Data inside Google Analytics and Google Ads may not match due to discrepancies in how each platform measures and reports. Let’s get to the bottom of how to fix it.
Here, you’ll find:
Is your data looking more scrambled than a breakfast burrito?
We’ve been there. (And now we’re hungry.)
The fact is, getting Google Analytics and Google Ads to match requires in-depth knowledge of data attribution. So, let’s get to the heart of why your data may not match and what you can do about it.
Why doesn’t the data in Google Ads and Google Analytics match?
Data inside Google Analytics and Google Ads may not match due to differences in how each platform measures and reports conversions and potential user behavior nuances.
While both platforms aim to capture user interactions, their methods and mechanisms can vary, leading to differences in your reported metrics.
We asked HawkSEM’s CEO, Sam Yadegar, to explain a bit more about why you might find differences between Google Ads and Analytics.
“Oftentimes, it’s the attribution model that causes the mismatch,” he says. “Understanding the difference between how Google Ads attributes a conversion versus how Analytics does may explain the discrepancy.”
How do I sync Google Ads with Google Analytics?
By integrating Google Ads with Google Analytics, you can gain a holistic view of user interactions, track conversions more accurately, and refine your digital marketing strategies based on data-driven insights.
Here is a quick explanation of how to sync your accounts:
Link your accounts
- Log into your Google Ads
- Navigate to the “Tools & Settings” menu
- Select “Linked accounts”
- Follow the prompts to link your Google Analytics account
Ensure auto-tagging is enabled in your Google Ads account. This feature appends a unique tracking parameter called a GCLID (Google Click Identifier) to your ad URLs, facilitating the exchange of data between Google Ads and Google Analytics.
Auto-tagging is essential for accurate data collection between these two platforms. If auto-tagging is disabled and you haven’t manually added campaign tracking variables to the final URLs, the incoming traffic might not be categorized as Google CPC (clicks originating from Google Ads campaigns).
Instead, it could be mistakenly attributed to Google Organic (clicks arising from organic search results on Google.com). To avoid this, ensure your Google Ads account has auto-tagging enabled or includes campaign tracking variables at the end of each final URL.
If you don’t have auto-tagging set up, Google has a simple guide you can follow. Setup takes a matter of minutes.
How do Google Ads and Google Analytics collect data?
Knowing the mechanics of data collection in Google Ads and Google Analytics will help you comprehend the disparities that can arise between the two platforms.
Google Ads data collection
Google Ads focuses on tracking interactions within its advertising ecosystem. When a user clicks on your ad, Google Ads registers a click, recording essential details like the ad’s placement, keyword triggers, and the ad’s content.
Google Analytics data collection
- Landing page
- Session duration
- Pages visited
- Their journey through your website
So, what are the key differences between how Ads and Analytics collect data?
Both tools gather valuable insights for you about your audience. However, there are some key differences in how they gather those insights. Here is a quick breakdown of how their methods diverge.
Why is Google Analytics not showing all my traffic?
Traffic is an important metric for most marketers. Yet, it’s not uncommon for marketers to notice a disparity in the reported traffic between Google Ads and Google Analytics.
This discrepancy can arise for several reasons, such as:
- Ad blockers: Some users employ ad blockers that can prevent the tracking codes from firing, leading to underreported traffic in Google Analytics.
- Server-side tracking: Google Ads uses server-side tracking, while Google Analytics employs client-side tracking. This variance can occasionally lead to data inconsistencies.
- Sessions not counted: If a user interacts with an ad but exits the website before the Google Analytics tracking code loads, the session might not be counted in Google Analytics, but Google Ads would still count the ad click.
Common causes of data discrepancies between Google Ads and Analytics
Traffic data isn’t the only place where you may see a mismatch between Google Ads and Analytics data. Let’s look at some of the other most common discrepancies that occur and why.
1. Google Ads clicks and Google Analytics sessions
Google Ads reports clicks, while Google Analytics reports sessions. A user can click one ad multiple times within a single session. This action leads to Google Ads reporting multiple clicks while Google Analytics only reports one session.
Another scenario that may occur is that a user clicks an ad and lands on the page. They bookmark the site and return later through the bookmark. In this case, Google Ads would count only one click while Google Analytics would count multiple sessions.
2. Attribution models
Different attribution models in Google Ads and Google Analytics can lead to variations in conversion counts and attribution credit. For instance, if your Google Ads conversion is set to last-click attribution, the data would have matched with Universal Analytics.
But now that Google Analytics 4 is the only game in town, you’ll have to make sure your models match. The default is data-driven, so you’ll need to adjust the settings for your data to match.
3. Cross-domain tracking
If your website includes multiple domains, you need to ensure proper cross-domain tracking to avoid data gaps. Using the conversion linker in Google Tag Manager will help you with this.
4. Bot and spider traffic
Google Ads might count clicks from bots and spiders, while Google Analytics filters out invalid clicks from non-human traffic.
5. Time discrepancies
Google Ads reports data in near real-time. In comparison, Google Analytics can have a data processing delay. With the differences in data processing times, your metrics might not match precisely at all times, especially in rapidly changing environments.
6. Slower syncs
According to Google, Google Ads conversion tracking numbers are usually reflected within 3 hours. However, Analytics is typically slower and can take up to 9 hours.
Discrepancies in the conversion rate on Analytics and Ads
Conversion rate is a crucial metric for ad companies. And it will often be one of the key performance indicators (KPIs) you use to measure their success.
However, it can sometimes differ between Google Ads and Google Analytics. This disparity may confuse your team and hinder the accurate evaluation of your marketing efforts.
Why conversion rate discrepancies matter
Differences in reported conversion rates can lead to misguided conclusions about the success of your ad campaigns.
Inaccurate metrics can prompt you to make changes to well-performing strategies or overlook underperforming ones, which will impact your return on investment (ROI).
Reasons for conversion rate discrepancies
There could be a few reasons you see different conversion rates reported between Analytics and your PPC campaigns.
- Different conversion tracking: Google Ads and Google Analytics use slightly different tracking mechanisms to record conversions.
- Attribution model differences: Variations in attribution models applied by the platforms can lead to distinct conversion counts for the same interaction.
How to fix conversion rate discrepancies
If you want to get a more accurate picture of your conversion rates across Analytics and Ads, there are a few things you can do to fix these discrepancies.
- Evaluate your conversion tracking: Review the setup of your conversion tracking codes on both platforms. Ensure that they are correctly implemented and consistently measure the same conversion actions.
- Standardize your attribution models: Select similar attribution models in Google Ads and Google Analytics. This can help align the credit given to touchpoints leading to conversions.
- Periodic audits: Regularly audit your tracking setup and conversion data flow. Identify and rectify any inconsistencies promptly to maintain accuracy.
- Holistic data analysis: Instead of solely relying on conversion rate metrics, analyze other performance indicators, such as click-through rates (CTR), session duration, and engagement metrics, to gain a comprehensive view of your campaigns’ effectiveness.
How to fix discrepancies between Google Ads and Analytics
With data being so valuable to every marketer, you want to make sure all of your stats are as accurate as possible. Beyond conversion rate, there are many other metrics you may be seeing disparities with. And they may have some other causes.
So, how can you avoid falling prey to some of these data discrepancy issues between Ads and Analytics?
Verify your tracking codes
The first place to start is to check your tracking codes. This may sound silly, but it happens to all of us! Mistakes can happen, so it’s good to get this checked off the list before exploring other causes because it’s easy to fix.
“Another common mistake we see is improperly installed tracking pixels,” explains Yadegar. “We would suggest having a developer make sure all the tracking codes are firing in the right place at the right time.”
It’s also important to inspect the implementation of tracking codes on your website meticulously. Ensure that your Google Ads and Google Analytics tracking codes are correctly embedded on every relevant page. A missing or incorrect tracking code may be the cause of your data discrepancies.
Set up Google Analytics goals
Setting up Google Analytics goals parallel to your Google Ads conversions will allow you to compare and track data more accurately. Setting up goals for actions you feel are important will allow you to compare data points side by side. It lets you connect the dots, and see the bigger picture.
Keep UTM parameters consistent
Use your UTM parameters consistently across both Ads and Analytics. These parameters give you access to extra data to help identify the source, medium, and campaign associated with an interaction. Inconsistencies in UTM parameters can lead to skewed attribution and inaccurate insights.
Test with debugging tools
Use tools like Google Tag Assistant to test your tracking codes thoroughly. These tools can help identify any issues with code implementation and provide valuable insights into the data collection process.
Understand your attribution models
Look at the attribution models used by both Google Ads and Google Analytics to better understand how they work.
Different models assign different levels of credit to various touch points in a user’s journey. This can create differences in conversion counts. You can examine what models you are using and then adjust and align these models across both platforms to help reduce discrepancies.
Establish a routine process to audit your tracking setup and data flow. Regularly review and compare the data reported by Google Ads and Google Analytics to identify any discrepancies. Regular audits will help you quickly identify problems, allowing for swift resolution of any issues in your data.
Investigate your data gaps
Analyze any periods of significant discrepancy to identify patterns. For example, if you notice a notable difference in data during specific times of the day or days of the week, this could give you a clue as to where the discrepancy is coming from. If it is time related, it may be due to one platform using real-time data and the other not.
Educate your marketing teams
Educate your marketing and analytics teams about the intricacies of data collection and the potential causes of discrepancies. When everyone understands the nuances, spotting and addressing issues collectively becomes easier.
Disparities between Google Ads and Google Analytics data may perplex you, but there is always a logical reason for their occurrence.
When you understand the technical nuances, employ synchronization strategies, and make sure all your parameters and codes are correctly set up, you can pave the way for data-driven marketing decisions that resonate with real user behavior.
Accurate data is essential for a successful marketing strategy; addressing these discrepancies ensures you’re on the right path to success.
By addressing the nuances of Google Ads and Google Analytics data discrepancies, you’re setting the stage for more effective campaigns, improved targeting, and greater ROI.