Generate Personas from GA4 Data

What does using Google Analytics 4 mean for algorithmically generating personas?

Google Analytics 4 (GA4) is an analytics service that measures traffic and engagement across websites and apps.  With the forced move from Google Universal Analytics (UA), a.k.a., Google Analytics, to GA4, on July 1, 2023, web properties using Universal Analytics will no longer be processing data.  Owners of these sites will be able to see the Universal Analytics reports for a short period; however, new analytics will only flow into GA4 properties.

Many organizations have already implemented the migration and are running both Google Analytics versions.  With something like 80% of websites using Google Analytics UA, imagine how many analytics installations need to be updated!!!

Google has made significant changes in how GA4 works, with many people complaining, but some liking the changes.  Nevertheless, the underlying idea of GA4 is different; everything is now an event.

Here is one resource explaining the change, [UA→GA4] Universal Analytics versus Google Analytics 4 data: Comparing the Universal Analytics and Google Analytics 4 data models, and the list of changes between the two Google Analytics versions is lengthy, including:

  • Hit types
  • Events
  • Pageviews and screenviews
  • Sessions
  • Custom dimensions/metrics
  • Content grouping
  • User ID
  • Client ID
  • Parameters (Google Analytics 4 properties)
  • User property (Google Analytics 4 properties)
  • Data collection settings that can be migrated
  • Data collection settings with no equivalent in Google Analytics 4
  • Event batching for Google Analytics 4 properties
  • Comparing report data in your Universal Analytics and Google Analytics 4 properties

What does the change mean for those who generate personas from Google Analytics data?

The good news is that GA4 logs aggregate age, gender, and country information, [GA4] Predefined user dimensions, including the following user dimensions:

  • Age – The age of the user by bracket: 18-24, 25-34, 35-44, 45-54, 55-64, and 65+.
  • App store – The store from which the app was downloaded and installed.
  • App version – The versionName (Android) or the Bundle version (iOS).
  • Browser – The browser from which user activity originated.
  • City – The city from which user activity originated.
  • Continent – The continent from which user activity originated.
  • Country – The country from which user activity originated.
  • Device brand – The brand name of the mobile device (such as Motorola, LG, or Samsung).
  • Device category – The category of the mobile device (such as mobile or tablet).
  • Device model – The mobile device model name (such as iPhone 5s or SM-J500M).
  • Gender – The gender of the user (male or female).
  • Interests – The interests of the user (such as Arts & Entertainment, Games, Sports).
  • Language – The language setting of the device OS (such as en-us or pt-br).
  • New/Established – New: First opened the app within the last 7 days.  Established: First opened the app more than 7 days ago.
  • Operating system – The operating system used by visitors to your website or mobile app.
  • OS version – The operating system version used by visitors to your website or mobile app.
  • Platform – The platform on which your website or mobile app ran (such as web, iOS, or Android).
  • Region – The geographic region from which user activity originated.
  • Subcontinent – The subcontinent from which user activity originated.

Combined with the event tracking above, one can still generate personas from GA4 data.

In fact, here is an algorithmically generated persona from GA4 data.

Algorithmically-Generated Persona from GA4 Data
Algorithmically-Generated Persona from GA4 Data

If you are interested in creating personas from GA4 data, please reach out to qcri.personas.contact@gmail.com

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