Reseñas y detalles del producto de Statsig

I love how straightforward and intuitive Statsig makes the entire experimentation process. Setting up tests, defining metrics, and interpreting results is incredibly seamless compared to other analytics platforms I’ve tried. The real-time insights and automatic feature gating let me move faster and iterate with confidence. Plus, the UI is clean, and the documentation and support are top-notch—so it never feels overwhelming to dive deeper into any area. Overall, Statsig delivers a powerful, yet accessible, solution for data-driven decision-making. I use statsig almost everyday, implementation was hard at first, but got easier. Their staff can he helpful with intergration. Reseña recopilada por y alojada en G2.com.

The only area I’d love to see further improvement on is a more granular level of customization in the reports and dashboards. Sometimes I find myself wanting to slice data in very specific ways that aren’t supported out of the box. It’s not a deal-breaker by any means, since the out-of-the-box functionality is already strong, but having additional customization options would make the platform even more powerful for deeper analysis. Reseña recopilada por y alojada en G2.com.

Statsig is incredibly intuitive and easy to use. Setting up and running experiments is seamless, and the UI is extremely user-friendly. The SDKs are top-notch—almost Stripe-level in terms of quality and ease of use. Integration was a breeze, taking only about a day to fully implement. Their customer support is also fantastic; we have a direct Slack channel with them, and they’re always quick to respond. I use Statsig daily for every single experiment, and it has become an essential part of our decision-making process. Reseña recopilada por y alojada en G2.com.

While Statsig covers about 90% of our experimentation needs, there are still some cases where I need to run ad hoc analyses using Python. Additionally, I’d love to see near real-time data syncing instead of the current one-day delay. Reseña recopilada por y alojada en G2.com.

The most important features are very useful and well thought, and I've never faced a moment where Statsig wasn't able to perform a specific test I wanted to. I also like how the app is very nice and intuitive and how the documentation is very deeply explanatory in case of doubt. Reseña recopilada por y alojada en G2.com.

I don't like how they put all primary metrics in all new experiments. Some experiments are very different from each other and I want to watch very different metrics. In particular, I believe that if I create an experiment based on a template or if I clone an experiment, I expect it's primary metrics to come just like the source, and not to be all repopulated again. Reseña recopilada por y alojada en G2.com.

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 Reseña recopilada por y alojada en G2.com.

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. Reseña recopilada por y alojada en G2.com.

The Statsig process was great. We booked a call and walked through the introduction of the platform. As the process progressed, I was able to ask more technical quetstions to the solutions engineer during each of our calls. Statsig has a series of YouTube videos that, while a bit out of date, can get a team up to speed relatively quickly.

Once we signed contracts, Statsig offered an a la carte learning solution for each of the various cohorts who would be using the platform. We're only using it for feature flagging and experimentation, but it's easy to get up to speed with those feature sets and setup was easy to integrate into our system using the Ruby SDK and a custom wrapper.

Turning on an experiment, and seeing those results come in, is relatively straight forward, and data (which we send to Statsig via a third-party connection) generally updates every day or so, but sometimes more frequently. It's easy to see clear winners and losers, and you're able to filter for specific things like custom analytics values. The team also integrates directly into Slack as a first line of communication. Reseña recopilada por y alojada en G2.com.

It takes some time to wrap your head around what the platform is doing and how you're supposed to set things up. The idea of Layers took some time to process, along with how to register analytics events for more granular visibility in an experiment. I think it's just the price of learning new software. Statsig employees were available to answer questions, and documentation is generally good. Reseña recopilada por y alojada en G2.com.

It's just very straightforward to rollout features and experiments to our customers and understand their impact. We use it across our tech stack with different languages and the SDKs all work well and without issues. Also get a quick response on the slack support. Reseña recopilada por y alojada en G2.com.

Takes a little time to understand the nuances of the different features (e.g. why you can't change what percentage of users go to a group in an experiment once it's started) Reseña recopilada por y alojada en G2.com.

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! Reseña recopilada por y alojada en G2.com.

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. Reseña recopilada por y alojada en G2.com.

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. Reseña recopilada por y alojada en G2.com.

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. Reseña recopilada por y alojada en G2.com.

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! Reseña recopilada por y alojada en G2.com.

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. Reseña recopilada por y alojada en G2.com.

Statsig hace que sea muy fácil analizar los resultados. Los gráficos que proporcionan son fáciles de leer y puedes hacer clic en cada métrica para obtener información adicional, gráficos y significancia estadística. De un vistazo rápido puedes ver qué está sucediendo con el experimento. Reseña recopilada por y alojada en G2.com.

Encuentro algunas de las características al enviar un experimento bastante confusas. Por ejemplo, los campos de duración de asignación, duración de cohorte y tiempo total del experimento no son claros. Además, la mayoría de nuestros experimentos los analizamos una semana después de la asignación y no hay opción para hacer esto en Statsig. Reseña recopilada por y alojada en G2.com.