How To: Configure Custom Dimensions reporting in GA4

How to Enable Custom Dimensions for DemandScience Firmographic Data in Google Analytics 4 (GA4) Integration using Google Tag Manager

In order to utilize this feature, you must have Web Experiences as part of your DemandScience plan. 

If you have any questions regarding your current subscription plan, please reach out to your Account Manager.

Overview

Users of DemandScience Web Experiences have the ability to send custom dimension reporting into Google Analytics. This allows DemandScience firmographic data to report into GA4 for use alongside your other data points. 

In order to send custom dimension data into GA4, you must first ensure your Web Experiences GA4 integration has been properly configured. 

For instructions on setting that up, please review How to: Configure the GA4 Integration using GTM

If everything has been configured correctly for the GA4 integration, you can set up the custom dimensions reporting as outlined below. 

 

Identify the Fields for Custom Dimensions Reporting

To begin, it’s important to know what fields are available to send data to GA4. The following is a list of all DemandScience firmographic fields that you can use for custom dimension reporting

• Display Ad Tactic
• Company Name
• Domain
• Is Mobile
• Country Code
• Industry
• NAICS Code
• SIC Code
• Employee Range
• Revenue Range

Each one of these fields will provide a relevant value (if known) and that combination of Field Name and Value will be sent to Google Analytics for each website visitor. 

If you want, you can send all 10 fields to GA4 as individual dimensions. You can also pick and choose if there are only a couple of fields of interest. Most commonly, customers will choose to send data for:

• Display Ad Tactic
• Company name
• Domain
• Industry

 

Once you have determined which fields you’d like to display in GA4, you can begin the process of configuring your instance.

 

Configure GTM to Receive Dimension Data

Note: This guide will walk through the process of configuring one field for custom dimension reporting. We will use “Company Name” as our field. You will need to follow this process for each dimension that you’d like to send.

 

Create New Variables

To begin, login to Google Tag Manager and navigate to the Variables section. 

Select “New” from the top right of the “User-Defined Variables” section.

• Name your variable “DemandScience Visitor Data - Company Name”
• For the “Variable Type” select “Data Layer Variable”
• For the “Data Layer Variable Name” enter the value “name”
  • Note: This value will vary based on which field you are creating the variable for. Use the following case sensitive values when completing this section:
    • Display Ad Tactic: displayAdTactic
    • Company Name: name
    • Domain: domain
    • Is Mobile: isMobile
    • Country Code: countryCode
    • Industry: industry
    • NAICS Code: naicsCode
    • SIC Code: sicCode
    • Employee Range: employeeRange
    • Revenue Range: revenueRange
• Make sure that the “Data Layer Version”  is “Version 2”
• Save your new variable
• Your completed variable should look like this:

 

Complete this process for each data field you’d like to send.

 

Create a New Trigger

Next, you will need to create a trigger for the visitor data

Begin by navigating to the Triggers section of GTM. 

Select “New” from the top right to create a new Trigger.

• Name your trigger, “DemandScience Event - Visitor Data”
• In the Trigger Configuration canvas, choose “Custom Event” as your trigger type
• For the event name, enter “webex_visitor_data”
  • Note: If, when you set up your original Web Experiences GA4 connection within the DemandScience Web Experiences dashboard, you used something other than the standard event and property prefix (shown below), you will use that here with your custom prefix followed by “visitor_data”

• Set your trigger to fire on “All Custom Events”. When finished, your trigger should look like this:

• Save your trigger.

 

Create a New Tag

After your variables and triggers are in place, you’ll need to create a new tag for the visitor data. 

Navigate to the Tags section of GTM and select “New” to create a new tag

• Name your tag “DemandScience Visitor Data - Send to GA4”
• In the Tag Configuration, select “Google Analytics: GA4 Event” as the Tag Type
• From the Configuration Tag dropdown, select “GA4 Configuration” as shown below

• For “Event Name” click on the lego icon to the right of the field and select “Event”
• Next, you will need to configure user properties for each of the fields for which you’d like to send data. Click on “User Properties” to expand that section of the Tag configuration and then add one row for each field for which you will be sending data. 
• Once your rows are added, fill them out as follows:
  • The Property Name field will be filled out with “webex_” followed by the name for the field. In the case of Company Name, it will be “webex_name” and will look like this

• Note: If you used a custom prefix in the Web Experiences GA4 connection instead of the default “webex_” you will need to use that prefix here
• The Property Names for each of the potential fields are:
  • Display Ad Tactic: webex_ad_tactic
  • Company Name: webex_company
  • Domain: webex_domain
  • Is Mobile: webex_is_mobile
  • Country Code: webex_country_code
  • Industry: webex_industry
  • NAICS Code: webex_naics_code
  • SIC Code: webex_sic_code
  • Employee Range: webex_employee_range
  • Revenue Range: webex_revenue_range
• To complete the “Value” field, click on the lego icon and then find the corresponding Variable for each field that you have already created.

• Once the Tag Configuration is complete, move down to the “Triggering” section
• Click on “Firing Triggers” and then select the previously created “DemandScience Event - Visitor Data” trigger from the list. 
• Once complete, your tag should look like this:

 

• Save your tag

Publish Your Updates

Once your variables, trigger, and tag have been created and saved, publish your updates. 

 

GA4 Set-Up

After you have saved and published your GTM updates, there is one final configuration step that will need to take place in GA4. 

To begin, login to GA4 and navigate to the Admin and then select Custom Definitions from the center column. 

Select Create custom dimensions. You will need to create a custom dimension for each of the fields that you selected for Google Tag Manager. You can follow the completion instructions below:

1. Dimension Name: This is the name that will appear in the GA4 interface. It is best to keep this simple and use something that you’d like to see in the dashboard. 
2. Scope: All custom dimensions are tied to the users so these will be “User” scope
3. Description: You can give your dimensions any quick description to remind you what the data is showing
4. User property: Here you will need to enter (or select from the dropdown) the User Property name that was entered in GTM. This needs to exactly match the value from GTM. Normally, these values will auto populate in the dropdown; however, it can take up to 24 hours before they become available so if you just created the values in GTM, you can go ahead and manually enter them here
   • Note: the User Property Names for each of the potential fields are:
     • Display Ad Tactic: webex_ad_tactic
     • Company Name: webex_company
     • Domain: webex_domain
     • Is Mobile: webex_is_mobile
     • Country Code: webex_country_code
     • Industry: webex_industry
     • NAICS Code: webex_naics_code
     • SIC Code: webex_sic_code
     • Employee Range: webex_employee_range
     • Revenue Range: webex_revenue_range

•  

Once all of your custom dimensions have been created, you should have a list that looks similar to this: 

 

At this point, your custom dimension configuration is complete. You will begin to receive the user property data for events on your website in GA4.

 

Reporting Discrepancies 

Please note that reporting data within the DemandScience platform will not match exactly with Google Analytics, or any other visitor or web tracking analytics platforms. Differences in reporting are expected and normal due to a variety of factors, including but not limited to differences in tracking methodologies, cookie usage, IP resolution, session definitions, and data aggregation standards. 

 

Tracking Methodology:

• Google Analytics: Uses cookies and JavaScript tracking tags to assign a unique client ID to each visitor (or User ID, if logged in). It tracks individual sessions, with a heavy reliance on user-centric data (e.g., page views, time spent on site). However, it anonymizes user data in compliance with privacy laws (e.g., by masking IP addresses). While Google Analytics can attribute traffic to sources (like campaigns or channels), it typically does not link visits to specific companies or accounts.
• DemandScience: Tracks users by IP address, firmographic data, and other identifiers that allow it to map website visits back to specific companies. DemandScience often uses IP resolution, reverse DNS lookups, or third-party data to identify the organization behind a website visit. This means that instead of tracking individual users, DemandScience focuses on identifying accounts (e.g., companies, departments, or buying groups) and attributing visits or actions to those accounts.

 De-anonymization Process:

• Google Analytics: Google Analytics anonymizes user data, such as IP addresses, by default. It doesn’t aim to associate site visits with specific companies or accounts. Instead, it focuses on individual sessions, which can lead to aggregation issues if many people from the same company visit the site anonymously. As a result, Google Analytics provides less granular, account-level attribution.
• DemandScience: DemandScience’s de-anonymization process is specifically designed to handle account-level tracking. It uses methods like IP resolution and partnerships with third-party data providers to de-anonymize traffic by linking visitors’ IP addresses to specific companies or organizations. DemandScience then aggregates all interactions from the same company under one account, providing insights into the engagement of that account. This approach is ideal for ABM, as it enables marketers to track multiple visitors from the same company and aggregate their activity for account-based insights.

Data Aggregation:

• Google Analytics: Primarily aggregates data by session or user, meaning it typically doesn’t merge interactions from the same company across different sessions. If different employees from the same company visit a website at different times, Google Analytics would likely track them as separate visitors, with no account-level aggregation.
• DemandScience: Aggregates multiple visits from different users within the same company or account. It identifies that multiple individuals from the same organization are interacting with your content, and it aggregates this data to reflect the overall engagement of the account. This allows DemandScience to provide account-based insights, such as how many decision-makers from a particular company are engaging with specific campaigns or content.

Attribution Models:

• Google Analytics: Attribution in Google Analytics is often session-based (e.g., last-click attribution, first-click attribution). It assigns conversion credit to the last or first interaction the user had with the website, which works well for individual-level tracking but may not accurately reflect the collective engagement of multiple decision-makers within a company.
• DemandScience: DemandScience uses account-level attribution. Instead of attributing visits or conversions to individual sessions, it aggregates all interactions from users within a specific account.