Statsig Developer Tier
StatsigReviews from AWS customer
0 AWS reviews
-
5 star0
-
4 star0
-
3 star0
-
2 star0
-
1 star0
External reviews
342 reviews
from
External reviews are not included in the AWS star rating for the product.
Fantastic unique product to run experiments
What do you like best about the product?
Its ability allow run seamless experiments and measure impact with metrics.
Love that it can accept analytics events from various plugins and allow us to create metrics through different touchpoints.
It is super powerful tool for running experiments and feature gating your changes. Industry leading experiment running platform and super easy to use.
Love that it can accept analytics events from various plugins and allow us to create metrics through different touchpoints.
It is super powerful tool for running experiments and feature gating your changes. Industry leading experiment running platform and super easy to use.
What do you dislike about the product?
I wish there were more video tutorials on different types of metrics and deeper analysis on automating pre-analysis processes.
What problems is the product solving and how is that benefiting you?
One platform for all needs related to experimentation, be it metrics, user analysis, feature gating, etc
Essential for Data-Driven Decision Making
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Statsig has made experimentation significantly faster and easier, allowing us to run tests seamlessly and with confidence. It has improved our decision-making by providing clear, data-driven insights, making it an essential tool for our team. We run experiments on every new feature, and Statsig has helped us scale this process efficiently across multiple teams.
One challenge we faced was evaluating results for specific user segments (e.g., comparing A1 vs. B and A2 vs. B separately, instead of just A vs. B). Since I’m not aware of a built-in feature for this, I handle it through ad hoc analysis in Python by exporting the data. Despite this, Statsig still covers about 90% of our experimentation needs and remains a critical tool in our workflow.
One challenge we faced was evaluating results for specific user segments (e.g., comparing A1 vs. B and A2 vs. B separately, instead of just A vs. B). Since I’m not aware of a built-in feature for this, I handle it through ad hoc analysis in Python by exporting the data. Despite this, Statsig still covers about 90% of our experimentation needs and remains a critical tool in our workflow.
Amazing Feature Flagging and Experimentation Platform
What do you like best about the product?
StatSig has built the implemented the functionality that I enforces good Feature Flagging and Experimentation features that are often hard to get right. The ability to create experimentation layers, parameter stores, automatic metric calculations for lift are incredibly important and designed well. Unlike other feature flagging platforms that couples together Feature Flagging with Experimentation, StatSig does a great job of separating the two concepts. Their customer support through their public Slack is incredible, they're super responsive and provide very helpful answers to get us on board.
What do you dislike about the product?
There are Parameter Store and Dynamic Config, there should really only be one.
What problems is the product solving and how is that benefiting you?
Currently, feature flagging and parameter store. It allows us to iterate on a product quickly, especially functionality of a mobile application without needing a new app release, which often takes a day or two.
Statsig is the easiest way to set up tests for your product
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Statsig is the best tool to perform A/B testing. Although other tools offer it as well, only Statsig give me enough freedom to analyse my tests data in detail.
Great product for analytics
What do you like best about the product?
Offers full control over feature gating, segmentation, A/B testing data all in one place.
What do you dislike about the product?
The design of the dashboard can change from time to time making it hard to navigate
What problems is the product solving and how is that benefiting you?
A/B testing
Best Analytics Platform | Statistically
What do you like best about the product?
- Prime user flow
- Best in class sdk
- Easy onboarding
- Best in class sdk
- Easy onboarding
What do you dislike about the product?
Screen capture doesn't work majority of the times
What problems is the product solving and how is that benefiting you?
It is helping me know my users better
pretty good easy to install, great for a start up
What do you like best about the product?
I liked how easy it was to install on my personal project
What do you dislike about the product?
I think the interface might have a bit of a learning curve, it's not obvious I will be able to do everything I want to do with it
What problems is the product solving and how is that benefiting you?
I want to know how people are using my app. A little tracking will be helpful for me
statsig experience
What do you like best about the product?
It has very user friednly interface which helps in navigating easily
What do you dislike about the product?
Creating FF in all the regions even if its not required
What problems is the product solving and how is that benefiting you?
It helps us using feature gate support
Statistically speaking…Statsig is great!
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Statsig is solving our feature flagging and experimentation problem. This helps us measure the impact of changes to our various systems and user flows, which we could easily do before.
Amazing features at fingertips
What do you like best about the product?
As a data scientist, Statsig makes it incredibly easy to handle everything from metric breakdowns to performance tracking and experiment setup. I'm truly impressed by how it allows me to analyze all experiments in one place, with just the click of a button.
What's even more helpful is that Statsig doesn't just support setting up and analyzing experiments—it also lets you import and analyze experiments run outside the platform. This feature is a game-changer, making it seamless to get insights from experiments, no matter where they were conducted.
What's even more helpful is that Statsig doesn't just support setting up and analyzing experiments—it also lets you import and analyze experiments run outside the platform. This feature is a game-changer, making it seamless to get insights from experiments, no matter where they were conducted.
What do you dislike about the product?
The UI could be improved. For first-time users, it can be a bit challenging to understand why certain actions aren't working as expected. For example, some buttons are greyed out on certain screens, and it's not always clear how to proceed. It feels a bit like a trial-and-error process.
What problems is the product solving and how is that benefiting you?
Previously, setting up an experiment as a data scientist involved running SQL queries to extract primary metrics and performing power analysis to plan the experiment. On top of that, metric definitions weren't standardized and could vary slightly across teams, which wasn’t ideal. Statsig has simplified the entire process by allowing us to create standardized metrics and easily perform pre-experiment analysis with just a click. This ensures consistency and robustness, making sure everyone in the company follows the correct process.
showing 231 - 240