Google Analytics for Beginners: an (almost) illustrated guide — Review
This is the part 4/12 in my series reviewing the Conversion Optimization Minidegree, provided by CXL Institute.
Since the beginning of September, I have received the amazing opportunity to access the Conversion Rate Optimization Minidegree.
Last week, I deep dived into Google Analytics with Chris Mercer, instructor of the “Google Analytics for Beginners” course. Here is a brief summary with the main lessons!
First things first: what is Google Analytics?
Collecting and analyzing data is essential for making assertive and profitable marketing decisions. This is why Google Analytics, the most popular digital analytics tool in the world, can be a great ally for those who want to start focusing on the right stuff and allocate marketing resources wisely.
If it is used and configured in the right way, you’ll be able to measure what really matters, understand your users’ behavior and answer specific business questions.
According to Chris Mercer, the platform has basically three different functions: collect data, store data and generate reports. Despite having the ability to perform all three functions, the main highlight of the tool is data storage. In order to perform the collection and to generate reports, it is preferable to use two other Google tools: Google Tag Manager and Google Data Studio, respectively.
Understanding Google Analytics’ structure
It’s time to understand the structure behind Google Analytics and familiarize yourself with three main terms: accounts, properties, and views.
The account is at the highest level of the hierarchy and it is through it that you access Google Analytics. As the owner of your Google Analytics account, you can manage users, create goals, access all reports, and configure all necessary settings. Each account can have up to 50 properties.
Properties are linked to accounts and are responsible for storing the data. Creating them most appropriately requires a prior analysis of your business and strategy.
Suppose you produce content for a website called “mysite.com” and that some of your posts point to your store, “shop.mysite.com”. If you choose to place each of the domains under a different property, you will lose a lot of data and make your analyzes much more complicated, because you will need to migrate from one property to another to understand the interactions that took place in the other domain.
That’s why, according to Chris Mercer, it’s recommended that connected sites and subdomains be present in a single property. This is true even for domains used by email tools or webinar platforms.
To understand whether it makes sense to separate the domains into different properties, the guiding question is: “do users naturally go from one domain to another?”. If the answer is yes, it is preferable to keep the same property.
While properties store the data, Views determine the information that will be displayed and are used to answer specific questions about the data. They use the data that are in the properties but show it in different ways depending on the previous configuration adopted.
Each property can have up to 25 views. It is recommended that you have at least three: production view, test view, and backup view.
Do not worry. These concepts will become clearer in the practical part!
Getting to know Google Analytics: Demo Account
An excellent tip to get familiar with Google Analytics and start to understand how the main features work is using the Demo Account, an amazing free resource provided by Google.
All you have to do is click on this link. If you already have a Google account, you will have to log in to that account. If you don’t have one, you will need to create one and then log in.
This is how it looks like:
Now that you already have access to Google Analytics’ Demo Account, it is time to explore the main reports.
Report types available on Google Analytics
Google Analytics offers different types of reports, and each of them will be used to answer specific questions.
Overview: it is a general report that you will hardly spend much time on. Its function is to provide a general overview, but it is rarely used to answer more specific questions.
Table: one of the most common table formats in Google Analytics. Especially when associated with secondary dimensions and filters, they enable a good detailing of information.
Flow: this type of report is very good for understanding what is happening at each step of your funnel and for identifying the paths that the user is flowing. It’s a great ally to check if the user experience really matches what you imagined.
Funnel: the funnel report is very similar to the flow report. In the funnel report, however, it is easier to visualize what happens at each step of the funnel.
Map: as the name reveals, this report makes the information available in map format, being more used to answer questions involving places.
Features to know
Also, take advantage of the Demo Account to explore the platform’s features.
- Date range: by default, the data displayed in Google Analytics is from the previous 7 days. You can change this period and compare different date ranges by checking the “Compare to” option. Análises envolvendo o dia atual são desencorajadas, pois os dados coletados podem precisar de algum tempo para serem processados pelos servidores do Google e exibidos na plataforma.
- Segmentation: rather than displaying all of your data, you can use segmentation to display only certain segments of users. This functionality is very powerful and helps you to answer very specific questions.
- Custom dimensions for table report: dimensions are attributes of your data. The dimension Page, for example, indicates the URL of a page that is viewed. Google Analytics allows you to change the primary dimension displayed at the top of table reports and/or add a secondary dimension to your analysis.
Nice to know: According to Google, “each dimension and metric has a scope: user-level, session-level, or hit-level. In most cases, it only makes sense to combine dimensions and metrics that share the same scope”. You can find more information about dimensions at this link.
Exploring the reports for obtain specific answers
Now that you’re familiar with the features of the demo account, it’s time to understand what answers you can get using Google Analytics.
On the left side of the screen, you can see the 5 types of reports provided by the platform: Realtime, Audience, Acquisition, Behavior, and Conversions. Each of them has its limitations and sets out to answer a specific question.
Realtime report: is it working?
The Realtime report shows what is happening in real-time on your website. It is not used to do a more in-depth analysis, but rather to answer a key question: “Is it working?”.
It’s ideal for testing and verifying that your settings are working as you intended.
Good to know: “active users” shows who was on your site in the last 5 minutes. The “page views” field shows the pages that were visited in the last 30 minutes. A single active user can be responsible for multiple page views.
Audience reports: who are my users?
Audience Reports help you understand who your site’s users are. Some of the possibilities it allows are:
- Understand a user’s path within your site;
- Obtain gender and age data, including being able to use segments to separate users from buyers;
- Understand the interests (affinity) of people who visit your site or buy from you;
- Understand what other products your audience shows interest in buying;
- Get data about the type of device and operating system used by your audience etc.
Good to know: it is necessary to understand what Google Analytics understands as a “user”. Basically, the concept of a user is the client ID. If you visit a website that you have never been to before, Google Analytics realizes that you have no prior identification and assigns your access to a piece of code known as a cookie. In that cookie is your Client ID.
Technically, you might think that this client ID is unique to you as an individual, but the point is that the client ID changes from device to device. This means you can have one client ID for your cell phone, another client ID for your computer, and so on. So when you hear the term “user”, think of “client ID” and understand that a single person can have more than one user per account on multiple devices.
Acquisition reports: where are my users coming from?
The main function of Acquisition Reports is to help you understand where your visitors are coming from.
Most of the answers you are looking for are available in the source/medium report. It reveals:
- Where the visits are coming from;
- How is the volume of users (users, new users, and sessions)
- How is the user engagement (bounce rate, pages/session, and average session duration);
- What are the results generated (conversion rate, transactions, and revenue).
It is noteworthy that this report requires integration with Google Ads and Google Search Console and that the source of traffic needs to be well tagged.
Behavior reports: what actions are my users taking?
The behavior report helps us understand what actions are being taken by users within the site.
With it, you’ll understand which pages are being viewed first, which pages your users decide to leave your site on, and whether the user flow within your site is really making sense.
To understand behavior reporting, it’s important to understand what each metric means:
- Pageviews: shows how many times the page has been displayed in full. A pageview is counted every time the page loads, regardless of who loaded it.
- Unique pageviews: measures the amount of unique pages loaded. If a certain user entered the site and loaded the same page twice, Analytics will show 2 pageviews and 1 unique pageview.
- Avg. time on page: shows the average time spent on the page.
- Entrances: reveals how many times the page in question acted as the gateway to your site, being the first page visited by the user.
- Bounce rate: Shows the percentage of people who viewed the page left as a sign-in page and then left. In other words, it is a percentage of the value relative to the “Entrances” field.
- Exit rate: shows the percentage of people who viewed the page and then left. Unlike bounce rate, it considers the total traffic volume on the page.
- Page value: is the average value for a page that a user visited before landing on the goal page or completing an Ecommerce transaction (or both). You can see more here.
Good to know: Analytics cannot automatically track events. To better understand issues such as user behavior when filling out a form or watching a video, for example, it’s worth understanding how to make the necessary settings — even if using the Google Tag Manager.
Conversion reports: what are the results of my users’ actions?
Finally, conversion reports allow you to analyze and understand the results of actions your site users are taking. The reports are divided into three areas: goals, eCommerce, and multi-channel funnels.
Goals:
- Goals URLs (Conversions > Goals > Goals URLs): tells you what page the user was on when he completed a goal you predefined. If you have several blog articles leading the user to selling content, for example, you can see which articles generated the most sales.
- Reverse Goal Path (Conversions > Goals): this shows the path taken by the user before conversion.
- Funnel visualization (Conversions > Goals): this shows the funnel previously configured by you on the platform, making clear the conversion rate at each step.
- Goal flow (Conversions > Goals): just like the funnel, it needs to be previously configured in Google Analytics. It is meant to understand if the user’s journey on the site is going as expected.
Ecommerce:
- Shopping behavior and checkout behavior: require prior configuration. They clearly inform the steps of an e-commerce funnel.
- Product performance: shows the products that sell the most. With the secondary dimensions, it is possible to have really cool insights, like the source/medium that led to the sale.
Multi-channel funnels:
- Assisted conversions: shows the contribution that each source/medium had throughout the process, informing, for example, when the last click happened before the purchase. It helps to have a clearer sense of overlapping channels.
How to install Google Analytics on your website
Now that you know the main theoretical aspects of Google Analytics, it’s time to get started!
To install the tool on your website, login into your Google account and go to Google Analytics’s website. If you have never created a GA account, the following message will appear on your screen:
After pressing the button “Start measuring”, you will start filling in your account information.
In “Account setup”, fill in your account name (in this case, I’m creating a test account for the Minidegree) and uncheck any data sharing options that don’t make sense to you. Don’t worry! You will be able to change the information later.
In “Property setup”, fill in your property name (you’re going to change this later) and make sure that the time informed corresponds to the same time zone used by your site’s servers. Otherwise, it will affect your reports.
Important: This article explores the concepts and functionalities of Universal Analytics, a version before Google Analytics 4. To enable property in the old format, it is necessary to click on “Show advanced options” and check the option “Create an Universal Analytics property”.
In “About your business”, fill in the information relating to your business in a reliable way if you want Google to use this information for benchmarking purposes with other industries.
After completing this step, you will see on your screen how to install the code using one of two options: tag on the website or Google Tag Manager. It is highly recommended that you use Google Tag Manager. Here are instructions on how to install Universal Analytics with Tag Manager.
After that, you will be ready to start configuring each level: account, property and view.
Setting up your account
Now that Google Analytics is installed on your website, it’s time to configure your account, properties and views.
It is during this stage that many companies make mistakes and end up harming the collection, storage and analysis of their data, so pay careful attention to details.
Once logged in, you will see that the admin area is divided into three columns: account settings, property settings, and view settings.
Let’s start with the first column, marked in red. The goal is to understand what each field does and what aspects you need to be concerned about.
Account settings:
What you can do:
- Rename your account;
- Access the Account ID;
- Change the country of your business;
- Set up data sharing with Google;
- Move the account to the trash.
Important precautions and pro-tips:
- Before accepting any data-sharing policies, check with your organization if do you really have that power;
- If you need to delete an account, change the name (something like “To delete”) so that people understand that the act was intentional. This reassures users who have access to the account the moment they receive an email from Google informing them that the account has been moved to trash.
Account Access Management:
What you can do:
- Add users and group users to your account;
- Remove users and group users to your account;
- Edit permissions (what they can see).
Important precautions:
- In Google Analytics there is only one type of administrator. If you define that someone in your organization can manage users, they will have the same level of power as you and may even remove your account access. So be very careful when managing your permissions.
All Filters:
What you can do:
- See all filters applied to views;
- Add filters applicable to all views or just some of them;
- Remove filters.
Important precautions:
- Filters are one of the most powerful and risky functions of Google Analytics, as they permanently modify the data collected by the platform. Therefore, avoid applying filters to all views and always keep a backup account, with the data fully preserved. We’ll talk about filters and backup views later.
Account change history:
What you can do:
- See what changes have been made to your account;
- See who made each change.
Important precautions:
- Change History maintains a record of activities for the last two years.
Trash Can:
What you can do:
- View the history of what you deleted in the last 30 days, such as accounts, properties, and views.
Pro-tip:
- Before you delete your account, property, or view, rename it with a name that signalizes that you want to delete it. When you delete accounts, properties, or views, Google Analytics sends an e-mail to all users saying that it just moved to the Trash Can. If you don’t rename it, people will probably get scared.
- The information only remains in the trash for 30 days. If you need to recover any information, do so before this period.
Setting up your properties
Setting the properties requires a little more attention. It is the property, after all, that determines what data will be stored and displayed in reports.
To make setup easier, follow the steps below.
1. Create a new property and make the first a decoy property:
Malicious people often spam Google Analytics data. They take random numbers and simulate different Tracking IDs ending with the number 1, the default option. Because of this, it is a good practice to make the first property a decoy property and create a new one. To create a new property, just click on “+ Create property”. To differentiate the two properties, rename the older one with a name that makes it clear that it shouldn’t be used (“Decoy”, for example) and put a “1” in the beginning of the second one, so it will be displayed first. You will see that the Tracking ID of the second property will end with a number 2, making it more protected from spam.
2. In “Property Settings”, configure and enable the necessary fields:
You will need to change the time zone according to the time of your website servers, indicate your industry, and activate the options “Enable Demographics and Interest Reports” and “Enable Users Metric in Reporting”. Before enabling them, however, check the terms of use and see if you really have the necessary permission within your company.
3. If necessary, add users in the “Property Access Management” field:
This field works similarly to the account, already explained in this article. The difference is that the person has access to the property and not the account. If you feel the need, use this field to add users or user groups.
4. Under “Data Collection”, enable the “Remarketing” and “Advertising Reporting Features” fields:
By enabling these Advertising Features, you enable Google Analytics to collect data about your traffic in addition to data collected through a standard Google Analytics implementation. Before enabling Advertising Features, ensure that you review and adhere to the applicable policies.
5. In “Data retention”, define the retention time of your data:
The default option already suits most people. In most cases, you won’t need to make any changes.
6. Skip the “User-ID” option:
This option requires advanced configuration which will not be covered in this guide.
7. Set the duration of the session and campaigns in “Session settings”:
- Session timeout: this field sets the time limit for Google to consider that a new session has started. It’s worth changing this setting according to the particularities of your site. If your home page displays a 45-minute video and users tend to watch it in its entirety, for example, a session of up to 30 minutes would not be enough to reliably represent what happens on your site. To prevent sessions from duplicating, change the session timeout or set specific events such as video time watched via Google Tag Manager.
- Campaign timeout: this field determines how long GA should associate sessions and conversions for a unique user. By default, GA sets campaign timeout duration to six months, but many businesses prefer to shorten it. It is recommended not to exceed 30 days, but it needs to be analyzed on a case-by-case basis.
8. Configure organic traffic sources under “Organic Search Sources”:
This space is intended to add all sites that can be considered organic traffic sources. There is a list available on the page itself.
9. In “Referral Exclusion List”, exclude sites that you don’t want to be pointed out as traffic sources:
This field should be used to list all domains that shouldn’t be considered a traffic source. This is the case of payment systems that direct to your website on the thank you page and tools such as ActiveCampaign, Vimeo, Infusion Soft, WebnarJam, and others.
10. In “Search term exclusion list”, list the terms that should be considered as direct traffic:
Do you know when the user types your site into Google instead of using the browser bar? You can use this section to set up terms that can be considered direct traffic. This is often the case for your brand name, your domain name, or the expert behind your site.
11. Under “Product Linking”, see which products are relevant to your business:
In general, most people want to link Google Ads and Google Search Console. For you to be able to perform the integration, however, you need to have the permissions properly configured.
Note: “User-ID” and “Custom definitions” fields are more advanced and, therefore, will not be covered here.
Setting up your views
While properties store the data, Views determine the information that will be displayed and are used to answer specific questions about the data.
By default, Google Analytics creates a single view called “All Web Site Data”, but ideally you have at least 3 different views:
- Production view: it is used to answers specific questions;
- Test view: used for testing purposes only;
- Backup view (or raw data view): used only in case there is a problem that compromises the receipt of data, such as the unwanted application of a filter.
How to configure in practice:
- In “View Settings”, rename the original view to be used as a backup (suggestion: “3. Backup”). Uncheck the Bot Filtering option (“Exclude all hits from known bots and spiders”) and confirm that the time and currency settings are correct. You don’t need to fill anything in the “Default page”. Press save.
- In the upper right corner, press “Copy view” and create the test view. To keep the default, use the name “2. Testing view”.
- Repeat the process and create “1. Production view”. In this case, however, check the Bot Filtering option (“Exclude all hits from known bots and spiders”).
Note: if you are an e-commerce, remember to flag this in “Ecommerce Settings”.
Exploring filters
Filters affect how views display the data collected by properties. They are extremely useful but very dangerous because they definitely affect your data.
By the time the filter is created, data collection is already done according to the parameters defined by you. You can delete them, but the information that has already been stored will not change.
Therefore, it is highly recommended that you create filters in a test view and only move them to your production view after confirming that they are really working correctly.
Basic filters:
During the course “Google Analytics for Beginners”, Chris Mercer teaches 4 basic filters. These filters can help us with three main areas: make the data easier to read, present “cleaner” data, and fix “fractured” page reporting.
1. Show Domain filter:
By default, Google Analytics does not display your domain name in reports that show pages on your website. This makes it difficult to read the information, as it makes it difficult to separate content that integrates your domain, your subdomains, or external pages (such as the tool for sending an email or creating landing pages, for example).
To change the way information is displayed and make the data easier to read, you can create a filter to display the domain by following the steps below.
- In your test view, click on “Filters” and then on “+ Add Filter” button.
- Name the filter as “Show Domain” and click on “Custom” in the “Filter Type” field;
- Select the “Advanced” option;
- In “Field A”, select the option “Hostname” and fill in the following text: (.*)
- In “Field B”, select the option “Request URI” and fill in with: (.*)
- In “Output To -> Constructor”, select the option “Request URI” and fill in the following text: $A1$B1
- Confirm that the options “Field A Required” and “Override Output Field” are selected and check to save.
Ready! After that, your domain will start showing.
Note: Hostname is everything that appears until the “.com”. The “request URI”, in turn, is everything that appears after the slash. In the link “example.com/term”, the Hostname is the “example.com" and the “Request URI” is the “/term”.
2. Include Hostname (and more) filter:
Another filter taught by Chris Mercer to make data cleaner is “Include Hostname”. The purpose of this filter is to act as a reinforcement to the Bot filter applied by Google itself. By using it, you define which domains will be able to send traffic to the view used.
When using it, you need to be careful not to end up filtering too much and leaving out relevant domains such as landing page builders, automation tools, and the like.
To create it, just follow the steps:
- In your test view, click on Filters and then on “+ Add Filter”;
- Name the filter as “Include Hostname” and click on “Custom” in the “Filter Type” field;
- Select the “Include” option;
- In “Field field”, select the option “Hostname”;
- In “Field Pattern”, enter all the domains you want to include and separate them with a “|”. It will look like this: mysite.com|mysecondsite.com
- Save and go for tests.
This same feature can be used to create views for analyzing traffic coming from a single domain. Chris Mercer, for example, has a view just to analyze traffic coming from YouTube.
3. Add a Slash filter:
In some cases, a single page on your site appears in two ways: with and without a slash at the end. This creates a problem with the data, which is split as if they were separate pages. To solve this, you can create a filter that adds the slash to the bottom of each page and unifies the information.
To create the filter, just follow the instructions:
- In your test view, click on Filters and then on “+ Add Filter”;
- Name the filter as “Add a Slash” and click on “Custom” in the “Filter Type” field;
- Select the “Advanced” option;
- In “Field A”, select the option “Request URI” and fill in the following text: ^(/[a-zA-Z0–9/_\-]*[^/])$
- Leave the option “Field B” blank;
- In “Output To -> Constructor”, select the option “Request URI” and fill in the following text: $A1/
- Save and test it!
4. Lowercase filter
Google Analytics is case-sensitive. When information appears in capital letters and then appears again in small letters, the information can be fragmented as if they were related to two different pieces of data. To avoid this situation, it’s a good idea to create lowercase filters for the Source, Medium, Campaign, Content, and Term Keyword fields.
To create the filter, just follow the steps:
- In your test view, click on Filters and then on “+ Add Filter”;
- Name the filter as “Lowercase — Search Term” and click on “Custom” in the “Filter Type” field;
- Select the option “Lowercase”;
- In “Filter Field”, select the option “Search term” and press save.
- Repeat for other terms.
These are just a few of the many possibilities when it comes to filters. It’s worth taking a look at this article and this article and understanding which other types apply to you.
Managing filters
Finally, Chris Mercer advises that duplicating filters is not a best practice and explains that we should use the “All Filters” tab at the account level to manage filters more securely.
Chris also informs us that it is possible to change the order in which the filters are applied by clicking on “Assign Filter Order” (in the view) and that we should not change the backup view.
Understanding traffic:
One of the great advantages of using Google Analytics is understanding the source of traffic that accesses our website.
By default, there are three main types of “medium” tracheal by Google:
- Organic: traffic coming from search engines;
- Referral: traffic coming from third-party websites that are not part of the search network;
- None: traffic that does not fit the above definitions.
There are many optimization opportunities in traffic categorized as “none”. The more time you spend customizing your traffic, the simpler it is to read and understand the data.
There is no report for all organic traffic, as the “Search Console” only includes traffic coming from Google. Despite this, there is a report called “Referrals” that, in some cases, lets you know which publication from a third-party site has sent traffic to your site.
Another use of the Referral report is to understand if there is any domain that belongs to you and that is being pointed out as third-party traffic. In this case, it is worth using the Referral Exclusion List area (Property > Tracking Info) for the necessary adjustments.
Customizing traffic measurement:
As not all traffic is detailed by the default settings, it is necessary to customize to have more clarity on the source of the traffic. For this, we use UTMs (Urchin Tracking Model).
You can access the site Campaign URL Builder to build yours according to the parameters below:
- Campaign source: refers to the brand, such as Google, Facebook, Infusionsoft, etc;
- Campaign medium: is the medium, such as CPC, social, email, affiliate, webinar, podcast, guest-post, etc;
- Campaign name: is the name of the purpose of the campaign, such as what you want to sell, for example;
- Campaign term: is the headline or something that helps to understand the content;
- Campaign content: used to differentiate ads, emails, etc.
Pro-tip: a tip given by Chris is to create a simple, standard structure for creating UTMs. Here are some golden rules:
- Always use lowercase letters;
- Do not repeat the same names in different contexts (example: use “organic” to talk about organic traffic from social media, as it is already used by Google Analytics itself);
- Always use the brand name in “Source”;
- In campaigns, always use the campaign purpose rather than detailing too much. Chris, for example, signals according to the product he wants to sell;
- Use hyphens in place of spaces and underlines, as it is more difficult to read;
- Do not use special characters and punctuation to avoid breaking links.
Correcting fractured traffic
During the use of UTMs, it is normal for errors to occur and for information to appear broken at times.
In the example above, for example, the Facebook domain is displayed in different ways:
- m.facebook.com: traffic that came from a mobile server;
- l.facebook.com: traffic that came through desktop, but happened to go through a malware scanner;
- lm.facebook.com: traffic that came from a mobile server and also went through a malware scanner;
- facebook.com: traffic that came from a desktop.
To solve this problem and make viewing the data simpler, let’s create a filter:
- In your test view, click on Filters and then on “+ Add Filter”;
- Name the filter as “Combine — Facebook” and click on “Custom” in the “Filter Type” field;
- Select the “Search and Replace” option;
- In “Filter Field”, select the option “Campaign Source”;
- Fill in the “Search String” field with the following text: ^.*facebook.com$
- Fill in “Replace String” field with the following text: facebook
- Save and test it!
Another case that can happen is a medium (or any other part of UTM) using an incorrect term.
Suppose you use the nomenclature “cpc” as the medium for advertisements and, by mistake, an advertisement has been cheated as medium = “ad”. In that case, you’ll search and replace the filter so the ad always shows up as CPC:
- In your test view, click on Filters and then on “+ Add Filter”;
- Name the filter as “Switch — Ad to CPC” and click on “Custom” in the “Filter Type” field;
- Select the “Search and Replace” option;
- In “Filter Field”, select the option “Campaign Medium”;
- Fill in the “Search String” field with the following text: ^ad$
- Fill in “Replace String” field with the following text: cpc
- Save and test it using a UTM and a realtime report!
Goals in Google Analytics:
Many people think that goals can only be associated with the completion of an action, such as registering the user as a lead or a purchase. Despite this, Chris Mercer recommends that you follow the A.C.E. and monitor three different types of goals:
- Aware: when the user becomes aware;
- Complete: when the user completes the action;
- Engage: when the user engages.
Following Chris’ model, ideally, your goals should create a sort of funnel. If you have a page that distributes free baits, for example, you can create the following goals:
1. Aware — Visited the free resources page
2. Engage — Visited the page to get specific material
3. Complete — Became a lead for the specific material.
Types of goals
To set a goal, you need to go to the Admin and click on “Goals”, in the view area. Remember that goals are unique to each view. In “Goal setup”, click on “Custom” and define the name next.
Next, you’ll see that Google Analytics itself displays four different types of possible goals:
- Destination (e.g. visited a destination page);
- Duration (e.g. spent more than 5 minutes on the page);
- Pages/screens per session (e.g. visited 3 pages);
- Event (e.g. play in a video)
Destination goals:
In this case, the goal is considered complete when the user visits a landing page flagged by you. In most cases, you should not use “Exact” (equivalent to exact match), but rather “Begins with”. This prevents the goal not working if the landing page comes with the URL parameters, for example.
Another important note is that you will need to include the hostname in the desired URL if you have configured the Show Domain filter. If the filter in question is not configured, just use the Request URI.
When inserting the link, do not copy the “https://” either. A good tip is to go to the Realtime report and analyze how the site is showing up in the reports.
Finally, remember that the goal is triggered once per session. If you want to test twice, close the window and log in again.
Note: In many cases, creating more complex and funnel-shaped goals will require you to use regular expressions, also known as “regex”. In this case, you will have to change the “Begins with” to “Regular expression” and make some adjustments.
Duration goals:
The goal is considered complete when the user spends a certain amount of time on the page. To configure it, just select the “Duration” option and set the time. It is also possible to assign a value to the goal.
Although it sounds simple, the duration goal is not as intuitive as it sounds, because, by default, Google Analytics cannot understand the duration of the session if the user does not fire a hit. This concept applies to the time displayed in “Avg. time on page”, which should not be interpreted literally.
The “avg. time on-page” should be used much more to understand patterns and proportions between one page and another than to try to estimate the time spent on each page.
The diagram below, presented by Chris Mercer, helps us understand how Google Analytics measures session time. Suppose the user enters a page and spends a few seconds reading the content, without clicking on anything at all, and then exits the site. In this case, Google Analytics will have fired a single hit, at the time of entry, and will consider that the session time was zero.
Now, suppose a user enters the site and clicks on another page after 33 seconds. It then spends a few minutes on the second page, but it doesn’t fire any hits either. In this case, the session time displayed will be equivalent to 33 seconds since that was the time of the second action marker.
In this case, the actions would be displayed like this in the report:
Note: You cannot test duration goals in the realtime report as duration goals are not displayed in the conversions area. To find out if it’s working, you need to use the other reports. To ensure that the test is done as technically as possible, a good suggestion is to use the UTMs.
Pages per session goals:
This goal is considered good for measuring engagement, but, as with duration goals, there are some quirks.
Standard sites trigger timestamps when there is a page change, but single-page applications do not, so page changes are not “seen” by Google Analytics.
For the timestamp to be triggered, it is necessary to configure it manually.
Note: to understand if it’s a Single Page Application, this link is worth visiting.
As with duration goals, page per session goals cannot be tested in realtime reports either. One possibility is to use the Source/Medium report.
Event goals:
Event goals offer countless possibilities. You can create an event for those who became a lead, for those who opened or responded to your support message, and even create a funnel based on different levels of engagement: exposed to the page, became aware of the page (a few seconds on the page) or engaged on the page (scroll the screen).
Despite the multiple possibilities, Google Analytics does not track events by default. To track them, you need pre-configuration and it is highly recommended to use Google Tag Manager.
Events follow a very clear hierarchy:
- Category;
- Action;
- Label.
To configure them, it is necessary to use the same nomenclature sent to Google Analytics by the platform receiving the events (Tag Manager, for example).
E-commerce reports:
As already explained, e-commerce reports need to be previously enabled in the view settings.
When using the option, you will have two possibilities: standard and enhanced. In general, the enhanced version is better for longer checkout processes, which require a cart.
As well as events, you also need to set up funnel steps.
It is possible to integrate e-commerce and Google Analytics using integrations, Google Tag Manager, or with the help of a developer.
It’s worth checking this link to learn more!
Analyzing reports — the basics:
Now that you understand the possibilities of Google Analytics and how to better track your results, it’s time to understand how to analyze and extract valuable insights from your reports.
To facilitate the review process, Chris Mercer recommends using the “QIA Framework”:
- Question;
- Information;
- Action.
The first thing you need to have is a guiding question.
After that, before going to Google Analytics, you need to think about what information is needed so that you can answer what you need.
Lastly, you need to understand what action should be taken from the answers you’ve found.
Practical example #01:
- Question: “Should we redesign the membership site to be mobile-friendlier?”
- Information needed: number of users on member pages and devices used to access.
- Action: if at least 20% of users are using mobile to access the site, we’ll look into a redesign.
How to solve:
- Go to Behavior > Site content > All pages;
- Increase the sample size and look for a page that only members have access to (screen immediately after login);
- Add a secondary device category dimension to check the percentage of mobile users.
Practical example #02:
- Question: “Should we focus on building more affiliate partners?”
- Information needed: traffic source and results.
- Action: if our partner traffic is selling products, then we invest resources in getting more partners.
How to solve:
- Go to Acquisition > All traffic > Source/medium;
- Increase the sample size and try to understand the patterns: do affiliates present significant numbers compared to other sources of traffic? Even if the volume is lower, is the conversion higher? In the case of the Google Merchandise Store, for example, the volume is low (0.48% of new users) and the conversion is much lower than most other traffic sources (only 0.23%).
- To further investigate, isolate the traffic source and use the secondary dimensions to find opportunities. Is there an affiliate who quits? Are there any campaigns that stand out? Are there any landing pages that convert more? In the case of the Google Merchandise Store, we noticed that the traffic sent by affiliates is not being well tracked, which makes it difficult to obtain more assertive responses.
- When analyzing the landing page, we noticed an opportunity: most affiliates send traffic to the homepage. Is this really the best page to get this traffic? Other pages have higher conversion rates. Is it just because the volume of traffic is smaller and more qualified?
Next steps and extra resources:
Wow! After so much content, you are now able to take full advantage of Google Analytics.
Now it’s time to practice and explore on your own!
To help you on this journey (which is just beginning), here are some additional resources:
Blogs and sites to explore:
This article was originally posted on fefy.com. It is part of a series of 12 posts sharing my main learnings during the Conversion Optimization Minidegree, provided by CXL Institute.
You can read the previous articles on the links below.
- Week 01: 5 conversion rate optimization best practices to increase your results
- Week 02: The (almost) mathematical formula behind millionaire salespages
- Week 03: Neuromarketing, emotional content strategy and influence design
- Week 04: Google Analytics for Beginners: an almost illustrated guide
- Week 05: Landing Page Optimization and Conversion Research
- Week 06: Google Analytics 4 and Google Tag Manager
- Week 07: User Research and Fast and Rigorous User Personas
- Week 08: Heuristic Analysis, Google Analytics Audit and Voice of Customer Data
- Week 09: A/B Testing Foundations, How to Run Tests, and Testing Strategies
