In the ever-evolving landscape of digital marketing and analytics, it's essential for businesses to stay ahead of the curve. With the arrival of Google Analytics 4 (GA4), the industry is witnessing a major shift in how data is collected and analyzed.
Here is the list of main changes that were introduced by Google Analytics 4:
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:
Streaming raw Google Analytics data means duplicating all the hits (events, page views, transactions, etc.) you send to Google Analytics in a different database (in BigQuery).
It means you will get all the raw unfiltered hits and you can either process this data further or use it for any kind of analysis.
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.
Some web-analytics services claim to have an advantage of tracking individual users that Google Analytics cannot do. However, this is not quite true.
Google Analytics tracks individual users, each interaction of individual users and has user-level reports. There are some limitations only regarding the personally identifiable information (PII).
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.
Data Studio is the tool used on Google Marketing Platform for data visualization. It became extremely popular among marketers in the past couple of years. The main reason for its popularity is that it is very extremely useful for building Google Ads and Analytics reports. Actually it is recommended to use Google Data Studio instead of Google Analytics built-in functions.
Two most popular opportunities to get Google Analytics data in BigQuery for non-premium Google Analytics users.
User-id tracking is the feature of Universal Analytics that many businesses implement. This is not a laborious process to implement User-Id tracking in case you have the unique identifier for each user available at front-end. But in real life few get any benefits from it.
Universal Analytics claims there are four main benefits of the User ID.
Thrivecart is used by many businesses for building their sales funnels. They have many useful opportunities for digital marketers. However tracking implementation on Thrivecart is a pain. Thrivecart do not officially support Google Tag Manager.
Here there is the documentation on how to implement Facebook pixel and Google Analytics on Thrivecart.