Ever noticed checkouts outnumbering items added to the cart in your CRM and GA4 data?

What’s up with that, right?

If you’re you’re trying to hunt down that gremlin in your reports then you’re probably dealing with something like this:

Usually, this boils down to a tracking issue, but other factors may also be in play.

This discrepancy feels like a head-scratcher at first, but we’ll explain the possible reasons behind this unusual occurrence and the steps to fix it.

Quick Context

The purchase event is often set up first when implementing GA4 ecommerce, because it’s the minimum required to push into your data layer for tracking revenue data.

Other events, like add-to-cart, can be added, changed, or triggered incorrectly (e.g., not set up on the right pages, firing multiple times), creating gaps and causing discrepancies with tools like your CRM.

Often, this leads to a Google Analytics checkout issue where checkouts appear higher than add-to-cart events.

Date Ranges and Anomaly Detection

Although we usually start by examining the tracking setup in GTM and the customer journey to check which event is firing, there’s a reason we also look at dates.

Sometimes, the add_to_cart event works perfectly fine. 

However, during reporting meetings, clients realize that it wasn’t at some point in the past, resulting in a significant gap in historical data, and clients may demand explanations. Even if you weren’t responsible then, and your hypothesis suggests a tracking issue, the burden of proof is on you.

To solve that, you need to trace it back.

When Did It All Start?

Start by checking the date ranges in GA4 that match those in your CRM where data is missing.

Look at the Ecommerce purchases report in GA4 to identify where the Itemps added to carts metric (related to the add_to_cart event but more on this later) is missing or not showing any data. This helps determine when the problem started and clarify the source of the Google Analytics checkout issue.

If anyone is keeping track of changes in the company, ask them if they are aware of any changes during that time.

To achieve this you can:

  • Manually check each day
  • Use a line chart in Explorations

Manually check each day

Manually checking each day to see where something is off is one way to do it but it can be tedious. You’ll have to access the Ecommerce purchases report.

1- In GA4’s navigation panel, click Reports
2- Click Monetization to expand its content
3- Select Ecommerce purchases

If you know the date range, select it and check if the number of Items purchased is greater than the number of Items added to cart.

As you can see here:


An easier way is to use a visualization tool or a line chart in Explorations to quickly identify dates where the shopping cart event wasn’t working or tracked.

1- In the navigation panel, click Explore
2- Select a blank Exploration card

Add the items added to cart metrics.

1- Click the plus sign + beside Metrics

2- Type Add to carts
3- Tick the box
4- Click Import

Repeat the process to add the Checkouts metric.

Now you have enough to build the graph.

1- Double click the Add to carts metric or drag it into the Values field.
2- Select Line Chart

Look for a flat line or a line break indicating when the add_to_cart event wasn’t working or not tracked.

You can also look for anomalies if the event works but occasionally has issues.

From there, it’s easier to determine when the issues began.

Compare Findings With Other Tools

For instance, check the history of your other tools to see if anything correlates. In our case, the add_to_cart event was tracked later than the purchase event. Investigating Google Tag Manager’s versions revealed a version change around the same time the event started working.

The add_to_cart event was named incorrectly (it lacked the required underscores).

Always consider if major events occurred during the timeframe of your issue.

For example, Universal Analytics was phased out during our investigation period. Not everyone adjusted to this change, with many relying on automatically created properties, which brought other challenges.

Experience Your Customer’s Journey: Events to Watch For

Taking the time to navigate the customer journey as if you were a customer provides invaluable insights.

As you go through the steps, carefully check the events being triggered and pay close attention to these critical aspects:

  • Duplicated events
  • User behavior
  • Custom events
  • Duplicate Events

We’ll cover each in detail.

If the same event is fired multiple times for a user action, it can inflate the event count. Or, if the checkout event is triggered twice when a user clicks the checkout button, this will lead to an overcount of checkouts.

In our situation, the GA4 checkout event occasionally fired twice.

Once the user clicked the order button (step 2)

And again during the billing step (step 3).

This caused the begin_checkout event to appear on the billing and shipping steps.

Take note of such pages and steps and report them to your developer.

Use these tools to check which events are fired during the sales journey:

  • DebugView
  • Real-Time report if DebugView is too buggy
  • Adswerve DataLayer Inspector (Chrome extension)
  • The Network tab in Chrome Developer Tools

User Behavior

In some cases, users might proceed directly to checkout without using the add to cart functionality, mainly if multiple ways exist to initiate a purchase on your site or app.

Custom Event Implementation

If your implementation of GA4 has customized events that don’t follow the required naming conventions, this might cause unusual patterns in the data as we noticed here.

Locate Pages Where the Event is Missing

Identify other pages where the add_to_cart event may not be working correctly. Finding these pages can help prevent future data loss.

Use Explorations to create a custom report focusing on the page location dimension. For metrics, use Add to Add to carts and Checkouts. Add the Referrer dimension to understand where the issue might have started in the user path.

You can then export it to Excel or Google Sheets for further analysis.

When it’s not a tracking issue

Other explanations for why checkouts might be higher than add_to_cart events include:

  • Date Range Adjustment: In a visualization tool like Tableau, try reducing the date ranges from GA4 to see if the numbers match better. Sometimes, discrepancies can be due to differences in how date ranges are processed.
  • Session Counting: Check how GA4 and your CRM or visualization tool are counting sessions. Differences in session counting methodologies can lead to discrepancies in event counts.

A friendly reminder: GA4 isn’t a financial software like QuickBooks or FreshBooks. Because it is continually being updated, it’s normal to see a difference of around 10%.


When you encounter a situation where checkouts outnumber add-to-cart events, it often points to tracking errors or discrepancies in your GA4 setup.

We discussed various methods to identify and fix these issues, from adjusting date ranges to checking event triggers. You can pinpoint and address inconsistencies by carefully navigating the customer journey and using GA4’s tools.

If data accuracy is important to you, check out how the removal of Google Signals affects your data.

Have you experienced Google analytics checkout issues in your reports?

How did you resolve them?