After exporting Google Analytics data to BigQuery, what new opportunity do you have to use your data?
You can use audiences to target website experiments and test variants of your web pages
You can access app-specific reports such as crash data, notification effectiveness, and deep-link performance
You can use SQL to query your data to answer questions and gain insights into your products, users, and channels
You can use conversions for ad campaign bidding, and audiences to target ad campaigns
Explanation
Analysis of Correct Answer(s)
The core benefit of exporting Google Analytics data to BigQuery is gaining access to your raw, unsampled, event-level data in a scalable data warehouse. This enables you to use SQL (Structured Query Language) to perform highly customized and complex analyses that go far beyond the standard reporting capabilities of the Google Analytics interface. You can join GA data with other datasets (e.g., from a CRM) and build custom attribution models or predictive analytics.
Analysis of Incorrect Options
- Using conversions and audiences for ad campaigns: This functionality is a primary benefit of linking Google Analytics directly with Google Ads. It does not depend on the BigQuery integration.
- Accessing app-specific reports: App-centric reports, such as crash data and notification effectiveness, are native features within a Google Analytics 4 property that has an app data stream (often integrated with Firebase).
- Using audiences for website experiments: Targeting audiences for A/B testing is typically achieved by integrating Google Analytics with a testing tool like Google Optimize. This feature is independent of the BigQuery export.