Getting Started with Google Analytics

Getting Started with Google Analytics is a free, self-paced introduction to Google Analytics 4 for people who work with an online shop. In ten hours and four modules, you learn how measurement works, where to find useful reports, and how to interpret shop data without drawing conclusions that the data cannot support.

Getting Started with Google Analytics at a glance

• Format: Self-paced, 4 modules
• Level: Basics
• Participants: unlimited
• Language: English
• Certificate: AEI certificate of attendance
• Investment: free of charge

What you take away

You gain a working orientation in Google Analytics 4. The course explains the basic logic behind measurement, including what happens when a person opens a shop, views a product, adds an item to the basket, returns later, or completes a purchase. You learn why a number in a report is never just a number, and why the way data is collected affects the questions you can answer.

You also learn how to read the interface with a practical shop perspective. You will be able to locate relevant reports, distinguish events from older page-view thinking, create useful segments, and follow the route from a first visit to a purchase. The focus is not on collecting every available metric. It is on selecting information that can help you understand a concrete situation, such as a change in sales, a weak product page, or a high number of visits without corresponding orders.

Your learning objectives

• You can describe what a session means in GA4 and explain why it is not the same as a person, an order, or a single page view.
• You can identify common data sources in an online shop and recognise limits caused by setup, consent, attribution, or incomplete tracking.
• You can find your way around the GA4 interface and explain the role of events, dimensions, metrics, reports, and segments.
• You can use shop-relevant reports to examine revenue, the path to purchase, and indications of repeat buying.
• You can compare figures in a way that takes period, audience, channel, device, and measurement conditions into account.
• You can turn a report into a careful next step without treating a correlation as proof or a single figure as a complete explanation.

The levers at a glance

Measurement context: Before reading a chart, you need to know what was measured and how. A session is a period of activity, not a guaranteed visit by one identifiable person. Data may come from a website, an app, or connected shop systems, and each source has its own conditions. Consent choices, tagging errors, blocked tools, payment-provider changes, and missing events can all affect what appears in a report. The course therefore starts with the measurement conditions rather than treating the interface as a neutral mirror of reality.

Event quality: GA4 is built around events such as viewing a product, selecting a variation, adding an item to the basket, beginning checkout, or completing a purchase. These events need clear names, useful parameters, and a consistent setup if they are to support decisions. A shop may see many product views but still lack reliable information about product selection or checkout completion. You learn to ask whether the event represents a meaningful action, whether it is recorded consistently, and whether its details are sufficient for the question at hand.

Audience comparison: A total shop figure can hide important differences. Visitors from a product search may behave differently from visitors arriving through an email, and mobile users may encounter different issues from desktop users. Segments help you separate such groups, but they also make small samples easier to misread. The course shows how to create comparisons with a clear purpose and how to avoid changing several conditions at once until the result no longer has a clear meaning.

Purchase path: Revenue is the result of a sequence, not an isolated starting point. A useful review can connect acquisition, landing pages, product views, basket actions, checkout steps, and completed purchases. This does not mean that every customer follows one fixed route. It means that the available events can help you locate where a process appears to lose people and which parts of the route deserve a closer look in the shop itself.

Decision discipline: Analytics can indicate where to investigate, but it does not automatically explain why a result occurred. A drop in orders may relate to traffic quality, stock availability, prices, delivery terms, technical problems, or a change in tracking. You practise moving from report to question, from question to check, and from check to a proportionate action. This keeps interpretation connected to the actual shop situation rather than to a dashboard alone.

Who is this course for?

This course is for shop owners, e-commerce teams, content and marketing staff, and people who support online sales and need a sound introduction to GA4. It is suitable if you have access to shop data or regularly discuss traffic, products, conversion, or revenue with colleagues. You do not need to be a measurement specialist. A basic understanding of how an online shop works is helpful because the examples use situations such as product views, basket actions, checkout steps, returning customers, and sales by channel.

It is not for people looking for advanced implementation training, detailed tag-management instructions, complex reporting architecture, or specialist analysis of large-scale data environments. It is also not a substitute for legal advice on privacy or consent, for a technical audit of a GA4 setup, or for a complete e-commerce strategy. If you already configure tracking professionally and work daily with advanced explorations, custom data models, or automated analytics pipelines, the basics covered here may not be the right starting point.

Cost and access

The course is free of charge. Sign-up takes place through the shop, and access is available immediately after registration. There is no fixed start date, and you do not need to wait for a scheduled group or live session.

You work through the material at your own pace within the self-paced format. The planned scope is ten hours across four modules, but you can pause between lessons and return to topics when a question arises in your own shop. The format allows you to spend more time on a report or concept that is new to you and to move more quickly through material you already understand.

After the course

A sensible next step is to apply the method to one specific shop question. For example, review the path from a selected landing page to a completed order, check whether the relevant events are present, and note which parts of the interpretation depend on assumptions. Keep the first review narrow enough that you can verify the result against the shop, such as stock levels, campaign timing, checkout behaviour, or a recent change to the website.

Once the basic questions are clear, you can decide whether further work is needed on the measurement setup, consent handling, report structure, or a particular business question. The course is intended to give you a reliable starting point for that work, not to replace the checks and discussions that follow from a real shop situation.

Programme: 4 modules

• Module 1: Understanding measurement — What a session is; Data sources and their limits; Setup and privacy
• Module 2: Reading the interface — How GA4 is built; Events instead of page views; Building segments
• Module 3: Reports for a shop — Where the revenue comes from; The path to purchase; Recognising repeat buyers
• Module 4: Interpreting numbers correctly — What bounces do not mean; Comparisons that hold; From report to decision

Our approach

We work from practical questions rather than from a list of interface features. Each topic connects the measurement concept with a recognisable shop situation and then separates what the data can show from what still needs to be checked elsewhere. The institute uses clear language, explains terms before relying on them, and treats privacy, data quality, and uncertainty as part of competent analytics work. This approach helps you build a usable foundation: understand the setup, read the report, question the result, and choose the next step with care.