How would you identify customers with highest average order value?
Divide total sales by distinct orders for each customer.
Example:SUM([Sales]) / COUNTD([Order ID])-
How would you calculate sales growth between two selected years?
Compare sales using year filter or parameter selection.
Example:(SUM([Sales CY]) - SUM([Sales PY]))
/ SUM([Sales PY]) -
How would you identify products never sold?
Use left join/scaffold and check for null sales.
Example:ISNULL(SUM([Sales])) -
How would you create a moving average for 6 months?
Use WINDOW_AVG table calculation.
Example:WINDOW_AVG(SUM([Sales]),-5,0) -
How would you show customers with sales above regional average?
Compare customer sales against window average.
Example:SUM([Sales]) > WINDOW_AVG(SUM([Sales])) -
How would you calculate profit contribution percentage?
Divide individual profit by total profit.
Example:SUM([Profit]) / TOTAL(SUM([Profit])) -
How would you identify seasonal sales spikes?
Compare monthly sales trends across years.
Example:LOOKUP(SUM([Sales]),-1) -
How would you create a customer retention dashboard?
Track repeat customers over periods using COUNTD.
Example:COUNTD([Customer ID]) -
How would you calculate days between first and last purchase?
Use MIN and MAX order dates.
Example:DATEDIFF('day',
MIN([Order Date]),
MAX([Order Date])) -
How would you identify underperforming regions?
Compare regional sales against target or average sales.
Example:
SUM([Sales]) < WINDOW_AVG(SUM([Sales]))