The request

From Andrew Ramos, Marketing Manager
Your goal
Return one row with: aov (2025 net revenue / 2025 booked orders), orders_per_customer (2025 booked orders / customers with a booked order in 2025), annual_churn_pct (share of customers with a booked order in 2024 who have none in 2025, × 100), lifespan_years (100 / annual_churn_pct), revenue_ltv (aov × orders_per_customer × lifespan_years) and margin_ltv (revenue_ltv × 0.5384, the 2025 gross margin rate). Compute everything from unrounded values and round each output to 2. The CTE order_rev (one row per booked order with its net revenue) is in the starter.
- Read from the
orderstablenot done yet - Read from the
order_itemstablenot done yet - Show exactly
aovorders_per_customerannual_churn_pctlifespan_yearsrevenue_ltvmargin_ltvnot done yet
Your query
Loading the editor…
Reference solution
| order_id | customer_id | order_date | status | channel |
|---|---|---|---|---|
| 1001 | 125 | 2023-01-01 20:51:19 | completed | web |
| 1002 | 156 | 2023-01-02 07:58:46 | completed | web |
| 1003 | 22 | 2023-01-02 10:25:27 | completed | marketplace |
| 1004 | 48 | 2023-01-02 11:21:51 | completed | marketplace |
Mote checks your result
Press Run. Each row that matches the goal becomes a firefly in your lantern.
What Andrew gets, and why
Tables
Harbor & Pine store data, ready to query.
orders12,000 rows · 7 columns
order_idintegercustomer_idintegerorder_datetimestampstatusvarcharchannelvarcharshipping_feedecimalcoupon_codevarchar
| 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_idintegerorder_idintegerproduct_idintegerquantityintegerunit_pricedecimaldiscount_pctdecimal
| order_item_id | order_id | product_id | quantity | unit_price | discount_pct |
|---|---|---|---|---|---|
| 1 | 1001 | 121 | 9 | 31.99 | 0.00 |
| 2 | 1001 | 154 | 3 | 11.99 | 0.00 |
| 3 | 1002 | 154 | 4 | 11.99 | 0.00 |
| 4 | 1002 | 194 | 1 | 149.00 | 0.00 |
| 5 | 1002 | 193 | 2 | 19.99 | 0.00 |
returns1,673 rows · 5 columns
return_idintegerorder_item_idintegerreturned_ondatereasonvarcharrefund_amountdecimal
| 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_idintegerfirst_namevarcharlast_namevarcharemailvarcharcityvarcharstatevarcharsignup_datedatesegmentvarcharreferral_sourcevarchar
| customer_id | first_name | last_name | 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 | |
| 5 | Kyle | Jimenez | kjimenez27@yahoo.com | Indianapolis | IN | 2022-06-07 | consumer | NULL |
products120 rows · 8 columns
product_idintegernamevarcharcategoryvarcharsubcategoryvarcharunit_pricedecimalunit_costdecimallaunched_ondateis_activeboolean
| 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 |
employees60 rows · 8 columns
employee_idintegerfirst_namevarcharlast_namevarchardepartmentvarchartitlevarcharmanager_idintegerhire_datedatesalaryinteger
| 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_idintegercustomer_idintegerstarted_attimestampdevicevarcharsourcevarcharpages_viewedintegerconvertedboolean
| 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_datedatechannelvarcharamountdecimal
| spend_date | channel | amount |
|---|---|---|
| 2023-01-01 | paid | 492.99 |
| 2023-01-01 | 37.38 | |
| 2023-01-01 | social | 200.53 |
| 2023-01-02 | paid | 709.13 |
| 2023-01-02 | 64.13 |
The lesson
From history to a forecast
Historic LTV only covers customers who have already had time to buy. Planning needs a number for a customer acquired today. The classic back-of-envelope formula multiplies three things:
- AOV, net revenue per order;
- purchase frequency, orders per active customer per year;
- expected lifespan, how many years a customer keeps buying.
AOV × frequency is what an active customer spends in a year. Times lifespan, it is what they spend in total.
Lifespan from churn
Nobody observes lifespan directly; it comes from churn. If a share c of this year’s customers does not come back next year, and that share stays constant, the average customer stays 1 / c years. Of the 1,003 customers with a booked order in 2024, 238 have none in 2025: annual churn is 23.73%, so the expected lifespan is 4.21 years.
-- 2024 buyers with no 2025 order
FROM c24 LEFT JOIN c25 USING (customer_id)
WHERE c25.customer_id IS NULL
Revenue LTV and margin LTV
With 2025’s AOV of $503.82 and 3.01 orders per buyer, revenue LTV is $6,385.71. But the store does not keep revenue: it pays for the products. Multiplying by the gross margin rate (53.84% of 2025 net sales on kept lines with a known product cost) gives the margin LTV, $3,438.07. That is the number to set against acquisition cost, because CAC is paid out of margin.
What the formula assumes
Every input is an average, and the formula assumes they stay fixed for years: same basket size, same frequency, a constant churn rate. Reality breaks each one. New customers buy less often than the loyal base that dominates the 2025 frequency, churn is usually highest in a customer’s first year, and 4.21 years is longer than the data itself. Treat the result as an order of magnitude, and show how much it moves if churn is 30% instead of 24%.
Common mistakes
- Rounding the inputs first. Rounded AOV, frequency and lifespan multiplied together give $6,384.46, more than a dollar off. Round only the outputs.
- Frequency over all customers ever. Orders per year must divide by customers active that year.
- Calling revenue LTV “profit”. It is not; say which version you report.
Interview note
“How would you estimate LTV for a new e-commerce store?” Give this formula, say that lifespan comes from 1 / churn, switch to margin, and name the assumptions. That is a complete answer.
Lantern lit!
Practised: ltvpredictive ltvaovpurchase frequencychurnlifespanmargin
- Solved
- No hints
- First run
