Why do Matomo data reports differ from Google Analytics and other analytics tools?

Cloud On-Premise

When comparing Matomo reports with other analytics platforms, such as Google Analytics, you should expect similar trends and broadly comparable totals. Visits, pageviews, and session counts typically differ by no more than 5% to 10%, when both tools are correctly configured.

Larger discrepancies usually indicate issues with configuration, tracking implementation, filtering, or attribution logic. If you notice differences in reported metrics when comparing Matomo with another platform, review the points below to identify the cause.

Data sampling

Not all discrepancies indicate configuration issues. Some differences are a result of how analytics platforms process data, specifically, data sampling. Matomo does not sample data. It processes all tracked data and returns complete results.

Some tools, including Google Analytics, may sample data in certain reports or when applying segments, which can lead to noticeable discrepancies, especially for high-traffic sites or complex reports.

Visitor and Behaviour reports

1. Hits vs Visits

Log analysers report hits, which count every HTTP request to a website, including pages, images, CSS files, and JavaScript files. Matomo reports user interaction metrics such as pageviews, visits, and unique visitors, which will be significantly lower than server hit counts.

2. Matomo tracks site searches automatically

When Site search tracking is enabled, Matomo automatically tracks internal site searches as a unique action. These searches do not increase the total pageview count, which can create differences when comparing reports with other tools.

3. Identifying visitors

Matomo identifies visitors using a first-party visitor ID when cookies are enabled. If cookies cannot be set, for example due to consent restrictions or browser settings, Matomo falls back to a visitor recognition method based on request attributes such as IP address and user agent.

Other analytics platforms may rely exclusively on cookies, IP addresses, or probabilistic techniques. Differences in visitor recognition methods can affect unique visitor and session counts, especially when cookies are restricted or disabled.

4. Average visit/session duration variations

Session duration and bounce rate calculations can vary between analytics platforms due to differences in measurement methods.

In Matomo, the heartbeat timer sends periodic signals while a page remains active. When the heartbeat timer is not enabled, time spent on the final page of a visit may be recorded differently, resulting in variations in reports.

Attribution and traffic sources

Higher Direct Entry visits in Matomo

When analysing source attribution, Google Analytics may continue to associate subsequent visits with a previously tracked campaign because campaign information from UTMs can persist in the user’s analytics cookie for months. Depending on the attribution model applied, this can result in visits that would appear as Direct being credited to the original campaign.

By default, Matomo treats new Direct Entry visits as direct traffic and does not automatically carry forward a prior campaign source across sessions. Matomo’s default attribution logic uses the last non-direct referrer seen before conversion. Campaign persistence between sessions does not occur the same way as in Google Analytics without custom attribution modelling.

With Matomo’s Multi Channel Conversion Attribution feature, you can apply alternative attribution models to goal or Ecommerce conversions to understand multi-touch contributions.

Tracking methods and configuration

1. JavaScript vs server logs

Tools that rely on server logs (such as AWStats or Webalizer) record all traffic, including bots and spam. Matomo’s JavaScript tracker records human interactions by default and excludes most bot traffic. Comparing a log analyser with Matomo will often show higher numbers in the log-based tool.

2. Tracking code placement

When comparing JavaScript-based metrics, ensure that the analytics tracking scripts are implemented consistently across all relevant pages. When a page loads one tracking script but not the other, the platforms will report different visit and pageview counts.

If you use Matomo Tag Manager or another tag management system, confirm that the container script is present on all pages you are tracking. The Matomo tracking code or Tag Manager container should be placed before the closing </head> tag to ensure it loads correctly and executes as expected.

3. Record loaded page

When the Matomo JavaScript tracker loads at the end of the page, it records a pageview only after the page has sufficiently loaded for the script to execute. If a visitor leaves before the script runs, the pageview is not recorded.

By contrast, log analytics tools record page requests at the server level. This can include requests for pages that were cancelled before the page fully loaded, which can result in higher pageview counts.

4. Duplicate tracking

While you can configure tracking to use Tag Manager and the JavaScript tracker code, it is recommended to use only one tracking method. There are rare scenarios where both methods are implemented but this is not recommended as it can result in double-counted pageviews, events, and conversions.

5. Incorrectly configured web server (On-Premise)

Restrictive web server settings (such as HTTP 413 or 414 errors) may prevent tracking requests from being recorded if the server limits request size or URL length. Review the web server access and error logs for the matomo.php endpoint. Any responses other than HTTP 200 (OK) or HTTP 204 (No Content) may indicate that tracking requests are being rejected or blocked.

Differences between Matomo and another analytics platform can occur from how consent managers are implemented. If consent is granted for one tracking script but not the other, the platforms will record different numbers of visits and actions. Learn how to identify visitors that used tracking cookies.

Review your consent manager configuration to ensure that both tracking scripts load under the same conditions and categories.

2. DoNotTrack support (will be deprecated)

Some browsers previously supported a Do Not Track (DNT) setting that signalled a user’s preference not to be tracked. Matomo respects this setting by default when using the JavaScript tracker. However, Do Not Track is being deprecated and is no longer widely supported by modern browsers, so its impact on reported metrics is typically limited.

When importing server logs, Do Not Track preferences are not available because this signal is only sent via the browser.

Exclusions and spam prevention

1. IP address exclusions

If IP exclusions are configured in one platform but not the other, visitor and session counts will differ.

Ensure that IP exclusion rules, IP ranges, and subdomain tracking settings are aligned across both tools. When Matomo or another analytics platform ignores traffic from specific IP addresses, equivalent exclusion rules must be applied in each system for accurate comparison.

2. Bots and spiders tracking

When comparing platforms, ensure bot filtering settings are aligned. If bot filtering is disabled in one tool, higher visit and pageview counts may occur.

By default, Matomo’s JavaScript tracker records only activity from browsers that execute JavaScript. As most traditional bots do not execute JavaScript, they are excluded automatically. However, advanced bots and headless browsers can execute JavaScript and may appear as regular visitors.

In Google Analytics, bot filtering must be enabled manually. Log analytics tools typically record all requests unless explicit filtering rules are applied.

3. Tracking spam prevention

Matomo’s Tracking Spam Prevention plugin can automatically restrict suspicious traffic. For example, you can configure the feature to ban IP addresses after a defined number of actions, block/allow specific countries or IP ranges, or prevent tracking from headless browsers and server-side libraries.

If these controls are enabled in Matomo but not in the other platform, fewer visits and actions may be recorded in Matomo, resulting in discrepancies between reports.

Next Steps

Conservative counting provides a more realistic view of user activity. Analytics tools are typically used to measure trends and relative changes over time rather than exact absolute numbers. For consistency, use the same analytics platform for all reporting and comparative analysis. Read more about migrating from Google Analytics to Matomo.

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