After you've exported Google Analytics data to BigQuery, what can you do with your data?

You can use conversions for ad campaign bidding, and audiences to target ad campaigns

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


Choose an option to see if it’s correct. Check the explanation below. Learn Smarter, not Harder.

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Explanation: After you’ve exported Google Analytics data to BigQuery, what can you do with your data?


Explanation: The correct answer for this question is **You can use SQL to query your data to answer questions and gain insights into your products, users, and channels**. When you export Google Analytics data to BigQuery, you gain the ability to utilize SQL queries to analyze and extract insights from your data. With this capability, you can ask specific questions about your products, users, and channels and retrieve data-driven answers. This allows for deeper analysis and can help inform decision-making processes. As an assistant, I have seen clients benefit from utilizing SQL queries on their exported Google Analytics data in BigQuery. For example, a client used SQL queries to segment user behavior by different product categories and analyze conversion rates and revenue. This allowed them to identify the most successful products and optimize marketing efforts accordingly. Additionally, they were able to analyze user behavior across various channels and understand the customer journey, ultimately improving their overall marketing strategy. In conclusion, exporting Google Analytics data to BigQuery enables the use of SQL queries, providing the opportunity to gain meaningful insights into products, users, and channels, which can drive informed decision-making and enhance overall business performance.
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