5 Things You Misunderstand about Google Analytics 4

The GA4 Problem

The GA4 announcement and multi-year rollout was a mismanaged, marketing disaster comparable to Coca-Cola's "New Coke" blunder in the 90s.

The 5 Questions my Frustrated GA4 Clients Keep Asking

Google Analytics 4 (GA4) represents a significant departure from the previous Universal Analytics (UA) version, and with any major change, there are bound to be misconceptions and misunderstandings. Here are five questions my frustrated clients regularly ask.

1. Why does my GA4 data not match what I see in Universal Analytics?
2. Why is there a data discrepancy between my Google Ads and GA4 reports?
3. My ecommerce data in Shopify or Stripe doesn't match my GA4 revenue and transaction data! What's wrong?
4. Why do the standard GA4 reports not match what I see when using Explorer or what I see in my Looker Studio dashboard?
5. How come when I add dimensions to reports or change date ranges, my data seems inconsistent?

“What clients misunderstand about GA4 is that it's not an accounting system. GA4 is a statistical tool for marketers useful for modeling user behavior and customer acquisition across an increasingly complex digital landscape. All models are wrong, but some are useful."

Why does my GA4 data not match what I see in Universal Analytics?

If you're comparing data between Google Analytics 4 (GA4) and Universal Analytics (UA), there are several reasons why the data might not match perfectly. Here are some common reasons for discrepancies:

1. **Different Tracking Models**:
   - **Sessions**: UA primarily focuses on sessions and users, while GA4 focuses on events. The definition and calculation of a "session" might differ.
   - **Users**: GA4 uses a different method to identify users, particularly when tracking across different devices or platforms.

2. **Event-Based Tracking**:
  - GA4 is designed to be event-based, while UA relies more on pageviews. This means that even basic interactions like page loads are treated as events in GA4.

3. **Differences in Bots Filtering**:
  - GA4 and UA may handle bots and spiders differently. If one is filtering out more bots than the other, you'll see discrepancies.

4. **Referral Exclusions**:
  - Referral exclusions that you've set up in UA might not be the same in GA4. This can influence how traffic sources are reported.

5. **Data Sampling**:
  - Universal Analytics sometimes uses data sampling in reports, especially for larger sites. GA4 aims to provide more granular data without sampling, which might cause differences.

6. **Differences in Default Channel Grouping**:
  - The way traffic sources are grouped into default channels may vary between the two platforms.

7. **Cross-Domain Tracking**:
  - If you're tracking multiple domains, the setup for cross-domain tracking differs between UA and GA4. If not implemented consistently across both, it can result in discrepancies.

8. **New and Improved Metrics**:
  - GA4 introduces new metrics that don't have direct equivalents in UA, like "Engaged Sessions".

9. **Differences in Attribution Models**:
  - GA4 introduces a more sophisticated attribution model, which can lead to differences in how conversions are attributed to different traffic sources.

10. **Tracking Code Implementation Issues**:
  - It's possible that one of the tracking codes (either UA or GA4) might not be implemented correctly on all pages or might be firing inconsistently.

11. **Filtering and Data Processing**:
  - If you've set up different filters in UA and GA4, they can cause variations in the data you see. This includes IP filters, custom filters, etc.

12. **Ad Blockers and Cookie Restrictions**:
  - Some ad blockers or browser restrictions may interfere more with one tracking code than the other.

13. **Data Retention Settings**:
  - The data retention settings might be different between the two platforms, affecting how much historical data is accessible.

14. **Differences in E-commerce Tracking**:
  - If you're tracking e-commerce transactions, there are differences in how UA and GA4 handle e-commerce data.

When noticing discrepancies, it's essential to thoroughly audit both setups to understand the causes. Over time, as you get more accustomed to GA4, you'll be better positioned to interpret its data in the context of your site and business objectives. Remember that GA4 is not just an upgrade but a complete reimagining of Google Analytics, so differences are to be expected.

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Why is there a data discrepancy between my Google Ads and GA4 reports?

When comparing data between Google Ads and Google Analytics 4 (GA4), discrepancies are common due to the fundamental differences in how the two platforms record and attribute data. Here are some common reasons for these discrepancies:

1. **Attribution Differences**:
   - **Clicks vs. Sessions**: Google Ads reports on clicks, while GA4 reports on sessions. A user might click an ad multiple times but only initiate one session, leading to more clicks reported in Google Ads than sessions in GA4.
   - **Different Attribution Windows**: Google Ads and GA4 may have different windows of time for attribution. For example, Google Ads might credit a conversion to a click that happened 30 days ago, while GA4 might have a different attribution window.

2. **Data Processing Delays**:
  - There might be a lag in data processing between the two platforms. If you're checking reports in near real-time, you might observe some temporary discrepancies.

3. **Ad Blockers**:
  - Some ad blockers might prevent GA4 from recording sessions even if they allow the ad click to go through. This can result in more clicks reported in Google Ads than sessions in GA4.

4. **GCLID Parameter Issues**:
  - If the "gclid" parameter (used by Google Ads for tracking) is stripped out due to website redirects or other reasons, GA4 can't associate the session with the Google Ads click, causing discrepancies.

5. **Conversion Tracking Differences**:
  - You might be tracking different types of conversions in Google Ads versus GA4, leading to discrepancies in conversion counts.
  - GA4 may count a conversion every time the conversion event happens, while Google Ads might have specific settings to count unique conversions.

6. **Invalid Clicks**:
  - Google Ads filters out invalid clicks, which means they won't be billed or reported in Google Ads. However, these might still appear as sessions in GA4.

7. **Different Reporting Time Zones**:
  - If the time zones set in Google Ads and GA4 are different, the data might not align perfectly when analyzing on a day-to-day basis.

8. **Cross-Device Conversions**:
  - Google Ads might report cross-device conversions if you've enabled this feature, but these might not be represented the same way in GA4.

9. **Referral Exclusions in GA4**:
  - If you've not properly set up referral exclusions in GA4, some Google Ads traffic might be reported as referral traffic instead.

10. **Location Targeting Differences**:
  - Google Ads might report on users who saw your ad based on their targeted location or interest, while GA4 reports on the user's actual physical location. This can result in discrepancies in location data.

11. **Auto-Tagging Issues**:
  - If auto-tagging is not enabled or not working correctly in Google Ads, GA4 won't be able to associate the traffic and conversions correctly.

It's crucial to understand these differences when comparing data between the two platforms. Regularly auditing and checking settings in both Google Ads and GA4 will help ensure data accuracy and a better understanding of discrepancies when they arise.

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My e-commerce data in Shopify or Stripe doesn't match my GA4 revenue and transaction data! What's wrong?

Perhaps the second-most common complaint Data Disciples hears from its clients is that they are not seeing 100% of the transactions and orders they see on the backend of their e-commerce platform. I get the frustration, but GA4 is not an accounting system

What clients misunderstand about GA4 is that it's not an accounting system. GA4 is a statistical tool for marketers and is useful for modeling user behavior and customer acquisition across an increasingly complex digital landscape. All models are wrong, but some are useful.

Perhaps the issue is really two-fold: 1.) Clients don't understand that GA4 is a statistical tool, 2.) clients don't understand or don't have faith in statistics.

Discrepancies between e-commerce platforms like Shopify or Stripe and Google Analytics 4 (GA4) in terms of revenue and transaction data are not uncommon. Here are some common reasons why these differences might arise:

1. **Tracking Issues**:
  - **Incomplete Implementation**: If the GA4 e-commerce tracking code isn't fully or correctly implemented, some transactions might not be recorded.
  - **JavaScript Errors**: Errors on your website, especially during the checkout process, can prevent the GA4 tracking code from firing correctly.
  - **Delayed Reporting**: GA4 might have a delay in processing data, leading to temporary discrepancies.

2. **Refunds and Cancellations**:
  - If you process refunds or cancellations in Shopify or Stripe but don't account for these in GA4, it can cause discrepancies in revenue data.

3. **Cart Abandonment**:
  - Users might start a checkout process (which might trigger an event in GA4) but abandon it before completing the purchase. Depending on how you've set up tracking, this might cause discrepancies.

4. **Browser Issues**:
  - Some users might have settings or extensions that block Google Analytics from recording data. This means their transactions won't be captured in GA4 even if they're recorded in Shopify or Stripe.

5. **Different Data Collection Methods**:
  - GA4 uses client-side tracking, capturing data directly from users' browsers. In contrast, platforms like Shopify and Stripe capture data server-side. This fundamental difference can result in discrepancies.

6. **Cross-Domain Tracking**:
  - If your checkout process involves multiple domains (e.g., moving from your main site to a separate payment gateway domain), and cross-domain tracking isn't set up correctly, you might lose tracking on some transactions.

7. **Currency Differences**:
  - Ensure that the currency setting in GA4 matches your Shopify or Stripe setup. If you're dealing with multiple currencies, currency conversion differences might lead to discrepancies.

8. **Discounts and Coupons**:
  - If you offer discounts or coupons, ensure that the discounted price, not the original price, is sent to GA4.

9. **Taxes and Shipping Fees**:
  - Shopify and Stripe might include taxes and shipping fees in the transaction totals, whereas your GA4 setup might not. Ensure consistent tracking of all components of a transaction.

10. **Referral Exclusions**:
  - Ensure that you've set up referral exclusions correctly in GA4. If not, a single transaction might be split into multiple sessions, leading to potential double-counting or other discrepancies.

11. **Manual Adjustments**:
  - If you make manual adjustments to transactions in Shopify or Stripe, these won't automatically reflect in GA4.

To address these discrepancies, it's essential to:

- Regularly audit your GA4 setup.
- Test the e-commerce tracking process frequently to ensure it's working as expected.
- Consider implementing server-side tracking in GA4 to complement client-side tracking for better accuracy.
- Understand the inherent limitations of client-side tracking and be prepared for minor discrepancies.

While it's challenging to get the data to match perfectly between GA4 and e-commerce platforms, understanding the reasons for differences will help you interpret the data more accurately.

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Why do the standard GA4 reports not match what I see when using Explorer or in my Looker Studio dashboard?

Differences between the standard GA4 reports and what you see in the GA4's Explorer or in an external tool like Looker Studio can arise from several factors. Here are some common reasons:

1. **Different Date Ranges**: Ensure that you're comparing data for the same date range in both places. It's easy to overlook date settings, especially when switching between multiple platforms or views.

2. **Data Freshness**: GA4, like other Google Analytics versions, might have a delay in processing the most recent data. If you're looking at real-time or very recent data, there might be discrepancies due to processing lags.

3. **Segments and Filters**:
  - The standard GA4 reports might use different default segments or filters compared to custom queries in the Explorer or Looker.
  - Ensure that any applied segments or filters in one view are replicated in the other if you're trying to match data exactly.

4. **Custom Dimensions and Metrics**: The GA4 Explorer and Looker Studio allow for more advanced and custom data configurations. If you're using custom dimensions or metrics, they might not align directly with the standard reports.

5. **Data Sampling**: For large datasets, Google Analytics (including GA4) sometimes uses data sampling to produce quicker reports. The level of sampling can differ between standard reports and custom queries, leading to potential discrepancies.

6. **Aggregation Levels**: The level at which data is aggregated might differ between views. For example, one report might aggregate at the user level while another aggregates at the session or event level.

7. **Looker Studio Specifics**:
  - **Data Synchronization**: If you're pulling GA4 data into Looker, there might be a delay or issue in synchronization.
  - **SQL Queries**: Looker Studio uses SQL queries to fetch and display data. Ensure that these queries are correctly set up and are equivalent to what GA4's standard reports or Explorer use.
  - **Joins and Relationships**: In Looker, if you're combining GA4 data with other data sources, ensure the relationships and joins are set up correctly.

8. **User Permissions**: Ensure that you have equivalent access rights in both places. Sometimes, user permissions can limit the data you see, leading to discrepancies.

9. **Data Retention and Deletion**: GA4 has settings related to data retention and deletion. If these settings are different for different views or if data has been deleted in one place and not another, it can cause discrepancies.

10. **Events and Goals**: If you're comparing event or conversion data, ensure that the event tracking setup and goals are consistent across all views.

To troubleshoot and align the data:

1. Double-check all settings, filters, segments, and date ranges.
2. If using Looker, validate your SQL queries and data integration setup.
3. Regularly audit your GA4 setup and tracking to ensure accuracy.
4. Use unsampled reports or increase the sample size in GA4 if sampling is the suspected cause.

Remember, any analytics tool's primary purpose is to provide insights, trends, and patterns, rather than exact counts. Minor discrepancies can be expected, but understanding the reasons behind them will help you interpret your data more accurately.

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