Analyze Customer Purchase Patterns Using SQL Query

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at DoorDash.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at DoorDash during technical interviews.

Question

orders

+----------+-------------+-------------+------------+------+
| order_id | customer_id | order_value | order_date | city |
+----------+-------------+-------------+------------+------+
| 101      | 1           | 120.50      | 2023-07-01 | LA   |
| 102      | 1           | 80.00       | 2023-07-18 | LA   |
| 103      | 2           | 200.00      | 2023-07-02 | NY   |
| 104      | 1           | 75.00       | 2023-08-01 | LA   |
| 105      | 3           | 50.00       | 2023-07-05 | SF   |
+----------+-------------+-------------+------------+------+

##### Scenario

E-commerce platform wants detailed insights into customer purchasing patterns over time.

##### Question

Write a SQL query that, for every order, returns:
1) order_id, customer_id, order_value, order_date;
2) the previous order_value for the same customer (lag);
3) the rank and percent_rank of the current order_value among that customer’s lifetime orders, ordered by order_date descending.

##### Hints

Use LAG, RANK, PERCENT_RANK window functions partitioned by customer_id and ordered by order_date.

PracHub · Accepted Answer

This question evaluates a candidate's competence with SQL data manipulation and windowing concepts, specifically using ordering and partitioning to compare and rank events within a customer's purchase history.

Quick Overview

Quick Overview