Universal Analytics to GA4: A Comprehensive Guide

Universal Analytics was introduced by Google in 2012, providing more accurate and detailed insights into user behavior.

It allowed for the collection of data from multiple devices and platforms, giving businesses a more comprehensive understanding of their customers.

One of the key features of Universal Analytics was its ability to track users across multiple devices and platforms, including mobile and desktop.

This made it easier for businesses to understand how users were interacting with their website or app.

You'll need to act fast to prepare for the Google Universal Analytics shutdown. Most users will lose access to the interface and API on July 1, 2023, with only a week's worth of data available after that.

Google recommends gathering close to a year's worth of past data to do year-over-year comparison of metrics. This will allow your teams to make better decisions based on historical data.

You must download your old Universal Analytics data before July 1, 2024, as it will be deleted forever. The data will be deleted within a week of the shutdown, so act quickly.

Exporting your previously processed data is crucial to preserving your old Google Universal Analytics data. You have 30 days to download it before it's gone for good.

Not much time is left to store Google Universal Analytics data before the July 1 deadline.

Several actions can still be done quickly to prepare for a life without Google Universal Analytics.

Acting quickly is essential, as users can still make plans for a life without Google Universal Analytics.

To get started, users can refer to the related article "Master the Move from Universal Analytics to Google Analytics 4" for more information.

GA4 seamlessly connects to other Google products, like Google Ads and Firebase, making it easy to share data and take action.

You can import data from your Google Ads account into GA4 and generate a report to see how your campaign performs. This is especially useful for monitoring the performance of your Ads campaigns.

GA4's integrations also allow you to sync data from other sources, such as Universal Analytics. This includes streams like website_overview, traffic_sources, and pages.

Here are some of the streams you can sync from Universal Analytics:

This allows you to access a wide range of data, including website overview, traffic sources, and page data.

When setting up your Google Analytics source connector, you have four sync modes to choose from.

Full Refresh - Overwrite is one of the supported sync modes, which will overwrite any existing data in your destination.

Full Refresh - Append is another option, which will add new data to your destination without deleting the existing data.

Incremental Sync - Append is a sync mode that will only add new data to your destination, without overwriting or deleting existing data.

Incremental Sync - Append + Deduped is a more advanced sync mode that will add new data to your destination and remove any duplicates.

To summarize, the four sync modes are:

Make sure to add the service account email address on the account level, not the property level, to avoid a 403 error.

Recommended events in Google Analytics 4 (GA4) are events that aren't implemented automatically or in the enhanced measurement.

These events are essential for tracking specific user interactions, like login, purchase, and sign_up. Creating recommended events ensures compatibility with future GA4 releases.

To create a recommended event, check if what you need is already listed in the recommended events section. If it is, follow the guide for that event.

Recommended events include login, purchase, and sign_up, which are crucial for understanding user behavior and interactions on your website or app.

Exporting data is a crucial step in preparing for Google's Universal Analytics 2023 sunset. You can export data in various formats, including CSV, TSV, or Google Sheets, using the Google Analytics Reporting API or the Data Export tool within the Universal Analytics interface.

The Google Sheets add-on for Analytics is a convenient option for exporting data, but it has a limitation of 5,000 rows per export. This means you'll need to repeat the process for each view data you want to archive.

To prioritize data export, focus on the most critical segments that fit planned operations and future analysis. These typically include referral sources and conversion reporting, such as user acquisition trends by channel, user behavior metrics, and demographic data.

There are three ways to export your data: exporting individual reports, using the Google Analytics Reporting API, or installing the Google Sheets add-on for Analytics.

Exporting individual reports is a manual process that can be done in a few hours, depending on how long you've been tracking data. You can download reports in PDF, Google Sheets, Excel (XLSX), or CSV format.

Here are the four main areas to export, along with some subreports to consider:

Additionally, you may want to export reports on:

Exporting data can be a tedious process, but it's faster and less expensive than learning the API code and setting up a new data transfer service.

GA4 and UA are almost two different products in terms of data models, infrastructure, capabilities, interface, and user experience. This means that while they share some similarities, they also have some key differences.

One way to tell them apart is by looking at the tracking ID. GA4 properties have a Measurement ID, which starts with a capital G and a hyphen, followed by up to 10 characters that can be numbers and letters. On the other hand, UA properties use a Tracking ID, which begins with a capital UA and a hyphen, followed by 7 numbers and a trailing hyphen and number.

If you're seeing nearly double the amount of sessions in your UA property than your GA4 property, it's likely due to how Google calculates sessions differently between the two.

GA4 properties have a Measurement ID, which starts with a capital G and a hyphen (G-), followed by a string of up to 10 characters that can be numbers and letters.

To find your GA4 Measurement ID, go to Admin » Property » Data Streams and click on a data stream. The Measurement ID shows up in the stream details after the Stream URL and Stream Name.

UA properties, on the other hand, use a Tracking ID instead of a Measurement ID. The Tracking ID begins with a capital UA and a hyphen (UA-), followed by 7 numbers and a trailing hyphen and number (-X).

The trailing number in a UA Tracking ID is a sequential number starting from 1 that maps to a specific property in your Google Analytics account.

You can find the Tracking ID for a UA property under Admin » Property (column) » Property Settings » Tracking Id.

If you've set up dual tracking to use both a GA4 and UA property to track site performance, you'll notice differences between your GA4 and UA reports when comparing numbers.

UA reports show higher amounts of sessions than GA4, which is likely due to the way Google calculates sessions differently between the two platforms.

To get the most accurate real-time data, use the Realtime report in a Google Analytics 4 property, as it shows more accurate numbers than the UA Realtime report.

The UA Realtime report may show low numbers when you first open it, but waiting a few minutes can give you more accurate data.

GA4 and UA also have different tracking IDs, making it easy to tell which property you're looking at - GA4 uses a Measurement ID that starts with G-, while UA uses a Tracking ID that starts with UA-.

Google Analytics 4 (GA4) is a powerful tool that allows you to track and analyze user behavior across multiple platforms.

One of the key features of GA4 is its ability to track events, which can be custom-defined to suit your business needs.

GA4 also allows for enhanced measurement of user interactions, including scrolling, clicking, and form submissions.

Data retention in GA4 is set to 2 months by default, but can be adjusted according to your specific needs.

GA4 introduces a new concept called "events" which replaces the traditional "goals" and "events" system of Universal Analytics.

With GA4, you can track user behavior across multiple platforms, including web, mobile, and even offline interactions.

GA4's machine learning capabilities enable it to automatically identify and track patterns in user behavior, without requiring manual configuration.

Universal Analytics has some limitations when it comes to cross-device reporting, but Google Analytics 4 (GA4) is a game-changer in this area.

GA4's new data streams approach and event-based data collection model allow for easy tracking of multiple devices on a single property using different streams.

With GA4, you can create custom reports and dashboards that precisely display the data you wish to see.

One of the biggest limitations of Universal Analytics is its restricted customization options, which can often require you to use indirect solutions like developing custom reports manually or transferring data to Excel or Data Studio for further analysis.

GA4's built-in report editor allows you to make adjustments directly within the platform, eliminating the need to export data to another tool.

Customization in GA4 is a game-changer for anyone who wants to get specific insights from their data.

With Google Analytics 4 (GA4), you can easily track multiple devices on a single property using different streams.

This is a significant improvement over Universal Analytics (UA), which is quite limited with its cross-device reporting.

GA4's new data streams approach and event-based data collection model allow for consolidated sessions and reports across devices.

To set up Airbyte for universal analytics, you'll need to log into your Airbyte Cloud account. Navigate to the left navigation bar and click Sources. Click + New source in the top-right corner.

You'll then be taken to the Set up the source page, where you'll select Google Analytics from the Source type dropdown. This is a crucial step, as it allows Airbyte to connect to your Google Analytics account.

To authenticate your Google account, you can use OAuth or Service Account Key Authentication. This will grant Airbyte permission to access your Google Analytics data.

You'll also need to enter the Replication Start Date in YYYY-MM-DD format. If you leave this field blank, Airbyte will replicate all data. Alternatively, you can enter a specific date to replicate data added on and after that date.

Here are the key fields to fill out:

Optional fields include the Custom Reports field, where you can enter a JSON object as a string, and the Data request time increment in days field, which you can leave blank or set to 1 for faster syncs.

When choosing a temporary storage location, marketers should select a platform that is both secure and reliable.

For most B2B companies, the data will be a reasonable size, often as simple as a few CSV files.

Cloud storage platforms like Google Cloud Storage, Amazon S3, or Microsoft Azure are useful for secure and scalable storage.

Local storage can be used while determining if better solutions that support centralized analysis exist.

In urgent instances, having any storage may be the only option, making a reliable platform essential.

Automated Event Tracking is a game-changer in Google Analytics 4 (GA4). GA4 automatically tracks events such as user_engagement, session_start, page_view, and first_visit.

You don't need to do anything to activate these events - there's no setting to turn on, and no code to write. This means you can start collecting valuable data right away.

Some examples of automatically collected events include first_visit, which tracks the first time a visitor comes to your website or Android instant app, and session_start, which marks the time when a visitor opens a web page or app.

Here are some examples of automatically collected events:

This is just the tip of the iceberg - there's more to discover about automatically collected events in the Google Analytics help docs.

To set up Airbyte to connect with Google Analytics, you'll need to follow these steps. First, log into your Airbyte Cloud account or navigate to the Airbyte Open Source dashboard.

To start, you'll need to select Google Analytics as the source type from the dropdown menu. This will take you to the Set up the source page. Enter a name for the Google Analytics connector, which will help you identify it later.

Next, you'll need to authenticate your Google account. You can do this via OAuth or Service Account Key Authentication. Choose the method that works best for you.

The Replication Start Date is also an important field. Enter the date in YYYY-MM-DD format to specify when data replication should start. If you leave this field blank, Airbyte will replicate all data.

You'll also need to enter the View ID for the Google Analytics View you want to fetch data from. This is a crucial step, as it determines which data Airbyte will sync.

If you want to fetch data from a specific date range, you can enter a value in the Data request time increment in days field. However, be aware that setting this value to more than 1 may result in sampled data and potential inaccuracies.

Here's a quick reference guide to help you set up your Google Analytics connector: