How to Use Comparisons in Google Analytics 4 (GA4)

One of the basic features you need to master in Google Analytics 4 is the use of comparisons. When you're managing a large-scale digital marketing campaign, you might have plenty of questions, and using comparisons will save you lots of time in finding the information you need. For example, you might want to know whether the organic search is working better on mobile or desktop, or if paid search is performing better in country A or country B.

Comparisons are the easiest feature you can use when you need to quickly gauge the performance between two different dimensions. This step-by-step guidewill help you quickly master how to use comparisons in Google Analytics 4, and show you some examples to make the most out of the feature.

How to Use Comparisons in Google Analytics 4 (GA4)

1. Login to Google Analytics 4 and access any report you would like to work on

2. Scroll up and select "Add comparison" (top-left-hand-side above the report)

3. Click to "+ Create new" (top-right-hand-side)

4. Select the dimension you want to add to the comparison

5. Click "Apply"

6. Repeat to add more comparisons (you can add up to 4 comparisons)

Examples of Comparisons in Google Analytics 4 (GA4)

Example 1: Desktop vs. Mobile Traffic Comparison

Goal: Compare desktop and mobile performance in Traffic Acquisition Report

Setting up Desktop Comparison:

1. Set dimension = device category

2. Set dimension values = desktop

3. Remove 'All Users' data by clicking the "X"

   
   

Adding Mobile Comparison:

1. Set dimension = device category

2. Set dimension values = mobile

   
   

Result: You'll see traffic data split between desktop and mobile for each channel.

Example 2: Country Performance Comparison

Goal: Compare traffic between Indonesia and Thailand

Setting up First Country:

1. Set dimension = country

2. Set dimension values = Indonesia

3. Remove 'All Users' data

   
   

Adding Second Country:

1. Set dimension = country

2. Set dimension values = Thailand

Result: View channel performance broken down by these two countries.

Example 3: Traffic Source Comparison

Goal: Compare organic search vs. referral traffic in Pages and Screens Report

Setting up Organic Search:

1. Set dimension = session default channel group

2. Set dimension values = organic search

   
   

Adding Referral Traffic:

1. Set dimension = session default channel group

2. Set dimension values = referral

   
   

Result: See how each page performs across these two traffic sources.

Example 4: Page Performance by Device

Goal: Compare home page vs. store page traffic across different devices

Prerequisites:

• Go to Tech Details Report

• Flip table to show device category

Setting up Comparison:

1. First Page:

   • Set dimension = page path and screen class

   • Set dimension values = / (home page)

2. Second Page:

   • Set dimension = page path and screen class

   • Set dimension values = /store.html

   
   

Result: View how home and store pages perform across different devices (mobile, desktop, tablet, smart TV)

Quick Tips on GA4 Comparisons:

• Always remove 'All Users' data when not needed

• Use clear dimension values for accurate comparisons

• Remember: pages are for websites, screens for mobile apps

• You can apply comparisons in any GA4 report

Frequently Asked Questions on Comparisons in Google Analytics 4 (GA4)

Can I create multiple comparisons at the same time in GA4?

Yes, but with limitations:

• Maximum of 4 comparisons at once

• Process:

  1. Create first comparison

  2. Click "Add comparison"

  3. Specify additional comparisons

• All comparisons can be viewed in a single report
  

Can I save comparisons in GA4 for future use?

Yes, with helpful features:

• Save comparisons within your GA4 property

• Access prebuilt saved comparisons

• Create new saved comparisons:

  1. Click "Comparisons"

  2. Select "Create new"

  3. Build your condition

• Benefits:

  • Easy access for team members

  • No need to recreate common comparisons

  • Define advanced user segmentations
    

How do comparisons differ from segments in GA4?

Comparisons

Key Characteristics:

• Function as temporary filters within reports

• Applied directly within standard GA4 reports

• Used for quick, side-by-side data analysis

• Cannot be used directly in Explorations

• Can be converted into segments if needed for Exploration use
  

Primary Use Cases

• Quick analysis of specific data subsets

• Temporary comparative analysis

• Standard report filtering

• Immediate insights gathering
  

Segments

Key Characteristics

• Function as permanent data filters

• Can be applied across multiple reports

• Used specifically in GA4 Exploration reports

• Cannot be used in standard GA4 reports

• More robust and reusable than comparisons
  

Primary Use Cases

• In-depth analysis

• Long-term data tracking

• Cross-report analysis

• Complex data exploration

• Free Form and Funnel reports

Use Case

• Comparisons: Best for quick, temporary analysis needs

• Segments: Better for sustained, in-depth analysis
  

Duration & Storage

• Comparisons: Temporary, need to be recreated unless saved

• Segments: Permanent, available for ongoing use
  

Flexibility

• Comparisons: Limited to individual report views

• Segments: Can be used across multiple reports and explorations
  

Report Compatibility

• Comparisons: Work in standard GA4 reports only

• Segments: Work in GA4 Exploration reports only
  

Important Note

While comparisons and segments serve different purposes, they can be complementary. A comparison can be converted into a segment when you need to use it in Exploration reports or need more permanent analysis capabilities.

How can comparisons help improve my analysis in GA4?

1. Quick Identification:

   • Differences between user segments

   • Similarities in behavior patterns

   • Performance variations

2. Metric Analysis:

   • Conversion rates

   • Engagement levels

   • Acquisition patterns

3. Strategic Insights:

   • Marketing campaign optimization

   • User experience improvements

   • Data-driven decision making