Lighthouse

Level 7 · Boss: the category P&L review

From Laura Bennett, Head of Finance

“For the quarterly review I need a 2025 P&L by category: first what share of sales our cost data covers, then gross margin per category, then what's left after refunds. Catherine will ask which category is really our most profitable, so the table has to hold up.”

Your goal

Step 1 of 3. Return one row with lines (all lines in l), lines_without_cost (lines whose unit_cost is NULL), net_sales (all net), net_sales_without_cost (net on lines with no cost) and coverage_pct (net on lines with a cost × 100 / all net). Round money and percent to 2.

Read from the products tablenot done yet
Read from the orders tablenot done yet
Show exactly lines lines_without_cost net_sales net_sales_without_cost coverage_pctnot done yet

Step 1 · your query

SQL

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Reference solution

ResultPreview of products · press Run to see yours

Preview of products
product_id	name	category	subcategory	unit_price
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00
102	Alder Oak Coffee Table	Furniture	Tables	919.00
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00
104	Upland Oak Bookcase	Furniture	Storage	429.00

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Step 2 · your query

SQL

Loading the editor…

Reference solution

ResultPreview of products · press Run to see yours

Preview of products
product_id	name	category	subcategory	unit_price
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00
102	Alder Oak Coffee Table	Furniture	Tables	919.00
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00
104	Upland Oak Bookcase	Furniture	Storage	429.00

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Step 3 · your query

SQL

Loading the editor…

Reference solution

ResultPreview of products · press Run to see yours

Preview of products
product_id	name	category	subcategory	unit_price
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00
102	Alder Oak Coffee Table	Furniture	Tables	919.00
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00
104	Upland Oak Bookcase	Furniture	Storage	429.00

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Tables

Harbor & Pine store data, ready to query.

products120 rows · 8 columns

product_idinteger
namevarchar
categoryvarchar
subcategoryvarchar
unit_pricedecimal
unit_costdecimal
launched_ondate
is_activeboolean

First 5 rows of products
product_id	name	category	subcategory	unit_price	unit_cost	launched_on	is_active
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00	NULL	2023-09-11	true
102	Alder Oak Coffee Table	Furniture	Tables	919.00	503.50	2024-05-16	true
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00	429.87	2023-05-27	true
104	Upland Oak Bookcase	Furniture	Storage	429.00	214.70	2022-12-20	true
105	Avery Leather Bed Frame	Furniture	Beds	449.00	232.70	2021-08-31	true

orders12,000 rows · 7 columns

order_idinteger
customer_idinteger
order_datetimestamp
statusvarchar
channelvarchar
shipping_feedecimal
coupon_codevarchar

First 5 rows of orders
order_id	customer_id	order_date	status	channel	shipping_fee	coupon_code
1001	125	2023-01-01 20:51:19	completed	web	0.00	NULL
1002	156	2023-01-02 07:58:46	completed	web	0.00	NULL
1003	22	2023-01-02 10:25:27	completed	marketplace	4.99	WELCOME10
1004	48	2023-01-02 11:21:51	completed	marketplace	4.99	WELCOME10
1005	82	2023-01-02 11:43:36	completed	web	0.00	WELCOME10

order_items30,338 rows · 6 columns

order_item_idinteger
order_idinteger
product_idinteger
quantityinteger
unit_pricedecimal
discount_pctdecimal

First 5 rows of order_items
order_item_id	order_id	product_id	quantity	unit_price
1	1001	121	9	31.99
2	1001	154	3	11.99
3	1002	154	4	11.99
4	1002	194	1	149.00
5	1002	193	2	19.99

returns1,673 rows · 5 columns

return_idinteger
order_item_idinteger
returned_ondate
reasonvarchar
refund_amountdecimal

First 5 rows of returns
return_id	order_item_id	returned_on	reason	refund_amount
1	14	2023-01-10	damaged	83.69
2	42	2023-01-10	wrong_item	19.99
3	105	2023-01-14	wrong_item	10.99
4	24	2023-01-16	changed_mind	26.99
5	126	2023-01-16	late	20.99

customers2,018 rows · 9 columns

customer_idinteger
first_namevarchar
last_namevarchar
emailvarchar
cityvarchar
statevarchar
signup_datedate
segmentvarchar
referral_sourcevarchar

First 5 rows of customers
customer_id	first_name	last_name	email	city	state	signup_date	segment	referral_source
1	Owen	Hudson	owen.hudson@icloud.com	San Francisco	CA	2022-06-02	consumer	search
2	Douglas	Mendoza	dmendoza69@gmail.com	Atlanta	GA	2022-06-02	consumer	NULL
3	Henry	Brooks	hbrooks@lakesidecafe.com	Los Angeles	CA	2022-06-04	business	NULL
4	Brian	Graham	bgraham@bluecedarhomes.com	Seattle	WA	2022-06-06	business	pinterest
5	Kyle	Jimenez	kjimenez27@yahoo.com	Indianapolis	IN	2022-06-07	consumer	NULL

employees60 rows · 8 columns

employee_idinteger
first_namevarchar
last_namevarchar
departmentvarchar
titlevarchar
manager_idinteger
hire_datedate
salaryinteger

First 5 rows of employees
employee_id	first_name	last_name	department	title	manager_id	hire_date	salary
1	Catherine	Hale	Executive	Chief Executive Officer	NULL	2016-03-01	285000
2	Robert	Kim	Executive	Chief Operating Officer	1	2017-01-09	235000
3	Megan	Collins	Sales	Head of Sales	1	2018-04-16	172000
4	Chloe	Gutierrez	Sales	Account Executive	3	2020-01-21	72000
5	Frank	Bell	Sales	Account Executive	3	2023-05-21	73000

web_sessions40,000 rows · 7 columns

session_idinteger
customer_idinteger
started_attimestamp
devicevarchar
sourcevarchar
pages_viewedinteger
convertedboolean

First 5 rows of web_sessions
session_id	customer_id	started_at	device	source	pages_viewed	converted
1	NULL	2023-01-01 23:02:24	mobile	paid	1	false
2	18	2023-01-01 15:07:49	desktop	paid	1	false
3	NULL	2023-01-01 16:55:46	desktop	direct	7	false
4	NULL	2023-01-01 12:43:28	mobile	organic	3	false
5	NULL	2023-01-01 13:06:21	mobile	social	2	false

marketing_spend3,276 rows · 3 columns

spend_datedate
channelvarchar
amountdecimal

First 5 rows of marketing_spend
spend_date	channel	amount
2023-01-01	paid	492.99
2023-01-01	email	37.38
2023-01-01	social	200.53
2023-01-02	paid	709.13
2023-01-02	email	64.13

The lesson

A P&L in three blocks

A category P&L for a review has a fixed shape: what the numbers cover, gross margin, and contribution after the variable costs you can measure. Each step of this boss is one block, all on 2025.

Step 1: coverage first

Nine products have no unit cost. Their lines can’t have a margin, so every margin figure covers less than all of sales. Before showing any margin, say how much it covers:

SUM(net) FILTER (WHERE unit_cost IS NOT NULL) * 100.0 / SUM(net)

FILTER restricts one aggregate to some rows while the others still see them all, so one query gives the total, the uncovered part and the share.

Step 2: gross margin per category

The same calculation as level 1, now in SQL on one year. Filter to the lines with a cost, group by category, and divide sums: SUM(net - cogs) * 100.0 / SUM(net). Sort by margin dollars, because the first question in a review is where the money comes from.

Step 3: contribution

Take refunds off too, as in level 2. A category with a fine gross margin and heavy returns can end up below one with a slightly lower margin and few returns. Sort by contribution % this time: the question has changed to “where does a dollar of sales leave the most”.

Reading the whole table

The three blocks together tell a story no single number does. Outdoor is the biggest category in sales, margin dollars and contribution dollars, and the weakest per dollar once returns are counted. Kitchen is the reverse: smaller, and the most efficient. Both statements belong in the review, next to the coverage footnote.

Common mistakes

Leaving the no-cost lines in step 2. cogs is NULL on them; SUM skips NULLs, so their sales count as pure margin.
Dividing by the wrong total. Contribution % divides by the category’s own net sales, not by the store total.
Ranking by one column and calling it the winner. Dollars and rates answer different questions.

Level 7 · Boss: the category P&L review

Your goal

Step 1 · your query

Reference solution

Mote checks your result

Step 2 · your query

Reference solution

Mote checks your result

Step 3 · your query

Reference solution

Mote checks your result

What Laura gets, and why

Tables

The lesson

A P&L in three blocks

Step 1: coverage first

Step 2: gross margin per category

Step 3: contribution

Reading the whole table

Common mistakes

Lantern lit!

Level 7 · Boss: the category P&L review

The request

Your goal

Step 1 · your query

Reference solution

Mote checks your result

Step 2 · your query

Reference solution

Mote checks your result

Step 3 · your query

Reference solution

Mote checks your result

What Laura gets, and why

Tables

The lesson

A P&L in three blocks

Step 1: coverage first

Step 2: gross margin per category

Step 3: contribution

Reading the whole table

Common mistakes

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