Why Google Analytics isn’t always accurate (and that’s okay)

Google Analytics is the default tool for businesses wanting to understand how users interact with their websites. But if you’ve ever compared Google Analytics data to that of other platforms like Google Ads, Facebook Ads, Microsoft Ads, or your own sales figures, you’ve likely noticed the numbers just don’t add up.

Kayn L April 21, 2025

Why is Google Analytics data inaccurate?

1. Tracking methods

Google Analytics relies on cookies and JavaScript to track user behavior. Platforms like Facebook and Google Ads use a mix of browser and server-side reporting, which can capture data even when Google Analytics can’t. So while Facebook and Google Ads will record a ‘view’ or ‘click’ when someone sees or clicks on an ad, Google Analytics will only record a ‘session’ if the tracking scripts load properly. Because of this, clicks will almost always be higher than sessions in Google Analytics.

2. Ad blockers, cookies, and privacy changes

A number of tools and settings can be used to block Google Analytics tracking scripts from firing or collecting data, and with growing privacy concerns, more and more people choosing to use them:

Disabling browser cookies
Sending “Do Not Track” signals
Opting out using cookie consent banners
Private browsing modes like Chrome Incognito or Safari Private.
Ad blockers

3. Attribution models

All marketing platforms attribute conversions in different ways. Google Analytics uses data-driven attribution by default, meaning it distributes credit for a conversion across multiple touchpoints based on how much each interaction contributed. And Google Ads could be using a ‘last click’ attribution model, while Facebook uses a ‘last touch’ model. These differences mean that even if the same conversion is reported in multiple platforms, each one can claim credit differently, often in a way that makes its own performance look good.

4. Cross-device and cross-browser behavior

Users often switch devices or browsers in their customer journey. If someone clicks on a Facebook ad on their phone and later makes a purchase on their laptop, Google Analytics might not be able to connect the dots.

Data modelling in Google Analytics 4 (GA4)

With the introduction of GA4 came data modeling. Data modelling uses machine learning to estimate user activity and fill in gaps when identifiers like cookies are missing, but it’s not available to everyone; to use it, you need to enable it and have a high volume of traffic.

Google Analytics is directional, not a system of record

Google Analytics is great for answering questions like:

“Are visits trending up or down?”
“Which pages are performing best?”
“What sources are bringing the most engaged users?”

But it’s not ideal for answering absolute questions like:

“Exactly how many people bought this product from Facebook?”
“How much money did we make from Google Ads last month?”

It’s tempting to chase down every discrepancy between Google Analytics and other marketing platforms, but no amount of digging will make the numbers match perfectly. Instead, use Google Analytics to spot trends, understand user journeys, and guide decision-making. For paid advertising, rely on the platform-native data (Google Ads, Facebook Ads, Microsoft Ads, etc.); those systems are built as the source of truth for their own ad delivery and performance.