Introduction

Custom Dimensions and Metrics in Google Analytics allow you to collect and analyze data that is specific to your business needs. They extend the default data tracked by Google Analytics, providing deeper insights into user behavior and interactions on your website or app.

Key Concepts

Custom Dimensions

Definition: Custom Dimensions are user-defined attributes that you can use to segment your data. They allow you to track additional information about your users or their interactions.
Scope: Custom Dimensions can have different scopes:
- Hit-level: Applies to individual interactions.
- Session-level: Applies to all interactions within a single session.
- User-level: Applies to all interactions by a single user.
- Product-level: Applies to individual products (e-commerce).

Custom Metrics

Definition: Custom Metrics are user-defined quantitative measurements. They allow you to track additional numerical data.
Scope: Custom Metrics can also have different scopes similar to Custom Dimensions.

Setting Up Custom Dimensions and Metrics

Step-by-Step Guide

Navigate to Admin Panel:
- Go to your Google Analytics account.
- Select the property where you want to set up Custom Dimensions and Metrics.
- Click on the "Admin" button.
Create Custom Dimensions:
- In the "Property" column, click on "Custom Definitions" and then "Custom Dimensions".
- Click on the "+ New Custom Dimension" button.
- Enter a name for the Custom Dimension.
- Select the scope (Hit, Session, User, or Product).
- Click "Create".
Create Custom Metrics:
- In the "Property" column, click on "Custom Definitions" and then "Custom Metrics".
- Click on the "+ New Custom Metric" button.
- Enter a name for the Custom Metric.
- Define the formatting type (Integer, Currency, Time).
- Set the minimum and maximum values if necessary.
- Click "Create".

Example Code for Implementation

To implement Custom Dimensions and Metrics, you need to modify your tracking code. Here is an example using Google Analytics' gtag.js:

<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-XXXXXX-X"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){dataLayer.push(arguments);}
  gtag('js', new Date());

  gtag('config', 'UA-XXXXXX-X');

  // Set a custom dimension at the user level
  gtag('set', {'user_id': 'USER_ID'});

  // Send a custom dimension with an event
  gtag('event', 'login', {
    'method': 'Google',
    'custom_dimension_name': 'custom_dimension_value'
  });

  // Send a custom metric with an event
  gtag('event', 'purchase', {
    'value': 1.99,
    'currency': 'USD',
    'custom_metric_name': 5
  });
</script>

Practical Exercise

Exercise 1: Setting Up a Custom Dimension

Objective: Track the membership status of users (e.g., Free, Premium).
Steps:
- Create a Custom Dimension named "Membership Status" with a User-level scope.
- Implement the tracking code to send the membership status when a user logs in.

Solution

Create Custom Dimension:
- Name: Membership Status
- Scope: User

Tracking Code:

<script>
  gtag('set', {'membership_status': 'Free'});
</script>

Exercise 2: Setting Up a Custom Metric

Objective: Track the number of articles read by a user.
Steps:
- Create a Custom Metric named "Articles Read" with an Integer type.
- Implement the tracking code to increment the metric each time an article is read.

Solution

Create Custom Metric:
- Name: Articles Read
- Type: Integer

Tracking Code:

<script>
  gtag('event', 'read_article', {
    'articles_read': 1
  });
</script>

Common Mistakes and Tips

Incorrect Scope: Ensure you select the correct scope for your Custom Dimensions and Metrics. For example, use User-level for attributes that apply to the user across sessions.
Data Overload: Avoid creating too many Custom Dimensions and Metrics, as it can complicate your data analysis.
Validation: Always validate your implementation using Google Analytics Debugger or similar tools to ensure data is being sent correctly.

Conclusion

Custom Dimensions and Metrics are powerful tools in Google Analytics that allow you to tailor your data collection to your specific business needs. By understanding and implementing these features, you can gain deeper insights into user behavior and make more informed decisions. In the next module, we will explore how to use filters to refine your data further.

Custom Dimensions and Metrics

Introduction

Key Concepts