One other Google Analytics 4 migration mission deadline is quick approaching, and this deadline is tough set. On July 1, Google will delete all historic information from Common Analytics properties. This deadline additionally impacts Analytics 360 prospects.
With little multiple month till the deadline, you probably have not achieved so by now, your group must prioritize archiving your historic information. There are three predominant phases I like to recommend for approaching this mission.
Section 1: Make a plan
Earlier than archiving information, it’s essential to determine:
What particular information is essential to you?
- Prioritize downloading information that you just repeatedly discuss with, resembling conversion and gross sales information.
- Make a full record of the information it’s worthwhile to archive.
What number of years of knowledge do you wish to preserve?
- Many people have been utilizing Google Analytics for the reason that mid-2000s – does your group have to archive information from practically 20 years in the past?
- Resolve how far again you wish to archive information. I like to recommend, at minimal, to contemplate archiving again to 2018 or so to make sure you have pre-pandemic information for the reason that pandemic actually offered information anomalies for a lot of firms.
At what cadence do you assessment information?
- Think about how usually you usually report in your information. Is it weekly? Month-to-month?
- Relying on the archiving methodology you select in Section 2, you might want to arrange the information into particular time increments.
Dig deeper: Why the shift from ‘conversions’ to ‘key occasions’ in GA4 is a game-changer
Section 2: Select an archiving methodology
There are 4 predominant choices accessible for archiving your Common Analytics information. Every has its personal professionals and cons, so select a technique primarily based in your workforce’s assets and expertise.
Choice 1: Guide file downloads
- Professionals: Straightforward for nearly all customers to do, free.
- Cons: Time-consuming, cumbersome, tough to entry information for reporting later, restricted to 5000 rows.
Whereas that is the best course of to know, it’s also time consuming.
Following your plan for years, cadence and information factors, you’ll want to enter every report within the Google Common Analytics interface, set the date, dimension and metric settings as wanted.
Additionally, bear in mind to vary the variety of rows from the default of 10 to the utmost of 5,000 rows to make sure you seize as a lot information as doable.
Click on the export button and export information to a Google Sheet, Excel or CSV. Repeat this course of till you may have downloaded the entire information recognized in your archive plan.
Choice 2: Obtain information to Google Sheets utilizing the Google Analytics add-on (most suitable choice for tech novices)
- Professionals: Pretty easy to implement for many customers with spreadsheet expertise, free, quick to obtain.
- Cons: Restrictive to a set timeframe (e.g., month-to-month), every sheet has complete information limitations, usually encounters sampling points.
This feature is pretty easy for many customers to carry out. Create a brand new Google Sheet and add the Google Analytics spreadsheet add-on.
The add-on basically makes use of the Google Analytics API to obtain information to Google Sheets however doesn’t require API programming data to function. Google has compiled a fundamental overview of this method on this assist doc.
The primary time you utilize the add-on, you’ll construct a report utilizing the add-on’s interface. However after the primary report is run, you may also merely replace the Report Configuration tab and create further stories instantly in columns of that sheet.
You can even conveniently use formulation within the Report Configuration sheet. Use the Dimensions and Metrics Explorer to seek out the correct API code to enter into every area.
One downside of the Google Sheets methodology is that you could be encounter sampling should you pull an excessive amount of information without delay (e.g., your whole 20-year dataset for periods) or your report is just too detailed (too many dimensions pulled collectively for a excessive degree of granularity).
If you run a report, you’ll see the sampling degree on the report’s information tab in cell B6. In case your report accommodates sampled information, you might wish to take into account decreasing the quantity of knowledge on this explicit pull, for instance, you may cut up the pull into two time frames.
Nonetheless, should you simply can’t keep away from sampling, verify the information pattern proportion on the report. Then, on the Report Configuration tab, unhide rows 14-17 and the sampling measurement on row 15 to this degree in order that your information stays constant.
Tip: The add-on defaults to 1,000 traces of knowledge in a report. Merely delete the 1,000 underneath the road labeled “Restrict” (usually row 11).
One other downside of the Google Sheets possibility is that every file is proscribed to 10,000,000 cells. Usually, every sheet begins out with 26 columns (A to Z) and 1,000 default rows (or 26,000 cells).
In case your downloaded information exceeds the ten,000,000 cell limitation (which may very probably occur), then you might have to have a number of Google Sheets to obtain the entire information.
Choice 3: Obtain information utilizing the Google Analytics API
- Professionals: Pulls information rapidly as soon as arrange.
- Cons: Requires net improvement data and assets, doesn’t resolve the information sampling situation, API quota limitations.
In case you have net improvement assets that may work on the archiving mission, they will pull the information detailed in your plan utilizing the Google Analytics API instantly.
This works equally to the aforementioned Google Sheets add-on possibility, however it’s a extra handbook course of in programming the API calls.
To find out about the best way to use the API for this mission, go to Google’s archiving info web page and assessment the second bullet, which particulars a number of assets and issues for utilizing the API for this information export mission.
Choice 4: Obtain information to BigQuery (most suitable choice general)
- Professionals: Easy to entry information later for reporting, elevated information insights, most versatile for information.
- Cons: Sophisticated for novices to arrange initially, can contain charges for BiqQuery, could require technical assets to arrange, have to contain an extra device.
The primary advantage of archiving your Common Analytics information to BigQuery is that BigQuery is a knowledge warehouse that means that you can ask questions of the information set via SQL queries to get your information in a short time. That is particularly helpful in accessing this information for reporting later.
Analytics 360 customers
If you’re an Analytics 360 person, Google gives a local export to BigQuery. I like to recommend this methodology. See these directions from Google.
Everybody else
In the event you’re not an Analytics 360 person, then you definitely’ll have to method the BigQuery backup in a different way as a result of Google doesn’t present innate BigQuery backup choices in Common Analytics for non-360 customers.
Listed below are the steps you’ll wish to observe:
- Step 1: Create a Google API Console mission and allow BigQuery.
- Log in to the Google APIs Console.
- Create a Google APIs Console mission.
- Navigate to the APIs desk.
- Activate BigQuery.
- Step 2: Put together your mission for BigQuery export.
- Guarantee Billing is enabled in your mission. You might not have to pay something, however it can fluctuate relying on the utilization and information you may have.
- If prompted, create a billing account.
- Settle for the free trial if it’s accessible.
- Validate Billing enablement. Open your mission at https://console.cloud.google.com/bigquery, and attempt to create a knowledge set within the mission. Click on the blue arrow subsequent to the mission title, then click on Create information set. In the event you can create the information set, billing is setup accurately. If there are any errors, ensure that billing is enabled.
- Add the service account to your mission. Add [email protected] as a member of the mission, and make sure that permission on the mission degree is about to Editor (versus BigQuery Information Editor). The Editor position is required with a view to export information from Analytics to BigQuery.
- If you’re within the EU, please additionally assessment further necessities.
- Step 3: Arrange a free trial of Supermetrics. Just like the Google Sheets add-on in possibility 2 above, Supermetrics is a device that helps non-technical customers interface with and use APIs. They provide a free 14-day trial, which is probably going all you’ll want for this mission because you’re solely downloading the Common Analytics information as soon as (not repeatedly).
- Join the BigQuery information supply within the Supermetrics dashboard.
- Step 4: In BigQuery, set up the connection to Supermetrics.
- Navigate to BigQuery, then to Information transfers.
- Click on + Create switch.
- Choose your Google Analytics by Supermetrics as your supply and click on Enroll.
- Fill within the switch particulars. See detailed directions on the best way to arrange a switch.
- Below Third-party connection, click on Join supply.
- Settle for the settlement.
- Click on Authorize along with your Google information supply.
- Click on Register with Google.
- Register with the Google Account you utilize with this information supply. This doesn’t must be the identical because the Google Account you utilize with Supermetrics.
- Click on Enable.
- Choose the accounts you’d like to incorporate in your reporting and outline the switch settings.
- Click on Submit.
- Click on Save.
Since you solely have to switch the Common Analytics information one time, you may also change the schedule on the switch to On demand after which run the switch now.
Dig deeper: 3 methods GA4 is manner higher than UA
Section 3: Make sure you’ve captured all of it
Earlier than you take into account the mission full, remember to double-check your archived information to make sure you’ve captured the whole lot you deliberate to archive.
On July 1, you’ll now not have the ability to entry Common Analytics information, both by API or via the interface.
Opinions expressed on this article are these of the visitor creator and never essentially MarTech. Employees authors are listed right here.
