7 GA4 E-commerce Tracking Mistakes That Make Your Data Useless

GA4 replaced Universal Analytics. Most e-commerce stores migrated. Most of those migrations have problems.

Not obvious, site-breaking problems. The quiet kind — where the numbers look plausible, the dashboard shows a conversion rate, and everything seems fine.

Until you dig in and realize you've been making decisions on data that's 30% wrong.

Here are the seven most common GA4 e-commerce tracking mistakes, why they matter, and how to fix them.

Mistake #1: Relying on GA4's Default Purchase Event Without Verification

GA4 automatically tracks a purchase event if you're on Shopify, WooCommerce, or most major platforms. It seems like it just works.

Often it doesn't.

Common problems:

• The purchase confirmation page fires the event on refresh, double-counting orders
• The tag fires before the order is actually confirmed (payment processing still pending)
• GDPR/cookie consent tools block the tag for a percentage of users, causing systematic undercounting
• Cross-domain issues between your store and a third-party payment gateway break the session, losing the conversion attribution

How to verify: Compare GA4 purchase counts against your actual order management system (Shopify admin, Stripe dashboard, WooCommerce orders) for the same 30-day period. If the numbers differ by more than 5%, your tracking has a problem.

Mistake #2: Not Filtering Out Internal Traffic

Your team visits your own site constantly. So do your developers, your agency, your staging tests.

If you haven't excluded internal IP addresses from GA4, these sessions pollute your data in ways that compound over time.

Internal traffic often:

• Has unusually high session duration (developers leave tabs open)
• Has near-zero conversion rate (team members rarely buy)
• Spikes on specific days (launch days, test days)
• Comes from unexpected geographic locations relative to your customer base

How to fix it: In GA4, go to Admin → Data Streams → Configure Tag Settings → Define Internal Traffic. Add your office IP, your team's remote IPs, and any known developer ranges. Then create a filter under Admin → Data Filters to exclude them.

If you have a distributed team or your IPs change, use a developer parameter (traffic_type=internal) that your team can add manually when testing.

Mistake #3: Missing Key Funnel Events

GA4 e-commerce tracking relies on a specific sequence of events:

• view_item
• add_to_cart
• begin_checkout
• add_payment_info
• purchase

Most sites track the purchase event. Fewer track every step.

Without the full sequence, you can't see where in the funnel visitors drop off. You can't identify whether the problem is at the product page stage, the cart stage, or the checkout stage. You're flying without a funnel map.

How to fix it: Implement all standard GA4 e-commerce events. In GTM, use a data layer push for each event with the correct parameters (item_id, item_name, value, currency). Test each one with GA4 DebugView before going live.

Mistake #4: Sending Revenue in the Wrong Currency or Format

GA4 stores revenue as a number. It doesn't always know which currency.

Common errors:

• Sending revenue in minor currency units (cents instead of dollars, so $49.99 becomes 4999)
• Not specifying the currency parameter, defaulting to the wrong currency
• Sending string values ("49.99") instead of numeric values (49.99), which GA4 may reject or mishandle

How to spot it: Check your average order value in GA4. If it looks 100x too high or too low, or if it's inconsistent across different reports, you have a currency/formatting issue.

How to fix it: Always send value as a float (49.99, not "49.99" and not 4999). Always include the currency parameter matching your store's currency (e.g., "currency": "USD"). If you operate in multiple currencies, ensure the currency parameter matches the actual transaction currency.

Mistake #5: Broken or Missing UTM Parameters

UTM parameters tell GA4 how to attribute conversions to campaigns.

When they break, GA4 attributes conversions to "Direct" — the black hole of attribution where every untracked click lands.

UTMs break when:

• Your email platform doesn't consistently add them to links
• Redirect chains strip UTM parameters before the user reaches your site
• Your landing page builder doesn't pass UTMs through to subsequent pages
• Users click an ad, leave, and return directly — and the session is still attributed to the original campaign

How to audit: In GA4, go to Acquisition → Traffic Acquisition. Look at the percentage of sessions attributed to "Direct/None." If it's above 20–25%, you likely have attribution leakage from broken UTMs or cross-domain issues.

How to fix: Use UTM-checking tools to verify every major traffic source is tagged correctly. For cross-domain issues (e.g., between your site and a payment gateway), configure cross-domain tracking in GA4's tag settings.

Mistake #6: Conflating Users, Sessions, and Events

GA4 changed how it counts users. Unlike Universal Analytics, GA4 uses event-based measurement, not session-based.

This creates confusion:

• A "user" in GA4 may be counted multiple times if they clear cookies, switch devices, or use incognito mode
• Reporting on "users" versus "sessions" yields different numbers for the same behavior
• Some conversion metrics in GA4 count "once per session" while others count "once per user per day"

The result: teams compare GA4 metrics to UA benchmarks and conclude performance changed when the measurement model changed.

How to handle this: Don't compare GA4 metrics directly to Universal Analytics metrics. They measure differently. Establish your GA4 baseline from GA4 data, then track trends within GA4 — not across platforms.

For user identification, implement User-ID if your store requires login at checkout. This dramatically improves cross-device attribution accuracy.

Mistake #7: Ignoring Consent Mode Gaps

In markets requiring cookie consent (GDPR, CCPA, and similar laws), a percentage of users will decline analytics cookies.

For those users, GA4 receives no data.

Most teams know this in theory. Few understand the scale: in markets like Germany, France, or Scandinavia, opt-out rates can reach 40–60%. If you're running a European campaign, you could be missing nearly half your conversion data.

GA4's Consent Mode v2 allows behavioral modeling — GA4 uses machine learning to estimate conversions from consenting users' behavior to model what non-consenting users likely did. This doesn't fully close the gap, but it's significantly better than nothing.

How to implement: Work with your consent management platform (CookieBot, OneTrust, Cookieyes, etc.) to properly implement Google Consent Mode v2. Ensure your GTM tags respect the consent signals correctly. Audit that modeling is enabled in your GA4 property settings.

The Compounding Effect of Multiple Mistakes

Here's what makes these mistakes dangerous: they stack.

Internal traffic not filtered (inflates sessions by 8%) + double-counted purchases (inflates conversions by 12%) + broken UTMs (30% of conversions attributed to Direct) = a data set that tells a completely different story from reality.

Your conversion rate looks like 2.4%. It might actually be 1.9%. Your best-performing channel looks like Direct. It's actually email. Your checkout success rate looks like 78%. It might be 65%.

Decisions made on these numbers — budget allocation, team priorities, which tests to run — are all wrong.

How to Audit Your GA4 Setup

1. Cross-reference GA4 purchases with your order management system. Any discrepancy over 5% needs investigation.

2. Check your funnel events in DebugView. Launch your store in debug mode and complete a test purchase. Verify every event fires in sequence with the correct parameters.

3. Review your Data Filters. Confirm internal traffic is excluded.

4. Check your Direct/None attribution. If it's above 25%, investigate UTM coverage and cross-domain tracking.

5. Verify currency and value format. Check a specific transaction in GA4 against your order system. Confirm the revenue matches exactly.

6. Audit your consent mode implementation. Confirm that users who decline cookies trigger consent signals correctly and that modeling is enabled.

Final Thought

GA4 is a powerful tool. But power doesn't equal accuracy by default.

Most e-commerce brands are running on data that's meaningfully wrong — not because they made obvious mistakes, but because GA4 has enough complexity that subtle errors hide easily.

Fix the tracking first. Then optimize.

Because everything you do in CRO — every test, every decision, every budget allocation — depends on the accuracy of that foundation.

Not sure if your GA4 setup is accurate?

An analytics audit is the first thing we do with every client. Book a free 45-minute call and we'll identify your tracking gaps before they cost you another month of bad decisions.