If you have a low-traffic website (less than 1000 visitors/day), your GA4 tracking will be completely messed up if you don’t do this
Your tracking will be messed up due to a gradual increase in the lack of consented data in your GA4 property.
There are two categories of data in the context of GA4 data modeling: Observed data and modeled data.
Observed data is the actual data that comes directly from users who granted consent for GA4 to track their behavior using identifiers like cookies or app IDs.
Observed data provide precise and reliable information about user behavior, including metrics like user counts, sessions, page views, events, and conversions.
Modeled data is the estimated data for users who did not grant consent (opt-out users).
The modeled data also comes directly from users who granted consent for GA4 to track their behavior using identifiers like cookies or app IDs.
In other words, the modeling itself leverages observed data.
Machine learning algorithms analyze patterns and behavior of users who consented and use these insights to estimate the behavior of similar opt-out users.
Therefore, modeled data isn’t directly collected from opt-out users but inferred from observed data with similar characteristics.
This distinction is crucial for interpreting reports in GA4.
While modeled data helps fill in data gaps and provide insights into opt-out user behavior, it’s important to remember that it’s an estimation and may not be as accurate as observed data.
Now, here is the bummer.
For data modeling to kick in, your GA4 property needs 1,000+ daily users with analytics_storage=’granted’ for 7 of the previous 28 days.
So, in real life, you will need a lot more than 1000 visitors/day because most of them will likely deny consent.
And the population of users who deny consent will only increase in the future.
Using BigQuery won’t save you either, as modeled data is not available in BigQuery export.
No observed data = no modeled data.
Without enough observed data from consenting users, GA4’s data modeling techniques won’t have enough information to generate reliable estimates for opt-out user behavior.
So what can you do then?
Find ways to maximize observed data collection.
- Review your consent messaging and design to improve user acceptance rates.
Offer incentives or rewards for users who consent, such as exclusive content, discounts, or early access to features.
- Focus on first-party data collection (user-provided data), like collecting email addresses.
- Use server-side tagging.
Server-side tagging can reduce reliance on user consent in several ways like converting third-party data into first-party data.
- Gather user data (qualitative and quantitative) from multiple online and offline endpoints.
The GA4 data can be easily enhanced in any data warehouse or CDP.
- Increase your overall website traffic.