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N015-M3 Tier 2 · Core SQL · medium ecommerce · Brightlane

Return each `status` and its unique-customer count for statuses that have been placed by **more than ten** different customers

Part of HAVING in SQL

The problem

Brightlane's CRM team is identifying the most widely purchased order statuses — those touching the broadest customer base.

Write a query to return each status and its unique-customer count for statuses that have been placed by more than ten different customers.

Assumptions:

  • The orders table contains every order Brightlane has processed.
  • A customer with multiple orders in the same status counts once for that status (not once per order).
  • The threshold (> 10) applies to the per-status unique-customer count.

Output:

  • One row per qualifying status, with columns status and unique_customers.
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
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Solution query
SELECT
  status,
  COUNT(DISTINCT customer_id) AS unique_customers
FROM
  orders
GROUP BY
  status
HAVING
  COUNT(DISTINCT customer_id) > 10

The shape

The statuses are the groups; the per-group metric is the count of distinct customers, not the count of orders. COUNT(DISTINCT customer_id) collapses repeat customers to one per status, and HAVING COUNT(DISTINCT customer_id) > 10 keeps only the statuses that span a broad customer base. delivered reaches 59 unique customers, shipped reaches 17, pending reaches 11. Other statuses fall below the threshold and drop out.

Clause by clause

  • SELECT status, COUNT(DISTINCT customer_id) AS unique_customers returns each status with its unique-customer count. The DISTINCT inside COUNT is what makes a customer with three delivered orders contribute 1 to delivered's count rather than 3.
  • FROM orders is the source set.
  • GROUP BY status partitions the orders by their status value. After this clause, each row in the working set represents one status with its underlying order rows aggregated behind it.
  • HAVING COUNT(DISTINCT customer_id) > 10 filters those status rows by the unique-customer metric. Statuses placed by ten or fewer distinct customers drop out; eleven or more survive.

Why this and not COUNT(*)

COUNT(*) and COUNT(DISTINCT customer_id) answer different questions on the same data. COUNT(*) would return the number of orders in each status — delivered would land somewhere above 100 because most orders are delivered and many customers ordered multiple times. COUNT(DISTINCT customer_id) returns the number of customers behind those orders, which is what "placed by more than ten different customers" actually asks. A status with a thousand orders from three customers would clear a COUNT(*) > 10 bar but fail the breadth test the CRM team is running.

The shape generalises. Once an aggregate is computing a per-group number, HAVING can compare it to anything — a literal threshold, another aggregate, even an arithmetic combination of aggregates. The constraint is only that the left side has to be an aggregate, not a raw column reference.

You practiced filtering on a COUNT(DISTINCT col) aggregate. The composability of HAVING with any aggregate is the recurring shape — once an aggregate produces a per-group number, HAVING can compare it to anything.

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