've struggled in the past with using multiple different products to achieve the same result and thankfully Statsig solves them all in one product
What do you dislike about the product?
There is definitely a bit of a learning Curve with the UI, and the product itself is built with a data science focus. However, both of those are overcome with time spent in the product and those become positives.
What problems is the product solving and how is that benefiting you?
Statsig is providing us a all in one experimentation platform. This helps a lot with post experiment analysis where I no longer need to manually calculate statistical significance for ongoing experiments or estimate error bars. This removes errors, makes me more efficient and gives me a lot more confidence in our results!
Super Useful
What do you like best about the product?
Statsig makes it so easy to experiment with new features and measure their impact in a truly data driven way! It exposes the true impact of your changes and allows you to focus on making changes that benefit your customers
What do you dislike about the product?
Once you go past 5M events per month it starts to increase in cost but you should be getting out more than you put in by then!
What problems is the product solving and how is that benefiting you?
It makes A/B testing so easy to perform and reduces the burden on engineers trying to test different versions of a feature
Go to tools for running experiments and rolling out new features
What do you like best about the product?
Running experiments is a breeze. Ability to define custom metrics, explore each metric individually through a metrics explorer, ability to view sample events is really helpful. User interface is very smooth and easy to use.
What do you dislike about the product?
not dislike but currently the experiment results are delayed by one day. there should be an option to view it in real time
What problems is the product solving and how is that benefiting you?
rolling out new features reliably
conducting experiments
conducting experiments
Statsig - super easy-to-use feature-flagging/experimentation tool
What do you like best about the product?
As a relatively new user of statsig I found it really simple to get started with as the setup was pretty quick and there was no real issues with getting things working. The documentation is also clear and full which were easy to follow and also helped with the onboarding flow. The onboarding was also helped with the simple and pretty seamless integration into our workflow without causing any major hassle. Especially, for something we use so often - I highly recommend it!
What do you dislike about the product?
I haven't had any major pain points with statsig so far - the only minor things I can really nitpick at is sometimes the UI could be clearer - granted it is super intuitive but some parts there would be a couple buttons disabled/greyed out and it wouldn't be clear as to why they are disabled.
What problems is the product solving and how is that benefiting you?
Think the key point is instead of spending lots of engineering time building our own feature flag system, Statsig gives us a solution which is essentially good to go out the box and helps us quickly test and roll out new features. The A/B testing also makes it pretty easy to track what is working and whats not which takes out any guess work.
Everyone running server-side experiments should consider Statsig
What do you like best about the product?
It is packed full of advanced features and they keep adding new features while being very competitively priced.
It's easy to use and implement. I'm a big fan of their experiment results visualisations, everyone in our organisation can understand experiment results.
You get useful answers from customer support and not some generic scripts that I usually see from big vendors.
It's easy to use and implement. I'm a big fan of their experiment results visualisations, everyone in our organisation can understand experiment results.
You get useful answers from customer support and not some generic scripts that I usually see from big vendors.
What do you dislike about the product?
You have no dedicated support for the pro-tier subscription but there are skilful Statsig people on Slack that you can ask questions and a useful support bot.
When asking more complex questions it might take a couple of days before you get a reply. When you factor in multiple questions back and forth with support + time differences between EU and US it may take a few weeks to get to the bottom of questions.
When asking more complex questions it might take a couple of days before you get a reply. When you factor in multiple questions back and forth with support + time differences between EU and US it may take a few weeks to get to the bottom of questions.
What problems is the product solving and how is that benefiting you?
Experimentation tool
Using Statsig daily to release and experiment with new features
What do you like best about the product?
Our initial use case for Statsig was for feature rollout using gates. Statsig has revolutionised this process for us - to a point where it seems strange that we never had it in the first place. Through Statsig's feature gates we've had a lot more confidence in rolling out features. In particular, we love the automated rollouts as it means that we can expose a feature, monitor its performance against key metrics, and then proceed once our confidence is high.
Monitoring is also very easy in Statsig. I have set up a dashboard for my team which includes all of the feature gates and experiments that we are currently running. I love how easy it is to set up the dashboards by just tagging any relevant gate/experiment with my team's custom tag.
I also love how easy it is to configure the UI. I now have things set up so that when I open the app I am presented with all the information I need straight away without having to dive into all the menus. This is very helpful when I just want to check the status of an experiment or stage of a rollout.
Monitoring is also very easy in Statsig. I have set up a dashboard for my team which includes all of the feature gates and experiments that we are currently running. I love how easy it is to set up the dashboards by just tagging any relevant gate/experiment with my team's custom tag.
I also love how easy it is to configure the UI. I now have things set up so that when I open the app I am presented with all the information I need straight away without having to dive into all the menus. This is very helpful when I just want to check the status of an experiment or stage of a rollout.
What do you dislike about the product?
I don't feel like there are major downsides to Statsig - all of the functions work great and we haven't had any trouble setting things up or using the features that are provided.
The one thing that would be nice from an interface perspective would be to have more in line documentation about a certain feature. This would lower the boundary for entry. I find myself having to flick between the docs and the app at times which can be frustrating. At the very least it would be great to have a button which links to the docs for a particular feature. I.e. if I want to implement a layer but I'm not 100% sure on the functionality - I should be able to get to the docs immediately from the `Layer` tab in the web app.
The one thing that would be nice from an interface perspective would be to have more in line documentation about a certain feature. This would lower the boundary for entry. I find myself having to flick between the docs and the app at times which can be frustrating. At the very least it would be great to have a button which links to the docs for a particular feature. I.e. if I want to implement a layer but I'm not 100% sure on the functionality - I should be able to get to the docs immediately from the `Layer` tab in the web app.
What problems is the product solving and how is that benefiting you?
As mentioned previously we use Statsig primarily for rolling out features using the feature gate tooling and performing experiments on certain parts of our app.
Feature gates benefit us by:
1. Allowing us to rollback features easily if there is a problem. This gives us a lot more confidence in our deployments.
2. Allows us to also monitor their success. Because we have configured our own events, it is easy to see if a feature is damaging key metrics.
We also use holdouts to see the impact that multiple features have had on a team-by-team basis. This is great for all the engineers, who can then see how the work they are doing is impacting the performance of our key metrics.
Feature gates benefit us by:
1. Allowing us to rollback features easily if there is a problem. This gives us a lot more confidence in our deployments.
2. Allows us to also monitor their success. Because we have configured our own events, it is easy to see if a feature is damaging key metrics.
We also use holdouts to see the impact that multiple features have had on a team-by-team basis. This is great for all the engineers, who can then see how the work they are doing is impacting the performance of our key metrics.
Used to roll my own feature flags but this is so much better
What do you like best about the product?
My favourite thing is how easy it is to manage feature rollouts and experiments on statsig. The SDK makes sense, and I love checking the pulse results during a roll out. One thing that I've noticed from using Statsig is that our team is better at defining experiments before hand, particularly in terms of what metrics we want to evaluate. It's also made us much more confident when making risky changes. Finally, I find it helpful that all of our gates and experiments are defined in one place and I can see what experiments other departments of the company are running if needed.
I would 100% recommend it!
I would 100% recommend it!
What do you dislike about the product?
I largely think statsig is very good, but there are two pain points that I find challenging:
Firstly, when doing a rollout it's not possible to reverse progress while maintaining the same cohort of experimental data and you need to start a new rollout. For metrics that have a long lead time, this can slow down experiments, and it makes me think it's not necessarily the right tool for assessing longer term impact of experimental changes.
Secondly, ad blockers can impact whether feature gates are evaluated as true. This is a known issue, but we do receive some (albeit very few) customer complaints from people expecting a feature that is currently blocked behind a rollout.
Firstly, when doing a rollout it's not possible to reverse progress while maintaining the same cohort of experimental data and you need to start a new rollout. For metrics that have a long lead time, this can slow down experiments, and it makes me think it's not necessarily the right tool for assessing longer term impact of experimental changes.
Secondly, ad blockers can impact whether feature gates are evaluated as true. This is a known issue, but we do receive some (albeit very few) customer complaints from people expecting a feature that is currently blocked behind a rollout.
What problems is the product solving and how is that benefiting you?
We use statsig to evaluate changes to our application and back end systems in a controlled way before rolling changes out to 100% of users. The ability to track outcomes of certain metrics by cohorts in the experiment, and see the impact of a feature, is a great benefit. We also benefit from not having to develop our own feature gate system in each repository that we work in.
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