With businesses immensely relying on effective data-driven decision-making for chalking out future strategies, Data Analysis has become an integral part of every growth strategy for them. In order to perform an in-depth analysis, businesses have to ensure that they collect as much data as possible, allowing them to ensure that their analysis would not lead to incorrect or partial insights.
The key to deriving valuable insights from data in Google Analytics lies in the grasp of Google Metrics and Dimensions. Google Metrics and Dimensions are considered to be building blocks of Google Analytics that help businesses segment, organize, and analyze their traffic and website data.
This article will provide you with a comprehensive understanding of what Metrics and Dimensions in Google Analytics are and how they can help you track the performance of your website.
Table of Contents
Introduction to Google Analytics
Google Analytics is a Cloud-based Analytical tool by Google that gives users the ability to analyze website traffic and report customer behavior. It houses numerous functionalities that allow users to integrate with different platforms and extract the website traffic data. It helps users segregate their campaigns upon various metrics to understand how their campaigns perform and make data-driven decisions to improve performance. It is the most popular choice for industries due to its extensive reporting capability.
Some of the most well-known features of Google Analytics are as follows:
- Google Analytics tracks websites and collects all necessary data across metrics like region, user, clicks, products, time spent, conversion, etc., for all visitors. With the information collected, it generates an extensive report allowing businesses to analyze their campaigning effort.
- Google Analytics dashboard helps understand customer behavior by analyzing the sources, organic traffic, keywords, sentiments, etc.
- Google Analytics offers easy integration with other Google products such as Google Search Console, Google Ads, Google Data Studio, etc., allowing users to perform an in-depth and accurate analysis.
- Functionality to keep track of various metrics such as page speed, mobile-friendliness, etc., that can help businesses measure the performance of their websites is also provided by Google Analytics.
- It also helps businesses study the competition and drive strategic decisions based on the customer segment and engagement.
More information about Google Analytics can be found here.
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Understanding Google Dimensions in Google Analytics
A Google Dimension in Google Analytics is any attribute representing the number and characteristics of visitors to a website that can be used to describe and segment, organize, and sort data as per requirements. The various kinds of Google Dimensions available in Google Analytics are Medium, Country, Language, Device Category, etc.
The following image shows how Google Dimensions are represented in Google Analytics:
It can be seen in the above image that the Source/Medium is the Dimension Name, whereas google/organic is the Dimension Value.
The following image shows another Google Dimension, i.e., Device Category:
It can be observed that each Google Dimension accepts a different set of values. For example, the Google Dimension Device Category indicates the type of device used to visit the website and only takes desktop, mobile, and tablet as values to help organize traffic across the three devices.
Each visitor coming to a website has specific characteristics associated with them that are represented as a collection of Google Dimensions. For example, suppose a 30-year-old man in New Delhi, India, accesses a website from a Facebook Ad on his smartphone; the dimension attributes would be as follows:
- Gender: Male
- Age: 25-34
- Location: New Delhi, India
- Source/Medium: Facebook/paid_social
- Device Category: Mobile
Understanding Google Metrics in Google Analytics
Google Metrics in Google Analytics are quantitative measurements that help you understand the number of people associated with each Google Dimension. For example, Google Dimensions will help you understand which country your visitor came from, but Google Metrics will let you know how many other visitors also came from that country, along with additional information such as the Average Session Duration, Bounce Rate, etc.
Hence, it can be said that Google Metrics are quantitative measurements of data that show how a website is performing with respect to a specific Google Dimension. For example, the following image shows the number of Users who came from Desktop, Mobile, and Tablet devices, along with additional information about user behavior such as Average Session Duration, Bounce Rate, etc., which are Google Metrics for the Device Category dimension:
Common Google Metrics in Google Analytics
All common Google Metrics can be grouped into the following categories:
1) Acquisition-related Google Metrics
- Users: The number of visitors who initiated at least one Session over a given period.
- New Users: The number of first-time visitors over a given period.
- Sessions: A Session can be defined as a group of user interactions that take place within a given time frame on a website. The default time frame for a Google Analytics Session is 30 minutes. If any user is inactive for more than 30 minutes, a new Session is started, and all future activity is attributed to that new Session. If a user leaves the website and returns within 30 minutes, it is counted as part of the original Session.
2) Behavior-related Google Metrics
- Bounce Rate: The percentage of all single-page Sessions in which no user interaction took place.
- Exit Rate: The percentage of visitors that left the website from a single page.
- Pages/Session: The average number of pages viewed within a single Session.
- Session Duration: The average length/duration of a Session.
3) Conversion-related Google Metrics
- Transactions: The number of completed transactions such as product purchases that took place on the website.
- Revenue: The amount of revenue generated from the transactions.
Scope of Google Metrics and Dimension in Google Analytics
Each Google Metrics and Dimension can only have one of the following Google Analytics Scope:
A Hit refers to any user interaction taking place on the website resulting in data being sent to Google Analytics. Each time a user interaction triggers the tracking code, Analytics records that activity and sends it to Google as a Hit.
The Session scope is a more time-based scope and considered to be at a level higher than the Hit-level scope. A Session consists of all Hits that occur in one Session for a given user. Google Metrics and Dimensions on Session-level collect all relevant data about a session. Examples of Google Dimensions include Source/Medium, Landing Page, Device Category, etc., and Google Metrics include Sessions, Bounce Rate, Exit Rate, etc.
The User scope is the highest level at which the user data is organized in Google Analytics. One user can have multiple Sessions, and one Session can have more Hits. Examples of Google Dimensions in the User scope include User Type, Days since the last Session, etc., and Google Metrics include Users, New Sessions, etc.
The Product-level scope is specifically for E-Commerce Analysis. This scope helps businesses get an understanding of specific product metrics, such as Product Transactions, Product Revenue, etc.
Shortcomings of Google Metrics and Dimensions in Google Analytics
Google Analytics allows businesses to get an in-depth understanding of their website performance as a whole and its individual pages on a User-level. It can help businesses efficiently perform the following operations:
- Map out their website’s entire ecosystem, allowing them to understand where users are coming from and how they move through the website.
- Compare user behaviors across multiple segments so that performance across different groups can be reviewed.
- Identify priorities and quantify their impact so that they can determine which pages have the potential of the most significant impact on your company’s growth goals and optimize accordingly.
Although Google Analytics can help businesses maintain a comprehensive log of everything happening on their website, it cannot help businesses understand the reason behind a majority of user actions.
For example, suppose a new product page of a business has an Exit Rate of 80%. This means that 8 out of 10 users landing on that webpage exit the website. Although businesses can analyze various Dimension and Metrics to form a few hypotheses, they cannot really understand the actual reason behind this behavior because they do not know what users were actually looking at on the web page at that point, if they left because the product did not fit their requirement, if they left because the product did fit their requirement, but they had certain questions about it that the page didn’t answer, etc. Google Metrics and Dimensions cannot help businesses find answers to these questions.
In order to understand the reason behind the above-stated user behavior, businesses can combine Google Analytics and other Behavioural Analytical tools to produce the following:
- Heat Maps: They aggregate visitor behavior on individual pages, showing which buttons and touchpoints receive the most and least interactions and whether people scroll down to the bottom of the page or fail to progress beyond a given point.
- Session Recordings: These are recordings of real actions that users performed on the website.
This article provided you with an in-depth understanding of what Google Metrics and Dimensions are in Google Analytics and how they can help businesses track the performance of their website and individual web pages on it.
Although tracking website performance is an easy task when all data is already present in Google Analytics, importing data into Google Analytics from some sources that are not directly supported by it can be a complicated task. If Google Analytics does not support a source, the data must be imported using the product API, which would require immense engineering bandwidth and resources. Businesses can instead integrate data from all their sources and Google Analytics in a Data Warehouse using existing automated No-code platforms like Hevo.
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