Ever wondered how to get deeper insights from your Google Analytics data?

By integrating it with Statsig, you can unlock advanced experimentation capabilities that were previously out of reach. Imagine combining the rich user behavior data from Google Analytics with the power of Statsig's experimentation platform—giving you a comprehensive view of your users and how they interact with your product.

In this blog, we'll explore how to leverage Google Analytics data within Statsig Warehouse Native for enhanced experimentation. We'll walk through connecting your GA data to Statsig, defining meaningful metrics, and running experiments that can drive data-driven decisions. Let's dive in and see how you can take your product optimization to the next level.

Leveraging Google Analytics data for enhanced experimentation

Combining Google Analytics (GA) data with Statsig experiments provides deeper insights into user behavior. By integrating GA data into Statsig Warehouse Native, you gain the ability to run advanced experiments and analyze raw event data. This approach overcomes GA's limitations, enabling comprehensive analysis and more informed decision-making.

Statsig's integration with Google Analytics allows you to join experiment data with existing GA events. This combination offers a more complete picture of how experiments impact user interactions and key metrics. With Statsig's platform, you can leverage GA data to create targeted user segments and personalize experiences based on user attributes.

Accessing raw event data through Statsig Warehouse Native empowers you to perform complex queries and analyses. This level of granularity is essential for uncovering hidden patterns and identifying opportunities for optimization. By leveraging the power of BigQuery and Statsig's experimentation tools, you can gain valuable insights that drive business growth.

To get started with leveraging Google Analytics data for enhanced experimentation:

1. Set up data export from GA to BigQuery

2. Connect BigQuery to Statsig Warehouse Native

3. Define metric sources, metrics, and assignment sources in Statsig

4. Run experiments and analyze results using Statsig's dashboard

By following these steps, you can unlock the full potential of your Google Analytics data and take your experimentation efforts to the next level. Statsig's integration with GA provides a seamless way to gain deeper insights and make data-driven decisions that drive business success.

Connecting Google Analytics to Statsig Warehouse Native

To bridge the gap between Google Analytics (GA) and Statsig, export GA data to BigQuery. This process creates a direct connection, enabling seamless data flow for experimentation and analysis.

Next, set up the BigQuery integration in Statsig to access and utilize the exported GA data. Navigate to the integrations section in Statsig, select BigQuery, and provide the necessary credentials and configuration details.

Before running experiments, verify data integrity in BigQuery to ensure accurate results. Check that the exported tables contain the expected data fields and that the data aligns with your original GA reports.

By connecting GA to Statsig Warehouse Native, you can leverage the power of BigQuery for advanced analytics. This integration allows you to combine rich user behavior data from GA with Statsig's experimentation capabilities, enabling data-driven decision-making and optimization.

Statsig tips for running experiments with Google Analytics data can provide valuable insights. By integrating these two platforms, you unlock the full potential of your data and make informed decisions based on real user behavior.

Defining metrics and assignment sources in Statsig

After connecting your Google Analytics data to Statsig Warehouse Native, the next step is to define metric sources. Metric sources are SQL queries that extract the data you want to analyze from your BigQuery tables. These queries can select specific fields from your GA sessions tables, such as user identifiers, event parameters, and session-level metrics.

Once you have defined your metric sources, you can create metrics in Statsig. Metrics are the specific user behaviors or outcomes you want to measure in your experiments. Examples include conversion rates, engagement metrics, or revenue per user. When creating a metric, you'll select the appropriate metric source and define the metric type (e.g., count, sum, average) and any necessary parameters.

If you are tracking experiment assignment events through Google Analytics, you'll also need to set up assignment sources in Statsig. Assignment sources tell Statsig where to look for the events that indicate which users were assigned to each experiment variant. To create an assignment source, you'll write a SQL query that identifies these assignment events in your GA data.

By defining metric sources, metrics, and assignment sources, you can leverage your Google Analytics data to gain valuable insights from your experiments in Statsig. These Google Analytics and Statsig tips for experiment insights enable you to make data-driven decisions and optimize your product based on real user behavior.

Running and analyzing experiments with integrated data

With your Google Analytics data connected to Statsig, you can now launch experiments using the defined metrics and assignment sources. This allows you to test hypotheses and gain valuable insights into user behavior.

Statsig's dashboard provides real-time monitoring of experiment performance, enabling you to track key metrics and make informed decisions. By analyzing the results, you can identify areas for improvement and optimize the user experience.

Leveraging the power of integrated data, Statsig helps you uncover actionable insights that drive product innovation. By combining Google Analytics data with Statsig's experimentation capabilities, you gain a deeper understanding of user interactions and preferences.

Statsig's platform simplifies the process of running experiments, allowing you to focus on what matters most: delivering value to your users. With its intuitive interface and powerful analytics, Statsig empowers you to make data-driven decisions that enhance user engagement and satisfaction.

By utilizing Google Analytics and Statsig tips for experiment insights, you can unlock the full potential of your data. This powerful combination enables you to identify opportunities for growth, validate hypotheses, and continuously improve your product's performance.

Closing thoughts

Integrating Google Analytics with Statsig opens up a world of possibilities for advanced experimentation and data-driven decision-making. By leveraging the rich user data from GA within Statsig's platform, you gain deeper insights into user behavior and can optimize your product more effectively.

Ready to take your experimentation efforts to the next level? Explore the resources linked throughout this blog to get started, and unlock the full potential of your data.

Request a demo

Statsig's experts are on standby to answer any questions about experimentation at your organization.

Grab a Demo