Marketing Engineers

There are a lot of reasons why you can encounter inconsistent data in your analytics environments, especially when comparing data from different platforms. Below you can find a summary of issues that we regularly encounter and we also wrote an article with recent examples.

Improper UTM Tagging

Incorrectly formatted or missing UTM parameters in marketing links prevent accurate source identification, leading to misattributed or lost conversions. As a result, your campaigns may appear less effective than they actually are.

Ad Blockers & Privacy Tools

These tools can block tracking scripts, preventing accurate recording of website visits and interactions, leading to underreporting of traffic and conversions from users employing them.

Consent & Cookie Management

Insufficient or improperly implemented consent mechanisms, coupled with restrictive cookie policies, can limit tracking capabilities, resulting in incomplete data and inaccurate attribution.

Tracking Script Issues

Errors in the implementation of analytics tracking scripts (e.g., incorrect placement, conflicts with other scripts) can disrupt data collection, leading to missing or inaccurate data points, affecting attribution accuracy.

Attribution Window Mismatch

An improperly set attribution window—the timeframe for assigning credit to marketing sources—may fail to capture conversions that occur after the initial click, leading to underreporting of campaign effectiveness.

Cross-Domain Tracking Issues

If users navigate across multiple domains (e.g., from an ad to a landing page to the main website), the analytics platform might not link these interactions, resulting in lost conversions and inaccurate attribution.

Referral Exclusions

Incorrectly configured referral exclusions can mask valuable traffic sources, preventing accurate attribution of conversions originating from those sources. Marketing campaigns might mistakenly be considered ineffective.

Redirect Issues

Broken or improperly configured redirects can interrupt the tracking process, leading to lost sessions and inaccurate attribution of traffic to the correct sources. Conversions might be lost or incorrectly assigned.

Analytics Filtering

Overly aggressive or improperly configured filters in your analytics platform can exclude legitimate traffic, causing inaccurate reporting and misrepresenting campaign performance.

Data discrepancies in practise

Please read this article to learn more about real-world implications of the data discrepancies as described above.

Questions?

We’re happy to help you with any of these issues. You can use the contact form below to get in touch with our engineers: