Why Google Analytics Is Not 100% Accurate
Google Analytics can display inaccurate data for several reasons. First, make sure you’re measuring the right metrics and that your tracking settings are configured correctly.
Another major reason for limited accuracy is that Google Analytics cannot fully identify users who behave differently across multiple devices. In addition, many users have ad or tracking blockers installed on their devices. If a user disables their ad blocker to access a certain website, Google Analytics may unintentionally attribute future interactions to that same user.
Other common reasons Google Analytics data may be inaccurate include:
- Blocked cookie permissions & private browsing
- Page timeouts or tracking script failures
- JavaScript errors and broken tracking codes
- Bots and spam interactions
6 Common Google Analytics Data Errors and How to Fix Them
Can you rely on your analytics data? In most cases, yes. Google Analytics is generally a reliable tool that delivers accurate results. However, it’s not possible to trust the data entirely, as certain errors and technical issues may occur.
Below are six common mistakes that can cause inaccuracies in Google Analytics data, along with practical ways to fix them. Let’s get started!
1. Offline Campaigns That Are Not Tracked
Tracking the results of an offline campaign, such as a magazine or newspaper ad, can be challenging. But does that mean you shouldn’t even try? 🧐 Not at all.
Redirecting someone to your website from a billboard or print ad is very different from driving traffic through a landing page or a banner on your site. While it’s true that offline advertising is harder to track, many marketers make the mistake of assuming it’s impossible.
Ignoring your offline campaigns creates “holes in your analytics bucket,” leading to confusion and misleading performance metrics. That’s why it’s best to address this issue as early as possible.
Since the campaign runs offline, you’ll need to find a way to attach a unique identifier that reflects the campaign details. Here are a few effective methods:
- Use discount codes specific to the campaign
- Redirect to a unique landing page with a shortened URL
- Run two-step marketing campaigns
- Add a “How did you find us?” popup
By tracking your offline marketing efforts, you can not only improve the accuracy of your Google Analytics data but also optimize campaign performance much faster.
2. Cross-Domain Tracking Errors
Google Analytics allows you to track visitor activity across domains and subdomains separately, but by default, it tracks sessions across all subdomains using a single domain.
⚠️ When users land on your site through cross-domain links, this can lead to issues such as inflated traffic numbers.
The reason is that, by default, Google Analytics cannot distinguish between traffic coming via a link from another domain and traffic from a search engine that goes directly to the new domain. This can significantly impact how you interpret visitor behavior. As a result, your marketing campaigns may seem to perform better than they actually do, leading to inaccurate data. 😵💫
To set up cross-domain tracking, you can use either Google Analytics or Google Tag Manager (GTM). While Google Analytics provides instructions to manually add the required parameters, it’s highly recommended to use the official Google Linker plugin.
With Google Tag Manager, implementing cross-domain tracking is often more convenient and typically done using one of the following two options:
- Link Click / Form Submission Tags → Helps Analytics recognize when a link is clicked or a form is submitted.
- Auto Link Domains → Uses cookie values and is easier to set up in GTM, though less flexible than the first method.
3. Duplicate Pages in Analytics Reports
One of the simplest ways to improve data clarity is to remove duplicate entries from your reports.
Duplicate data often appears when someone types your URL using different capitalizations. This happens more frequently than you might expect!
Here’s an example of how this inconsistency may look in Google Analytics:
/smartmarket/groceries/Fig
/smartmarket/groceries/fig
/smartmarket/groceries/FIG
Even though users land on the correct page regardless of how they type the URL, this inconsistency can harm your Google Analytics accuracy. Each unique URI (end of the URL) is treated as a separate row in analytics reports. Unfortunately, duplicate data cannot be removed once it appears in reporting.
The good news? You can prevent this issue by taking precautionary measures.
To prevent data duplication in Google Analytics, follow these steps:
- Go to the Admin panel in Google Analytics, under the View settings (usually named All Website Data), select Filters
2. Click “Add Filter”, then select “Create New Filter.”
3. In the Filter Name field, enter “Force Lowercase.”
4. Set Filter Type to Custom.
5. Check the option “Lowercase.”
6. From the dropdown menu, select “Request URI.”
7. Click “Save” to apply the filter.
4. Missing Raw Data in Reports
When you create or view a report in Google Analytics, it contains numerical data about your website visitors, traffic sources, and how users behave on your site. However, raw data is far more valuable than most people realize!
By default, raw data is available in the All Website Data view when you set up a new property in Google Analytics.
⚠️ Never modify or delete your raw data, there’s no way to restore it once it’s filtered!
If you apply filters to your primary data and you don’t have another view within the same property, you will lose that information permanently. It also won’t be possible to apply data analysis retroactively to filtered data.
This raw data view is essential for solving analytics issues, whether you’re working with a filtered segment or analyzing the full dataset. So, treat it carefully and always preserve it!
5. Self-Referrals Showing Up in Reports
Self-referral occurs when someone redirects traffic to their own website using a keyword. These referrals can affect acquisition, behavior, and conversion data in Google Analytics, compromising overall data integrity.
Self-referrals often appear when you use a single Google Analytics property to track multiple domains and subdomains. Fortunately, you can prevent this issue by applying filters.
You can find the setting under:
Google Analytics → Admin → Account → Property → Tracking Info → Referral Exclusion List
Simply add any domains that should not appear in your traffic reports.
Other common causes of self-referrals in Google Analytics include:
- Incorrectly configured cross-domain tracking
- Missing tracking code on certain pages
- Incorrect use of UTM tags in internal links
6. Abnormally Low Bounce Rate
Is your bounce rate unusually low and making you wonder what’s happening in your Google Analytics account? If so, you’ve likely uncovered an issue with your data collection method.
Any analytics tool needs to interpret the information it collects, so understanding different metrics and what they mean is crucial. A typical bounce rate varies depending on the type of content, but it's not uncommon to see rates at 60% or higher.
When the bounce rate drops to extremely low levels (e.g., below 10%), it usually indicates:
- Multiple tracking codes firing simultaneously
- Incorrect Google Analytics setup
- Auto-events falsely counted as interactions
In such cases, the data does not reflect real user behavior and can lead to misleading insights, which is why it's important to investigate immediately.
If your bounce rate suddenly drops below normal, here’s what you should check:
✔️ Make Sure There Are No Duplicate Tracking Codes
For example, if there’s an analytics plugin using the same property ID under Theme Settings, that’s a red flag.
This issue may occur when the same property ID is used multiple times across different pages or posts, causing the data to appear under separate property identifiers (PIDs) when reports are viewed.
You should remove or adjust any faulty code until it matches the one displayed in your Google Analytics account — otherwise, the data gets mixed up, which can cause major inaccuracies.
⚠️ Watch Out for GTM & GA Conflicts
Google Tag Manager is an important tool when working with Google Analytics 👀
Make sure you’re not running GTM alongside a standalone GA tracking code.
If both are triggered on the same website, you’ll end up with two tracking instances. Choose which one to use and remove the other.
🎯 Configure Non-Interaction Events
Chances are, your website includes a popup or live chat widget.
Sometimes, these features send trigger signals to Google Analytics. To prevent them from affecting your bounce rate, set them as non-interaction events.
And yes, that’s exactly how you can fix the issue!
👉 Bonus Tip: Popup builders like Popupsmart can help stabilize your bounce rate while also increasing market growth and conversion rates.
Improving Data Accuracy Starts with Awareness
Just like any analytics solution, there will always be a margin of error. In fact, the better you understand your analytics platform (such as Google Analytics), the smaller that margin becomes.
Review the list above and check whether you’ve experienced any of these issues. If you have, don’t worry — you’re definitely not alone. Instead of relying on outdated methods or assumptions, stay informed with the latest updates and always look for the most effective solutions.
✅ Have you encountered other data accuracy issues, and how did you resolve them? Share your experience in the comments below. 👇🏻
FAQs
- How long does it take for Google Analytics to start tracking?
After setting up Google Analytics for the first time, it typically takes 24 to 48 hours for website traffic data to appear. However, if you’re using real-time reports, you can quickly verify whether Analytics is working correctly. - Is all the data in Google accurate?
Unfortunately, not entirely. Like any analytics tool, Google Analytics may include inaccuracies due to tracking errors. This article highlights the most common ones. One of the biggest causes of incorrect data is the lack of information about where your visitors are coming from. - Is Google Analytics free to use?
Yes. Google Analytics offers a free basic version, which is ideal for small businesses. As your business grows, you may need more advanced features to monitor traffic and website performance, at that point, switching to a paid version may be required. - Is it worth using Google Analytics?
In short, yes. Setting up Google Analytics is a smart choice when building a business and website. However, since it does not provide 100% accurate results, larger brands may consider alternatives such as Matomo, which offers deeper insights into traffic trends.
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