If you're migrating from Universal Analytics (UA) to Google Analytics 4 (GA4), you might want to compare similar UA and GA4 conversion events within Google Analytics, and also similar UA and GA4 events when imported into Google Ads. It's important to note that some differences are unavoidable because GA4 measures web data differently from UA. This article explains the most common reasons for differences and what actions you can take if you want to minimize those differences.
Introduction
In some cases, Conversions can be quite close, such as when your conversions are based on destination URLs or on Universal Analytics events (i.e., Category/Action/Label) for which you have set up equivalent Google Analytics 4 conversion events. However, there are important differences between UA and GA4 that may make it difficult to compare conversion counts. There are three main sources of discrepancy:
- Inherent differences between UA and GA4: GA4 properties have a different data model than UA properties. For example, GA4 collects events, while UA collects hits. Additionally, to support new privacy-preserving technologies, GA4 is built with AI-powered solutions, such as behavioral and conversion modeling. These solutions give you a complete view of performance without compromising user privacy, but they're not available in UA properties.
- Differences in setup: Differences in site coverage for UA tags vs. GA4 tags, tag firing conditions, and ecommerce schemas can all result in conversion differences.
- Differences in settings: There are many settings in UA, GA4, and Google Ads that can result in conversion differences. Examples include conversion count, filters, URL parameter exclusions, and more.
Below, we’ll outline the most common drivers of conversion differences between UA and GA4, focusing on those driven by product/setup/setting differences in Google Analytics, and those driven by product/setup/setting differences in Google Ads.
Most common reasons for differences
The following two tables outline the eight most common reasons for conversion differences between similar UA and GA4 events within Google Analytics and Google Ads. When encountering conversion differences, reviewing and aligning these eight drivers is the best place to start to reduce discrepancies between UA and GA4 conversions. In most cases, aligning these product, setting, or setup differences will resolve major differences in conversions.
In Google Analytics
These are the top drivers of differences between similar UA and GA4 conversions based on product, setup, or setting choices made in Google Analytics.
| Description | Solution / Recommendation |
|---|---|
|
Conversion counting: UA counts one goal conversion per session, while GA4 often counts one conversion per event. For example, when a user completes a goal 5 times in a single session, UA will show one conversion and GA4 will usually show 5. Note: Once per event is the default counting method for most conversions, except those created in an automatically created GA4 property or using the Setup Assistant goals migration tool. The default settings can cause a higher conversion count in GA4. |
Use conversion counting settings as described here. To align GA4 counting to UA goals counting, make sure the GA4 conversion counting method is set to Once per session. Notes:
This recommendation isn't relevant when comparing UA ecommerce transactions because they're already counted as Once per event in UA. |
|
Site coverage: If the UA tag is implemented across a different set of pages within a website than the GA4 tag, measurement gaps can emerge. Especially if a landing page from a Google Ads ad isn't accurately tagged, it could be that the information you need to accurately measure and attribute a conversion to that ad interaction isn't available. Depending on whether GA4 tags are implemented on more or fewer pages than UA, GA4 will respectively show more or fewer users, sessions, page views, and subsequent conversions. |
We recommend relying on a standardized method of implementation to make sure tags are implemented across your site (for example, the Google tag or Google Tag Manager). Also consider settings you may have configured in the past, such as cross-domain tracking. Use the Tag coverage summary to confirm if the Google tag is implemented across your website. Learn more. To minimize discrepancies, rely on the same tag implementation methods for UA and GA4. |
|
Implementation errors: When setting up data collection for GA4, it's possible a tag is implemented incorrectly. This can result in seeing no data at all in your GA4 property, but in some instances, you’ll see partial data in your GA4 property. If so, you’ll see discrepancies when comparing it to UA. It's likely that a broken implementation shows lower conversion counts for GA4 than UA. |
We recommend you rely on standardized implementation methods outlined in the Developers Guide instead of non-standard implementations. A tag management system can help bring consistency in implementations. Using the Google tag is sufficient for many users as this allows the use of the same tag for both Google Ads and Google Analytics (Developer Guide). |
|
Filters: UA filters work very differently from GA4 filters. It's common for UA filters to be in place and significantly alter the data inside a UA property (for example, "only show data from France"). GA4 has a very different set of possible filters. If UA filters reduce reported traffic, this can result in GA4 showing higher amounts of traffic.
|
Data filters: Create include/exclude filters for internal and developer traffic. Event modifications and custom events: Modify event names and parameters. Identify unwanted referrals: Include only the referrals you want. Create subproperties (360 only): Create fully-functional properties that are subsets of the data in your 360 properties. |
|
Referral exclusions: Exclusions set in UA can affect conversions attributed to Google Ads. If these exclusions are not set up accordingly in GA4, the credit attributed to Google Ads can differ (for example, exclusions for payment providers like PayPal are often made in UA.) If referrers were excluded in UA but not in GA4, GA4 conversions can be misattributed in GA4, resulting in fewer conversions attributed to the Google Paid channel when compared to UA. Referral exclusions affect the amount of conversion credit that is exported to Google Ads. |
Match referral exclusions settings between UA and GA4 to minimize incorrect attribution. Note that excluding referrals does not change the overall amount of conversions in the Google Analytics property; it only affects how conversions are attributed. |
In Google Ads
These are the top drivers of differences between similar UA and GA4 conversions based on product, setup, or setting choices made in Google Ads.
| Description | Solution / Recommendation |
|
Conversion window: Conversion window settings in Google Ads define how long after a Google Ads touchpoint conversion credit can be attributed to that touchpoint. Often this setting is set to a value of choice (for example, 90 days). A difference in settings can mean a touchpoint gets attributed conversion credit by UA while it doesn't by GA4, or vice versa. |
Align your conversion window settings in Google Ads for both the UA and GA4 conversion actions, inline with the setting used in the GA4 property settings. |
|
Attribution model settings (in Google Ads): Attribution models affect how credit is distributed across touchpoints in a conversion path. Differences in attribution model settings in Google Ads between the UA and GA4 conversion action can result in different credit allocations across campaigns in a Google Ads account or manager account (MCC). Note: Changing attribution settings in Google Ads does not affect the overall amount of conversions attributed to Google Ads. |
Align the attribution models in the conversion settings in Google Ads. |
|
Reporting methodologies in Google Ads: In Google Ads, to show which ad drove a conversion, conversions are reported based on interaction time reporting. In Google Analytics, conversions are reported differently, using conversion time reporting. For example, if a conversion that took place on May 10th, it can be attributed to an ad click on May 5th. Google Analytics generally reports this conversion on May 10th, while Google Ads will report this conversion on May 5th. |
This effect applies both to UA and to GA4 imported events in Google Ads, although differences in settings (like attribution model or conversion window) between conversion actions can amplify it. If you align settings across conversion actions imported into Google Ads, you minimize the affects of reporting methodologies. Keep in mind that conversions can be attributed during the full length of the conversion window (up to 90 days in Google Ads), so it can take up to 90 days for GA4 and UA to fully compare to one another. To assess whether a conversion pair can be compared, or whether you must wait longer, use the Path metrics report in Google Ads for the UA conversion to see how long it takes the majority of users to convert. Note: More than 95% of conversions get attributed within the first 14 days. This means you must use Google Ads data in your comparison between UA and GA4 that is at least 14 days old. |
Other reasons for discrepancies
If after aligning the above drivers of conversion differences, you’re still encountering significant discrepancies between your UA and GA4 conversions, review the comprehensive list of drivers below.
As a reminder, differences between similar UA and GA4 conversions are expected, but this list should help you align product, setup, and setting differences where possible to reduce discrepancies.
In Google Analytics
These are additional drivers of differences between similar UA and GA4 conversions based on product, setup, or setting choices made in Google Analytics.
| Description | Solution / Recommendation |
|
Ecommerce tracking: Google Analytics is compatible with various ecommerce schemas. You can implement the GA4 schema and the UA schema simultaneously, or rely on one schema for both properties. If you use two schemas, data discrepancies can emerge. See the Developer Guide for more information. Differences in ecommerce schema can cause conversion counts in GA4 to be higher or lower than in UA. |
When collecting ecommerce data for GA4, it's best practice to rely on the GA4 ecommerce schema (Developer Guide). It's recommended that you not rely on connected site tags if you’re using ecommerce tracking. It's also recommended you use the same ecommerce schema for UA and GA4 when comparing the two. |
|
Tag firing conditions: Hard-coded tag firing conditions can affect how and when a tag fires. Since setting up GA4 data collection in many cases consists of implementing new tags, it's possible previous firing conditions need to be implemented for GA4 for them to take effect. We recommend firing tags according to the same conditions to minimize data collection differences. If data collection is restricted in UA and not in GA4, then user, session, page view, and conversion counts can be higher in GA4. |
It's recommended you rely on gtag.js or gtm.js (using GA4 tags) to collect data for GA4 properties. Tag firing conditions are not directly impacted if you use other forms of tagging (for example, connected site tags), but retagging is the first recommendation in case tag firing conditions cause tags to fire inconsistently across UA and GA4. Once tags are implemented, align any tag firing conditions. As an example of a condition, see this Developer Guide on measuring time. |
|
Exclude internal traffic: Settings can be used to filter out internal users (from a customer’s perspective, i.e., a customer’s employees) or test traffic. If settings differ in UA and GA4, the property without the exclusion filters is expected to show higher user, session, page views, and subsequent conversions. |
It's recommended you align settings in UA and GA4 to minimize discrepancies. For more information, see this article for UA, and this article for GA4. |
|
Page changes based on browser history events: GA4’s enhanced measurement by default measures page changes based on browser history events ; UA does not. This will cause higher pageviews in GA4 than UA and can lead to discrepancies. For example, if your site’s construction and usage patterns cause many pages to be loaded via changes in the browser history, enabling this setting will create measurement for these events. This will result in discrepancies from UA where these events haven't been measured. |
If you want pageview counts to more closely match between UA and GA4, disable the enhanced measurement setting in GA4. Learn more. |
| Other event sources (Audience triggers, Measurement Protocol, event editing, etc.): Generating these events and marking them as conversions can cause conversion volume inflation in GA4 if you compare the conversions on a property level with UA. |
Use matching setups for similar UA and GA4 conversions in Google Analytics. You can configure newly-created events from these sources to distinct event names so that UA and GA4 measurement can match more closely. If it isn't possible to set up in the same exact fashion, the two should not be compared. |
|
Spam and bot filters:
Filters reduce traffic in UA. If not applied in GA4, GA4 will report more traffic and subsequent conversions, in cases where spam/bot traffic manages to convert. |
Enable the bot filtering setting in UA, and consider adding spam filters in UA if you’re receiving spam. |
| URL parameter exclusions: In UA, customers can have a goal configured to exactly match a particular URL. In GA4, since there are no URL parameter exclusions, the URL can have many versions that wouldn’t be caught in the definition for the conversion. |
Confirm if URL parameter exclusions are used in UA to understand potential differences in GA4. |
|
DDA model for conversions and revenue: In UA, the attribution model is last non-direct click for goals. GA4 conversions use the data-driven attribution (DDA) model by default, but is modifiable. Depending on how credit shifts based on DDA, users can see more or less credit being attributed to paid (Google) channels. Note that the attribution model doesn't affect the overall amount of conversions for a given event. |
Although not recommended, this can be tested/quantified by switching the property’s attribution model to Last click in GA4. Note: Since attribution models within Google Analytics don't affect the overall amount of conversions within a property, it’s recommended to first troubleshoot all other drivers of discrepancies to minimize overall property-level differences for conversion pairs (i.e., similar conversions in UA and GA4). |
|
Time zone differences and campaign reset: UA cuts a session off at midnight and restarts a session with new campaign parameters. GA4 does not. This can lead to session discrepancies, which can then lead to goals/session conversion discrepancies. This isn't expected to drive any significant differences in the total amount of conversions in a given property. It's expected to only be visible if individual days are compared in UA vs GA4. |
No direct solution – this has been resolved in GA4. |
| Pageview measurement configuration differences: Pageview measurement based on browser history events can be disabled in GA4. Single-page sites don’t get proper measurement forwarded to GA4 when using connected site tags. |
GA4 can be configured to measure pageviews based on browser history events; UA doesn't do this. This leads to richer measurement in GA4 but can be a source of discrepancies. You can disable this setting if you want the numbers to more closely align between UA and GA4. Single page application measurement can be set up for UA following this Developer Guide. This won't fully align UA with GA4 but can minimize differences for single-page sites. |
|
Google signals and User ID: These settings help deduplicate users in GA4 properties. In UA, both settings only affect a few reports and a separate view. In GA4, they affect all information in the property. Turning on Google signals and User ID in GA4 reduces new/overall user counts, connecting interactions that in UA would be considered from multiple users. As such, conversion credit can be attributed differently. These features aren't expected to affect the overall amount of conversions within Google Analytics but can result in differences in exports to Google Ads. If an advertiser measures engaged-view conversions (EVCs), they can be influenced by the use of Google Signals and User ID. |
No direct solution – GA4 deduplication provides better insight into how users interact with a customer’s assets. We recommend implementing both features in both platforms to minimize discrepancies, although they can't be prevented.
|
| Session timeouts: You can adjust session timeout settings. If these are changed from their default, it can influence traffic counts and attribution. | It's recommended that you rely on the default settings. If you changed session timeouts in UA, you should adjust this setting in GA4, too. Learn more. |
|
Cookie override |
When you change cookie settings in UA, you need to match the setting when you configure GA4. Reducing cookie expiration dates can affect attribution and result in differences in conversion attribution. Learn more. |
| Use of auto-tagging plus manual tagging (in the same URL) | You can use auto-tagging plus manual tagging in the same URL, but there are cases where this won't work. |
| Choice of dimensions and metrics | GA4 offers a larger number of acquisition dimensions than UA. Because of this, not all possible combinations of reporting dimensions can be compared between UA and GA4 |
| App tracking implementation differences between UA and GA4 | It’s recommended you rely on one SDK where possible. Note that a very small subset of users can currently collect app data in UA. Users must implement the Firebase SDK if they want to collect app data and report on it using GA4 properties. |
|
For connected site tags (including sideloading) only: Connected tags load sequentially; that is, the GA4 tag loads after the parent tag (an existing gtag.js or analytics.js tag). This can mean:
|
To minimize the risk of missing events, it's recommended you implement dedicated GA4 tags rather than relying on connected site tags or sideloading. In particular, for large, complex Analytics setups, you should avoid relying on connected site tags or sideloading. |
| Inclusion of App and Web data in on property for GA4: GA4 unifies app and web data and events. If you combine app and web data in GA4, but didn't do anything similar in UA, this will cause a higher conversion count in GA4. | For the best comparison, you shouldn't include app data streams if your UA properties didn't contain app traffic. If the app stream is already included, you should segment reports to exclude app conversions if you want to compare UA with GA4. |
| Updated channel groupings: GA4 channel groupings can assign a conversion to a channel in a different manner. Learn more. | There's no option for users to override which conversions are exported to Google Ads. |
In Google Ads
These are additional drivers of differences between similar UA and GA4 conversions based on product, setup, or setting choices made in Google Ads.
| Description | Solution / Recommendation |
|
Conversion modeling from Consent Mode: Conversion modeling is available in Google Ads for advertisers who have imported Google Analytics conversions from properties implemented using gtag.js or Google Tag Manager. For analytics.js implementations, we don't offer conversion modeling in Google Ads for imported Analytics conversions. This is because the consent state can't be defined accurately without having a gtag.js or Google Tag Manager implementation. If both UA and GA4 rely on tags compatible with Consent Mode, both can receive conversion modeling in Google Ads. |
For a fair comparison, make sure you have a Consent Mode-compatible tag type for both your UA and GA4 properties. |
| Engaged View measurement: GA4 is able to attribute a conversion to a YouTube Engaged View ad interaction, even if that ad interaction did not result in a website visit directly, but still led to a conversion at a later point. This can result in a conversion being exported to Google Ads, for which UA does not export any credit to Google Ads. This means that GA4 can attribute more conversions to Google Ads if an advertiser has a significant amount of YouTube spend. |
In GA4, this shouldn't lead to an increase in conversions for web traffic, but it’s possible that more conversion credit is attributed to the Google Ads channel in GA4 than in UA, leading to better Google Ads performance. To compare this, you can segment campaign – or account level – reporting in Google Ads. Make sure to compare conversion actions that measure the exact same conversion action. It isn't possible to segment standard reports by Ad event type and conversion source at the same time, so it’s difficult to make a direct comparison in the Google Ads UI. |
|
Credit export model: The model by which conversions are exported from GA4 to Google Ads is different from UA. Where UA, and initially GA4, relied on a last non-direct click export model, GA4 now uses a final credit export model, allowing for fractional conversion credit to be exported, even if the last non-direct touchpoint was not a Google Ads touchpoint. Although this isn't resulting in property-level differences, it can result in a different number of conversions exported to Google Ads. This number can be both higher or lower when compared to UA and is dependent on a user’s independent user journeys. |
Final credit export has been launched as last non-direct click models aren't sufficient. This means that GA4 exports true cross-channel conversion credit to Google Ads. You can't take specific actions to minimize the differences between UA and GA4. |
| Ads-side conversion counting method: Google Ads has a count setting that can be used to control one or multiple conversions being counted within a set conversion window for a given user. |
It's recommended to align conversion counting settings for UA and GA4 conversion pairs. Learn more. |
|
Applies to manually created GA4 properties and Smart Campaign customers: The GA4 Google paid channels export model attributes all conversions exported to Google Ads to Google channels. This results in more conversions being exported to Google Ads than the Paid and organic channels setting because it excludes non-Google paid channels from the conversion path. Using Google paid channels can provide deeper insight into how paid Google interactions drive impact. This model isn't available in Universal Analytics, so it can be difficult to compare similar UA and GA4 events when imported to Google Ads. |
By default, new GA4 properties are set to Google paid channels. You can use the GA4 property-level attribution settings in the Admin section to control how conversions are exported to Google Ads. To align settings between Universal Analytics and Google Analytics 4, use the Paid and organic channels setting. Learn more
|
