Tracking | Understanding Variance Between Different Data Systems

Since both Google Analytics (GA) and your Customer Relationship Management (CRM) system are collecting data about your conversions, it seems logical that numbers should match up exactly when comparing the two systems. The reality is that there are many reasons that your data might not match exactly. This article explains the most common root causes for those discrepancies. 

 

 

Goggle Analytics v3 (Universal Analytics) Goals will only count a maximum of one conversion per session. So if your goal is to get users to submit a form and a users makes multiple submissions from the same session, you will see your conversion goal count increment by only one, while your CRM will count multiple.

 

Google Analytics v4 (GA4) does not behave the same by default. GA4 conversions can occur multiple times per session unless specifically configured to behave differently. 

 

From a business perspective, it is important to understand this key difference and decide what makes the most sense for your requirements. These difference between v3 and v4 will result in discrepancies in the conversion data if both are installed on the same site. And these differences may explain discrepancies between your CRM and GA reports. 

 

Conversion Trigger

Google Tag Manager (GTM) is used to create Tags and Triggers which send data to GA for reporting and analysis. Those Triggers must be configured to perfectly in order for GA data to match with CRM data. 

We recommend data layer support for maximum accuracy and maintainability but sometimes triggers have to be configured in other ways.

Example - Form Submission: shown below is a Trigger that has been configured to fire when a Form Submission is detected from the /contact-us page.  The problem with this Trigger is that it will no longer fire if certain changes are made to the website, including but not limited to: 

• embedding the form within an iframe
• updates to the page path

Example - Form Submission: shown below is a Tag Trigger that has been configured to fire when a user clicks a link where the link text is 'SUBSCRIBE'. With this trigger, the risk is that the text on that link may be changed in the future by someone who is not aware of the tracking requirements, thus breaking the tracking implementation. 

These are just two examples of triggers that may fail, resulting in underreporting in GA vs your CRM.

Google Analytics Filters

Google Analytics Filters may be applied to include or exclude traffic from specific domains and/or IP addresses. In GA3, filters are applied to the View. In GA4, filters are applied to the data stream.

IP address exclusions - If the value entered excludes IPs from which users can still complete a conversion, those conversion will be counted in your CRM but not in GA. 

Domain exclusion filters are useful to remove irrelevant data. However, if it is possible for users to complete a conversion from an excluded domain, that may be included in your CRM but excluded from GA reports. If that is the case, then this logic should be documented and communicated internally in order to prevent confusion. 

Cross-Domain Tracking

Cross-domain tracking ("cross-domain measurement" in GA4) allows you to collect and analyze data about user sessions that occur across different website domains (ex. channelmix.com and help.channelmix.com). When correctly implemented, these sessions are treated as one unique session for the purpose of analytics. Your CRM system may allow for this kind of cross-domain logic but if the rules are not exactly the same, you will find discrepancies in data, especially session counts. 

Conclusion

If you see some discrepancies between Google Analytics and data collected by another system, the above pitfalls should be considered. You may even experience some combination of these pitfalls which makes debugging especially difficult. Contact ChannelMix to find out how we can help with any discrepancies you are experiencing.