Why would Filtered GA4 Property be greater than Raw Data?

The title sums it up: I have one Google Analytics property with internal traffic filters, and another Google Analytics property without any filters. What could be the reason the filtered view is showing higher traffic than the unfiltered view?
Things I’ve already checked:
- Reporting Identity
- Time Zone of Property
- Ensuring the tag is only featured on the same domains

 

It's great that you've already taken some important steps to troubleshoot the issue. When you have one Google Analytics property with internal traffic filters showing higher traffic than another property without filters, there could be a few reasons for this discrepancy. Here are some additional considerations to check:

1. Filter Criteria: Double-check the filter settings in your Google Analytics property with internal traffic filters. Ensure that you've set the filter criteria correctly, including the IP addresses or patterns that need to be filtered out. Sometimes, incorrect filter settings can cause discrepancies.
   
   
2. Exclusion Errors: Confirm that you haven't accidentally included the wrong IP addresses or patterns in the filter, leading to legitimate traffic being filtered out.
   
   
3. Filter Sequence: The order in which filters are applied can impact the results. If you have multiple filters, make sure they are applied in the desired sequence. Filters are processed in order from top to bottom.
   
   
4. Sampling: If your unfiltered view has a higher volume of data, it may be subject to sampling. Sampling can lead to differences in reported data between filtered and unfiltered views. Check for sampling in your unfiltered view and try to reduce it if possible.
   
   
5. Data Processing Delay: Google Analytics can have some delay in processing data. Ensure that you're comparing data for the same time period in both views and consider that data may not be updated in real-time.
   
   
6. Excluded Hostnames: In your filtered view, make sure you haven't inadvertently excluded hostnames that should be included. Hostname settings can impact data collection.
   
   
7. Bot Filtering: Google Analytics automatically filters out known bots and spiders. Confirm that bot filtering is enabled in both properties to avoid discrepancies due to bot traffic.
   
   
8. Cross-Domain Tracking: If you have multiple domains or subdomains, check if cross-domain tracking is properly implemented to ensure that sessions aren't getting split between different properties.
   
   
9. Data Quality: Evaluate the data quality in both properties. If you suspect spam or invalid traffic in the unfiltered property, it can lead to artificially lower numbers.
   

By carefully reviewing these aspects and making any necessary adjustments, you should be able to narrow down the reasons for the traffic discrepancies between your filtered and unfiltered views in Google Analytics. Remember that consistent monitoring and periodic reviews of your settings can help maintain data accuracy.