What Scope Levels Available for Dimensions and Metrics?​

In the world of digital analytics, understanding what scope levels available for dimensions and metrics​ is crucial for accurate reporting and actionable insights. Without grasping this foundation, your data can easily mislead you and that can cost your business big time. In this detailed guide, we’ll walk through dimensions, metrics, their types, and explain scope levels with examples to help you navigate Google Analytics like a pro.

Whether it is a website redesign agency or a b2b web design agency, get the fundamentals right on what scope levels are available for dimensions and metrics, and that will empower you to make better decisions.

What is a Dimension and Metric in Google Analytics?

Let’s clarify for now about the beginners. Dimension describes the attribute types of your users, sessions, and actions in Google Analytics. For instance, City, Browser, or Page Title.

A metric, on the other hand, is a quantifiable measurement like Sessions, Pageviews, or Bounce Rate.

Understanding what scope levels available for dimensions and metrics​ ensures you’re matching the right dimensions with the correct metrics for accurate data analysis.

What Are the Different Types of Dimensions in Google Analytics?

There are a variety of dimensions available, each providing different insights:

• User Dimensions (e.g., Age, Gender)
  
• Session Dimensions (e.g., Traffic Source)
  
• Hit Dimensions (e.g., Page URL)
  
• Product Dimensions (specific to ecommerce data)
  

Learning what scope levels available for dimensions and metrics​ helps you apply the correct types of dimensions to your analysis for accurate reporting.

Understanding Dimensions and Metrics: A Quick Overview

In simple terms:

• Dimensions answer the “what” What city is the visitor from? What device are they using?
  
• Metrics answer the “how much” How many pageviews? How long was the session?
  

Without knowing what scope levels available for dimensions and metrics​, even the best Google Analytics consulting services may provide flawed interpretations.

What Dimensions and Metrics Cannot Track

Despite their power, dimensions and metrics can’t track:

• Emotional reactions
  
• Offline conversions (unless integrated properly)
  
• Certain real-time behavioral patterns
  
• Cross-device behavior without User ID setup
  

When exploring what scope levels available for dimensions and metrics​, understanding these limitations is key to setting realistic expectations.

What Is Scope in Analytics?

Scope defines how dimensions and metrics relate to each other within a report.

When you ask what scope levels available for dimensions and metrics​, you’re really asking: “At what level are these data points measured and associated?”

There are four major scope types, and matching scopes correctly is essential for valid reporting.

Types of Scope Levels for Dimensions and Metrics

To master what scope levels available for dimensions and metrics​, you need to know the four scope types:

User-Level Scope

Associate data with a single user across multiple sessions. Example: User ID, Gender.

Session-Level Scope

Group data under a single session. Example: Session Duration, Source/Medium.

Hit-Level Scope

Connects data to a specific interaction. Example: Pageview, Event Action.

Product-Level Scope

Specific to ecommerce actions related to products. Example: Product Name, Product SKU.

Each level plays a vital role in answering what scope levels available for dimensions and metrics​ precisely.

How Scope Affects Data Collection and Reporting

If you mismatch scopes (like combining a hit-level dimension with a session-level metric), your reports can become inaccurate or even fail.

Knowing what scope levels available for dimensions and metrics​ ensures:

• Clean reports
  
• Accurate insights
  
• Better marketing decisions
  

You might even rely on a travel website development company or Google Tag Management consulting services to help set up and audit your data if needed.

Examples of Dimensions and Metrics at Different Scope Levels

Here’s how it looks in action:

• User-Level: Gender (Dimension) + Sessions (Metric)
  
• Session-Level: Source (Dimension) + Session Duration (Metric)
  
• Hit-Level: Page Path (Dimension) + Page Load Time (Metric)
  
• Product-Level: Product Category (Dimension) + Product Revenue (Metric)
  

This structure clarifies what scope levels available for dimensions and metrics​ at every stage.

Best Practices for Matching Scope Between Dimensions and Metrics

When working through what scope levels available for dimensions and metrics​, follow these tips:

• Always pair dimensions and metrics of the same scope.
  
• Double-check combinations inside custom reports.
  
• Use Google’s Core Reporting API to verify scope types.
  
• Rely on a Google analytics audit checklist to keep things tidy.
  

Common Mistakes to Avoid When Working With Scope Levels

While exploring what scope levels available for dimensions and metrics​, beware of:

• Mismatching dimension and metric scopes
  
• Overlooking ecommerce-specific scopes
  
• Neglecting to set custom scopes when creating custom metrics
  

These mistakes can corrupt your data, which no website maintenance services can fully fix later.

Why Choosing the Right Scope Matters for Your Analysis

Choosing the correct scope when studying what scope levels available for dimensions and metrics​ helps you:

• Maintain data accuracy
  
• Improve reporting clarity
  
• Make smarter business decisions
  
• Enhance marketing ROI
  

A poor scope setup could even misguide a major website redesign agency project.

Complete List of Dimensions and Metrics as Per the Core Reporting API (Google Analytics)

Google’s Core Reporting API categorizes dimensions and metrics by their function. To master what scope levels available for dimensions and metrics​, familiarize yourself with these categories:

User Related

• User Type
  
• User ID
  

Session Related

• Session Count
  
• Landing Page
  

Traffic Sources

• Source
  
• Medium
  
• Campaign
  

Google Ads Related

• Ad Group
  
• Campaign ID
  

Goal Conversions Related

• Goal Completions
  
• Goal Value
  

Platform or Device-Related

• Device Category
  
• Operating System
  

Geo Network-Related

• City
  
• Region
  

System-Related

• Browser
  
• Screen Resolution
  

Page Tracking Related

• Pageviews
  
• Unique Pageviews
  

Internal Search Related

• Search Term
  
• Search Category
  

Site Speed-Related

• Avg Page Load Time
  
• Server Connection Time
  

App Tracking Related

• App Name
  
• App Version
  

Event Tracking Related

• Event Category
  
• Event Action
  

Ecommerce Related

• Product Name
  
• Product Category
  

Social Interactions Related

• Social Network
  
• Social Action
  

User Timings Related

• User Timing Label
  
• Timing Category
  

Exceptions Related

• Exception Description
  
• Exception Fatal
  

Content Experiments Related

• Experiment ID
  
• Variant ID
  

Custom Variables or Columns Related

• Custom Dimension Index
  
• Custom Metric Index
  

Time-Related

• Hour
  
• Minute
  

DoubleClick Campaign Manager Related

• DCM Campaign
  
• DCM Placement
  

Audience Related

• Audience List
  
• Audience ID
  

AdSense Related

• AdSense Ad Units Viewed
  
• AdSense Revenue
  

Publisher Related

• Publisher Name
  
• Publisher Pageviews
  

Ad Exchange Related

• Ad Exchange Impressions
  
• Ad Exchange Revenue
  

DoubleClick for Publishers Backfill Related

• DFP Backfill Impressions
  
• DFP Backfill Revenue
  

DoubleClick for Publishers Related

• DFP Impressions
  
• DFP Revenue
  

Lifetime Value and Cohorts Related

• Lifetime Value
  
• Lifetime Transactions
  

Channel Grouping Related

• Channel Grouping
  
• Default Channel Grouping
  

DoubleClick Bid Manager Related

• DBM Cost
  
• DBM Clicks
  

DoubleClick Search Related

• DS Impressions
  
• DS Clicks
  

This deep categorization ensures that you deeply understand what scope levels available for dimensions and metrics​.

How to Set Up Custom Dimensions and Metrics in Google Analytics

Custom dimensions and metrics allow you to capture data Google Analytics doesn’t track natively. Setting them up is key to tailoring your data to your business needs.

When setting them up:

• Define the correct scope
  
• Use Google Tag Manager for efficient deployment
  
• Validate through real-time reports
  

If needed, consult Google tag Management consulting services to assist with technical setups.

How to Delete a Custom Dimension or Custom Metric in Google Analytics

Deleting a custom dimension or metric is simple but irreversible:

1. Navigate to Admin > Property Settings > Custom Definitions.
   
2. Find the dimension/metric you wish to delete.
   
3. Click Remove.
   

Caution: Deleting impacts all historical reporting where it was used. Make sure you really know what scope levels available for dimensions and metrics​ before deciding.

How to Set Up a Custom Dimension via Google Tag Manager

Setting up a custom dimension using Google Tag Manager involves:

1. Adding a new variable for your dimension.
   
2. Mapping it within the correct tag.
   
3. Publishing the container.
   

Make sure the scope you assign matches your data collection goals accurately, understanding what scope levels available for dimensions and metrics​ at every step.

Final Thoughts

Understanding what scope levels available for dimensions and metrics​ isn’t just about knowing the theory. It’s about applying that knowledge to make better data-driven decisions, ensuring clean, reliable, and actionable reports for your business growth.

Whether you’re running a travel website development company or working alongside a website redesign agency, mastering what scope levels available for dimensions and metrics​ will supercharge your digital strategy and set you up for success.

FAQs

What scope levels are available for dimensions and metrics?

In Google Analytics, there are four main scope levels available for dimensions and metrics: user-level, session-level, hit-level, and product-level. User-level scope connects data to an individual user across multiple sessions, helping track long-term behavior. Session-level scope groups all hits during a single visit, giving insights into session activities. Hit-level scope captures individual interactions, like pageviews or events, providing very detailed data. Product-level scope, mainly used in ecommerce tracking, relates to specific product actions. Understanding these scope levels is essential for properly aligning dimensions and metrics, ensuring accurate data collection, reporting, and analysis within your analytics setup.

What are dimensions in metrics?

Dimensions are, in this respect, attributes or characteristics of your data, such as the city where a user is from or where the user has visited. Metrics are quantitative measures such as session count, bounce rate, and pages per session. Dimensions say what a dataset is about while metrics tell how much there is of it. So, if your data dimension is “City,” your metric associated with it might be “Sessions”, which tells how many visits came from each city. Then there exist dimensions and metrics, and those two things will generate a proper report, which will tell about what users do, how do they get into your site, use it, and its performance overall.

What is a dimension in Google Analytics?

Google Analytics defines dimensions as descriptive attributes or characteristics that contribute to the categorization and organization of information. Dimensions provide context to your metrics by answering questions in reference to place, content, or entity; examples include City, Browser, Landing Page, or Device Category. For instance, if you are measuring sessions (a metric), then a session dimension could describe which city the sessions originated from. Dimensions are necessary for segmenting and understanding user behavior; they allow performance to be viewed against varied categories and provide further insights into how visitors interact with your website or app.

What are predefined and custom dimensions?

Predefined dimensions in Google Analytics are those built-in attributes that are automatically available for tracking, e.g., Page Title, Browser, City, or Device Category. Therefore, these standard dimensions cover the majority of common reporting needs without requiring additional setup. Custom dimensions, on the other hand, are those attributes that are defined by users to be able to collect and analyze data that companies do not automatically track by default. For example, you can create a custom dimension for monitoring membership levels, logged-in status, or types of customers. Custom dimensions provide you with more flexibility to customize your analytics data to your specific business objectives and deliver insights beyond the predefined data collected by Google Analytics.

What is a metric in Google Analytics?

Google Analytics metrics are measurements that quantify user behavior and website performance. Metrics are numeric values based on the client’s interaction with your site or app. Examples include Sessions, Bounce Rate, Pageviews, and Average Session Duration. From a metrics perspective, it is all about a “how much” or “how many” that’s presented in your reports, offering insights into traffic numbers, engagement levels, and conversion successes. Add those to the dimensions that describe attributes of the data to form workable reports. Understanding metrics is key to trend analysis, assessing marketing initiatives, and making informed decisions to improve the overall performance of your digital presence.

What are the differences between a dimension and metric in Google Analytics?

Dimensions and metrics exhibit divergent functionalities in Google Analytics. Dimensions are descriptive qualities that classify your data such as “City,” “Page Title,” or “Device Type” and thus serve to contextualize your information. Metrics however, usually numerical values representing your website’s performance or behavior, stand synonymously to classes such as “Sessions,” “Bounce Rate,” and “Pageviews.” Dimensions elaborately qualify the ‘what’ or ‘who’, and metrics realistically quantify the ‘how much’ or ‘how many’. Where the two meet are where dimensions and metrics ultimately give a complete view on the behavior of users and performance of the website.