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Why marketers are frustrated with Google Analytics 4

Author: Tiffany Staples

When it comes to digital analytics, Universal Analytics (UA) set the standard for data collection and organization. But in July 2023, Google officially pulled the plug on the popular platform and replaced it with Google Analytics 4 (GA4). While GA4 has been around since 2020, complaints about the platform have grown exponentially — especially from marketing departments.

Aside from GA4 being difficult to use, marketers are frustrated that many core features and familiar standard settings they relied on for years are missing in the new version. While GA4 is still evolving, the limitations and frustrations that marketers are feeling are too many to be ignored.

Lagging data 

In Universal Analytics, four hours was the typical data-processing delay that marketers had to account for. In GA4, the wait time (which Google now refers to as “data freshness”) is much longer — anywhere between 12 and 48 hours. Why so long? Mainly because GA4 now uses an event-based data model. This model requires more processing time, which leads to delays. Data volume, complex custom configurations, and even the difficulty of event tracking itself are also causing problems. Processing larger data sets contributes to further lags in reporting.

Digital marketing moves fast, which means data delays in GA4 are a huge headache for marketers. Without live-time data and reporting (like insight on website visitors, consumer behaviors, and campaign performance), marketing departments are forced to make decisions based on outdated information. This leads to missed opportunities such as identifying emerging trends, optimizing campaigns, and personalizing experiences in-the-moment.

Limited historical data 

Migrating historical data from UA to GA4 is limited because the two versions rely on different data collection models. In UA, data is structured in sessions, but GA4 focuses on event-based data.

For marketers, this means it’s more difficult to analyze past trends and compare metrics from different time periods. Instead of leveraging historical data (like past behaviors and performance metrics) to make informed decisions, marketers are forced to focus on incomplete metrics to plan their future campaigns.

Historical data storage limits are also a new concern. In GA4 the maximum storage limit is 14 months, whereas in UA storage was unlimited. As a workaround, Google provides access to BigQuery, a data warehouse. But configuring and using the data warehouse isn’t intuitive and includes a steep learning curve.

Data discrepancies 

In GA4, events are tracked at an individual level, not at the session level as they were in UA. So an event that was counted multiple times in a session in UA may only be counted once in GA4. How sessions are counted within a time period has also changed from UA to GA4, causing further discrepancies. Essentially, trying to compare monthly or yearly sessions between GA4 and UA won’t work. Marketers need to understand metrics at an individual level; how many sessions or events are attributed to that individual — regardless of where, when, or how they interacted.

Because the data’s being collected and processed differently in GA4, it’s leading to inconsistencies in reporting. For marketers, this raises red flags about data accuracy and causes many to doubt the validity of the platform.

Metrics issues 

Many familiar metrics from UA are either missing or altered in GA4. While events in UA had their own categories, action, and label, GA4 has replaced all three with “event parameters.” Bounce rate (another favorite metric among marketers) has also been demoted in GA4. While it’s been replaced by a metric called “engagement rate,” the transition requires marketers to adjust their analytics strategies and interpretation of engagement data.

How sessions are measured in GA4 is posing additional problems for platform users. In UA, a new session began when a user visited a website or when a user visited a site from a new source. A session ended after 30 minutes of inactivity, when the timestamp restarted at midnight, or when there was a change in campaign parameters. In GA4, sessions begin with a “session_start” event, and each session ends after 30 minutes of inactivity. But a new session doesn’t start at midnight or when a user visits the website with new campaign parameters.

Reporting issues 

Marketers are also annoyed that GA4 has less pre-defined reports than UA (which came standard with over 30 reports). Common missing reports include behavioral flow reports and recurring email reports. And GA4 now has only two acquisition reports — UA had roughly 25.

To work around the issue, GA4 encourages customized reports. While customization is possible, and sometimes even preferable, building custom reports is time-consuming and frustrating —especially when you’re used to having them readily available.

Compliance and data privacy 

Data privacy is a big focus of GA4, prompting updates like shorter data storage duration, tracking opt-out, and default IP anonymization. It’s likely that a lot of the issues marketers are having with GA4 are a direct result of the limitations on capturing, tracking, and keeping third-party data. They simply can’t do what they did with UA.

While many privacy issues have been updated, one glaring fact remains: GA4 is not compliant with GDPR, HIPAA, or other standard privacy regulations. GA4 hasn’t yet reached an agreement with European regulators regarding protecting EU citizen and resident data against US surveillance laws. And Google clearly states users can’t collect personal identifiable information, nor will they sign a BAA for HIPAA compliance. With the evolving privacy landscape, this is a major roadblock for marketers across industries.

The general consensus 

While Google has addressed several issues and limitations that marketers are unhappy about in GA4, responses have been slow and irregular. Challenges and roadblocks are to be expected when big updates or new platforms roll out, but the main frustration marketers have overall is “why change something that isn’t broken.” And, if you must start from scratch anyway, it may be a good time to find a better solution for digital analytics.

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