Mastering Google Analytics recommended events

Let’s introduce recommended events

In the digital ecosystem, understanding user behavior is crucial for optimizing web and app performance.

This understanding is facilitated by tracking specific user interactions, known as Google Analytics recommended events.

In this article, we dive deeper into the significance of these events, focusing on their setup and practical applications in digital analytics.

The Importance of Google Analytics Recommended Events

Recommended events in Google Analytics play an important role in capturing detailed user interactions beyond the automatically collected events.

These events are essential for web analysts and digital marketers as they provide deeper insights into user behavior, enabling data-driven decision-making.

Tracking recommended events requires explicit configurations. However, the insights gained are invaluable for optimizing user experience and marketing strategies.

What is a recommended event?

A recommended event in the context of Google Analytics 4 refers to a predefined type of user interaction that Google suggests tracking on websites and mobile apps.

This is in addition to both automatically collected events, which are tracked by GA4 by default without any configuration, and events captured through enhanced measurement, which are automatically recorded once enabled in the GA4 settings.

Unlike these automatically tracked events, recommended events require manual setup by the user. They encompass a broad array of user actions, from e-commerce-related activities such as adding an item to a shopping cart (add_to_cart), to engagement metrics like video plays.

The aim of recommended events is to offer a standardized collection of relevant interactions that are applicable to a wide variety of digital platforms. The idea behind this comes down to having a uniform approach to data collection.

By integrating these events, analysts and marketers can delve deeper into understanding user behavior, facilitating the development of more precise and effective optimization tactics.

Each recommended event can be detailed further with specific parameters, thus providing a comprehensive dataset for thorough analysis and informed decision-making.

For an extensive overview of all recommended events and their parameters, definitly have a look at Google’s Developer documentation.

Example of a Recommended event

Let’s start this chapter of with understanding a recommended event more in-depth. E.g. The add_to_cart event is a prime example of a recommended event. It’s one specific event taking place in a customer journey.

It tracks when a user adds a product to their shopping cart, offering valuable insights into purchasing behavior. Some even consider it to be a key event.

Parameters:

• currency: Indicates the currency type for the transaction. Essential for financial analysis and reporting.
• value: Represents the total value of the item(s) added to the cart, crucial for assessing potential revenue.
• items: An array that provides detailed information about the item(s) added, including the item ID, name, brand, and price. This level of detail aids in inventory and marketing strategy refinement.

This event and its associated parameters offer a detailed view of user engagement with products, helping businesses understand purchasing trends and user preferences.

Let’s map out a customer journey for purchasing a gaming computer on an e-commerce website.

Why not highlight the relevant recommended events at each step in this customer journey, from viewing an item list to making the purchase. Indeed, why not!? So, here we go.

This journey not only captures the customer’s interactions but also sheds light on their decision-making process.

1. Viewing an Item List (view_item_list)

Rosita begins her journey by browsing through a list of gaming computers. The view_item_list event is triggered, capturing Rosita’s interest in this particular category.

Parameters Captured:

• item_list_id: “gaming_computers”
• item_list_name: “Top Gaming PCs”

2. Selecting a Product (select_item)

From the list, Rosita selects a high-performance gaming PC for more details, triggering the select_item event. This action provides insights into which products are drawing users attention.

Parameters Captured:

• item_list_name: “Top Gaming PCs”
• items: [{item_id: “pc123”, item_name: “Predator Gaming PC”}]

3. Viewing Product Details (view_item)

Upon selecting the Predator Gaming PC, Rosita is taken to the product detail page. This step triggers the view_item event, indicating Rosita’s interest in learning more about the product’s features.

Parameters Captured:

• items: [{item_id: “pc123”, item_name: “Predator Gaming PC”, price: 1500.00}]

4. Adding Product to Cart (add_to_cart)

Convinced by the specifications and reviews, Rosita decides to add the Predator Gaming PC to her shopping cart. The add_to_cart event is recorded, marking an intent to purchase.

Parameters Captured:

• currency: “EUR”
• value: 1500.00
• items: [{item_id: “pc123”, item_name: “Predator Gaming PC”, quantity: 1}]

5. Initiating Checkout (begin_checkout)

After reviewing her cart, Rosita proceeds to checkout, initiating the begin_checkout event. This action signifies a transition from consideration to the purchasing phase.

Parameters Captured:

• currency: “EUR”
• value: 1500.00
• items: [{item_id: “pc123”, item_name: “Predator Gaming PC”, quantity: 1}]

6. Entering Payment Information (add_payment_info)

During the checkout process, Rosita enters her payment information, a crucial step towards completing the purchase. The add_payment_info event captures this significant action.

Parameters Captured:

• payment_type: “Credit Card”

7. Completing the Purchase (purchase)

Finally, Rosita confirms the details and completes the purchase. The purchase event is logged, encompassing all relevant details of the transaction and marking the successful conclusion of this journey.

Parameters Captured:

• transaction_id: “order789123”
• affiliation: “Gaming Gear Online”
• currency: “EUR”
• value: 1500.00
• tax: 315.00
• shipping: 20.00
• items: [{item_id: “pc123”, item_name: “Predator Gaming PC”, quantity: 1}]

Tracking these recommended events throughout Rosita’s journey offers valuable insights into the effectiveness of the website’s e-commerce customer journey.

More specific, the website’s navigation, product presentation, and checkout process.

This data can help identify areas for optimization to improve the user experience and ultimately increase sales in this competitive gaming computer market.

Build Audiences based on Recommended Events.

The newly collected data provides an opportunity to build audience segments in Google Analytics 4.

As audience building in GA4 allows for creating audiences based on conditions related to Recommended Events. Creating and utilizing these audience segments enables further marketing personalization, increasing the positive results of your marketing efforts.

An example could be the creation of an audience that has realized purchases, named “Purchasers” and present in the general reference templates in the audience building section in Google Analytics 4.

How to set up Google Analytics Recommended Events

Data Layer Implementation

The first step in tracking recommended events is to push the event and its parameters to the Data Layer. This involves adding JavaScript code to your site that executes when the event occurs.

The following code snippet is an example of the dataLayer.push() method to send event data when an action occurs that you’d like to measure.

dataLayer.push({
  'event': 'add_to_cart',
  'currency': 'EUR',
  'value': 1500.00,
  'items': [{
    'id': 'SKU123',
    'name': 'Predator Gaming PC XQ',
    'brand': 'Predator',
    'category': 'Gaming PC',
    'variant': 'Black and RGB',
    'price': 1500.00,
    'quantity': 1
  }]
});

Configuration in Google Tag Manager (GTM)

After updating the Data Layer, the next step is to configure Google Tag Manager to recognize and process this event.

This involves creating a new tag configured to fire on the add_to_cart event, using the data pushed to the Data Layer to send the event to Google Analytics 4.

More specific, once the tag is created with the aforementioned parameters, add a trigger of type ‘Custom Event’ with event name corresponding to the event’s name, in this case: add_to_cart.

When looking at the tag in GTM’s Preview Mode, you’d encounter something like this:

When setting up event triggers and tags to capture the data for recommended events, it is important to ensure correct functioning.

Debugging is essential to ensure correct firing of tags and validating the captured information is as expected.

For an extended article on how to debug, read our article on ‘Debugging in Google Tag Manager‘.

Viewing Events in Google Analytics 4

With the tag configured and activated in GTM, events like add_to_cart will be visible in the GA4 interface under the “Events” section.

Here, analysts can review event occurrences and analyze the data to gain insights into user behavior and preferences.

As seen in Google Analytics 4:

Conclusion

Tracking recommended events, such as add_to_cart, is essential for deepening your understanding of user interactions on your website or app.

By configuring and setting up these events through the Data Layer, GTM, and GA4, digital marketers and web analysts can access a wealth of data that can inform strategic decisions.

For an even further and deepened analysis of all data collected, think about setting up the GA4 to BigQuery data connection. The BigQuery data warehouse allows for an even more granular data analysis.

Although the setup process requires initial effort, the resulting data is a powerful asset for optimizing digital marketing efforts and improving overall business performance.

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