Top Tableau Scenario-Based Interview Questions Set -33 (1- 5) - Important

 

1. How would you calculate Customer Lifetime Value (CLV)?

Calculate total revenue generated by a customer throughout their relationship with the company.

{ FIXED [Customer ID] :
SUM([Sales])
}

For Average CLV:

AVG(
{ FIXED [Customer ID] :
SUM([Sales])
}
)

Interview Follow-up: Why use FIXED LOD instead of SUM(Sales)? Because CLV should be calculated at Customer level regardless of view granularity.

---

2. How would you identify customers likely to churn?

Find customers who haven't purchased in the last 180 days.

DATEDIFF(
'day',
{ FIXED [Customer ID] :
MAX([Order Date])
},
TODAY()
) > 180

These customers can be targeted with retention campaigns.

---

3. How would you calculate Year-to-Date (YTD) Sales?

Calculate sales from January 1st until today.

IF YEAR([Order Date]) = YEAR(TODAY())
AND [Order Date] <= TODAY()
THEN [Sales]
END

Then aggregate:

SUM(
IF YEAR([Order Date]) = YEAR(TODAY())
AND [Order Date] <= TODAY()
THEN [Sales]
END
)

---

4. How would you calculate Same Period Last Year (SPLY) Sales?

Compare current YTD against previous year's YTD.

IF YEAR([Order Date]) = YEAR(TODAY()) - 1
AND DATEPART('dayofyear',[Order Date])
<= DATEPART('dayofyear',TODAY())
THEN [Sales]
END

This is frequently asked in Tableau and Power BI interviews.

---

5. How would you identify the Top Customer in each Region and Category simultaneously?

Rank customers within Region and Category.

RANK(SUM([Sales])) = 1

Compute Using: Customer Name
Partition By: Region, Category

This returns the highest revenue-generating customer for every Region-Category combination.

---

Bonus Architect-Level Question

How would you calculate Repeat Purchase Rate?

Percentage of customers who placed more than one order.

COUNTD(
IF
{ FIXED [Customer ID] :
COUNTD([Order ID])
} > 1
THEN [Customer ID]
END
)
/
COUNTD([Customer ID])

This is one of the most commonly used KPIs in Retail, E-commerce, and Customer Analytics projects.

Top Tableau Scenario-Based Interview Questions Set -28 (1- 7)

 

1. How would you identify the customer who contributed the highest profit in each region?

Use Rank on Profit and partition by Region.

RANK(SUM([Profit])) = 1

Compute Using: Customer Name
Partition By: Region

This returns the top profit-generating customer in every region.

---

2. How would you calculate the average number of days taken to ship an order?

Calculate the difference between Order Date and Ship Date.

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

This measures shipping efficiency.

---

3. How would you identify products that have sales in every month of the year?

Count distinct sales months and compare with 12.

{ FIXED [Product Name] :
COUNTD(DATETRUNC('month',[Order Date]))
} = 12

This identifies consistently selling products.

---

4. How would you calculate each customer's share of profit within their region?

Divide customer profit by total regional profit.

SUM([Profit])
/
WINDOW_SUM(SUM([Profit]))

Set Compute Using: Customer Name.

This shows profit contribution within a region.

---

5. How would you identify orders where discount is given but profit is negative?

Filter orders having discount and loss.

[Discount] > 0
AND
[Profit] < 0

Useful for identifying poor discounting strategies.

---

6. How would you calculate the average revenue generated per active month?

Divide total sales by distinct active months.

SUM([Sales])
/
COUNTD(
DATETRUNC('month',[Order Date])
)

This gives average monthly revenue.

---

7. How would you identify customers whose latest purchase amount is higher than their average purchase amount?

Compare latest order sales with customer average sales.

IF [Order Date] =
{ FIXED [Customer ID] : MAX([Order Date]) }
THEN [Sales]
END

Compare it against:

{ FIXED [Customer ID] : AVG([Sales]) }

This identifies customers whose recent spending is above their historical average.

Top Tableau Scenario-Based Interview Questions Set -27 (1- 5)

 

1. How would you identify customers who generated profit in every year?

Count the number of years with positive profit and compare it with total years.

{ FIXED [Customer ID] :
COUNTD(
IF [Profit] > 0
THEN YEAR([Order Date])
END
)
}
=
{ FIXED : COUNTD(YEAR([Order Date])) }

This returns customers who were profitable every year.

---

2. How would you calculate the percentage change between current sales and average sales?

Compare current sales against overall average sales.

(
SUM([Sales])
-
WINDOW_AVG(SUM([Sales]))
)
/
WINDOW_AVG(SUM([Sales]))

This shows how much a value is above or below the average.

---

3. How would you identify the customer with the highest single order value?

Compare each order against the maximum order amount.

SUM([Sales])
=
WINDOW_MAX(SUM([Sales]))

This returns the order/customer with the highest order value.

---

4. How would you calculate the ratio of profit to quantity sold?

Measure profit earned per unit sold.

SUM([Profit])
/
SUM([Quantity])

Useful for analyzing product efficiency and profitability.

---

5. How would you identify products whose sales are greater than the average sales of their category?

Compare product sales with category-level average using FIXED LOD.

SUM([Sales])
>
{ FIXED [Category] : AVG([Sales]) }

This highlights products outperforming their category average.

Top Tableau Scenario-Based Interview Questions Set - 24 (1- 3)

 

How would you identify customers who buy only one product category?

Count distinct categories purchased by each customer and filter those with exactly one category.

Example:

{ FIXED [Customer ID] : COUNTD([Category]) } = 1

This helps identify customers with limited product adoption and cross-sell opportunities.

---

2. How would you calculate the percentage of customers retained from the previous year?

Count customers who purchased in both the current and previous year and divide by last year's customers.

Example:

COUNTD(
IF YEAR([Order Date]) = YEAR(TODAY())
AND
{ FIXED [Customer ID] : MIN(YEAR([Order Date])) } < YEAR(TODAY())
THEN [Customer ID]
END
)
/
COUNTD(
IF YEAR([Order Date]) = YEAR(TODAY()) - 1
THEN [Customer ID]
END
)

This provides a simple annual customer retention metric.

---

3. How would you identify the category contributing the highest profit percentage?

Calculate each category's share of total profit and rank it.

Example:

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

To get the top category:

RANK(SUM([Profit])) = 1

This highlights the category contributing the largest share of company profit.

Top Tableau Scenario-Based Interview Questions Set - 21 (1- 5)

 

1. How would you identify customers whose sales are declining for 3 consecutive months?

Compare current month sales with the previous two months using table calculations.

Example:

SUM([Sales]) < LOOKUP(SUM([Sales]),-1)
AND
LOOKUP(SUM([Sales]),-1) < LOOKUP(SUM([Sales]),-2)

---

2. How would you calculate the percentage of new customers each month?

Identify customers whose first purchase occurred in the selected month and divide by total customers.

Example:

COUNTD(
IF DATETRUNC('month',[Order Date]) =
{ FIXED [Customer ID] : DATETRUNC('month',MIN([Order Date])) }
THEN [Customer ID]
END
)
/
COUNTD([Customer ID])

---

3. How would you identify products with sales above the category average?

Compare product sales against category average using a FIXED LOD.

Example:

SUM([Sales]) >
{ FIXED [Category] : AVG([Sales]) }

---

4. How would you calculate customer profitability ranking?

Rank customers based on total profit generated.

Example:

RANK(SUM([Profit]))

Sort Profit descending to get highest-profit customers at Rank 1.

---

5. How would you identify regions contributing more than 25% of total sales?

Calculate regional contribution and filter regions above 25%.

Example:

SUM([Sales])
/
TOTAL(SUM([Sales]))
> 0.25

This highlights the regions driving a significant portion of overall revenue.

Top Tableau Scenario-Based Interview Questions Set - 20 (1- 5)

 

1. How would you identify customers who have purchased from multiple product categories?

Count distinct categories purchased by each customer and filter those with more than one category.

Example:

{ FIXED [Customer ID] : COUNTD([Category]) } > 1

---

2. How would you calculate the percentage of orders delivered within SLA?

Count orders delivered within SLA and divide by total orders.

Example:

SUM(
IF DATEDIFF('day',[Order Date],[Ship Date]) <= 3
THEN 1
ELSE 0
END
)
/
COUNT([Order ID])

---

3. How would you identify the highest-selling product in each category?

Rank products by sales within each category.

Example:

RANK(SUM([Sales])) = 1

Compute Using: Product
Partition By: Category

---

4. How would you calculate average days between customer purchases?

Find the difference between consecutive orders and average them.

Example:

WINDOW_AVG(
DATEDIFF(
'day',
LOOKUP(MIN([Order Date]),-1),
MIN([Order Date])
)
)

---

5. How would you identify customers whose profit margin is below 5%?

Calculate profit margin and filter low-margin customers.

Example:

SUM([Profit])
/
SUM([Sales])
< 0.05

This highlights customers generating sales but very little profit.

Top Tableau Scenario-Based Interview Questions Set - 18 (1- 5)

 

How would you identify customers whose sales increased by more than 20% compared to the previous year?

Calculate YoY growth and filter customers above 20%.

Example:

(
SUM([Sales]) - LOOKUP(SUM([Sales]),-1)
)
/
LOOKUP(SUM([Sales]),-1)
> 0.20

---

2. How would you calculate the average number of orders per customer?

Divide total distinct orders by total distinct customers.

Example:

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

---

3. How would you identify products that have never generated profit?

Filter products whose total profit is zero or negative.

Example:

SUM([Profit]) <= 0

---

4. How would you calculate the percentage of customers contributing to 80% of sales?

Use cumulative sales percentage and count qualifying customers.

Example:

RUNNING_SUM(SUM([Sales]))
/
TOTAL(SUM([Sales]))
<= 0.8

Sort customers by Sales descending before applying the calculation.

---

5. How would you identify the most recent order for each customer?

Use a FIXED LOD to get the latest order date.

Example:

{ FIXED [Customer ID] : MAX([Order Date]) }

Then filter:

[Order Date] =
{ FIXED [Customer ID] : MAX([Order Date]) }

to display only the latest order record per customer.

Top Tableau Scenario-Based Interview Questions Set - 17 (1- 10)

 

How would you calculate the percentage of total sales for each product?

Divide product sales by total sales.

Example:

SUM([Sales]) / TOTAL(SUM([Sales]))

---

2. How would you identify customers who placed only one order?

Count distinct orders per customer and filter those with exactly one order.

Example:

COUNTD([Order ID]) = 1

---

3. How would you calculate the average sales per day?

Divide total sales by the number of distinct order dates.

Example:

SUM([Sales]) / COUNTD([Order Date])

---

4. How would you identify the month with the highest sales?

Rank monthly sales and select Rank 1.

Example:

RANK(SUM([Sales])) = 1

---

5. How would you calculate the sales variance from the previous month?

Subtract previous month's sales from current month's sales.

Example:

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

---

6. How would you identify products contributing less than 1% of total sales?

Calculate contribution percentage and filter.

Example:

SUM([Sales]) / TOTAL(SUM([Sales])) < 0.01

---

7. How would you calculate the average order value by region?

Divide regional sales by distinct order count.

Example:

SUM([Sales]) / COUNTD([Order ID])

Place Region in the view.

---

8. How would you identify customers who generated a loss?

Filter customers whose total profit is negative.

Example:

SUM([Profit]) < 0

---

9. How would you calculate the percentage of returned orders?

Divide returned orders by total orders.

Example:

COUNT(
IF [Returned] = "Yes"
THEN [Order ID]
END
)
/
COUNT([Order ID])

---

10. How would you identify the best-performing state within each region?

Rank states by sales within each region.

Example:

RANK(SUM([Sales])) = 1

Compute Using: State
Partition By: Region

Top Tableau Scenario-Based Interview Questions Set - 14 (1- 12)

 

1. How would you calculate year-over-year profit growth?
   Compare current year profit with previous year profit.
   Example:

   (SUM([Profit]) - LOOKUP(SUM([Profit]),-1))
   / LOOKUP(SUM([Profit]),-1)
   

2. How would you identify customers with highest return orders?
   Count returned orders by customer and rank them.
   Example:

   COUNT([Return Flag])
   

3. How would you display only profitable regions?
   Filter regions where total profit is positive.
   Example:

   SUM([Profit]) > 0
   

4. How would you calculate average revenue per product?
   Divide total sales by distinct products.
   Example:

   SUM([Sales]) / COUNTD([Product ID])
   

5. How would you identify orders with unusually high sales?
   Compare sales against average plus standard deviation.
   Example:

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

6. How would you create a sales forecast trend?
   Use Analytics pane and enable Forecast option.
   Example:

   SUM([Sales])
   

7. How would you calculate median sales value?
   Use MEDIAN aggregation on Sales.
   Example:

   MEDIAN([Sales])
   

8. How would you identify products sold in all regions?
   Compare distinct region count with total region count.
   Example:

   COUNTD([Region]) = 4
   

9. How would you create a customer aging analysis?
   Calculate days since last purchase.
   Example:

   DATEDIFF('day',MAX([Order Date]),TODAY())
   

10. How would you display profit variance from target?
    Subtract target profit from actual profit.
    Example:

    SUM([Profit]) - SUM([Target Profit])

11. How would you identify top-selling products by state?
    Use RANK calculation partitioned by State.
    Example:

    RANK(SUM([Sales])) = 1

12. How would you calculate cumulative customer count over time?
    Use running total on distinct customers.
    Example:

    RUNNING_SUM(COUNTD([Customer ID]))