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Google Analytics 4 (GA4) represents a major shift in the way businesses track and analyze their online performance. Unlike Universal Analytics, GA4 focuses on events and users instead of sessions, offering marketers and small business owners powerful tools to understand their audiences on a deeper level.

Despite the fact that Google Analytics 4 (GA4) is not primarily designed to focus on individual user behavior, it does offer a User Explorer report to analyze the activity of individual users. This report allows businesses to see detailed data on how users interact with their website, including event tracking and session data. However, while the User Explorer report provides valuable insights, it has some limitations that can affect its overall effectiveness.

Google Tag Manager (GTM) provides an efficient way to implement tags without needing to constantly modify website code. However, to take GTM's flexibility even further, custom templates can be created to streamline and optimize tracking implementations — both on the client-side and server-side.

The landscape of e-commerce has evolved significantly, with a growing number of businesses use subscription models to get a consistent stream of revenue. For these businesses, the real challenge lies in maximizing user lifetime value. Effectively tracking transactions, recurring payments, and account cancellations is essential for sustainable growth. In this blog post, we'll explore a crucial aspect of this challenge and provide insights into using server-side tracking with Google Analytics to enhance control and visibility over subscription transactions.

Samplation has often been a pain for Universal Analytics users. With the move to Google Analytics 4, the quotas for queries have been greatly increased. In GA4, the quota limit for event-level queries is 10 million events for standard Google Analytics properties and up to 1 billion events for Google Analytics 360 properties. This enables GA4 users to report on large timeframes and multiple dimensions without any sampling.

Roll-Up Property is a single property which aggregates data from multiple source properties. This might be useful for businesses that have multiple websites for different regions. In this case, they can safely track each of the regional sites into a separate Google Analytics property and also have a separate roll-up property to analyze a larger amount of data than you have in single-site properties.

Here is how the Google Analytics account structure would look like in case of using the roll-up property:

Goals and funnels reports are extremely useful for marketers. These reports help to evaluate traffic sources and campaigns, to analyze the user flow through the funnel before conversion, to find drop-off points and bottlenecks in the funnel. Google Analytics is tricky when it comes to funnel configuration.

Unlike many other analytics systems Google Analytics processes the goal and funnel data. It means that you cannot build a funnel report on historical data. you need to configure your goals and funnels first and only after this Google Analytics will start collecting data about funnel flow and conversions.

Google Analytics presents their data sampling technology is a way to present meaningful data on large data subsets (here is official documentation on this topic https://support.google.com/analytics/answer/2637192?hl=en). However most of the medium-sized online businesses worry a lot when they get a notification that the report is built on 70% of their data and not 100%.

And they worry not without reason especially in case they analyze some small segments of their audience.

Two most popular opportunities to get Google Analytics data in BigQuery for non-premium Google Analytics users.