Claravine + Google Analytics 4

Julia Randall
Julia Randall
  • Updated

Google is replacing sessions and hits with users and events. Advertisers and publishers must now model interactions on websites as a user completes each individual event instead of a user’s session and the events (goals) that are completed during that session.

Due to the limitations of this newest iteration of Google Analytics, Claravine has no direct integration with Google Analytics 4 (GA4), but we do offer several workflows. Use this article for solutions to work around the GA4 limitations when using The Data Standards Cloud with GA4.

Our considerations were:

  • GA4 supports custom parameters for event-scoped, user-scoped, and item-scoped dimensions. Session-scoped custom parameters are on an indefinite hold.
  • Event-scoped custom dimensions require you to create custom event tags along with a data layer on your site to pass information.
  • Whether user-scoped or event-scoped, to pass first-party user information you would have to create the data layer. Both options require a dedicated Web Development Operations team for the creation and implementation of the tags and data layer.

Custom Events

If you have the resources and want to follow the standard practice by adding custom event-scoped dimensions to your sites:

  1. Using GTM, create a custom event for your landing pages.
    The event parameters of the custom event should capture metadata from URL parameters in the tracking link using JavaScript code to parse the URL for keys and values.
    Google Tag Manager (GTM) has a Lookup Table feature (1:1 dependent list) for clients using coded values.
  2. For GA4 to use the data, create custom event-scoped dimensions in your GA4 environment.
  3. Finally, update your GA4 tag configuration.

UTM Parameters Only

You can use the default utm parameters to track campaigns. These are the default parameters:

  • utm_id: Campaign ID or other unique identifier
  • utm_source: Web traffic referrer
  • utm_medium: Type of creative or marketing
  • utm_campaign: Campaign name or other identifier
  • utm_term: Search keyword
  • utm_content: Additional identifier used mainly for creative
  • utm_source_platform: The ad platform

Data-Driven Attribution Modeling With Google Ads / CM360

You can take advantage of Google’s product suite linking, specifically Google Ads and Campaign Manager 360, to perform data-driven attribution modeling in GA4. GA4 requires at least three pieces of data: source, medium, and campaign. For manual traffic, use the following Analytics reference to match the correct channel grouping:

  • utm_source: Web traffic referrer
  • utm_medium: Type of creative or marketing
  • utm_campaign: Campaign name or other identifier

Custom Dimension Widening

As of July 2023, Google does not allow a data import for session-scoped custom dimensions. Consider custom dimension widening if you want to include additional metadata that is not captured by GA4 to enhance your analytics and reporting. We recommend the following:

  1. Use utm_id to pass a unique identifier to Google Analytics.
  2. Export to BigQuery.
  3. Match the utm_id to Claravine’s submissions in your reporting platform of choice.

<GA4→{utm_id}→BigQuery→Reporting Platform←Data Warehouse←{utm_id}←Claravine>

Custom Dimension Widening With Google Products

As of July 2023, Google does not allow a data import for session-scoped custom dimensions. As a result you can not report on custom dimensions in GA4. To include additional metadata that is not captured by GA4 to enhance your analytics and reporting using only Google products, we recommend the following:

  1. Use utm_id to pass a unique identifier to Google Analytics.
  2. Export to BigQuery.
  3. Connect it to Data Studio (previously known as Looker).
  4. Match the utm_id to Claravine submissions in Google Cloud Storage.

<GA4→{utm_id}→Data Studio←Google Cloud Storage←{utm_id}←Claravine>

Dimension Widening Options

GA4 captures web traffic on my campaigns UTM IDs, but if you also want to have additional custom dimensions and expansive metadata, there are two ways to work with GA4 (note that in both options GA4 collects your traffic on a UTM ID). The decisive factor is:

Are you doing native reporting within GA4?

  • If NO (if you are doing your reporting outside of GA4 in another BI tool, like Tableau), then Option 1 is available and recommended because you can add dimensions/metadata without development work.
  • If YES (if you are doing native reporting with GA4), then Option 2 is available, but not recommended, because it requires development work and is generally less flexible.

Option 1 (Recommended)

  1. Use Claravine's templates to create your UTM IDs and associated, additional metadata (widened dimensions) for your campaigns.
  2. Push this data (UTM IDs and additional dimension widened metadata) into Google Cloud Storage or another file drop destination to make it available to your BI tool.
  3. Combine Claravine and GA4 data:
    • If you use Google Cloud storage and Data Studio (Google's BI tool), you can combine the Claravine data and the GA4 traffic data (joining on UTM IDs).
    • If you use another storage system or a BI tool other than Data Studio, Google's Big Query is a useful way to pull your GA4 Traffic data and join it via UTM IDs with your other data in your BI Tool (e.g., Tableau).
  4. Match up your site traffic data with your wider campaign metadata via UTM ID lookup on Claravine metadata.

Option 2

If you are natively reporting within GA4, and you have a development team that can create custom event triggers in Google Tag Manager, then you can use these to create custom dimensions inside GA4.
If you are not doing native reporting within GA4 (and most people don't; they typically use another downstream BI tool), then consider our recommended Option 1.

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