In my last article, I explained the mechanism of how Google Analytics 4 (GA4) measures user interaction with Events and DataLayer. This time, I will use Google Merchant Store as an example to explain the function of each eCommerce user's interactions. Dive in to see how GA4 can support and improve your eCommerce strategy.
Typically, this is what happens when a user enters your site to engage in purchase behaviour:
1.1: Initial Visit by Promotion Banners - The user visits the homepage to view the top promotions.
1.2: Initial Visit by Navigation Bar - If they know what they want, they use the navigation bar to go directly to the product list page.
2: Product List Browsing - The user views the list of items.
3: Product Interaction - The user views the product details and either adds the item to the cart or saves it to the wishlist for later.
4: Cart Review - The user reviews the shopping cart to confirm their items. This step often sees the highest dropout rate as users may leave to browse other pages.
5: Shipping Information - The user enters their shipping information.
6: Payment Information - After filling in the shipping details, the user adds their payment information. This step typically has the second-highest dropout rate as users may hesitate to complete the purchase.
7.1: Purchase Success- If all goes well with the payment gateway, the purchase is successful.
7.2: Purchase Failure - If there are issues with the payment gateway, the purchase may not be successful.
Step 8: Post-Purchase - If the user is dissatisfied with the product, they may request a refund.
Please find the detailed explanation here:
First, an event called view_promotion should be triggered.
If the user clicks on the promotion banner to find out more, another event called select_promotion should be triggered as well.
While this is not an official ecommerce event by Google Analytics 4, I recommend businesses implement this for comprehensive tracking.
First, an event called view_item_list should be triggered.
If the user clicks on a product to visit the product detail page, another event called select_item should be triggered as well.
*Please note that multiple items can also be pushed with their information simultaneously in the same item array.
First, an event called view_item should be triggered once the page is loaded with product information.
If the user clicks the "ADD TO CART" button, an event called add_to_cart should be triggered;
Similarly, if the user clicks the "Add to Wishlist" button, an event called add_to_wishlist should be triggered.
First, an event called view_cart should be triggered once the shopping cart is loaded.
If the user decides to adjust the quantity or remove an item from the cart, the following events should be triggered:
*If you have passed the location_id information (e.g., cart_page), you will be able to understand where the product was added or removed.
If the user clicks the "CONTINUE" button, an event called begin_checkout should be triggered to mark the start of the checkout process;
If the user has entered a coupon code, it should also be included in the DataLayer. Of course, it is recommended to create a custom event to record just this action with the entered coupon code.
An event called add_shipping_info should be triggered once the shipping details are entered by clicking the “UPDATE” button.
An event called add_payment_info should be triggered once the payment method is confirmed by clicking the “PAY NOW” button.
An event called purchase should be triggered once the order is confirmed.
While this is not an official eCommerce event in Google Analytics 4, I recommend businesses implement this for comprehensive tracking.
An event called refund should be triggered once the refund request is submitted by clicking the "Done" button, including all entered refund request details.
Google Analytics 4 is a powerful tool when every measurement point is meticulously implemented. Again, establishing a comprehensive DataLayer is not easy, often requiring 3-6 months depending on complexity and scale.
However, in my view, without robust data, any optimisation or enhancement effort remains merely speculative.
With a well-structured DataLayer, not only can you refine your optimisation strategies, but you can also enhance the precision of your advertising campaigns. Data may never be the solution itself, but it can certainly enable precise decision-making.
In my next blog, I will discuss how to view the eCommerce report on Google Analytics 4 using the GA4 property of Google Merchant Store.
