Google launches Google Analytics refresh with machine learning predictions
Google LLC today rolled out a major refresh of Google Analytics with new trend prediction features powered by machine learning, a streamlined interface and extra privacy controls.
Google Analytics is the go-to tool companies use to track their online marketing efforts. It provides information such as the number of people who visit a company’s site, what percentage of them make a purchase and how much revenue ad campaigns bring in.
Google Analytics 4, the refreshed version of the platform announced today, brings a set of new machine learning features. It can now automatically notify marketing teams about important events such as a sudden jump in sales of a particular product. Moreover, Google Analytics 4 can generate a number of “predictive” metrics, like the potential revenue a company could earn from a certain customer group in the future if it improves engagement.
“This allows you to create audiences to reach higher value customers and run analyses to better understand why some customers are likely to spend more than others,” Vidhya Srinivasan, Google’s vice president of measurement, analytics and buying platforms, wrote in a blog post today.
Marketers can access this data in Google Analytics 4’s revamped interface. The search giant has reorganized the platform’s data dashboards into a more intuitive arrangement designed to make it easier to find information. For instance, if a marketer wishes to know the channels through which their company is acquiring the most users, they can now find this information in the new “user acquisition” dashboard.
The revamped interface also has a few other additions. There’s an improved data deletion tool for when users ask a company to stop retaining their activity information. Also new is codeless event tracking, a feature that reduces the amount of Google tracking code companies need to embed into their websites to track user actions such as video views.
“It uses a flexible approach to measurement, and in the future, will include modeling to fill in the gaps where the data may be incomplete,” she elaborated.
On top of heightened privacy expectations, another challenge the update seeks to address is data fragmentation. In cases when a user’s interactions with a company span multiple platforms, for example if they make a purchase inside a mobile app after seeing an ad on their desktop, it’s technically difficult to connect the dots. It’s such a challenge that there has emerged an entire multibillion-dollar category of so-called customer data platforms designed to help marketers gain a complete view of buyer activity.
Google Analytics 4 employs marketer-provided user identifiers and signals from Google itself to match activity data recorded across different platforms to users. The result is higher-quality information to support online ad campaigns.
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