Discrepancies between N.Rich and Third-Party Analytics Tools

Understand why N.Rich and third-party analytics tools like Google Analytics may report different traffic and visit numbers. Learn the key factors causing these discrepancies and how you can improve reporting metrics and tracking.

At N.Rich, we understand the importance of accurate data when evaluating the performance of your account-based marketing campaigns. When comparing analytics, you may notice discrepancies between the analytics reported within our platform and those from third-party tools like Google Analytics (visits or sessions mismatch). Let's explore the factors contributing to these differences :

Advertising Engagement vs. Website Visits

It's crucial to distinguish between advertising engagement metrics and website visit metrics. While N.Rich reports on both, third-party analytics tools typically focus solely on website visits. This distinction is important to remember when comparing metrics across platforms as tools that focus on website visits will have more sophisticated and customizable configurations and technology.

Different Tracking Technologies

N.Rich and third-party analytics tools use proprietary tracking technologies that differ in definitions, methodology, configuration, and filtering rules. This inherently results in variations in reported numbers. Filtering in Google Analytics (or other tracking tools) may use less or more restrictive filters or allow the configuration of custom filters. The filtering methods and their aggressiveness vary between platforms, affecting reported visit counts. N.Rich also focuses on ABM-specific metrics, which can include additional layers of validation and identification to ensure the accuracy and integrity of the data reported within our platform. This includes filtering out visits originating from IP addresses not associated with any of your target accounts

Tracking and Tag Coverage

Discrepancies may arise from differences in how tracking tags are configured:

• Check if N.Rich and third-party trackers are deployed on the same pages across the site.
• Verify that both trackers fire in the correct sequence using the Tag Priority setting in your tag manager.
• Use debugging tools to ensure all tags are firing correctly and at the right time. If you are using Google Tag Manager, you can debug your tags using their tag assistant.

Consent Management Configuration

Cookie Consent settings play a significant role in data discrepancies. The N.Rich tag can track visits happening on your website regardless of cookie conset (based on our tag working in cookieless and standard mode). Dedicated web analytics tags like Google Analytics often relies on stricter cookie consent policies. Users who do not opt-in for cookies will not be tracked, leading to lower reported visits. You can check for ways to understand your current consent management opt-in rate and how to optimize it.

Ad Blockers and Brower Tracking Protection

Tracking Protection in browsers blocks a range of tracking technologies to protect user privacy. This includes:

• Third-party cookies
  Often used by analytics tools to track user behavior across websites.
• Tracking scripts
  Essential tracking scripts may not load. Scripts associated with analytics platforms or advertising networks, causing certain visits or interactions to go untracked.
• Fingerprinting technologies
  Techniques that collect unique user information to track devices. Third-party cookies used for session tracking may be blocked, preventing visits from being accurately logged.
• Cross-Site Tracking Prevention
  Browsers prevent tracking across domains, which can interfere with attribution for multi-channel campaigns.

While beneficial for user privacy, these features can block critical trackers, leading to reduced visit counts in web analytics tools and impacts them differently (N.Rich tag might not be blocked by a specific tracker while Google Analytics tag might be blocked and vise-versa).

Landing Page/Website Load Speed

Web page loading speed impacts tag performance and effectiveness. If your web pages take too long to load, tags not fire in a timely manner or get blocked. Visitors may also leave before trackers are loaded, leading to low tracking effectiveness. You can try to:

• Optimize landing page speed to ensure the analytics tracker loads before users exit the page.
• Prioritize loading essential trackers first to reduce the impact of script blocking.
• Use lightweight trackers to minimize latency.
• Use tools like Google Pagespeed Insights to understand how to improve your website performance.

Audit Clicks and Visits (non-chargeable clicks)

When you use N.Rich to run your ABM campaigns, your ads will undergo an ad review process that happens across our advertising ecosystem. This results in test/audit clicks and visits aimed at making sure that your ads and destination pages adhere to advertising policies and standards used by the different ad networks.

The visits resulting from this process are not associated with real user engagement and do not reflect genuine traffic. N.Rich uses filtering to exclude non-chargeable clicks and visits from your final reports and dashboards to prevent these interactions from contributing to metrics like cost-per-click (CPC) or engagement rates. Third-party analytics tools may report these visits, leading to a mismatch between reported visits and actual user traffic.

Recommendation: Focus On Relative Trend

When using N.Rich alongside third-party analytics tools, it's essential to consider relative trends rather than discrepancies in reporting across two platforms. The factors impacting tracking and reporting are numerous and complex. Metrics will most likely never match and it’s more rational to focus on relative trends and patterns rather than absolute numbers. While the specific metrics may vary, the overall trends in user engagement should remain consistent across platforms.

FAQ

How can I see N.Rich traffic using third-party analytics tools?
N.Rich uses different UTM parameters to tag the traffic coming from it’s advertising ecosystem. Read this help article to understand how you can leverage these tracking parameters to create reporting.

Why the number of visits reported are lower than the number of clicks reported?

Not all ad clicks result in website visits. This click-to-visit drop-off is caused by several factors. It’s important to understand these factors to be able to potentially improve your click-to-visit drop-off rate. Some of main ones are:

• Landing Page Load Times: Slow-loading landing pages can result in users abandoning the page before it fully loads.
• Device and Browser Compatibility: Some browsers or devices may block redirects or fail to load landing pages due to settings, or connectivity issues.
• User Behavior: Users may click an ad unintentionally or exit the page before the analytics tracker is triggered.
•  The click-to-visit ratio differs across advertising platforms and ecosystems (open web vs closed ecosystems like Meta or Linkedin. This is because users interact differently with the ads across these platforms. For example, ads clicked by mobile users on LinkedIn will open up in their native application browser, circumventing some of the drop-off factors related to browser and script blockers.