Dimensions and metrics in Google Data Studio
A dimension is the attribute of visitors to your website. It is used to describe or categorize your data.
For example, let’s say a man aged between 25-34 from London visited your website after clicking on an organic search listing on Google which he found by searching for the keyword ‘attribution modeling’. Let’s also assume that he visited your website via the Chrome browser which is installed on a desktop computer that runs Windows.
Now following are the attributes of the visitor to your website along with their values:
Gender – male
Age – 25-34
City – London
Source / Medium – Google / Organic
Keyword – Attribution Modelling
Browser – Chrome
Device Category – desktop
Operating System – Windows
Here Gender, Age, City, Source /Medium, Keyword, Browser, Device Category and Operating System are all examples of dimensions because they are the characteristics of your website users.
Dimension in your data source appears as green fields.
Get the ebook on Google Data Studio (50+ Pages)
Types of dimensions in Data Studio
There are three types of dimensions in Data Studio:
- Regular dimension – It is the attribute of visitors to your website. It is used to describe or categorize your data.
- Data source specific calculated dimension – It is a dimension that performs some action(s) on other field(s) in your data source via a formula.
- Chart specific calculated dimension – It is a dimension that performs some action(s) on other field(s) in your chart via a formula.
All calculated dimensions appear in the data source with an ‘fx’ symbol:
Metrics in Google Data Studio
A metric is a number that is used to measure one of the characteristics of a dimension.
A dimension can have one or more characteristics. For example, the following are the characteristics of the dimension called ‘Source / Medium’:
- Sessions
- % New Sessions
- New Users
- Bounce Rate
- Pages / Sessions
- Avg. Session Duration
- Goal Conversion Rate
- Goal Completions
- Goal Value
Here, Sessions, % New Sessions, New Users, Bounce Rate, Pages / Sessions, etc are all examples of metrics because they are the characteristics of the dimension called ‘Source / Medium’
Metrics in your data source appear as blue fields:
Types of metrics in Data Studio
There are three types of metrics in Data Studio:
- Regular metric – It is a number that is used to measure one of the characteristics of a dimension.
- Data source specific calculated metric – It is a metric that performs some action(s) on other field(s) in your data source via a formula.
- Chart specific calculated metric – It is a metric that performs some action(s) on other field(s) in your chart via a formula.
All calculated metrics appear in the data source with an ‘fx’ symbol:
Difference between dimensions and metrics in Google Analytics and Google Data Studio
In Google Analytics, a dimension can not be used as a metric and vice versa. Whereas, in the Google Data Studio, a dimension can be used as a metric and vice versa.
For example in the data table below, ‘age’ (which is defined as a dimension in GA) is used as a metric:
And you can see how Data Studio is reporting the values of the ‘age’ field in the data table. But when you use ‘age’ as a dimension, you see the correct data in the data table:
Similarly, in Google Analytics, certain dimensions and metrics can not be used/queried together.
However, this is not the case with Google Data Studio.
For example, in Google Analytics you can not use/query ‘user type’ dimension with Adwords ‘impressions’ metric. In Data Studio you can do that but you are going to see ‘User Configuration Error’:
When you are using Google Analytics dimensions and metrics in Google Data Studio, you need to be extra careful.
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#1 Why digital analytics is the key to online business success.
#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.
#4 Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
#5 The number 1 reason why conversion optimization is not working for your business.
#6 How to advertise on any marketing platform for FREE with an unlimited budget.
#7 How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com
A dimension is the attribute of visitors to your website. It is used to describe or categorize your data.
For example, let’s say a man aged between 25-34 from London visited your website after clicking on an organic search listing on Google which he found by searching for the keyword ‘attribution modeling’. Let’s also assume that he visited your website via the Chrome browser which is installed on a desktop computer that runs Windows.
Now following are the attributes of the visitor to your website along with their values:
Gender – male
Age – 25-34
City – London
Source / Medium – Google / Organic
Keyword – Attribution Modelling
Browser – Chrome
Device Category – desktop
Operating System – Windows
Here Gender, Age, City, Source /Medium, Keyword, Browser, Device Category and Operating System are all examples of dimensions because they are the characteristics of your website users.
Dimension in your data source appears as green fields.
Get the ebook on Google Data Studio (50+ Pages)
Types of dimensions in Data Studio
There are three types of dimensions in Data Studio:
- Regular dimension – It is the attribute of visitors to your website. It is used to describe or categorize your data.
- Data source specific calculated dimension – It is a dimension that performs some action(s) on other field(s) in your data source via a formula.
- Chart specific calculated dimension – It is a dimension that performs some action(s) on other field(s) in your chart via a formula.
All calculated dimensions appear in the data source with an ‘fx’ symbol:
Metrics in Google Data Studio
A metric is a number that is used to measure one of the characteristics of a dimension.
A dimension can have one or more characteristics. For example, the following are the characteristics of the dimension called ‘Source / Medium’:
- Sessions
- % New Sessions
- New Users
- Bounce Rate
- Pages / Sessions
- Avg. Session Duration
- Goal Conversion Rate
- Goal Completions
- Goal Value
Here, Sessions, % New Sessions, New Users, Bounce Rate, Pages / Sessions, etc are all examples of metrics because they are the characteristics of the dimension called ‘Source / Medium’
Metrics in your data source appear as blue fields:
Types of metrics in Data Studio
There are three types of metrics in Data Studio:
- Regular metric – It is a number that is used to measure one of the characteristics of a dimension.
- Data source specific calculated metric – It is a metric that performs some action(s) on other field(s) in your data source via a formula.
- Chart specific calculated metric – It is a metric that performs some action(s) on other field(s) in your chart via a formula.
All calculated metrics appear in the data source with an ‘fx’ symbol:
Difference between dimensions and metrics in Google Analytics and Google Data Studio
In Google Analytics, a dimension can not be used as a metric and vice versa. Whereas, in the Google Data Studio, a dimension can be used as a metric and vice versa.
For example in the data table below, ‘age’ (which is defined as a dimension in GA) is used as a metric:
And you can see how Data Studio is reporting the values of the ‘age’ field in the data table. But when you use ‘age’ as a dimension, you see the correct data in the data table:
Similarly, in Google Analytics, certain dimensions and metrics can not be used/queried together.
However, this is not the case with Google Data Studio.
For example, in Google Analytics you can not use/query ‘user type’ dimension with Adwords ‘impressions’ metric. In Data Studio you can do that but you are going to see ‘User Configuration Error’:
When you are using Google Analytics dimensions and metrics in Google Data Studio, you need to be extra careful.
EXCLUSIVE FREE TRAINING REVEALS....
"How to use Digital Analytics to generate floods of new Sales and Customers without spending years figuring everything out on your own."
Here’s what we’re going to cover…
#1 Why digital analytics is the key to online business success.
#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.
#4 Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
#5 The number 1 reason why conversion optimization is not working for your business.
#6 How to advertise on any marketing platform for FREE with an unlimited budget.
#7 How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com