When Google decided to sunset Universal Analytics in favor of GA4, it certainly ruffled some feathers. The UX was a lot less intuitive and you’ve likely had a hard time recreating your favorite reports.
But something that has really frustrated users? Data delays.
With GA4, you now have to wait several days for some of your reports to be accurate.
Why is that the case?
We’ll cover that below and provide an alternative for faster data insights.
Why GA4 Data is Delayed
First off, it’s important to know that data delays in GA4 are “normal” and by design. If data processing takes 30 minutes, then it will take 30 minutes for your reports to be up-to-date.
According to Google, it may take 24-48 hours to process data. And during that time, data in your reports may change.
Data freshness also varies depending on the time interval. For example, intraday data is updated throughout the day for quicker access, while daily data is more complete and available once per day for data with longer processing times.
So why is there a delay at all?
Data delays in GA4 compared to Universal Analytics are due to multiple structural changes in how data is collected, processed, and reported.
Here’s an overview of what’s changed and how it’s led to a slowdown in data processing.
Event-Driven Data Model
GA4 uses an event-driven data model which tracks each action individually, rather than grouping by sessions like in Universal Analytics. This requires more processing time to compile events into meaningful insights.
So, while the GA4 model is technically more flexible, it also demands more resources and leads to delays in processing and data reporting.
Data Sampling and Event Queuing
Another important distinction between Universal Analytics and GA4 is the use of sampling.
GA4 uses sampling to manage large volumes of data by analyzing a subset rather than the entire dataset, especially in high-traffic properties or for complex reports with filters or custom dimensions. Sampling helps conserve resources but requires additional processing to ensure the sampled data is representative of the whole.
Unlike UA where session-based data is processed quickly, GA4 causes slower report generation times, especially for detailed or customized views.
Advanced Attribution Modeling
Finally, GA4 also introduces cross-platform and cross-device attribution modeling, which incorporates machine learning algorithms to assign value to user actions across channels.
This attribution model is more complex and requires additional processing time. Inevitably, this leads to delays in reports involving conversion paths, channels, and multi-touch attribution data.
Other Causes of GA4 Data Delays
In addition to the structural changes in GA4 that cause delays in data processing, there are several other factors which may cause delays as well.
Offline Events: In GA4, if a user loses internet connection, event data is stored locally on their device and sent to GA4 when the device reconnects. This process can cause data delays, as offline events only sync once the device is back online. Additionally, if events are delayed more than 72 hours, they’re discarded, which can lead to incomplete data and discrepancies in reporting.
Tag Configuration and Tracking Issues: Misconfigured tags or tracking settings can delay data if events aren’t correctly triggered or sent to GA4. This leads to incomplete data that GA4 may process slower as it attempts to handle missing or misfired events.
High Data Volume: Large data volumes can overload GA4's processing capacity, especially in free accounts, where limits are stricter. High traffic causes GA4 to queue and sample data to manage the load, delaying report availability and completion.
GA4 Real-Time Data vs. Standard Reports
Real-time data in GA4 provides recent insights into user interactions within the last 30 minutes, designed to give a high-level view of recent activity. This type of data is processed quickly to support monitoring recent site activity or troubleshooting tracking issues. However, real-time data doesn’t undergo the same thorough processing as standard reports.
On the other hand, standard GA4 reports go through complete processing which includes attribution modeling, data thresholding, and sampling. This additional processing ensures that standard reports provide more accurate and complete insights but results in delayed data availability.
Ultimately, real-time data is best used for quick insights, monitoring user spikes, or checking if tracking events are firing as expected. For more accurate and detailed analysis, standard reports offer a fuller picture but require more patience as GA4 completes its in-depth processing.
Alternatives for Faster Data Insights
If GA4’s data delays are slowing down your decision-making, you may want to consider alternative analytics tools that prioritize speed and real-time insights. And if that’s the case, I encourage you to explore GoodMetrics which provides a faster, more straightforward approach to tracking.
Unlike GA4’s event-driven model, GoodMetrics uses session-based tracking similar to Universal Analytics, meaning there’s no waiting for data to process. As soon as users interact with your site, data is available instantly in your reports, letting you see the full picture in real-time without delays or sampling adjustments.