How to archive your Universal Analytics historical data

One other Google Analytics 4 migration challenge deadline is quick approaching, and this deadline is difficult set. On July 1, Google will delete all historical data from Common Analytics properties. This deadline additionally impacts Analytics 360 prospects.

With little greater than a month till the deadline, in case you have not finished so by now, your group must prioritize archiving your historic knowledge. There are three predominant phases I like to recommend for approaching this challenge.

Part 1: Make a plan

Earlier than archiving knowledge, it’s essential to determine:

What particular knowledge is essential to you? 

• Prioritize downloading knowledge that you just commonly check with, equivalent to conversion and gross sales knowledge.
• Make a full checklist of the information you could archive.

What number of years of knowledge do you wish to hold?

• Many people have been utilizing Google Analytics because the mid-2000s – does your group must archive knowledge from almost 20 years in the past? 
• Resolve how far again you wish to archive knowledge from. I like to recommend, at minimal, to think about archiving again to 2018 or so to make sure you have pre-pandemic knowledge because the pandemic actually introduced knowledge anomalies for a lot of corporations.

At what cadence do you overview knowledge?

• Contemplate how usually you usually report in your knowledge. Is it weekly? Month-to-month? 
• Relying on the archiving technique you select in Part 2, you might want to arrange the information into particular time increments.

Part 2: Select an archiving technique

There are three predominant choices obtainable for archiving your Common Analytics knowledge. Every has its personal professionals and cons, so select a way primarily based in your group’s sources and abilities.

Possibility 1: Handbook file downloads

• Execs: Simple for nearly all customers to do, free
• Cons: Time-consuming, cumbersome, troublesome to entry knowledge for reporting later, restricted to 5000 rows

Whereas that is the simplest course of to grasp, it’s also time consuming.

Following your plan for years, cadence and knowledge factors, you’ll want to enter every report within the Google Common Analytics interface, set the date, dimension and metric settings as wanted.

Additionally, keep 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 knowledge as potential.

Click on the export button and export knowledge to a Google Sheet, Excel or CSV. Repeat this course of till you’ve gotten downloaded all the knowledge recognized in your archive plan.

Possibility 2: Obtain knowledge to Google Sheets utilizing the Google Analytics add-on (best choice for tech novices)

• Execs: 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 whole knowledge 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 spreadsheetadd-on.

The add-on basically makes use of the Google Analytics API to obtain knowledge to Google Sheets however doesn’t require API programming data to function. Google has compiled a fundamental overview of this strategy on this help document.

The primary time you employ the add-on, you’ll construct a report utilizing the add-on’s interface. However after the primary report has been run, you can too merely replace the Report Configuration tab and create extra experiences straight in columns of that sheet.

You too can 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 discipline. 

One downside of the Google Sheets technique is that you could be encounter sampling for those who pull an excessive amount of knowledge directly (e.g., your whole 20-year dataset for classes) or your report is just too detailed (too many dimensions pulled collectively for a excessive stage of granularity). 

If you run a report, you’ll see the sampling stage on the report’s knowledge tab in cell B6. In case your report accommodates sampled knowledge, you might wish to contemplate decreasing the quantity of knowledge on this explicit pull, for instance, you may break up the pull into two time frames.

Nevertheless, for those who simply can’t keep away from sampling, examine the information pattern share on the report. Then, on the Report Configuration tab, unhide rows 14-17 and the sampling dimension on row 15 to this stage in order that your knowledge stays constant.

Tip: The add-on defaults to 1,000 strains of knowledge in a report. Merely delete the 1,000 below 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 knowledge exceeds the ten,000,000 cell limitation (which may very seemingly occur), then you might must have a number of Google Sheets to obtain all the knowledge.

Possibility 3: Obtain knowledge utilizing the Google Analytics API

• Execs: Pulls knowledge rapidly as soon as arrange
• Cons: Requires internet growth data and sources, doesn’t clear up the information sampling concern, API quota limitations

When you have internet growth sources that may work on the archiving challenge, they will pull the information detailed in your plan utilizing the Google Analytics API straight. 

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 how you can use the API for this challenge, go to Google’s archiving information page and overview the second bullet, which particulars a number of sources and concerns for utilizing the API for this knowledge export challenge.

Possibility 4: Obtain knowledge to BigQuery (best choice total)

• Execs: Easy to entry knowledge later for reporting, elevated knowledge insights, most versatile for knowledge
• Cons: Sophisticated for novices to arrange initially, can contain charges for BiqQuery, might require technical sources to arrange, must contain an extra instrument

The principle good thing about archiving your Common Analytics knowledge to BigQuery is that BigQuery is a knowledge warehouse that permits you to ask questions of the information set by way of SQL queries to get your knowledge in a short time. That is particularly helpful in accessing this knowledge 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 technique. See instructions from Google.

Everybody else

In the event you’re not an Analytics 360 person, then you definately’ll must strategy 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 here are the steps you’ll wish to comply with:

• Step 1: Create a Google API Console challenge and allow BigQuery.
  • Log in to the Google APIs Console.
  • Create a Google APIs Console challenge.
  • Navigate to the APIs desk.
  • Activate BigQuery.
• Step 2: Put together your challenge for BigQuery export.
  • Guarantee Billing is enabled on your challenge. Chances are you’ll not must pay something, however it should fluctuate relying on the utilization and knowledge you’ve gotten.
  • If prompted, create a billing account.
  • Settle for the free trial if it’s obtainable.
  • Validate Billing enablement. Open your challenge at https://console.cloud.google.com/bigquery, and attempt to create a knowledge set within the challenge. Click on the blue arrow subsequent to the challenge identify, then click on Create knowledge set. In the event you can create the information set, billing is setup accurately. If there are any errors, be sure that billing is enabled.
  • Add the service account to your challenge. Add [email protected] as a member of the challenge, and be certain that permission on the challenge stage is ready to Editor (versus BigQuery Knowledge Editor). The Editor function is required to be able to export knowledge from Analytics to BigQuery.
  • If you’re within the EU, please additionally review additional requirements.
• Step 3: Arrange a free trial of Supermetrics. Much like the Google Sheets add-on in possibility 2 above, Supermetrics is a instrument 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 challenge because you’re solely downloading the Common Analytics knowledge as soon as (not commonly).
  • Join the BigQuery knowledge supply within the Supermetrics dashboard. 
• Step 4: In BigQuery, set up the connection to Supermetrics.
  • Navigate to BigQuery, then to Knowledge 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 instructions on how to set up a transfer.
  • Beneath Third-party connection, click on Join supply.
  • Settle for the settlement.
  • Click on Authorize together with your Google knowledge supply.
  • Click on Register with Google.
  • Register with the Google Account you employ with this knowledge supply. This doesn’t should be the identical because the Google Account you employ with Supermetrics.
  • Click on Permit.
  • 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 must switch the Common Analytics knowledge one time, you can too change the schedule on the switch to On demand after which run the switch now. 

Part 3: Make sure you’ve captured all of it

Earlier than you contemplate the challenge full, be sure you double-check your archived knowledge to make sure you’ve captured all the pieces you deliberate to archive.

On July 1, you’ll not be capable to entry Common Analytics knowledge, both by API or by way of the interface.