Getting Ready For GA4: Saving Your Historical Data

As you’re making ready to arrange Google Analytics (GA4), you’re in all probability asking the identical factor we had been: What’s the very best technique for migrating our historic knowledge?

There ought to be a approach to do that, proper?

In this column, you’ll be taught whether or not we will merge knowledge in GA4 and three DIY methods to avoid wasting your historic knowledge.

Can You Migrate Your Data To GA4?

The main concern is whether or not GA customers can switch or migrate Universal Analytics knowledge into their Google Analytics 4 property.

Unfortunately, you can’t migrate your knowledge to GA4, and it’s not prone to be a characteristic we’ll see added within the coming months.

Migrating your knowledge to GA4 is just not prone to be a characteristic as a result of the 2 variations use utterly completely different knowledge fashions.

I spoke with Charles Farina, Head of Innovation at Adswerve, and he defined that:

“It is the difference in schema and dimension definitions/calculations that make merging the data not possible.”

Schema refers to how the info is organized and the language used to make sure compatibility. Essentially it’s the blueprint.

He explains you may see the variations in schema effectively when evaluating the MassiveQuery integrations for UA and GA4.

“The UA export is sessionized, meaning each row in the export is a session, and every interaction is nested in that row. The GA4 export is very different, where each row is the event (interaction) itself,” shared Farina.

Another key purpose is how dimensions and metrics are outlined and calculated in GA4 in comparison with UA.

Google has an ideal assist web page that goes over many of those.

For instance, let’s have a look at some of the widespread KPIs, “Users.”

Universal Analytics stories on Total Users or all customers, whereas GA4 focuses on Active Users or customers which have visited the web site a minimum of as soon as previously 28 days.

Even if we may migrate UA knowledge to GA4, it will be like evaluating apples to oranges.

If you’re questioning why this transformation is going on, you’ll discover the reply in our article, Google Analytics 4 FAQs: Stay Calm & Keep Tracking.

How To Export Google Analytics Historical Data

Google does empathize and encourages customers to export their historic knowledge.

“We know your data is important to you, and we strongly encourage you to export your historical reports during this time.”

Screenshot from Google Help, April 2022

Google hints that extra steerage on find out how to export could also be coming sooner or later.

The excellent news is whereas we can not migrate our knowledge, we will nonetheless reserve it.

Google permits GA360 (paid product) customers to export Universal Analytics knowledge to MassiveQuery. However, the price of this product makes it inaccessible for smaller organizations.

So, what about normal customers? How do the remainder of us export historic knowledge?

I’ll present you three DIY strategies and some instruments that may deal with extra advanced requests.

1. Manual Export

The best solution to export knowledge is to get it straight out of your Google Analytics account.

Open the GA normal report you wish to maintain. For instance Acquisition > All Traffic > Source/Medium.

Set any customizations you need, resembling a phase for a selected nation, a filter for a selected web page grouping, or a secondary dimension for touchdown pages.

Click EXPORT within the high proper nook.

Select the file format from the drop-down menu. You can select PDF, Google Sheets, Excel (xlsv), or CSV.

Though that is the simplest solution to export your historic knowledge, there are limitations.

You can solely apply two dimensions and are restricted to a most of 5,000 rows.

If you’re registering 1000’s of hits per day your knowledge could also be sampled.

Check for the inexperienced checkmark defend within the high left close to the title of the report you’re viewing; this implies your knowledge is just not sampled.

2. Google Analytics Dev Tools: Query Explorer

Google Analytics dev instruments sound off-putting (and technical), however you’re probably already acquainted with one of many instruments.

The Campaign URL Builder is usually used to create UTM parameters for campaigns.

GA dev instruments even have a question explorer.

This is a simple (and free) solution to export knowledge for non-technical customers (yeah!).

Open Query Explorer and click on the orange button, LOGIN.

Sign in to your Google Analytics account that has entry to the property you’re engaged on.

Screenshot from UA Query Explorer, April 2022

Select the account, property, and consider you wish to save knowledge for.

The instrument will mechanically set the GA ID, so that you don’t want to fret about that.

Set the remaining question parameters: Date vary within the format YYYY-MM-DD, metrics, dimensions, and any filters or segments you want to apply.

For metrics, choose the columns out of your Google Analytics report that you’re extracting knowledge from.

You can select each metric within the report you wish to replicate or just some metrics that assist obtain your objectives like “Users,” “bounceRate,” “avgSessionsDuration” and “goalCompletionsAll.”

Dimensions would be the rows from the Google Analytics report from which we’re exporting knowledge.

For instance, if we wish to see metrics (customers, bounce fee, length, and objective completions) by site visitors supply choose “ga:sourceMedium” because the dimension.

Note: If you intend to visualise this info in Data Studio, you’ll need to set the size “ga:Medium” and “ga:Source” individually.

“ga:SourceMedium” doesn’t work in Data Studio. More on visualizing to come back.

The remainder of the question parameters are non-obligatory. I like to recommend leaving these clean on this use case to drag the max quantity of information.

You can at all times kind, filter, and phase inside your spreadsheet.

Scroll to the underside and click on the orange button RUN QUERY.

From right here, obtain the info as .tsv (tab separated values) and open it in Excel or Google Sheets.

Note: Notice the UA – GA4 toggle within the left-hand menu navigation. By clicking this toggle, you may entry Query explorer for GA4 accounts.

3. Google Analytics Sheets Add-On

This possibility is a tad extra advanced however connects Google Analytics on to Sheets, so that you don’t have the additional steps of downloading and importing.

Create a folder in your Google Drive that can maintain your historic knowledge. Create a brand new Google Sheet and title one thing that can make sense for future staff members, like “UA Historical Data_Traffic Acquisition_2021.”

Along the highest menu navigation, click on Extensions > Add-Ons > Get Add-Ons.

Search for the Google Analytics app within the Google Workspace Marketplace. Click to put in and comply with the onscreen prompts.

Back to your Google Sheet. Click Extensions once more. This time you must see the app for Google Analytics.

Hover and click on Create new report.

Now it’s time to export your historic knowledge.

Step 1. Name your report one thing that is sensible on your fellow staff members. For instance, we are going to pull knowledge by monetary quarter, so report no. 1 shall be named “Q1 2021.”

Step 2. Select the Analytics view you wish to extract knowledge from by selecting our Account, Property, and View.

Step 3. Configure report. Here we are going to select our metrics, dimensions, and segments.

I’m going to maintain it easy for this instance and select “Users,” “Bounce Rate,” and “Goal Conversions” for my metrics and “source” and “medium” for my dimensions.

Note: ga:supplyMedium is just not appropriate with Data Studio. If you intend on visualizing this sheet, it’s best to drag the site visitors supply dimensions individually like ga: Medium, ga:Source.

Leave Segments empty to see all customers.

Clicking the blue button Create Report will lead you to configuration choices.

There are extra choices to customise our report that aren’t accessible on the earlier display screen.

We can regulate the date vary utilizing the format YYYY-MM-DD.

We can apply filters like nation, ga:nation==United States.

Double-check that all the pieces appears to be like appropriate, then click on Extensions > Google Analytics > Run stories to export your historic knowledge.

Screenshot from Google Sheets, April 2022

Note: Speed up this course of by copying and pasting the configuration over to the following column, updating the date vary, and working a number of stories concurrently.

A report standing popup will let you realize if you happen to’ve made any errors or as soon as the report is accomplished efficiently.

Row Number 6 will present us if the info is sampled or not. Row quantity 7 will inform us how a lot if the sheet comprises sampled knowledge.

In Universal Analytics, knowledge sampling occurs after 500,000 periods within the timeframe.

So, you may regulate your report knowledge vary to cut back the variety of periods in your timeframe.

Or, if you happen to want the complete dataset and wish to skip the forwards and backwards, use a third-party instrument to keep away from knowledge sampling.

Third-Party Tools

Optimizesmart.com has a 46-step walkthrough of utilizing Supermetrics for sending GA knowledge to MassiveQuery.

On March 12, 2022, JR Oaks introduced that they’re engaged on releasing an open-source GA to MassiveQuery backup script/workflow to the general public.

There are pre-built knowledge pipelines by firms like Hevo and Electrik AI that export historic knowledge from Google Analytics to a database file or knowledge warehouse of your alternative.

You may additionally think about switching to a paid Analytics supplier.

A couple of have already launched a Google Analytics historic knowledge import possibility.

Visualizing Historical Data With Data Studio

Now that you’ve got pulled your historic knowledge, you wish to make one thing simple to match to GA4.

Note: I’ve to forewarn you that trying to match UA and GA4 shall be actually tough as a result of the info fashions are utterly completely different.

Farina provides,

“Google intends for you to run GA4 side-by-side with UA and, instead of merging the data, just cut over to GA4 as soon as it has 13 months of historical data.”

Be assured that a whole lot of your hard-earned information and expertise carry over to GA4! Read, Getting began with GA4 to be taught the place to search out website site visitors, consumer engagement, occasions, and conversion stories.

Ok, again to visualizing historic knowledge.

Follow these steps to create a Data Studio report that can stack a historic knowledge desk on high of a GA4 knowledge desk, so your YoY outcomes are a minimum of in a single place.

Open Data Studio and click on to start out a Blank Report.

There shall be an overlay display screen to pick out the info supply you wish to join. Select Google Sheets.

Locate the spreadsheet you made above when exporting your knowledge. If you adopted the steps precisely, will probably be named “UA Historical Data _Traffic Acquisition_2021.”

Select the worksheet “Q1 2021.”

Using the primary row as headers will mechanically title your metrics and dimensions, so maintain packing containers each checked.

Select the non-obligatory vary that matches your sheet.

For instance, my headers begin at A15, and the final quantity in my sheet is E62, so my vary shall be “A15:E62.”

Data Studio will mechanically create a desk. Double-check that the configuration is identical as your sheet within the right-hand menu.

Medium is the first dimension. Flip the toggle so as to add a secondary dimension of Source.

Metrics are Users, Bounce Rate, and Goal Completions.

Your historic knowledge desk will look much like the screenshot beneath.

Next, we are going to create the identical desk however for our GA4 knowledge in the identical time-frame: Q1 2022.

Right-click to repeat and paste your desk, then change the info supply from UA Historical Data to your Google Analytics 4 account.

Because the metrics have completely different names, you will notice an error – invalid metric.

Click on every metric and replace it to one thing comparable like “Total Users,” “Engagement Rate,” and “Conversions.”

Dimensions will replace to “session/source” and “session/medium.”

Last, in the identical menu, scroll down and set the date vary so it matches your historic knowledge: January 01 – January 31, 2022.

The remaining report will look much like the screenshot beneath.

You can simply see main metrics 12 months over 12 months by evaluating historic knowledge with GA4.

Although, it’s pretty bare-bones.

You cannot mix this knowledge as a result of the definitions and calculations of the size and metrics are essentially completely different.

For extra strong historic reporting choices, resembling graphic customers or objective completions over a time frame, it’s possible you’ll wish to think about MassiveQuery.

Final Thoughts

Unfortunately, migrating your knowledge to GA4 is just not at present doable (and never prone to come) as a result of the 2 variations are essentially completely different knowledge fashions.

There are just a few DIY options for saving your historic knowledge, however the outputs are pretty bare-bones.

If you want extra strong info and reporting capabilities of historic knowledge, look into an information warehouse like MassiveQuery.

Google hints that extra info on exporting historic knowledge will come earlier than the July 2023 finish date.

Maybe that shall be an information connector for MassiveQuery for Google Analytics normal customers – one can hope.

More assets:

Featured Image: Paulo Bobita