Quick Overview

A PostgreSQL interview problem about measuring the monthly percentage of customers who place more than 30 deliveries. It tests calendar-month aggregation, distinct-customer denominators, threshold logic, and precise percentage calculation.

Calculate the Monthly Share of High-Frequency Customers

Company: DoorDash

Role: Data Scientist

Category: Data Manipulation (SQL/Python)

Difficulty: easy

Interview Round: Technical Screen

# Calculate the Monthly Share of High-Frequency Customers Write one PostgreSQL SELECT statement or CTE query. Do not create, alter, or modify tables. ## Schema delivery_orders | column | type | description | |---|---|---| | delivery_id | integer | Unique delivery | | order_place_time | timestamp | Order placement time | | customer_id | integer | Customer | | restaurant_id | integer | Restaurant | | dasher_id | integer | Courier | ## Task A high-frequency customer places more than 30 deliveries in a calendar month. For every month, calculate the percentage of distinct customers who ordered that month and were high frequency in that same month. ## Required Output Return order_month as a date, monthly_customers, high_frequency_customers, and high_frequency_pct rounded to two decimal places. Sort by month ascending. ## Constraints - Count deliveries, not days. - A customer can be high frequency in one month and not another. - The denominator includes every distinct customer with at least one delivery that month. ```hint Aggregate customer-months first Create one row per month and customer with an order count, then aggregate the high-frequency flag. ```

Quick Answer: A PostgreSQL interview problem about measuring the monthly percentage of customers who place more than 30 deliveries. It tests calendar-month aggregation, distinct-customer denominators, threshold logic, and precise percentage calculation.

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