Statsig Platform Overview
Learn the basics you need to get started with Statsig with the Intro to Statsig webinar! This live training will provide a comprehensive overview of the Statsig platform including an introduction to SDKs, feature management, experimentation, and product analytics. Register for Intro to Statsig on May 29 at 11am PST or June 5 at 11am PST.
What do I use Statsig for?
Statsig's goal is to be the single platform to ship, measure, and learn from the products you build. The most popular features of Statsig are:
- Feature Flags: Expose new features to select user groups, roll them out (and roll them back, when things go wrong), and measure the impact they have.
- Experiments: Run randomized, controlled experiments on different variations of your product, and measure the exact impact on your users. Customers use Statsig to run thousands of experiments each year, and iterate in the right direction.
- Product Analytics: Understand the trends of your core business metrics, user behavior, and more. While these three are some of our most popular, Statsig offers other tools like Session Replay, Web Analytics and all of these features together are greater than the sum of the parts.
How do I setup Statsig?
While Statsig is flexible to many setups models, the most common setup approach is to integrate Statsig's SDKs which let you integrate flags/experiments, and track your core business metrics. While SDK installation is most common, you might want to bring existing data to Statsig. If so, you have a few options:
- I'd like to bring existing data from my Data Warehouse: You'll likely want to use Statsig Warehouse Native, a zero-ETL model for running experiments and product analytics on top of your existing data. Alternatively, you can import warehouse data into Statsig Cloud with our warehouse ingestions.
- I'd like to bring existing data from my Segment, Rudderstack, Amplitude, or another platform: Consider one of Statsig's integrations, which can port your events straight into Statsig Cloud.
- I'd like to import my existing experiment assignment data, and use Statsig for Analysis: You'll need to use Statsig Warehouse Native.
Statsig has two models to leverage its core products based on your needs: Statsig Cloud (where we host your data) and Statsig Warehouse Native (where you host your data in your own warehouse) a little more on each of these:
Statsig Cloud
With Statsig Cloud, setting up is simple. Install the Statsig SDK and configure event logging—we handle everything else.
- You get feature flags and 2 million metered events for free.
- Enjoy powerful analytics tools such as Dashboards, Metrics Explorer, and Insights.
- For more details on the pricing, check our pricing page.
Statsig Cloud is a great choice for those who want to get started quickly without needing to manage infrastructure or data warehousing.
Statsig Warehouse Native (WHN)
If your events and metrics already reside in your own data warehouse and you have a dedicated data team, Statsig Warehouse Native (WHN) may be a better option.
- WHN allows you to host Statsig’s Stats Engine within your warehouse, enabling you to calculate metric lifts on your pre-existing datasets.
- You can choose between two methods:
- Using 3rd party or your own SDKs: You handle feature assignment and provide us exposure data (you randomize the users).
- Using Statsig SDKs: We handle randomization and write data into your warehouse for you.
The first method helps you scale analysis, while the second can 10x your experimentation velocity.
WHN is available only with Enterprise contracts. If you’re interested in this option, check this link or schedule a demo with our Sales team.
Which Model is Right for You?
Below is a summary of key criteria to consider when making your decision between the two modes of deployment:
| Criteria | Cloud-hosted | Warehouse native (WHN) |
|---|---|---|
| Data Source | Primary source of metrics come from Statsig SDKs or CDPs like Segment. Some metrics can still come from a warehouse. | Warehouse is the primary source of metrics, making WHN ideal when wanting to reuse existing data pipelines and computation. |
| Analysis needs | Automated experimentation for every experiment and product launch, especially with metrics derived from event logging. | Flexible analysis on top of your existing source of truth metric data. |
| Data team involvement | Involvement is optional but recommended for experiment design and readouts. | Necessary for setting up the warehouse connection and configuring core metrics, but not mandatory for every experiment. |
| Costs | TCO is slightly lower. No warehouse costs involved. | TCO includes Statsig license + costs incurred for computation and storage in your warehouse. |
| Modularity | An integrated end-to-end platform that spans SDKs for feature rollout, experiment execution, analysis, and experiment readouts. | Modular: You can opt for the integrated end-to-end platform or choose to use only a subset of capabilities, such as assignment or experiment analysis. |
Still unsure! Read this blog post for further information: Statsig Cloud vs Warehouse Native.
Next steps
Once you've decided whether Statsig Cloud or Statsig Warehouse Native fits your organization’s needs, choose the appropriate getting started guide for your first use case:
Have a question or need help getting set up? Our Engineering, Data, and Product teams are ready to answer questions in our Slack community.