Decoding Google Analytics Basics with a Real-Life Scenario
Google Analytics is a vital digital marketing tool but seriously underused by most businesses. It allows you to measure the results of individual campaigns in real-time, compare the data to previous periods, and so much more.
Terms like sessions, page views, filters, and segments have all been used by web analytics tools in the past, but Google Analytics was the first to combine them into a powerful free tool. On the one hand, this is wonderful- you can write complex queries, create custom reports, and set goals after a quick 15-minute setup process.
But on the other hand, it creates a significant barrier to entry- you must learn how all these new concepts work together so you can understand your data. After thinking about these concepts for a few hours, I realized these Google Analytics concepts were similar to the organization of a shopping mall! So, if you have ever visited a shopping mall, you can understand the basics of Google Analytics.
I will explain a few of the terms from the perspective of a shopping mall visitor, and other ones from the perspective of a shopping mall manager – the person who is in charge of making sure that people make purchases at the mall. First, we will cover some standard metrics and dimensions and then get into the different ways to organize your data.
What’s the different between Metrics vs Dimensions:
Let’s say that 25 people enter your mall over the course of one day. Maybe on Monday morning.
This is a metric combined with a date range. A metric is a quantitative measurement of some activity on your site. This example is similar to the Google Analytics concept of “Users”- how many people enter your site in one day. This doesn’t tell us very much, however.
Not all website visitors are equally valuable- you will need to look closer at your data to find the visitors who are serious about buying. Let’s say you learn that people with suitcases or other baggage have a lot of money. You want to analyze the activity of just the people holding baggage.
That is a metric that is combined with a dimension. The metric is all visitors to the mall over the course of one day. The dimension is “baggage carriers” (I made that up). So, you could run a report on just the baggage carriers to see how they behaved within your mall- how many shops they visited, how much they purchased, etc.
Google Analytics has hundreds of dimensions, so I can’t summarize all of them. Here are a couple of ideas:
- What are the activities of the people that enter the mall after work? (Hourly dimension)
- How does the first store affect the rest of the visitor’s trip to the mall? (Landing page dimension)B
- What are the most popular stores, based on purchase totals? (Page dimension)
Difference between Users – Sessions – Pageviews:
Users, sessions, and pageviews are three ways of measuring your website’s ability to acquire traffic. Here’s how they work together in the context of a mall.
Let’s say that your local mall is called “The Main Street Mall”. Like any mall, it has 10 different types of stores, so there are always multiple reasons to make a trip to the mall. Within each trip, you don’t visit the mall for just one store- you want to check out a few of them.
We have three levels of organization:
- Individual people
- A trip to the mall
- Stores that you visit within each trip
Google Analytics (GA) has the same structure. Users are individual people that visit your site. GA determines this via a browser cookie- a tracking ID based on the browser from the user’s computer.
An individual user can have multiple sessions- he or she can visit your domain multiple times over the course of weeks or months. A session is a visit to the domain as a whole, like https://satheeshkchinnappan.com.
Within that session, a user can visit multiple pages, like /blog, /author and /pricing. Those count as pageviews. A session has one or more page views.
Google Analytics also tracks the order of the pages within the session. This introduces the concept of a landing page– the first page that a user visits within the session.
Think about the times that you visit a mall. You usually enter one store in particular, like a department store. So, if you were a mall manager, you would probably want to know whether mall visitors continued on to other stores in the mall, or left after finding what they wanted in that store.
Session Duration v. Time on Page Explained
We just covered a few acquisition metrics. Now let’s get into behavior metrics- what users actually do on your site. One common way to measure the quality of your content is via time spent on site. Once users reach your site, do they actually read or watch what is on the page? Or do they leave immediately? If a user spends more time on page, it is more likely that they will take a key action, like sign up for your newsletter or buy a product.
A mall has the same goal. The longer that a visitor spends in a mall, the more likely that they will buy more stuff. (I’m assuming that most mall visitors don’t just go to hang out.) Google Analytics has two metrics to measure this behavior- session duration and time on page.
Here’s one important note- Google Analytics has no way to count minutes and seconds for the last page visited within the session. Google Analytics uses timestamps that fire when a user opens a new page within your domain, so on the last page of the session, the timestamp will count 0 seconds.
Time on Page looks at the time spent on an individual page. When calculating the average time on page, we remove all the people that exited the page so that we do not skew the number.
This is like looking at the time that somebody spent in an individual store before moving on to the next store. All people that left the mall from that store are not counted.
Avg Time on Page = Time on Page / ( Pageviews – Exits)
Session Duration looks at the total time spent across the entire session. It includes exits on the last page, so it is considered a less reliable metric since the last page will always have a value of 0.