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The Gist
- Maximizing Google Analytics 4 (GA4) reporting tools: GA4 offers four methods to extract data, including Standard Reports, Explorations, Data API, and BigQuery Export, giving users flexibility and powerful analytics options.
- Understanding the strengths and limitations of GA4’s reporting options: Standard Reports serve high-level and frequent lookups; Explorations offer advanced report types and deeper analysis.
- Leveraging GA4 for advanced marketing decisions: The transition from Universal Analytics to GA4 provides an enhanced platform for marketers to extract valuable insights.
Congratulations! You put in the work, rallied your engineers, and successfully migrated from Universal Analytics to Google Analytics 4 (GA4).
Now what?
How do you pull the data you need to make well-informed marketing decisions? With GA4, there’s an abundance of choice which can make it daunting for users who don’t know where to start.
Google has provided four different methods to pull data out of GA4: Standard Reports, Explorations, the Data API and the BigQuery export. In contrast, free users of Universal Analytics had only two options: Standard Reports & the Reporting API. The two additional options in GA4 (Explorations and BigQuery Export) are unique in that they work from raw data as opposed to pre-aggregated data. With raw data, you can pose questions that you otherwise cannot to aggregate data, but the computational power required is greater. What that means in practice is that Explorations are subject to data retention and sampling limits while your requests to BigQuery will potentially generate usage fees.
GA3 Reporting Options
Aggregate Data | Raw Data |
Standard Reports Reporting API | BigQuery Export (GA360 Customers Only) |
GA4 Reporting Options
Aggregate Data | Raw Data |
Standard Reports Data API | Explorations BigQuery Export |
Now that you have a high-level overview, let’s dig into when you might want to use or avoid each option.
GA4 Standard Reports: Use for Basic Inquiries
Standard Reports are the reports available as soon as you log in to the GA4 interface. While these are meant to mimic the Standard Reports available in GA3, you may notice that they are limited in both form and function. Not all dimensions are available in standard reports and the chart types are limited to line, scatter and bar. Google has moved advanced visualizations and analyses to the “Exploration” reports (more on those later) which means that “standard” reports should be used only for frequent lookups and basic inquiries.
When to Use GA4 Standard Reports
- When you have frequent needs to look at the same high-level metrics broken down by one or two dimensions.
- When you need to view metrics across very long time periods and want to avoid sampling.
- When you’ve deployed a consent banner and want to view modeled data.
When to Avoid GA4 Standard Reports
GA4 Standard Reports
- When you need to break down your report by more than two dimensions.
- When you want to view data broken out by segment and the segment has not yet been defined as an “Audience.”
Related Article: 8 Google Analytics 4 Features That Leave Universal Analytics in the Dust
GA4 Explorations: Fueled by Raw Data
Explorations are a new, advanced reporting option available in GA4. Given that it’s brand new, it tends to cause some confusion around how its reports and the data behind those reports differ from other reporting options. What may be helpful to know is that the reason Explorations are broken out into its own interface is because they are fueled by raw data while Standard Reports are fueled by pre-aggregate data. What this means in practice is that you can ask questions in Explorations that you can’t ask in Standard reports.
With this additional power comes a few limitations: The raw data fueling these reports is retained for up to 13 months and data will be sampled after 10 million events are included in the analysis. Both limitations are relaxed for paying customers.
When to Use GA4 Explorations
- When you need to evaluate user segments and have not yet created these segments as Audiences.
- When you need to view your analysis using advanced report types such as a funnel report, Sankey diagram or Venn diagram.
- When you need access to all available reporting dimensions and metrics while conducting your analysis.
When to Avoid GA4 Explorations
- When you need to share an analysis that others can manipulate and edit. Explorations are shared as read-only objects and the report date range cannot be changed by others.
- When you need to analyze >13 months of data or >10M events.
Related Article: Master the Move from Universal Analytics to Google Analytics 4
GA4 Data API: Adds Unsampled Data Queries
When there is a need to automate, extract, or otherwise programmatically access Google Analytics data, look toward the Data API. The GA4 Data API replaces the GA3 Reporting API while offering some new capabilities like unsampled data queries and the ability to generate funnel reports. Most commonly, users deploy the Data API alongside ETL (extract, transform, load) tools such as Fivetran, AirByte, Stitch or Supermetrics, which provide an easy-to-use interface for creating a connection to GA4 and extracting data into a data warehouse.
When to Use GA4 Data API
- When you need to pull GA4 data into your own data infrastructure for reporting in business intelligence (BI) tools such as Tableau or Power BI.
- When you want to avoid quota limits encountered when using the Looker Studio GA4 connection.
- When you want to access GA data from programming languages like Python or R.
When to Avoid GA4 Data API
- When your needs are met by GA4 Explorations and Standard reports.
- When you need to pull >9 dimensions at a time. The Data API is limited in the number of dimensions that can be extracted in any single request.
- When you need access to raw data or data about individuals (see BigQuery Export).
BigQuery Export: Unique Integration Effort
Working with GA4 raw data in BigQuery is not for the faint of heart. The data schema is cryptic, the SQL skills necessary range somewhere between advanced to ninja, and the risk of accidentally running a query that adds hundreds of dollars to your credit card bill are real.
That said, the opportunities this integration affords are unique compared to the prior three reporting options. The BigQuery export is the only way to access information about an individual to the extent that GA4 can become an extension of your CRM (customer relationship management) or CDP (customer data platform) stack.
With GA4, Google has decided to make the raw data export feature free. Keep in mind, however, that Google’s benevolence here only goes so far. The company expects that this free integration will inspire customers to make use of their paid Google Cloud products such as BigQuery.
When to Use BigQuery Export
- When you have use cases that rely on individual-level data. This could include building a composable CDP, blending data with a CRM system, or creating user-level segments.
- When you have advanced analysis needs that go beyond the capabilities of the Explore Reports and Data API.
When to Avoid BigQuery Export
- When you don’t have advanced SQL expertise on staff to make use of the data in BigQuery.
- When you don’t have any use cases that require raw data.
Conclusion on GA4 Reporting Options
With the deprecation of GA3 behind us, it’s a new era of Google Analytics. The reporting options available in GA4 are powerful, but each fulfill specific use cases, which can make it daunting when deciding where to go. One thing that is clear is that there is no turning back. Arming yourself with this information can help you make the right Google Analytics reporting decisions moving forward.
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