GA is a popular solution for data collection and traffic analysis in e-commerce. However, it was built before mobile devices played a significant part in e-commerce. For this reason, the long-standing version of Universal Analytics has ceased to adapt to the changes in the manner of conducting consumer contacts electronically with e-businesses.
As a result of rising customer knowledge, internet buying trends have for some time established a pattern of multiple cross-platform encounters. This3++indicates that visitors visit the website multiple times while making decisions and becoming accustomed to the options. Mobile devices and PC browsers are supported. Sometimes the final conversion occurs after weeks or months have passed after the initial visit.
The natural progression of events for an online business owner is to optimise the store for both large and small screens. While technically the mobile layer of e-commerce is evolving rapidly, it has not yet been able to aggregate data from all devices in a single Google Analytics service. This eventually made the analyst problematic.
Google Analytics 4 reflects Google’s understanding of these changes and the needs of e-business owners. With the statement that this version will become the standard in the future. The previous version of the service will only process data through July 1, 2023. (paid version 360 – until October 1). Google developers will consequently substantially invest in GA4 as a service.
In beta, the new analytics module in Google Analytics was formerly known as App + Web. The standard of tracking all communication channels in a single panel is expected to provide a fresh view on statistics now that it is officially available.
Google Analytics 4 keeps data for 14 months, therefore it is worthwhile to deploy it as soon as feasible to remain ahead of the competition this year and to have comparable information as soon as possible next year.
What differs between Google Analytics 4 and Google Universal Analytics?
The password for the updated version of Google Analytics is Events.
Sessions have been replaced with user events as a benchmark. There are numerous types of event tracking. Depending on the business strategy, it may consist of app launches, purchases, and micro conversions of all types.
With Google Analytics 4, you may more precisely measure data from the browser and mobile channel, enabling you to analyse the effectiveness of interactions without dividing the analytics into Google Firebase and Universal Analytics (session-based measurement) (measurement based on events).
The event, or user engagement, signifies that user engagement data is gathered during the entirety of the interaction when the page or screen is in the foreground. Each first page or screen presentation is bypassed, but the session without user interaction is also logged.
When data from the mobile and online channels are collected in relation to events, it is simpler to construct an accurate consumer profile and comprehend their journey. Observe which device the purchasing procedure begins and concludes on, as well as what occurs in between.
- Which pages does he visit?
- What is he doing on them?
- Does it enlarge photos?
- Does it play videos with presentations?
- Does it scroll information?
- Does it use tabs to get to know the product more closely?
- Will it go through micro conversion processes?
With this information gathered from all devices in a single location, UX optimization is facilitated by a deeper understanding of user decisions. Then, each repetitive behaviour can be wrapped in the optimal arrangement of a certain interaction stage.
GA4 vs GUA: the most important changes and differences.
|Google Analytics 4||Google Universal Analytics|
|Measuring the entire relationship in the form of events that are stages of the sales funnel.||Measure interactions in the form of sessions|
|Counting for converting events on Youtube||X|
|Parallel tracking of events from mobile applications and the browser||Browser data only|
|Analysis cube for everyone||Only in the paid version 360|
|Automated marketing lists powered by machine learning||Marketing lists created by hand|
|Event tracking and customization in the GUI||Edits or gtag.js required for tracking|
|Integration of URLs in the form of consistent titles of subpages and screens||The displayed URL and URI may differ depending on the device|
|Data gaps filled with AI||X|
|Functionality without cookies||X|
|Built-in IP anonymization||X|
|Support in compliance with GDPR: option to request deletion of data from Google||X|
The importance of artificial intelligence in Google Analytics 4 is significant. It enables the creation of measures that forecast future user events – “predictive metrics.” Accounts with a substantial database of collected information, as identified by the “Insights” feature, can provide forecasts. These accounts are identified as having conversion potential within the following week. They are added to marketing lists for which customised campaigns are developed. This makes it easier to undertake relationship-based marketing (LTV).
How do you integrate GA4 with Google Tag Manager?
The ability to add tracking tags to Google Analytics without the assistance of the IT department or third-party intervention garnered GTM a large number of fans. Will it also support Google Analytics 4 implementation?
The user is unable to move from Universal Analytics to GA4 as a result of the introduction of the new data gathering model. This first makes the task difficult. You must develop a brand-new service and collect data from begin. As compensation, another useful feature can be mentioned: both the implementation of GA 4 and the collecting of measurements occur without altering the tags in GTM.
Google Analytics 4 can be implemented and configured in steps that do not conflict with the existing Google Universal Analytics service. Notably, the new service will be easier to handle in the future if we select individual names using a consistent key.
Moving on to the steps:
- Creating a new service in the administration panel requires the following fields: name, country (target time zone), and currency, followed by corporate information.
- Creation of data streams for all customer-accessible digital products: website and mobile applications as desired (advanced metering: enabled) – Consideration should be given to the regulations protecting against measurement disturbances caused by internal traffic. To accomplish this, we add the IP addresses of administrators to the tag configuration option (additional tagging options > defining internal traffic).
– In the same tab, there is one more significant option. List of undesirable referrer sites In this section, we include all parties who are not directly involved in the client-business interaction. Therefore, email, own URL, and payment processors.
- Summary window. It is essential to copy the measurement ID or remember its location, since it will be necessary for future configuration. – The Add new tag option displays the copyable content. It should be inserted to the page as early as feasible in the <head> section so that the tag loads early. The implementation of tags varies based on the CMS employed. When adding it manually, the situation becomes more difficult. Interfering directly with the website’s code can be risky.
– At this time, Google Tag Manager is preferable to the alternatives listed above.
- Account – Container – A new tag is being created.
- Select GA4 configuration for tag configuration
- Paste the measurement ID
- Rule: All pages
- After saving, it is prudent to examine the preview.
- Upload – Publish the container
Following this operation, the tag will be visible in the workspace.
You may also utilise a related site tag. Option provided in the summary window as well. Simply paste the Google Analytics tag ID into the pop-up window.
This is how Google Analytics 4 would ideally be setup. Google Tag Manager is a fundamental tool that, in most circumstances, is as easy to use as reading the preceding list. However, each site is unique and the issue may be more difficult.
What potential issues could come from the implementation of GA4?
Occasionally, it will be essential to modify the page’s source code or integrate other solutions, such as in the field of User Experience.
First, it is necessary to accurately update the dataLayer. It requires the addition of new parameters, events, and rules introduced in Google Analytics 4. The provided data is dependent on the accuracy of the data layer’s update – and, subsequently, the value of the overall analytics. The Google Tag Manager, which receives and maps the data, also performs this function.
In these or similar circumstances, it is prudent to entrust the implementation of GA4 to professionals who have dealt with several non-standard scenarios, are familiar with their dependencies, and are able to quickly and risk-free navigate among them. Together with developers who are familiar with the website, the agency with expertise of Google Analytics 4 will handle it most efficiently.
Ecommerce: What Data to Collect in GA4?
In GA4, metrics are dimensions and metrics for user-generated event parameters. There is a database of default metrics to which you can add your own. (I am confused as to what means originally so this needs to be edited)
User dimensions include the following:
- Device brand
- Device category
- The version of the operating system
- Platform used
Geographic data is collected approximately, based on your IP address.
Additionally, the application recognises its version, the shop from which it originated, and the device model on which it is launched. Each instance of a programme is provided its unique ID. The user is then identified as either new or returning. Seven days after the last login, it also lands in the first category.
In the case of a website, only browser-related information is gathered in addition to the aforementioned.
What conclusions can be drawn from the individual metrics for e-commerce?
- Micro- and macro-conversion ratio – the precision of the offer’s targeting and the purchase effectiveness of the gained traffic.
- Effectiveness of promotional efforts, configurators, upselling, and cross-selling on the average order value.
- Customer value across the full conversion phase – marketing initiatives’ return on investment
- Unique visitors – The proportion of site visitors who are accessing the offer for the first time.
- Returning clients – the efficacy of loyalty programmes, email marketing, and discount promotions.
- The buying patterns of dominant gadgets.
- Entry pages – efficacy of partner pages, Google advertisements, SEO position in terms of individual phrases, and visibility of current demand in Google searches.
- Exit pages are weak places in the UI, user experience, purchasing process, and CTA button effectiveness.
- Bounce rate – the precision of the offer targeting and the performance of the landing page.
- Cart abandonment rate – sales process efficacy.
- E-mail marketing: opt-ins, ECR, EOR, CTR – the message’s attractiveness at various contact phases, from the incentive to subscribe to the newsletter through the CTA in the email.
- Performance marketing: ROAS, CPC – campaign profitability and effectiveness.
In addition, each of the metrics makes it easier to recognize the areas where you need to work on the UX layer.
What data should be collected from the web application using Google Analytics 4?
Thanks to Google Analytics 4, SaaS KPIs can be measured in the following ranges:
- Monthly Recurring Revenue (MRR) – The fundamental metric of the subscription system’s health.
- Annual Recurring Revenue (ARR) – considering statistics of new, expired, extended, decreased, and renewed subscriptions following the cancellation period.
- Revenue churn rate – enables you to see the impact of people abandoning your service.
- Customer churn / churn rates Is a marketing metric.
- Gross margin – the value remaining after acquiring, servicing, and sustaining a customer.
What data should I collect from the landing page using Google Analytics 4?
Lead optimization metrics depend on the funnel. It can be built from one landing page or from several. Events will always be the most important thing to measure. And their parameters, such as:
- Sources and media of traffic – suggestions on efficacy and where to optimise.
- Utilizing device usage statistics to optimise the length of content.
- Page scroll depth – describes how the interaction with the message develops and where it ends.
- Demographic data enable you to optimise content, select traffic sources, and alter the nature of your campaign.
- Conversion Rate – Evaluates the effectiveness of the page and its call-to-actions (CTAs) in generating conversions.
- Time Spent on Page Average – Indicates how quickly the text is consumable. The shorter the duration, the better.
- Form abandonment rate – Indicates the proportion of visitors that decide not to complete the form. Perhaps the layout is illegible, the CTA button is not prominent enough, or the page requires an excessive amount of information.
With the help of Google Analytics 4, it is possible to analyse the weak points of LP much faster and better match its content to the behaviour that can be seen in the statistics without building assumptions.
There are more and more reasons for implementing Google Analytics 4. If the mobile version of your product has started to match the traditional one and you appreciate the support of artificial intelligence in e-business, you have long understood the potential of machine learning-supported collecting data on user behaviour from the mobile and WEB area in one dashboard.
- The bad news is that others have been waiting for this for years as well. Some have the service implemented a long time ago, others are just starting to collect data in GA4.
- The good news is that most companies usually wait for the old service to close before learning the new one for good and for all. You can overtake these.
- Bonus good news: If you have experience with Google Analytics for Firebase, GA 4 onboarding can turn out to be much faster.
However, the race against the competition is simply one of the reasons for beginning the implementation immediately. Google Analytics 4 will transform the way you think about consumers, regardless of whether your business is focused on the construction of a website, application, service, store, or SaaS service. The reports will detail their online decisions and actions in greater detail. AI is dedicated to enhancing the worth of client interactions. Intelligent algorithms will learn to recognise user behaviour and anticipate their future actions with increasing accuracy. Thus, the new GA version will combat John Wanamaker’s statement that “half of advertising expenditures are wasted.”
Regardless of the pace of implementation, familiarisation with the interface, and capabilities of the new service, the ideal strategy appears to be keeping both GUA and GA4 concurrently until the second tool collects sufficient data to assume the function of a comprehensive analytics centre.