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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
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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 Statsig has a series of YouTube videos that, while a bit out of date, can get a team up to speed relatively quickly.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.
The best in the industry
What do you like best about the product?
I've used other experimentation platforms before from Meta's "Deltoid" platform to one I built myself in python... Statsig far surpasses the other platforms out there in terms of both ease of use and flexibility. It has been a game changer for experimentation across my company. The whole process is now seamless, from adding new metric sources & metrics, setting up scorecards for new experiments, and diving into more detailed analysis with things like days-since-first-exposure view & metric results split by user dimensions.
What do you dislike about the product?
There are a lot of options to pick from for metric types, experiment settings, etc. This provides a TON of flexibility in how you analyze experiments, which is great. But the number of choices can be a bit daunting when you are newly onboarding! So definitely ask questions to the Statsig support team, and they will promptly give you advice to help you with any choice you are making.
What problems is the product solving and how is that benefiting you?
Statsig makes experimentation in my organization easier, faster, and more trustworthy. It is straitfroward both for engineers to setup A/B tests using the platform, for analysts to setup the metrics & analysis, and for everyone in the company to follow the results.
Amazing product - easy and powerful
What do you like best about the product?
It's about the easiest thing to set up and start using in a React Native app to handle feature gating, experiments, event logging, remote config, and other essentials. I think of StatSig now as indispensible for anyone building a phone app.
The documention is good, and gets you started quickly. I was running StatSig in my app within 10 minutes of signing up.
The documention is good, and gets you started quickly. I was running StatSig in my app within 10 minutes of signing up.
What do you dislike about the product?
TBH, I haven't hit anything I'd say I dislike. If you forced me, I guess the SDK update changed several APIs, but it made them universally better than before, so that's hard to complain about.
What problems is the product solving and how is that benefiting you?
feature gating is the biggest one, and experimentation. it's so easy to gate features and to figure out what's working better.
A/B testing made easy for client developers
What do you like best about the product?
As a client developer, StatSig is very intuitive to use, reducing a lot of the boilerplate set up with experiment templates. My favorite feature is the ease of overriding experiment assignments for bug bashing across multiple environments. This has definitely increased our velocity when testing and shipping experiments.
What do you dislike about the product?
One area of improvement would be the user interface for reviewing / approving changes to experiments. There have been some changes made to this recently, so it's nice to see that this is an area of focus for the team at StatSig.
What problems is the product solving and how is that benefiting you?
StatSig helps us ship and analyze experiments.
Powerful and flexible solution for Experimentation
What do you like best about the product?
Statsig can handle almost any kind of online controlled experiment a company can think of. The statistical analyses are also very powerful.
What do you dislike about the product?
Reports could be friendlier for Marketers and other types of users with no background in statistics.
What problems is the product solving and how is that benefiting you?
Statsig is our Experimentation tool, handling almost all Experiments we run on dozens of websites across multiple countries. Experiment behavior is reliable and easy to manage.
Perfect for fast experimentation without having to build in-house platforms
What do you like best about the product?
There's no compromise in the platform, you can get everything you would expect from an in-house experimentation platform, and more, without the hassle of building it.
We launched the first experiment in 1 week and started getting results immediately.
Also, it pairs well with the existing poduct analytics platform that we use, Amplitude.
We launched the first experiment in 1 week and started getting results immediately.
Also, it pairs well with the existing poduct analytics platform that we use, Amplitude.
What do you dislike about the product?
Unfortunately, product analytics is not yet on par with the competition. However, it pairs well with them.
What problems is the product solving and how is that benefiting you?
We wanted to run bayesian ab tests as often as possible in order to improve some critical features of a mobile app.
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