Google Analytics for SaaS - Detailed Guide Exploring the Nuances of Moving to GA4

Google Analytics vs Google Analytics 4: Main differences explained.

Let's take a look at this infographic about some of the key differences between GA4 and Universal Analytics.

Tracking Paradigm: In UA, the tracking method is session-based, which means that it tracks the number of times a page is loaded during a session. This method is limited in its ability to track user behavior across multiple devices and channels, as it doesn't account for interactions beyond page views. 

Google Analytics 4 (GA4) on the other hand, uses an event-based tracking paradigm, which means it tracks specific user interactions, such as clicks, scrolls, and video views, as well as page views. This method enables you to gain deeper insights into user behavior, as it tracks interactions across multiple devices and channels. Another significant difference between UA and GA4 is that GA4 uses a more intelligent approach to data analysis, with built-in machine learning and AI capabilities. GA4's AI-powered "Insights" feature can automatically identify trends and anomalies in data, providing valuable insights and recommendations for optimization.

The shift from session-based page views to event-based tracking in GA4 represents a significant evolution in the field of data analytics, providing businesses with more comprehensive and customizable insights into user behavior.

Attribution: Attribution in Universal Analytics is generally dependent on the last non-direct click before a conversion, giving the session precedence. This means that if a user interacts with a website or app numerous times, the conversion is attributed to the most recent non-direct source of traffic.

In contrast, Google Analytics 4 (GA4) prioritizes the user in attribution. GA4 uses machine learning to monitor user behavior across several sessions and devices, taking into consideration all touchpoints in the user's journey, not simply the most recent non-direct click. This enables a more comprehensive knowledge of how various marketing channels and touchpoints contribute to a conversion. Furthermore, GA4 introduces a new model called "data-driven attribution," which uses machine learning to analyze the actual conversion paths of individual users and assigns credit to the marketing touchpoints that are most impactful for driving conversions.

The transition from session-based prioritization in UA to user-based prioritization in GA4 enables a more comprehensive understanding of how different touchpoints contribute to conversions, providing businesses with more accurate insights for optimizing their marketing strategies.

Data Setup Organization:  In Universal Analytics (UA), data setup is organized around views within properties. A property is a collection of data associated with a website or mobile app, and views are subsets of that data that allow for customized reporting and analysis.

Google Analytics 4 (GA4) leverages data streams within properties for data configuration. A data stream is a collection of information gathered from a single source, such as a website or mobile app. A single property can be associated with many data streams, providing for more detailed control and customization of data analysis. As a result, GA4 offers a more flexible and configurable approach to data creation, allowing businesses to generate independent data streams for different portions of their website or app and analyze the data separately. GA4's data streams can collect data from a variety of sources, including web, mobile apps, and offline sources, providing a more complete picture of user behavior.

This improvement in Google Analytics 4 for SaaS businesses is great, allowing them to better tailor their analytics setup to their specific needs. SaaS businesses rely heavily on metrics such as sign-ups, upgrades, and renewals to gauge their success. With universal analytics, we need to track app events separately, and it was almost impossible to connect website traffic to the app, to better understand which campaigns, blogs, and sources drive the most engaged users. GA4 offers more advanced conversion tracking that allows businesses to see which events lead to conversions and how different segments of users behave in relation to these events.

User Entity Modeling: User entity modeling in Universal Analytics (UA) mostly depends on cookies. A cookie is a short text file saved on a user's device that carries information about their online behavior. This enables UA to recognize repeat users and follow their behavior across numerous sessions. 

For user entity modeling, Google Analytics 4 (GA4) uses a combination of "Google Signals" and cookies. Google Signals is a function that allows GA4 to collect data from people who have enabled tailored ads on their Google account, even if they have never visited the website or app under investigation. Additionally, GA4 employs cookies for user identification and tracking; however, unlike UA, GA4 employs first-party cookies by default. This means that cookies are placed by the website or app being tracked rather than by third-party trackers, resulting in improved data privacy and security.

In general, the combination of Google Signals and first-party cookies in GA4 enables more complete user entity modeling, since businesses can identify and monitor users who have never visited their website or app before, all while protecting data privacy and security.

Engagement Metric: In Universal Analytics (UA), the primary engagement metric is bounce rate. A high bounce rate is typically seen as a negative indicator of user engagement, as it suggests that users are not finding the content they are looking for or are not sufficiently engaged with the website.

The major engagement statistic in Google Analytics 4 (GA4) is engagement rate. The percentage of sessions in which a user interacts with the website or app is measured as the engagement rate. Clicks, scrolling, and video views are examples of interactions. A high engagement rate implies that visitors actively engage with the website's or app's content and features.

The difference between these two metrics reflects a shift in how user engagement is defined and measured in GA4. Rather than simply measuring the absence of interaction (as in bounce rate), GA4 focuses on measuring the presence of engagement through a wider range of user interactions, which provides a more comprehensive view of user engagement and allows businesses to better understand how users are interacting with their website or app. It's a huge improvement for content marketing as with GA4, if the user reads the blog and doesn't make an action it's considered a bounce, but in reality, it's an engagement session. Now with the default scroll-depth event, it will be considered an engagement session.

Cross-device tracking։  Cross-device tracking in Universal Analytics (UA) is limited to separate data streams for different devices. This means that if a user accesses a website or app on multiple devices, such as a phone and a laptop, their activity is tracked separately on each device. UA can link these separate data streams together if the user is logged into the website or app on each device, or if they have previously provided identifying information such as an email address.

Google Analytics 4 (GA4) offers more advanced cross-device tracking capabilities. GA4 allows businesses to combine multiple data streams into a single property, which means that user activity across multiple devices is tracked together. This is made possible through a combination of advanced tracking techniques, including cross-device tracking through Google signals and the use of first-party cookies.

In B2B SaaS industry the decision-making is not impulsive. What we see from our clients is that user clicks- on 1-3 ads, and blogs from different devices, before signing up to test a platform or schedule a demo, so this is a huge improvement.

Data Storage: Universal Analytics (UA) allows businesses to choose their data storage period, with options ranging from 14 to 50 months. This means that user data is stored for a longer period of time, which can be useful for businesses that need to analyze historical data and trends.

Google Analytics 4 (GA4) has a default data retention period of just 2 months, with an option to extend it to 14 months (make sure you switched this metric to 14 months). This shorter data storage period is due to privacy concerns and the increasing focus on data protection regulations, such as GDPR (General Data Protection Regulation).

While a shorter data storage period may seem like a limitation, it can actually be beneficial for businesses in several ways. First, it helps to ensure compliance with data privacy regulations, as businesses are not holding onto user data for longer than necessary. Second, it encourages businesses to focus on more recent data and trends, which can be more relevant to their current goals and strategies. Finally, it can help to reduce storage costs and optimize performance, as less data is being stored and processed.

Reports: Universal Analytics (UA) provides a lot of pre-defined reports that are organized into categories such as Audience, Acquisition, Behavior, and Conversions. These reports are designed to provide businesses with a broad overview of their website or app performance and allow them to quickly access commonly used metrics and dimensions.

Google Analytics 4 (GA4), on the other hand, features fewer pre-defined reports but provides more flexibility with its "Explore" area. This section enables businesses to generate custom reports and dashboards by selecting the dimensions and metrics to be analyzed, as well as applying various filters and segments. GA4 also features a number of AI-powered insights that can give businesses valuable data-driven recommendations.

While UA's pre-defined reports are useful for quickly accessing commonly used metrics and dimensions, they can also be limiting in terms of customization and flexibility. GA4's Explore section, in contrast, enables businesses to produce more customized reports and obtain deeper insights into their data, which can be very valuable for businesses that want to track certain goals or metrics. In the B2B SaaS mostly used are funnel and user path reports, so make sure you track unique events and page views to see the insightful report.

Audience creation: Universal Analytics audience creation is based on predefined segments such as demographics, technology, and behavior. These segments are limited in number and cannot be easily modified or customized. However, they can still provide valuable insights into audience behavior and help optimize marketing campaigns.

GA4 offers greater flexibility and customization options for audience creation. It enables users to build audiences based on a variety of criteria such as events, user characteristics, and custom dimensions. Businesses can develop more focused audiences and acquire deeper insights into audience behavior with this level of customization.