N025-M2 Tier 2 · Core SQL · medium ecommerce · Brightlane

Return the customer ID and name for every customer with no purchase history

Part of Subqueries in WHERE (IN, EXISTS, ANY, ALL) in SQL

The problem

Brightlane's reactivation campaign targets customers who have never placed an order.

Write a query to return the customer ID and name for every customer with no purchase history.

Assumptions:

  • The customers table contains every customer Brightlane has on file.
  • The orders table contains every order; customer_id identifies the buyer.
  • Brightlane's orders.customer_id column is never missing — every order is tied to a real customer.

Output:

  • One row per customer with no orders, with columns id and name.
Schema · ecommerce 5 tables
categories
id integer
name text
parent_id? integer
products
id integer
name text
category_id integer
price numeric
stock_qty integer
attributes? jsonb
order_items
id integer
order_id integer
product_id integer
quantity integer
unit_price numeric
customers
id integer
name text
email text
city? text
country text
created_at timestamptz
is_active boolean
orders
id integer
customer_id integer
ordered_at timestamptz
status text
total_amount numeric

Run previews · Check grades

Write a query, then run it to see results here.

Worked solution Try it yourself first
Solution query
SELECT
  id,
  name
FROM
  customers
WHERE
  id NOT IN (
    SELECT
      customer_id
    FROM
      orders
  )

The shape

NOT IN (subquery) inverts the membership test. The inner query collects every customer_id that has placed an order, and the outer keeps customers whose id is not in that set. The eight result rows are customers Brightlane has on file with zero orders against their name.

Clause by clause

  • SELECT id, name FROM customers reads every customer on file. The filter trims this to the ones that have never appeared in orders.
  • WHERE id NOT IN (SELECT customer_id FROM orders) runs the inner query first, builds the set of all customer_id values across orders, and keeps an outer customer row only when its id is absent from that set. Customers 63 through 70 come through — none of them have an order recorded against their id.

The trap

NOT IN is safe here only because the assumptions guarantee orders.customer_id is never missing. If even one row in orders had a NULL in customer_id, this query would return zero rows. Not eight, not most-of-eight, zero.

The reason is three-valued logic. PostgreSQL can't confirm that customer 63's id is "not equal to NULL" because comparisons with NULL are undefined. The NOT IN test collapses to NULL for every outer row, the WHERE treats NULL as falsy, and no row passes.

The fix when the inner column might be nullable is to add WHERE customer_id IS NOT NULL to the subquery, or to rewrite the negation as NOT EXISTS. Brightlane's schema is clean, so the bare NOT IN works here. The same shape against a nullable column is one of the most common silent-zero-rows bugs in SQL.

You practiced NOT IN with a subquery and saw it produce the right answer because the inner column has no missing values. The recurring shape any time a presence/absence question can be expressed by membership in a set.

How you actually get good at SQL

Reading explains SQL. Writing it, over and over with instant feedback, is what makes you fluent.

That's the whole SQLMaxx loop: 600+ real problems, instant AI feedback, mastery you can actually see, and spaced review that won't let you forget.

A stack of SQL practice problem cards, the top card showing an employees table.
615 problems · 66 concepts

Real problems. Not toy examples.

615 hand-built problems spanning all 66 concepts, from basic SELECTs to window functions, built on real schemas and real business questions, the kind you'll actually get asked on the job. Enough reps to make SQL automatic.

A retro computer showing a SQL query marked correct with a green checkmark.
Instant AI feedback

Write a query. Know if it's right in one second.

No copying an answer and hoping it clicked. The AI grader checks your real query against real data, catches exactly what's wrong, and explains the fix in plain English, like a senior analyst reading over your shoulder on every problem.

A circular mastery progress dial filling from blue to green, the SQLMaxx diamond at its center.
Mastery tracking

Stop guessing whether you actually know it.

SQLMaxx tracks every concept and shows you what you've mastered and what's still shaky. Your skills fill in one concept at a time, so 'I think I get joins' becomes something you can prove.

A SQL query editor circled by a blue return arrow with a clock, scheduled to come back for review.
Spaced review

Learn it once. Keep it for good.

Most of what you learn this week fades by next week. So when a concept comes due for review, SQLMaxx hands you a fresh problem to solve from a blank editor, not a flashcard to re-read. A research-backed spaced-repetition algorithm (FSRS) times each return for right before you'd forget, so your SQL is still there months later, when the interview or the job actually needs it.

Practice, feedback, mastery, review. That's the loop that turns reading into real skill.

Start free

No account, no credit card. Start solving in under a minute.