Calculated Columns for Copilot Usage Segmentation

This page provides DAX scripts for calculated columns used to segment users by their Copilot usage patterns in Power BI.

RL12W (12-week rolling) Approach

Recommended if the adoption timeframe is longer than 12 weeks, and the goal is to evaluate long term habit formation on Copilot usage.

• _Total Copilot actions_RL12W.dax:
  Calculates the average weekly Copilot actions for each user over the last 12 weeks.

• _IsHabit_RL12W.dax:
  Flags users as “habitual” if they used Copilot in at least 9 of the last 12 weeks.

• _CopilotUsageSegment_RL12W.dax:
  Categorizes users as Power, Habitual, Novice, Low, or Non-users based on their calculated usage and habit status.

Definitions

• Power User: average 15+ weekly total Copilot actions and any use of Copilot in 9 of the last 12 weeks.
• Habitual User: any use of Copilot in 9 of the last 12 weeks.
• Novice User: average 1+ weekly Copilot actions over the past 12 weeks.
• Low User: at least one Copilot action in the past 12 weeks.
• Non−user: zero Copilot actions in the past 12 weeks.

RL4W (4-week rolling) Approach

Recommended if the adoption period is shorter than 12 weeks, or adoption is being evaluated as part of an agile pilot program.

• _Total Copilot actions_RL4W.dax:
  Calculates the average weekly Copilot actions for each user over the last 4 weeks.

• _IsHabit_RL4W.dax:
  Flags users as “habitual” if they used Copilot in all of the last 4 weeks.

• _CopilotUsageSegment_RL4W.dax:
  Categorizes users as Power, Habitual, Novice, Low, or Non-users based on their calculated usage and habit status.

Definitions

• Power User: average 15+ weekly total Copilot actions and any use of Copilot in all of the last 4 weeks.
• Habitual User: any use of Copilot in all of the last 4 weeks.
• Novice User: average 1+ weekly Copilot actions over the past 4 weeks.
• Low User: at least one Copilot action in the past 4 weeks.
• Non−user: zero Copilot actions in the past 4 weeks.

Usage Instructions

1. Open Power BI Desktop and select your table in Data view.
2. Download the DAX file you want to use from the links above.
3. Copy the DAX expression and paste it into Power BI as a ‘New Column’ formula.
4. Use the resulting columns to analyze and visualize Copilot adoption and habit formation.

Available DAX Files

12-Week Rolling (RL12W) Files:

• 📄 _Total Copilot actions_RL12W.dax
• 📄 _IsHabit_RL12W.dax
• 📄 _CopilotUsageSegment_RL12W.dax

4-Week Rolling (RL4W) Files:

• 📄 _Total Copilot actions_RL4W.dax
• 📄 _IsHabit_RL4W.dax
• 📄 _CopilotUsageSegment_RL4W.dax

Creating Total Copilot Actions Column

It may be necessary to create a custom “Total Copilot actions” column in the Power Query step under ‘Transform Data’. Here’s an example M (Power Query) script:

= let
    Source = #"Changed Type", // Update with name of previous step as appropriate
    AddedCustomColumn = Table.AddColumn(
    Source, 
    "Total Copilot actions",
    each [#"Copilot actions taken in Teams"] + 
         [#"Copilot actions taken in Outlook"] +
         [#"Copilot actions taken in Word"] +
         [#"Copilot actions taken in Excel"] +
         [#"Copilot actions taken in Powerpoint"],
    Int64.Type
    )
in
    AddedCustomColumn

Source Files

• 📁 View on GitHub: Complete source code and DAX files
• 📖 Original README: Detailed documentation

Need Help?

For detailed usage instructions and additional context, see our Usage Segmentation Guide or visit the source folder on GitHub.