Logical calculations

Logical calculations apply conditions to decide what to aggregate or return.

Count if

Counts the total number of items in a group with conditions.

Inputs

Same as Count, with a Filter so only matching rows are counted.

Use cases

• Number of female users above 30
• Count of delivered orders
• Tickets marked as urgent

Count distinct if

Counts the total number of distinct items in a group with conditions.

Inputs

Same as Count distinct, with a Filter so only matching rows are included.

Use cases

• Unique customers from a region
• Distinct products sold on promotion
• Unique users who completed onboarding

Average if

Calculates the average of values in a group with conditions.

Inputs

Same as Average, with a Filter so only matching rows are included.

Use cases

• Average order value for repeat buyers
• Average session duration for mobile users
• Mean delivery time for express shipping

Min if

Returns the item in the group with the smallest value with conditions.

Inputs

Same as Min, with a Filter so only matching rows are included.

Use cases

• First order date for VIP customers
• Earliest login among active users
• Lowest quote amount that was accepted

Max if

Returns the item in the group with the largest value with conditions.

Inputs

Same as Max, with a Filter so only matching rows are included.

Use cases

• Largest order from a campaign
• Latest renewal date for paid plans
• Highest NPS score among promoters

Sum if

Calculates the sum of values in the group with conditions.

Inputs

Same as Sum, with a Filter so only matching rows are included.

Use cases

• Revenue from a specific product line
• Total discount amount on cleared carts
• Sum of refunds issued this month

Case when

Returns the value associated with the first condition that evaluates to true.

Inputs

Input	Required?	Description
Case	Yes	One or more cases. Conditions that must match.
Then	Yes	Value for each case when it matches.
Default value	No	Fallback when no case matches.

Use cases

• Bucket customers into spend tiers
• Map status codes to friendly labels
• Flag high-risk orders based on amount and country