Spot eCommerce Conversion Issues with GA4

🟢 Quick Summary for Busy Readers

Want to improve your eCommerce conversion rate? Start by comparing the number of users who added items to cart vs users who completed a purchase in Google Analytics 4 (GA4).
A large gap (over 10%, but it depends on the industry) could point to technical problems or poor user experience during checkout. Fixing these issues can significantly boost your sales conversion rate.

How to Identify eCommerce Conversion Issues Using GA4(Google Analytics 4)

If you run an online store, one of the easiest ways to detect hidden issues is by tracking this simple—but powerful—metric:

In GA4, track:

• How many users added to cart (add_to_cart event)
• How many users completed a purchase (purchase event)

✅ Add to Cart to Purchase Conversion Rate Formula:

(Number of Users Who Purchased ÷ Number of Users Who Added to Cart) × 100

This gives you the add-to-cart to purchase conversion rate, a key eCommerce metric. A healthy conversion rate means your sales funnel is working smoothly. But if too many users drop off after adding to cart, something needs your attention.

What Is a Good Add to Cart to Purchase Conversion Rate?

A typical conversion drop-off between add to cart and purchase should be under 10%, but this varies based on:

• Industry
• Product type
• Business size and stage

This metric is a starting point to identify whether there is a drop-off in customer journeys.
“Number of Users Who Added to Cart” refers to all users who added at least one item to their cart during your selected time period. The same definition applies to “Purchased Users.”
Since this is a high-level metric, you can use it to quickly check for any major issues.

🔄 Common Reasons for Add to Cart Abandonment

Always start by checking your “Add to Basket” and “Purchase” events in GA4 to ensure your tags are working correctly. If your tagging is working as expected, then move on to analysing the checkout journeys. In many scenarios, users drop off during the checkout steps, I’ll explain this with a real example in the next section.
However, there are also other common reasons why users abandon their carts before completing a purchase:

Real GA4 Funnel Example: How I Increased eCommerce Conversion by 120%

On one of my recent projects, I found that only 25% of users who added items to their cart ended up making a purchase — a huge red flag.
I started by checking the “Add to Basket” and “Purchase” tags to ensure they were firing correctly. Then, I analysed the checkout journeys, since most of the drop-offs were happening in that part of the funnel.

Here’s the step-by-step process I used:

1. Funnel Analysis in GA4

I built a Funnel Exploration in the Explore tab of GA4 to visualise the full checkout process, as the website had four steps in its checkout flow. This helped me identify the main drop-off point.
As you know, GA4 shows you what happened and where it happened, but it doesn’t explain why it happened.
So after pinpointing the drop-off step, I used Hotjar to understand why it was happening by analyzing user behavior through session recordings.
I also went through several checkout sessions myself to spot any confusing steps or bad user experiences firsthand.

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2. Watched Real User Behavior with Hotjar

At this step, I discovered several poor user experiences and a few technical issues that caused confusion. In some cases, these issues even made it impossible for users to complete their journeys.

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3. Watched Real User Behavior with Hotjar and documentation

It’s really important to document all of these issues clearly so the development and digital teams can take action. I always break down my findings into three parts to make things easy to understand and act on:

Subjects	Explanation
What’s the issue?	A clear, specific description of the problem. This includes where it happens (e.g. on which page or step), how users are affected, and any relevant screenshots or data.
Why does it matter?	An explanation of the impact — such as lost conversions, increased bounce rate, or user frustration. This helps teams understand the urgency.
how it should be? (Suggestion)	A proposed solution based on analysis. It could be a technical fix, a UX improvement, or a content change — whatever best addresses the root cause.
Priority level	I assign a priority (Must Have, Should Have, Could Have, Won’t Have) based on the severity of the issue and its potential business impact.

🔧 4. Fixed the Issues

Once the issues were resolved, the conversion rate jumped from 25% to 55%—a 120% improvement.

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✅ Final Tips to Increase Conversion Rate on Your Online Store

1. Use this metric for high-level analysis to spot potential issues early.
2. Always monitor the checkout steps — keep the process short, clear, and optimized.
3. Watch session recordings with tools like Hotjar — it’s like reading your customer’s mind to uncover pain points.
4. Use Funnel Exploration in GA4 to identify exactly where users are dropping off.
5. Be transparent: show all costs upfront, including shipping and taxes, to avoid surprises at checkout.