A Guide to Google Analytics 4 (GA4)

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A Guide to Google Analytics 4 (GA4)

Today’s marketer faces some unique challenges. Privacy laws make it harder to analyze customer data. Additionally, the landscape of channels users utilize increases the scope of data needing to be assessed. On the positive side, the increase in digital media provides more information for evaluation.

Fortunately, Google Analytics 4 (GA4) has come to the rescue with a new platform that is created to handle the types of data being generated and obtain meaningful information from these sources. This platform is currently running in tandem with Universal Analytics. Users have until July 2023 or October 2023 to make the move from Universal Analytics to Google Analytics 4. In the interim, dual data tracking can be used to confirm conclusions.

Benefits of Google Analytics 4

The most exciting benefit of Google Analytics 4 is its contribution to return on investment (ROI). It can recognize consumer segments that are primed to convert to sales. This is due to its modelling abilities that are underpinned by artificial intelligence, machine learning and tailored algorithms.

Whether consumers access products and services through the web or on their mobile devices, Google Analytics 4 collects and analyzes both sets of data. Furthermore, it can integrate its findings to provide a holistic picture of consumer behavior.

With the loss of cookies on the horizon, marketers face a new challenge in gaining insight into consumer intent and actions. This step towards better protection of privacy rights was planned initially for 2020 but has shifted to 2023. Google Analytics 4 is designed to work in a cookie-less environment.

A Change in Approach to Data Collection

Prior analysis of consumer data collected information based on user sessions in a specified period of time, thus pooling the data. Google Analytics 4 assesses data differently, making use of events. Thus, each user interaction is viewed as a standalone happening.

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By activating Google Signals, the marketer is not reliant on cookies. Where users have given permission for ‘ads personalization’, advertisements can be provided in prepared marketing campaigns for specific products.

Google Analytics also provides Google Analytics 4 free properties, for example, BigQuery. Data sources can be connected to a destination, such as the dashboard, then analyzed as desired. Many of these features were only accessible by marketers using Analytics 360 in the past.

A Comparison of Universal Analytics and Google Analytics 4

As a legacy system, Universal Analytics relied on data sourced via laptops and/or desktops. Google Analytics 4 required a complete reconstruction of the platform to account for data from mobile smartphones, tablets, and mobile app tracking. Universal Analytics was based on a hierarchy that looked at labels, actions, and category names for a review of events (e.g., clicking on a button or playing a video) or viewing of website pages. The available parameters have opened up to beyond the simple label, action, and category names classifications.

Instead of a hierarchy of events or pages accessed, Google Analytics 4 has a flat structure. Regardless of the number of events attributed to a user, all digital activities can be tracked. This is irrespective of whether it is a mobile application or a web page.

This provides the marketer with consistent data capture for any data type that can be collected. It therefore offers greater flexibility to assess events. The marketer can determine the amount of detail to work with.

Dealing with the General Data Protection Regulation (GDPR) of 2018

The General Data Protection Regulation (GDPR) of 2018 was designed to give force to the individual’s right to privacy and requires the consent of consumers to store and process personal information. This has placed an obstacle in the way of marketers and led to a cookie-less landscape which hampers the analysis of data for targeted product and service advertisements. Google Analytics 4 has enshrined the privacy rights of individuals in its platform while providing the most comprehensive data analysis, given this restraint. It has accomplished this with its Consent Mode and Data Modeling.

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Consent Mode tracks the type of consent given, for example, that the user has agreed to personal information being stored and used for sending advertisements or for analysis purposes. This aspect ensures that all data that can be stored and analyzed is collected. It also differentiates between a permission given and a permission denied choice from the consumer. This protects marketers by making sure that they do not inadvertently or deliberately retain personal identifying information (PII) of users who have opted out.

Data Modeling fills in the gap in data caused by adherence to the GDPR. Machine learning takes up this slack by its direct observation and analysis of data that can be collected and stored. Thus, marketers do not come away empty-handed.

Identity Management with Google Analytics 4

The identity management aspect of Universal Analytics ensured that Google tracked users and collated their searches and online behavior via the allocation of a ‘Client ID’ that worked across browsers and sessions. This is despite marketers losing the ability to use their own identity tracking without cookies, as legislated to user consent only by the GDPR, to retain the information. The latter makes it difficult for marketers to distinguish between new and existing visitors to their sites.

However, Google Analytics 4 has added Google Signals, which retains data on individuals through the ‘Client ID’ but presents it to marketers without personal identifiers. This increases the accuracy of data that marketers need to rely on, not being able to use their own means of user identification, by, for example, removing duplications.

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Reporting and Analysis Tools

Marketers can access four sets of analysis: reports, explore, advertising, and configure. The first, Reports, supplies four sets of reports: Engagement, Acquisition, Retention, and Monetization. The Explore interface allows the marketer to build custom reports and select how data is displayed. Advertising gives marketers unique insights into how users behave and are converted to sales, allowing for strategic planning of campaigns. Finally, Configure gives the marketer options for desired settings around custom dimensions and events. The marketer can view data according to demographics, a Tech Overview split by types of operating systems, platforms, device used, or other qualifiers.

Marketers can get ahead of the game by running Google Analytics 4 parallel to Universal Analytics. While the former undergoes continued developments, they can get a head start on gaining familiarity with the new platform. They will also be able to assess how Google Analytics 4 advances the capabilities of Universal Analytics.