Top Tableau Scenario-Based Interview Questions Set - 16 (1- 5)

 

1. How would you calculate Customer Retention Rate in Tableau?

Calculate customers who purchased in both current and previous periods divided by total customers.

Example:

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

A retained customer can be identified using a Set or LOD calculation.

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2. How would you identify the Top 3 Products within each Category?

Use Rank table calculation partitioned by Category.

Example:

RANK(SUM([Sales])) <= 3

Set Compute Using = Product and Restart Every = Category.

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3. How would you calculate a customer's first purchase date?

Use a FIXED LOD expression.

Example:

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

This returns the first purchase date regardless of filters in the view.

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4. How would you show customers whose sales are above their regional average?

Compare customer sales against the average sales within the region.

Example:

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

Compute using Customer and partition by Region.

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5. How would you identify the Bottom 10 Products by Profit?

Use Rank on Profit in ascending order.

Example:

RANK(SUM([Profit]),'asc') <= 10

Filter TRUE to display the 10 least profitable products.

Top Tableau Scenario-Based Interview Questions Set - 15 (1- 8)

 

How would you identify customers who purchased in consecutive months?

Use a table calculation to compare purchase months for each customer.

Example:

DATEDIFF(
   'month',
   LOOKUP(MIN([Order Date]),-1),
   MIN([Order Date])
) = 1

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2. How would you calculate the percentage of orders shipped late?

Divide late orders by total orders.

Example:

SUM(
IF [Ship Date] > [Required Date]
THEN 1
ELSE 0
END
)
/
COUNT([Order ID])

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3. How would you identify the customer with the highest lifetime sales?

Use a FIXED LOD to calculate total sales per customer and rank them.

Example:

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

Rank:

RANK(
{ FIXED [Customer ID] : SUM([Sales]) }
)
= 1

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4. How would you calculate average monthly profit?

Aggregate profit at month level and average it.

Example:

WINDOW_AVG(SUM([Profit]))

Or:

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

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5. How would you identify regions where sales exceeded target?

Compare actual sales against target.

Example:

SUM([Sales]) > SUM([Target Sales])

Variance:

SUM([Sales]) - SUM([Target Sales])

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6. How would you find customers who have not purchased in the last 6 months?

Calculate days since the last purchase.

Example:

DATEDIFF(
'month',
{ FIXED [Customer ID] : MAX([Order Date]) },
TODAY()
) > 6

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7. How would you calculate the average gap between customer orders?

Find the difference between consecutive order dates.

Example:

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

Then apply:

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

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8. How would you identify the most profitable customer in each region?

Rank customers by profit within each region.

Example:

RANK(SUM([Profit])) = 1

Set Compute Using = Customer and Partition By = Region.