Customer Segmentation Strategies in DAX

Customer Segmentation Formulas in DAX

This guide provides a set of DAX formulas for different customer segmentation strategies. Each formula is explained clearly with a practical example to illustrate its use.

Segmentation by Total Sales

Formula

Customer Sales Segment = 
SWITCH(
    TRUE(),
    [Total Sales] < 500, "Low Value",
    [Total Sales] >= 500 && [Total Sales] < 2000, "Medium Value",
    [Total Sales] >= 2000, "High Value"
)

Explanation

• Syntax: SWITCH(TRUE(), ..., ...) evaluates multiple conditions and segments customers based on their total sales.
• Logic:
  • Customers with total sales < 500 are categorized as "Low Value".
  • Customers with total sales >= 500 and < 2000 as "Medium Value".
  • Customers with total sales >= 2000 as "High Value".

Practical Example

If a customer has a total sales amount of 1500, the segment would be "Medium Value".

Segmentation by Purchase Frequency

Formula

Customer Purchase Frequency Segment = 
SWITCH(
    TRUE(),
    [Total Purchases] < 5, "Infrequent",
    [Total Purchases] >= 5 && [Total Purchases] < 15, "Regular",
    [Total Purchases] >= 15, "Frequent"
)

Explanation

• Syntax: SWITCH(TRUE(), ..., ...)
• Logic:
  • Customers with total purchases < 5 are categorized as "Infrequent".
  • Customers with total purchases >= 5 and < 15 as "Regular".
  • Customers with total purchases >= 15 as "Frequent".

Practical Example

A customer making 10 purchases would fall into the "Regular" segment.

Segmentation by Recency of Purchase

Formula

Customer Recency Segment = 
SWITCH(
    TRUE(),
    [Last Purchase Date] <= TODAY() - 365, "Dormant",
    [Last Purchase Date] <= TODAY() - 180, "Inactive",
    [Last Purchase Date] > TODAY() - 180, "Active"
)

Explanation

• Syntax: SWITCH(TRUE(), ..., ...) along with TODAY()
• Logic:
  • "Dormant" for customers whose last purchase was more than 365 days ago.
  • "Inactive" for those whose last purchase was more than 180 days but less than 365 days ago.
  • "Active" for purchases within the last 180 days.

Practical Example

If a customer's last purchase was 200 days ago, he/she would be segmented as "Inactive".

Segmentation by Revenue Growth

Formula

Customer Growth Segment = 
SWITCH(
    TRUE(),
    [Revenue Growth] < 0, "Declining",
    [Revenue Growth] >= 0 && [Revenue Growth] < 10, "Stable",
    [Revenue Growth] >= 10, "Growing"
)

Explanation

• Syntax: SWITCH(TRUE(), ..., ...)
• Logic:
  • "Declining" for customers with negative growth.
  • "Stable" for growth between 0% and 10%.
  • "Growing" for growth above 10%.

Practical Example

A customer with a revenue growth of 5% would be categorized as "Stable".

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Conclusion

These DAX formulas provide a concise and efficient way to segment customers based on various criteria such as total sales, purchase frequency, recency of purchase, and revenue growth. Proper segmentation enables better-targeted marketing strategies and improved customer relationship management.