It is imperative to use Google Analytics to analyze your website traffic. You must be aware by now that Google has launched the most awaited GA4 in 2020. Many of you have already shifted to this platform, but for those who are still using the old Universal Analytics (GA3), it’s time to pack up and move on.
Google Analytics, since 2005, has helped marketing strategists in analyzing web traffic with statistical data. Consequently, GA3 came as an advanced tracking system with tools to capture details about customers’ insights and behavior on a webpage.
Now is the age of GA4, which renders data based on events and parameters. It is an entirely different methodology than GA3, which measured sessions and page views.
The article below talks about procedures you can apply to secure your website’s Universal Analytics (GA3). But why has Google launched the new GA4, and is it necessary to shift to this new interface? Let’s find out more!
What is the Scenario After the Launch of GA4
Going back into history, Google has regularly made changes in analytics. The Classic Google Analytics took over in 2007 with upgrades to Synchronous code (ga.js) followed by Asynchronous code (ga.js.) These changes enabled better tracking of e-commerce transactions with quick page load.
In comparison, Universal Analytics (GA3) used advanced tracking codes (analytics.js tags) to generate more responsible data. Moreover, the GA3 platform with property id (UA-XXXXXXXXX-1) incorporated the entire data of the former version with no extra effort for the users.
Finally, the new GA4 has enhanced its operability and creates reports based on web and app platforms. It focuses on the privacy concerns of the user. While UA records first-party cookies and the user’s IP address, the GA4 tracks data using the first-party cookies along with AI, which is the trend in user behavior.
The interface of GA4 is different from the earlier version with property id (G-XXXXXXXXX.) Therefore, it is not an upgrade but a replacement of the earlier analytics tool with no automatic transformation of the data to the new platform.
So, here is the ultimatum for the GA3 properties. Google has recently taken down Universal Analytics from the standard sites on 1st July 2023. This means there will be no data processing done after this due date.
Although Google Analytics 360 property will remain active until 1st October 2023, Google will end the platform completely by next year on 1st July 2024.
What is the way out for Google UA properties?
The market research professionals handling big brands or e-commerce portals have worked for years with their clients to understand the customers and other crucial factors. So, what will happen to the years👨💻 of effort on your website data research and analysis?
What does Google recommend about UA data? And do you still need this data, or is it worthless?
The answer lies in the fact that this website data can be an immense source of information, which you can reference for future marketing tactics. Hence, you can consult with your marketing team on specific metrics that have been a matter of concern in the past and have relevance in the next campaigns.
Here, the point is if you are late, you will lose all the website’s analysis processed on the UA interface. Google has officially announced the cease of the UA platform and advises using optimum methods to export the data well before it ceases permanently.
Therefore, the question arises: how to back up Universal Analytics or GA3 data before it gets deleted?
Factors That Impact Data Backup in Universal Analytics
While exporting the data from the UA platform, you must tackle the following aspects that may cause issues in the process.
🔆A few rows may get skipped if you do not properly set the custom dimensions or events during the backup process.
🔆Expanding nine dimensions and ten metrics in a query is restricted.
🔆Report query limiting is another problem faced with long-range data when the backup file has high cardinality dimensions marked as “other” in a single row.
🔆User engagement metrics also have trouble in data backup, as incorporating the figures on a weekly or monthly basis per user cannot be done.
🔆With heavy data on the platform, it becomes difficult to avoid sampling while exporting the data. Therefore, it is recommended to backup a few days of data at a time to keep the sessions less than 500,000, after which sampling takes place.
Hence, you should be careful while choosing the right method or tool to export Universal Analytics.
What is the Process to Backup Universal Analytics Data
It is clear by now that you need to shift your website resources or, to be precise, integrate them with the new and advanced analytical tool, GA4. In the meantime, take a backup of the historical analytical data from the UA interface.
However, exporting complete UA data is a complex issue; hence, you should know which metrics are more important and which are insignificant. We have listed the three most prominent methods to preserve the Universal Analytics or GA3 data.
🔶Data backup on CSV, Excel, or Sheets by applying the Export function or a Sheets connector add-on.
🔶Data backup on BigQuery
🔶Data backup using external tools
We’ll expand each method in detail.
Data Backup on CSV, Excel, or Sheets
By opting for this procedure, you can secure the data on Google Sheets or the local system in CSV, Excel, or PDF formats. The Export function on UA data is easy to adapt, but there is no doubt it is tedious, especially if there is a bulk of data to copy down.
Large data sets may cause you much stress doing the same task for many days. It only allows 5,000 transactions at once, with limitations on dimensions and metrics. The export feature usually causes sampling issues, while multiple headers and rows create excessive trouble.
Exporting to CSV formats locally
This method requires rigorous efforts by the user.
Step 1. Log in to the UA interface and open a report or table to export.
Step 2. Set the specific date from where to take the backup.
Step 3. Find the “Export” button on the top and click on it.
Step 4. Choose a file format from Excel, CSV, PDF, Google Sheets, etc.
Step 5. Browse to the location on the local device where you can save the data.
You can check the report data exported to the desired location.
Using Sheets Connector Add-ons
It is a complicated method to connect UA data with Google Sheets.
Step 1. Log-in to your Google Drive and create a Sheet in a separate folder with a unique identifiable name.
Step 2. Click on the “Extension” tab from the navigation bar.
Step 3. Choose “Add-Ons” followed by “Get Add-Ons.”
Step 4. Download and install the Google Analytics application from the Google Workspace Marketplace.
Step 5. Open the newly created Google Sheets, and hit the “Extension” tab again to check the “Google Analytics” option.
Step 6. Bring the cursor on the Google Analytics option, and click on “Create new report.”
Step 7. Rename the report, and choose the Account, Property, and View that you aim to back up.
Step 8. Select the metrics and dimensions on the report, such as Users, Bounce rate, Source, Medium, etc., as per the requirements. You can leave the Segments column blank. You may also customize the report with date range or other filters.
Step 9. Click the “Create Report” at the bottom of the page.
Step 10. Now hit the “Extensions” tab on top.
Step 11. Click “Google Analytics” and select “Run Reports.”
The process will export the data on the sheets.
Export UA Data Using BigQuery
BigQuery is a cloud-based enterprise data warehouse designed by Google and is suitable for big-size data handling. Although it is included in the GA4 platform, only paid customers of Google Analytics 360 can use it for data backup⬇️.
The process of exporting data through BigQuery is called backfill, which leaves it to a table of row and column format rather than the regular report.
Begin with creating a data set, and get the Google Cloud account, BigQuery project with billing enabled, and a paid connector (such as Supermetrics for BigQuery), which is essential to start the process.
It may be challenging to manage large and complex data structures. The process is lengthy with critical steps; hence thoroughly follow the below procedure for creating the data set, customizing the schema, and managing the data transfer, to schedule the backfill procedure.
Step 1. Open the BigQuery project on Google Console.
Step 2. Check the Project ID under the Explorer section, and hit the three vertical dots next to it.
Step 3. Click to “Create data set.”
Step 4. In the new window type the Dataset ID, which will be the name of the data set, and hit the “Create Data Set” button given below.
Step 5.Now open your BigQuery Data Transfer your Google Console Account and check the project name on top.
Step 6. Click the “Create Transfer” link in a caption on the top.
Step 7. Under the Source type section, open the drop-down menu for source, and click the “Explore Data Sources” link at the bottom.
Step 8. A new window slides on the screen with the Marketplace heading. Type “Google Analytics by Supermetrics” in the search bar.
Step 9. Select on the searched product and click the “Enrol” button in the next window.
Step 10. Now check the Source drop-down menu again, and then choose Google Analytics by Supermetrics.
Step 11. Under the “Transfer Config name,” type “Backfill UA data to BigQuery.”
Step 12. Choose the data set you created (UADataExport) under the Destination settings, and click on the “Connect Source” button at the bottom.
Step 13. Accept the agreement and follow the sign-in steps for connecting Google Analytics API to BigQuery.
Step 14. After the Google Account confirmation, next, choose the Schema and Accounts followed by hitting the Submit button.
Step 15. Lastly the Source is connected. “Save” the settings.
Finally, the backfill process begins and displays “The transfer run is pending.”
In a few minutes, “The transfer run is complete”✔️ notification appears on the screen.
UA Data Backup Using External Tools
There are a couple of third-party tools that ease the process of exporting data from Universal Analytics. We’ll discuss them below.
#1. Analytics Safe
Analytics Safe is a tech company that ensures data safety for your businesses. More than forty data scientists and engineers have teamed up to create this data analytics tool, which you can avail for basic, Mid-tier, and Enterprise plans on a yearly basis.
It is embedded with a user-friendly customizable dashboard that lets you generate efficient output from useful metrics data. The tool tracks web activities for startups and big brands dealing with complex services, products, marketing plans📝, or user communication.
They have technical experts to handle the queries of eCommerce website analytics while securing the UA data. These experts take care of the complete process of Universal Analytics data export. All you have to do is share your UA interface’s access, and they will create an interactive dashboard for you to visualize the migrated data.
This online tool gives the flexibility to incorporate UA data into the GA4 interface, which you can access on any internet device.
#2. Piped Out
Piped Out is an all-in-one data service provider company. They work both as an in-house team or an outsourced agency and offer all sorts of data warehousing services like UA data migration, Rank tracking, or Full data service.
The tool is designed to primarily focus on SEO data sources while also managing Google Analytics📈, Search Console, Logs Files, Crawl Data, Rank Tracking, and Link Data. Piped Out query builder has pre-build queries for SQL work and enables the user to fill the form for SEO metrics.
The company has experience in handling large websites with huge amounts of data. Hence, they easily get over issues relating to sampling and data limits. The tool is capable of processing the raw UA data exported over BigQuery and also manages the GA4 interface in a manner for instant analysis.
It is often irritating to use the Google Analytics platform, as it takes a lot of time to load the data while scrolling, and thus, exporting the bulk of data creates glitches. But the Piped Out is sufficient to deal with all such issues, and you can easily create your business account on GA4 for smooth and effortless usage.
The team will formally consult with your technical staff about the business details and data requirements for growth. They will create a data warehouse to save the UA data and integrate it with the tool for flexible usage along with data storage.
#3. Upped Game
The web analytics at Upped Game hold expertise in data gathering, analysis, and reporting in Google Analytics. They assist in launching and configuring GA4 accessibility for the client. The team ensures to delivery of efficient results with Google Tag Manager, Google Looker Studio, and Audit actions for the GA4 platform.
The Universal Analytics data export service is provided by technical specialists at the company who share screens and connect through video calls anywhere around the World🌏. They have arranged the right set of tools with professionals with core knowledge of the Google Analytics interface.
The cost of the whole UA data backup process varies depending on the client’s data requirements. They may charge on the basis of several hours spent on the project or the number of rows extracted from the UA database.
Instead of creating the database on an online portal, this tool gives complete freedom to export the UA data on BigQuery, Excel, CSV, or Google Sheets as needed.
Electrik.AI is a full-fledged cloud-based software service provider company. It has listed several software integration products for iO: Data Pipelines and CMi: Customer and Marketing Intelligence.
Database management services are offered for free🆓 to all users to initiate the backup process. And later, they charge a minimal fee on a monthly basis, which gives you the option to end the service anytime.
The data extraction from Universal Analytics does not require the installation of any specific software on the system, and you can provide the export destination such as Excel, Sheets, or BigQuery. You only have to create a free account on Electric.AI and provide Google Analytics with Tag Manager details.
The tool requests a few steps on the panel about selecting a data source, destination, date & month🗓️, etc. The data backup process will begin, and you will start getting results within a day. It takes UA data backup at hit-level granularity and has the capability to manage all the Google Analytics properties.
Some of its features include unsampled data, event details at hit level, unfragmented data with more than 250 attributes, unique visitor ID to link visitors from different sites, and complete data ownership.
Can you migrate UA (GA3) data to GA4
The notable fact is that there are some basic differences between Universal Analytics and GA4. The GA4 interface collects event-based data, i.e., records📃 each webpage interaction. In contrast, the data model for UA is based on sessions (hits) or user interaction with the page. GA4 collects data and incorporates it in a more informative pattern than the Universal Analytics interface. Another prominent factor that makes GA4 reports different from UA is adding engagement metrics and removing the bounce rate of earlier UA interfaces. That explains why the UA data is not directly merged into the GA4 interface. Due to the unmatched data model of both platforms, you cannot migrate the UA data directly to the GA4 interface.
Since the sunset of GA3 is pretty close🏁, it is essential to get familiar with the new web analytics interface, GA4. But business strategists’ real concern is preserving the analytics data before it vanishes.
You can apply the procedures of manually exporting the data into CSV, Excel, Sheets, or other formats and secure the data in a desired location. BigQuery is a helpful solution recommended by Google 360 users to back up the data. However, implementing these methods requires technical skill and patience, as they are error-prone and time-consuming.
Alternatively, contacting third-party service providers with dedicated UA data backup tools can ease the whole process. The tools discussed here are loaded with additional features, such as creating & managing GA4 accounts. They require minimal assistance from the client and deliver accurate results.
Nitesh Malviya is a proficient writer who delivers credible and unique write-ups in multiple genres. He writes authoritatively producing well-researched and optimized content depicting the reader’s perspective. A Computer Sc. Engg…. read more
Narendra Mohan Mittal
Narendra Mohan Mittal is a Senior Digital Branding Strategist and Content Editor with over 12 years of versatile experience. He holds an M-Tech (Gold Medalist) and B-Tech (Gold Medalist) in Computer Science & Engineering.
Having a website is a very exciting and powerful thing. It’s the equivalent of owning real estate but on the Internet. Once you have an active website, specific metrics will be crucial in helping you determine how well your website meets its intended objectives.