Top Tableau Scenario-Based Interview Questions Set - 13 (1- 10)

 

1. How would you calculate customer purchase frequency?
   Divide total orders by distinct customers.
   Example:

   COUNTD([Order ID]) / COUNTD([Customer ID])
   

2. How would you identify the most profitable product category?
   Rank categories based on total profit.
   Example:

   RANK(SUM([Profit])) = 1
   

3. How would you calculate average discount percentage?
   Use AVG aggregation on Discount field.
   Example:

   AVG([Discount]) * 100
   

4. How would you identify customers with zero profit orders?
   Filter orders where profit equals zero.
   Example:

   SUM([Profit]) = 0
   

5. How would you compare quarterly sales performance?
   Use Quarter dimension with Sales measure.
   Example:

   DATETRUNC('quarter',[Order Date])
   

6. How would you calculate average shipping delay by region?
   Use DATEDIFF and aggregate by Region.
   Example:

   AVG(DATEDIFF('day',[Ship Date],[Delivery Date]))
   

7. How would you identify high-discount low-profit orders?
   Apply conditional filter using Discount and Profit.
   Example:

   [Discount] > 0.3
   AND
   [Profit] < 0
   

8. How would you create dynamic ranking in Tableau?
   Use parameter-driven rank calculation.
   Example:

   RANK(SUM([Sales])) <= [Top Rank]
   

9. How would you calculate customer-wise profit margin?
   Divide customer profit by customer sales.
   Example:

   SUM([Profit]) / SUM([Sales])
   

10. How would you identify products with declining sales trend?
    Compare current sales with previous period sales.
    Example:

     SUM([Sales]) < LOOKUP(SUM([Sales]),-1)

Top Tableau Scenario-Based Interview Questions Set - 12 (1- 15)

 

1. 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])
   

2. 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])
   

3. How would you identify products never sold?
   Use left join/scaffold and check for null sales.
   Example:

   ISNULL(SUM([Sales]))
   

4. How would you create a moving average for 6 months?
   Use WINDOW_AVG table calculation.
   Example:

   WINDOW_AVG(SUM([Sales]),-5,0)
   

5. How would you show customers with sales above regional average?
   Compare customer sales against window average.
   Example:

   SUM([Sales]) > WINDOW_AVG(SUM([Sales]))
   

6. How would you calculate profit contribution percentage?
   Divide individual profit by total profit.
   Example:

   SUM([Profit]) / TOTAL(SUM([Profit]))
   

7. How would you identify seasonal sales spikes?
   Compare monthly sales trends across years.
   Example:

   LOOKUP(SUM([Sales]),-1)
   

8. How would you create a customer retention dashboard?
   Track repeat customers over periods using COUNTD.
   Example:

   COUNTD([Customer ID])
   

9. 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]))
   

10. How would you identify underperforming regions?
    Compare regional sales against target or average sales.
    Example:

    SUM([Sales]) < WINDOW_AVG(SUM([Sales]))