Google Analytics 4 is AI-powered: have cookies come to an end?
The new Google Analytics 4 uses machine learning to fill in gaps of information. Yet, a solid dataset based on cookies has never been so important.
The newly rolled out version of Google’s platform – Google Analytics 4 (GA4) – brings in a new vision for the future of analytics. In this article, we’ll walk through the impact this has on the role of cookies.
Remember the App & Web property? It was an update that unified app and website data in one property. By doing so, Google accelerated one of the key trends dominating marketing analytics: cross-platform customer journey insights.
This year, Google decided to step up their game and introduced an even more intelligent version of the App + Web property. The newest Google Analytics update applies machine learning across devices and platforms. Here are the main features:
- AI-powered insights and predictions;
- Deeper integration across Google marketing products;
- Customer-focused measurements and reporting structure;
- Privacy-centric design.
The measurement evolution
“We’re in the midst of a measurement evolution, and global ecosystem changes are challenging marketers to be forward thinking and privacy focused”
Philip McDonnell – Director, Product Management at Google
Google clearly developed the new version of Google Analytics with the evolving landscape of technology in mind. Indeed, especially in the midst of the COVID-19 pandemic, many trends such as e-commerce, streaming services, and cloud-based operations have accelerated.
These ongoing changes represent big challenges to digital marketers, whom are faced with a complex measurement landscape. In the past, online measurement was heavily dependent on cookies. However, the growing concerns about privacy and the rise of a multi-device world are also creating numerous blanks in the data.
This is where artificial intelligence becomes critical in understanding the customer journey. Machine learning can use historical trends and observable signals to create an accurate view of consumers and fill in gaps. This is referred to as conversion modeling.
Machine learning and cookies
This is awesome! But how does it work?
Simply put, machine learning is a computer algorithm that learns to reason and act by finding patterns in big amounts of data. In digital marketing, platforms like GA4 collect as much data as possible and then make a highly educated guess (prediction) about consumer preferences, behaviors, and needs.
The keyword here is still data. Data-driven environments for modeling need a huge amount of observable data to start from – this being cookies, signals, conversion type, etc. To this end, Google suggests implementing strong online infrastructures.
At this point, we can draw a key conclusion. Google Analytics 4 offers great data capabilities, but it also makes it obvious that a solid dataset is critical. The more quality data the platform can train with, the more accurate predictions it can make.
A solution for a strong data foundation could be that of a well-built cookie database. Find out how to maintain your cookies intact despite the growing privacy concerns. Companies such as Apple have already introduced measures that have an unintended impact on your analytics.
So, have cookies come to an end? Absolutely not.
Cookies play an important role in capturing more conversion data. They have become even more important in building a strong foundation for high-quality predictions.