Welcome back! In our last lesson, we unpacked the fundamental data model of Google Analytics 4, learning about the hierarchy of users, sessions, and events. You now have a solid grasp of how GA4 collects raw data about member interactions.
Today, we'll explore how that raw data is transformed into the tables and charts you see in reports. This brings us to two of the most essential concepts in all of analytics: dimensions and metrics. Understanding the difference between them is the key to unlocking any report, in GA4 or elsewhere. By the end of this lesson, you will be able to clearly distinguish dimensions from metrics and understand how they work together to provide insights.
What, Who, and Where vs. How Many, How Much, and How Long
At its core, every data report answers two types of questions.
- "What?" questions about categories and attributes: What page are they on? Who are they (e.g., what country are they from)? Where did they come from?
- "How many?" questions about quantities: How many times did this happen? How much time did they spend? How many users were there?
In Google Analytics, the descriptive attributes are called dimensions, and the quantitative measurements are called metrics. Let's watch a short video from Google's Analytics Academy that explains this core distinction.
1.8 How dimensions and metrics power your reports - Analytics Academy on Skillshop
This video provides a concise and clear explanation of how dimensions and metrics are the foundation of GA4 reports.
Please watch the entire video. Pay close attention to the simple definitions it provides for each term starting around the definitions, and the examples it gives (Event Name vs. Event count).
As the video explained, dimensions and metrics are the two non-negotiable components of any report.
- A Dimension is an attribute of your data. It describes the data and is usually text-based. Examples include
City,Page title, orSession source. - A Metric is a quantitative measurement. It's always a number, like a count, average, or percentage. Examples include
Active users,Average engagement time, orEvent count.
One of the simplest ways to tell them apart is to ask: can I do math with it? You can calculate the average of Average engagement time. You cannot calculate the average of City.
Putting Dimensions and Metrics to Work
Looking at a metric by itself is rarely useful. If I tell you "we had 5,000 users yesterday," what does that tell you? Not much. It lacks context. But if I say, "here are our 5,000 users broken down by country," that's a report.
Users is the metric. Country is the dimension.
A dimension gives a metric its meaning by slicing it into comparable groups. Let's dig deeper into this relationship with a helpful article.
Metrics and Dimensions: A Guide for GA4 Newbies
This blog post from DashThis provides a very clear breakdown of the two concepts with practical examples.
Please read the first main section, titled "Metrics vs. Dimensions: Key Differences." Focus on the clear definitions and the "HOW TO RECOGNIZE THEM" tips. Read from the start of that section down to the end of the "How metrics and dimensions work together" subsection. Pay special attention to the example of analyzing the 15,000 site visitors; it's an excellent illustration of why you need both dimensions and metrics. You can read from the start of the definitions to the end of the first example.
As the article makes clear, dimensions provide the context for metrics. The metric tells you what happened; the dimension tells you where, how, or to whom it happened.
In any standard GA4 report, you'll see this pairing in action. Reports are fundamentally just tables where dimensions are the rows and metrics are the columns.
For our fictional community, a basic acquisition report might look like this:
| Dimension: Session source | Metric: Active users | Metric: Engaged sessions |
|---|---|---|
| 2,450 | 1,832 | |
| twitter.com | 1,102 | 645 |
| (direct) | 856 | 701 |
| news.ycombinator.com | 321 | 299 |
Here, the dimension Session source gives us the context we need to interpret the metrics Active users and Engaged sessions. We can now see not just how many users we had, but where they came from.
Scopes: Linking Dimensions and Metrics to Your Data Model
In our last lesson, we talked about users, sessions, and events. GA4 organizes many of its dimensions and metrics around these same concepts, which analytics professionals call "scope."
- User-scoped dimensions describe the user (e.g.,
Country,Age,Language). - Session-scoped dimensions describe a single visit (e.g.,
Session source/medium,Landing page). - Event-scoped dimensions describe a specific interaction (e.g.,
Event name,Page title).
The same applies to metrics. Active users is a user-scoped metric. Session conversion rate is a session-scoped metric. Event count is an event-scoped metric.
Let's briefly look at some common examples to make this tangible.
Metrics and Dimensions: A Guide for GA4 Newbies
The same article we just looked at has excellent lists of common dimensions and metrics.
You don't need to memorize these lists. Instead, quickly scan the sections "Common Metrics in GA4" and "Common Dimensions in GA4." As you read, notice how the items are grouped by scope (User, Session, Event, etc.). This will help you connect today's lesson back to our previous discussion on the GA4 data model.
A Quick Note on Customization
While Google provides hundreds of default dimensions and metrics, you'll eventually want to track things that are specific to your community. For example, you might want to track a user's membership level ("Free," "Pro," "Founder") or the number of comments they've posted.
To do this, GA4 allows you to create custom dimensions and custom metrics. We'll cover how to do this in a later module, but for now, it's important to know that they follow the exact same logic.
[GA4] About custom dimensions and metrics - Analytics Help
This is the official Google documentation on the topic. We're just going to look at the high-level summary.
Please read the short paragraph under the "How it works" heading. Focus on this key sentence that summarizes the purpose of custom dimensions and metrics.
The key takeaway is that even when you create your own tracking, the principle remains the same: you use custom dimensions for descriptive, text-based data (like membership level) and custom metrics for numerical data you want to count or average (like comment count).
Conclusion
Today we've established a critical distinction that applies to all analytics reporting. Let's recap the key points:
- Metrics are quantitative measurements—they are always numbers. They tell you "how many" or "how much."
- Dimensions are qualitative attributes—they are usually text. They provide context and answer "who," "what," or "where."
- Every report in Google Analytics is built by combining metrics with one or more dimensions. A metric without a dimension is just a number without context.
You now understand how the raw data of users, sessions, and events gets organized into the rows and columns of a report.
In our next lesson, we will zoom in on the event itself. We'll examine how an event's name and its associated "parameters" are the raw ingredients that GA4 uses to populate the very dimensions and metrics we discussed today.