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Month-over-Month Customer Growth

MediumFreeQuerying BasicsAggregation & GroupingWindow FunctionsDate Functions

The marketing team wants a monthly signup momentum report. For each signup_year and signup_month with new customers, show new_signups (COUNT of customers that month), previous_month_signups (last month's count within the same year), difference (this month minus last), and mom_growth_pct (percentage change rounded to 2 decimals). Partition by year so January always resets (LAG returns NULL — that's intentional, not a bug — it's how you say "compare me within my own year only"). Sort by signup_year, then signup_month.

The analytical pattern here is identical to any MoM aggregation: sales MoM, active-user MoM, support-ticket MoM — same shape, different column.

_Inspired by a thread on MoM analysis by [@FortuneDataGuy](https://x.com/FortuneDataGuy). The real skill isn't calculating MoM — it's interpreting what the number means in context. A 100% MoM jump on a small base (1 → 2) is a different story than a 5% jump on a large base (10,000 → 10,500)._

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Schema

customers

customer_id	name	email	signup_date	membership	total_orders
1	John Smith	john.smith@email.com	2023-01-15	Gold	15
2	Emma Wilson	emma.wilson@email.com	2023-03-20	Silver	8
3	Michael Brown	michael.brown@email.com	2023-02-10	Gold	12

Expected output: ~15 rows — one per (year, month), with Jan of each year showing NULL for previous_month_signups

Hint

You need LAG(COUNT(*)) OVER (PARTITION BY year ORDER BY month) — but COUNT has to happen BEFORE LAG can use it. Wrap the GROUP BY aggregation in a subquery, then compute LAG and the difference in the outer query. Use strftime('%Y', signup_date) and strftime('%m', signup_date) for year/month. Subtle: PARTITION BY year means every January's LAG returns NULL — that's the 'reset' pattern. If you wanted MoM across the full timeline (Dec 2023 → Jan 2024 as a real comparison), you'd drop the PARTITION BY.

Concepts

SELECT GROUP BY Aggregation Window Functions LAG Date Functions

Practise the topic: SQL practice questions · GROUP BY exercises · Window function practice · Date function practice

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Month-over-Month Customer Growth

Schema

Hint

Concepts

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