How does Google Analytics track visitors
Google Analytics: A Comprehensive Guide for 2020
Are you confused or maybe even intimidated by Google Analytics? Then you are not alone. Because the tool is not exactly straightforward. Nevertheless, it is worth giving it a chance - because Google Analytics is one of the most helpful online tools of all.
So in this guide we explain what Google Analytics can like you it set up and how to do the numerous Interpreting reports correctly.
What is google analytics
Google Analytics is an analysis tool that gives you precise insights into the performance of your website or app. It can be combined with all Google marketing products, including Google Ads, Search Console or Data Studio. This makes the tool an attractive option for marketers who use multiple Google services.
Should you use Google Analytics?
If you are looking for a tool that provides you with a lot of data, and you also have the time and capacity to evaluate it, Google Analytics is the right solution. Especially its compatibility with all other Google marketing products, includingGoogle Ads or Data Studio, makes the solution attractive in this case. On the other hand, if you want the software to be easy to set up and intuitive to use, Google Analytics may disappoint you.
Because Google Analytics is time-consuming, both in setup and training as well as in everyday administration and use. Other marketing analysis tools (such as HubSpot) make it much easier for you to generate relevant data with significantly less effort.
Is Google Analytics Free?
There's a free one as well paid version (Analytics 360) of Google Analytics. Small and medium-sized companies usually get by with the functions of the free basic version. Corporations, on the other hand, have to rely on the premium version - at least if they want to benefit from the following features:
Comprehensive funnel reports and attribution modeling (at which touchpoints are the actual monetary values?),
more data views, dimensions and metrics per property and
unlimited, non-sampling records.
Analytics 360 also includes dedicated customer support, including a personal account manager. For this alone, the fee can be worthwhile. However, it is not cheap: The Analytics 360 costs start at € 135,000 per year (billed monthly) and increase as soon as your website reaches more than 500 million hits per month.
This means that the cost of analytics is certainly higher than what many companies can afford. However, if you have the budget to both pay for the tool and an agency or an in-house analyst who can carry out the relevant evaluations, you should consider investing in the premium version.
How to use Google Analytics
Here you will find compact instructions on how to set up Google Analytics step-by-step:
How to set up Google Analytics
- Create an account (if you don't already have one).
- Add the name, url, and industry of the website you want to track.
- Add this code immediately after the head tag of your website (more on this below).
- Visit your Google Analytics portal and check that the code is working properly. To do this, keep an eye on the "Real-time reports" section while you are active in a separate tab or on the relevant website on your smartphone. The report should show at least one visitor (you!) To the site when this happens.
Does the Google Analytics code have to be included on every page of the website?
Many people ask this question - after all, it means a lot of work, especially if your website has more than 50 pages. Also, what happens when you add new pages? Does that mean that the tag has to be added every time?
Fortunately, the quick answer to this is no. In a little more detail, you just need to add the tag to each page template. So if you only use a single page type on your website (i.e. each individual page uses the same header module), you only have to add the tag to this module. It is then automatically applied to each page.
If you are using two different page types, you have to use the Insert code in both head modules. With three different page types, in all three head modules etc.
If you use a content management system (CMS) like HubSpot or WordPress, the whole thing is even easier. Because these tools have a separate field in which you only have to insert the tracking code once. HubSpot users can follow these simple instructions to do this.
Note:In order to track legally cleanly, you must not forget to add a Install opt-out cookie, with which the user can prevent the collection of their data.
How does Google Analytics work? The hierarchy
Around Set up Google Analytics properly, be sure to understand its different levels:
Image: Google Analytics
The organization is the highest level and represents the company. For example, our organization is HubSpot, Inc. An organization can easily do this include multiple Google Analytics accounts.
Establishing organizations is recommended for larger companies, but is not compulsory.
Accounts, on the other hand, are not optional - you need at least one account to use Google Analytics.
However, this form of account is not to be equated with a user account. For example, users can log into the company account with their individual Google email ID.
You can do both assign a property to several accounts as well as different properties to one account. Each account can contain up to 50 properties.
You can give users the Access to a full Analytics account allow, on a property within an account or on a data view in a property.
Now you may be wondering whether it is better to create a new account for each property or to link each account to the same property. The answer to this cannot be given in general terms, but depends on your specific use and your goals.
For example, suppose you are Tony Stark aka Iron Man and you have a website called the Stark Industries corporate website. At the same time, you also maintain five subdirectories, namely the company blog, a career section, media materials, case studies and information on investor relations. In this case, it makes sense to create separate properties for each subdirectory so that the individual team members can easily keep an eye on the performance of their specific page as well as the overall website.
Or maybe you have another page dedicated to Tony Stark's work for S.H.I.E.L.D. employed. In this case, you want the S.H.I.E.L.D. team to be able to see the data for this one subdirectory, but not for the rest of the website. Here you should set up a new account as well as a new property for the S.H.I.E.L.D.page.
Google Analytics Properties
A property is understood to be a website or app. Each property supports up to 25 data views.
You need at least two versions of the data view per property:
A version without any configuration, so the "raw" data view and
a version with filters that exclude all traffic that comes from your company itself (for example via a filter for the corresponding IP address) and does not include traffic from bots.
A data view only shows the information that the corresponding filters and advanced settings permit. As soon as you delete a data view, this data is irretrievably lost. It is therefore crucial to always have an unfiltered view of the data.
Google Analytics: Dimensions and Metrics
To use Google Analytics successfully, you need to understand the difference between dimensions and metrics:
Dimensions = categorical variables, such as names, colors or locations
Readings = quantitative variables such as age, temperature and population
A quick reminder: measured values are data that you can calculate with.
Examples of dimensions
Kind of customer
Examples of measured values
In every Google Analytics report, the dimensions are shown as rows and the metrics as columns.
Image: Google Analytics
Custom dimensions and metrics
With Google Analytics, you can create custom dimensions and metrics - both from Google Analytics data and data from other sources. For example, imagine that you want to track the type of membership that customers have who have created an account in your CRM system. You could now combine this information with the number of page views to identify the page views per membership type.
Or maybe you run a blog too. Now, if you wanted to know how your audience engagement affects other metrics (such as conversions or the number of pages visited per session), you could create three custom dimensions for each reader type:
Advocate: People who have shared at least one of your posts on social media
Subscriber: users who have signed up for your e-mail newsletter
Customer: Users who have purchased premium access
These three dimensions provide you with invaluable insights. Follow the corresponding guide from Google Analytics to create your own custom dimensions and metrics.
What is a Google Analytics Audience?
Roughly speaking, a target group is a group of users who have something in common. This common ground can be anything: You may have specifically targeted customers from Australia, in which case you have an “Australian target group”. Or, you might want to sell your products or services to millennials as a priority. In this case you are serving a “target group between 25 and 34 years of age”.
Google Analytics offers you various integrated target groups (including those mentioned, location and age). You don't have to do anything to set it up - once the Tracking code installed, Google Analytics gets your website visitors automatically split into these audience reports.
You can also create custom target groups. For example, you might only be interested in Australian millennials. In that case, you'll need to create a custom audience that includes visitors who a) live in Australia and b) are between 25 and 34 years old.
Creating an audience yourself is pretty easy. The hardest part is surely thinking about what exactly you want to achieve with your target audience and then identifying the user characteristics that will help you with that. Once you've done that, you can check out the Google help pages on exactly how to set up audiences. You can then import a segment that will serve as the basis for your audience report.
That leads us to the next question:
What is a Google Analytics segment?
A segment is a subset of your data. To illustrate this, imagine a pizza made up of many different pieces with different toppings - each of those pizza pieces is, metaphorically speaking, a segment.
You can create segments based on three different criteria create:
Users (For example, users who have already bought something on your website or have signed up for a consultation)
Meetings (For example, all sessions that were generated by a specific marketing campaign or all sessions in which users viewed the costs page)
Hit (For example, all hits where the purchase value exceeded 85 euros or all hits where a specific product was added to the shopping cart)
Similar to the target groups, Google Analytics also provides some preset segments to disposal. But of course you don't have to limit yourself to that. Segments allow you to make extremely granular settings if you wish.
To inspire you, here are some of the Segments that HubSpot uses:
Users who viewed a specific product page and the demo video
Users who viewed the same product page but not the video
Users viewing a specific Academy course page
Users viewing a specific Academy lesson page
Users viewing a blog post and a product page
There are no limits to your imagination. Up to four segments can be applied to any report at any time. You can find more information about the Google Analytics segments on the corresponding Google help page.
Google Analytics: reports
The left sidebar in Google Analytics can quickly overwhelm users. Here you will find six options for different reports, the names of which are sometimes confusing and vague. As soon as you click on an option, further options are added.
For a better overview, let's go through the different types of reports piece by piece:
Image: Google Analytics
As the name suggests, it enables Real-time report Give you insight into what is happening on your website right now. You can see how many visitors are currently there, which pages they are visiting, which social networks they come from, which location they are surfing from and much more.
While this report can be useful at times, it is probably the least useful in general. For example, you could use it like this:
Track how much traffic you're getting from a new social media or blog post.
See immediately whether a one-day event or sales campaign is driving views or conversions.
You can make sure that the URL or custom event tracking you just set up is working properly.
Image: Google Analytics
This report gives you a comprehensive overview of the property you are currently looking at.
Image: Google Analytics
You should check this report once a day to keep an eye on the general development of your website.
Under “Overview” you will find the field “Target group” and expandable menus for the items “Demographic characteristics”, “Interests”, “Geography”, “Behavior”, “Technology”, “Mobile”, “Across all devices”, “Personalized” and "Benchmarking". Take a look at all of these areas to get a feel for the valuable information they can give you about your website visitors.
Each area describes a specific target group.
This term is quite confusing, because the corresponding report does not refer to users who are currently active on your website - these are shown in the real-time report. Rather, the “Active Users” report shows you the number of users who
last day (Users who were active on 1 day),
last week (Users who were active on 7 days),
the past two weeks (Users who were active on 14 days) or
four weeks (Users who were active on 28 days)Visited your website.
Image: Google Analytics
What added value does this report offer you? If you have more users in the past day than long-term users, you have a problem with the retention of your users. Obviously these don't return to your website or app - it's up to you to find out why.
Also, be sure to take a look at this report with different segments. For example, you might find that you retain users in a certain age range significantly better than the average of all users.
The Lifetime Value Report is based on the Customer Lifetime Value (CLV) and gives you a sense of how valuable individual users are to your company. You can compare different user groups by, for example, comparing the CLV of the users you have generated via email marketing with that of the users you have acquired via organic search. This information can then be used to decide which channel to invest more in.
A note: The lifetime value is currently a maximum of 90 days. The acquisition date range, which you can freely set, begins in March 2017, however. This period reflects all users that you have acquired during this period.
Imagine you want to take a closer look at the transactions per user for all those users that you acquired in the month before Christmas. In this case, adjust the period exactly to this month. From now on you will be shown the average transactions per user for this cohort over the next 90 days.
For software-as-a-service companies like HubSpot, the target achievement per user, the page views per user and the sessions per user, sorted by acquisition channel, are of particular interest. If a marketing campaign was carried out shortly before, it makes sense to look at the same metrics sorted by acquisition campaign. E-commerce companies, on the other hand, should set up customized tracking that provides them with information on purchase and transaction data.
This report groups users based on a characteristic. So far, only the acquisition date can be set as the corresponding dimension - i.e. the day on which a user visited your website for the first time.
From here you now have several options:
First choose your “cohort size”: day, week or month
Then define the measured value that you want to take a closer look at. This can then be broken down further into "per user", "user loyalty" or the "total measured value":
Per user means the total value of the corresponding measured value divided by the cohort size. For example, if you choose transactions per user, you will see the average number of transactions per user for this cohort.
User loyalty means the number of users who returned to your website on that day, week or month (depending on the selected cohort size), divided by the total number of users in this cohort.
total shows the total number of all sessions, transactions etc. that occurred in this cohort size.
Select the appropriate period. Google Analytics allows you to view data from up to three months.
The following is a correct interpretation of the report, as it is not necessarily intuitive.
Image: Google Analytics
In the left column you can see the selected one Cohort type (by default the acquisition date) after Cohort size (Day, week or month).
The first line shows all users in this cohort. Each line below that represents the activity on that day, week, or month. In our example, let's look at the month.
The line in light blue shows you the cohort size you selected. Please note that the analyzed data go back a maximum of three months.
The yellow line shows the values of the selected metric, in this case “target achievement per user”.
Now look at the first line. This shows that the average target achievement of the entire cohort in the first month after the acquisition was 1.09. The average target achievement for the entire cohort fell to 0.09 in the second month after the acquisition and was 0.02 in the last month.
Now look at the next three lines. It looks like the average target achievement per user in the first month after the acquisition increased slightly between December and January and between January and February.
This behavior is pretty common. So let's imagine instead that the report showed us that the average goal achievement per user for the period from 01.02. until 02/28/2019 (the last line) would be 4.07. That would then be almost four times as high as in December and January.
We would definitely want to investigate such a result more closely. All you need to do is right-click on the cohort that interests us. Make sure that you click the entire column if you want to analyze the entire day, week, or month. On the other hand, click on a specific cell to analyze, for example, only those users who have achieved a goal within three days of the acquisition on 02/27/2019.
After right clicking this box will appear:
Image: Google Analytics
Give this cohort a name that is as descriptive as possible. Then change the Data Views to All Data Views if you want to apply this segment to your entire property (which is usually recommended). Then all you have to do is click on “Create”. Now you can compare this cohort to any other segment in any report!
This report breaks down your traffic by source, for example:
"Other" (this category uses Google Analytics if the tool cannot classify the corresponding traffic otherwise)
Image: Google Analytics
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