Google Analytics 360 now offers the ability to create product line sub-properties, custom user roles and large caps on dimensions, audiences and conversion types.
The update -- announced Thursday for enterprise-level companies -- builds on Google Analytics 4 as a foundation for larger companies and agencies to address measurement needs for custom campaigns.
Google introduced Analytics 4 in 2020, dubbing it the future of measurement because of its machine-learning capabilities, among other technology.
A Forrester Research study released in mid-2020 showed that although 84% of decision-makers surveyed considered cross-platform analytics “critical” or “very important,” only 43% had cross-platform analytics tools implemented.
Analytics 360 gives advertisers new collaborative capabilities to create up to four product line sub-properties for each country team, then customize settings. Those sub-properties link to the Google Ads and the Google Marketing Platform accounts associated with the campaigns running in those countries.
He explains in a blog that advertisers may also have analyst teams in each of those countries that need to access the data across all product lines for their markets to understand what’s driving sales for the brand, locally.
Marketers can do this, he wrote, by creating “dedicated roll-up properties for the United States, Canada and Mexico across all four product lines.” This will let them better understand the audiences interested in the products.
Roll-up and sub-properties will become available in Analytics 360, only, and will launch in the coming months.
This latest version of Analytics 360 has higher limits for up to 125 custom dimensions, 400 audiences and 50 conversion types. For those wanting to run their own analysis, Analytics 360 allows marketers to export billions of daily events to BigQuery. Custom user roles can be assigned to select reporting collections, groups of reports based on topics like customer acquisition.
Marketers also gain continuous intraday data via Analytics 360’s interface and the API. The data typically appears within an hour after collection to make faster, near-real time decisions during crucial periods like on Black Friday, Ganem explains.