Overview
Google Analytics (GA) data often doesn't align with other platforms like Feathr, and this discrepancy is common across the digital advertising industry. Here's a breakdown of why differences occur and how to better understand your analytics.
Key Reasons for Discrepancies
1. Platform-Specific Interactions
- Definition of Metrics: Platforms like Feathr and GA may count impressions differently.
- Example: What Feathr considers a valid impression might differ from GA’s definition of a "viewable impression," resulting in data mismatches.
2. Ad Blockers and Privacy Settings
- User Impact: Ad blockers and browser privacy settings vary, and these tools can block or restrict tracking differently across platforms.
- Result: Some interactions might be captured in Feathr but not in GA, or vice versa.
3. Filtering Rules and Data Cleaning
- Bot Traffic: Platforms apply different filtering standards for bot traffic, duplicate clicks, and irrelevant interactions.
- Effect: GA might include data that Feathr excludes (or the reverse), creating differences in reported metrics.
4. Tracking Methodologies
- Mechanics of Tracking:
- GA primarily relies on UTM parameters and cookies for tracking.
- Feathr uses its proprietary tracking methods.
- Outcome: Differences in tracking technologies can lead to variations in captured data.
5. Data Processing and Reporting Timelines
- Timeliness:
- Some platforms, like GA, may report data in real-time.
- Others, like Feathr, might have a processing delay.
- Result: Discrepancies in the timing of reports can create temporary mismatches.
6. Attribution Models
- Attribution Differences:
- GA often uses last-click attribution, crediting the final click before a conversion.
- Feathr offers various attribution models, which may allocate credit differently.
- Impact: Variations in attribution methods lead to differences in how clicks and conversions are reported.
7. Cross-Device Tracking
- Tracking Across Devices:
- Feathr may more effectively track users across devices, capturing cross-device interactions.
- GA might miss conversions that occur on a different device than the initial click.
- Effect: This leads to gaps in data when comparing the two platforms.
8. Test Clicks/Views
- Clicks and Views from creative testing:
- Feathr allows for test views and clicks of creatives. Our reporting logic knows how to filter out those tests, but GA would have no way of knowing those were from testing.
- When creatives are submitted to the ad vendor for approval, the vendors each scan and click through the creatives to make sure they fall within their guidelines, ensure click through works properly, and check the destination URL for malware.
- Effect: This leads to an increased number of views and clicks in GA, sometimes outside the run time of the campaign in Feathr. These views and clicks can appear to come from outside of the target audience and/or target area.
Why Does GA Report 0-Second Sessions?
GA’s Session Duration Tracking
- GA calculates session duration based on the time difference between page interactions.
- Key Limitation: If no further interactions occur (e.g., navigating to another page or clicking on-page elements), GA logs the session as 0 seconds.
Impact in Ad Campaigns
- Ad Audit Clicks: Many 0-second sessions result from ad audits:
- Supply-side vendors test ad creatives by clicking on them to ensure compliance and legitimacy.
- These interactions typically lack engagement (e.g., scrolling or additional clicks), causing GA to log them as 0-second sessions.
- GA Reports All Activity: Unlike Feathr, which filters out some audit clicks, GA includes all interactions, inflating 0-second session counts.
Steps to Mitigate Discrepancies
1. Analyze Devices and Locations in GA
- Identify devices and locations with poor engagement (e.g., high bounce rates, low session durations).
- Exclude these devices/locations from future campaigns to improve targeting.
2. Review Referring Sites
- Check sites with the highest click-through rates (CTR) but low engagement.
- Manually exclude these sites from campaigns to minimize low-quality traffic.
3. Optimize Campaign Setup
- Monitor performance during the early stages of a campaign.
- Work with your ad provider to refine exclusions and adjust targeting criteria as needed.
Key Takeaways
- Discrepancies in data are normal across platforms due to differences in tracking methodologies, privacy settings, and attribution models.
- 0-second sessions often stem from tracking limitations and do not always indicate poor performance.
- Audit clicks are part of the ad publishing process, ensuring compliance but contributing to GA’s engagement skew.