Where Are New Signups Coming From?
Kindled, a small direct-to-consumer brand, is about to raise its advertising budget and wants to see which acquisition channel has actually been bringing people in first. The growth lead has asked for the signup count per channel.
Each user row records the channel that brought that person in, as a short text label. There is no separate list of channels anywhere in the dataset, so the set of channels has to come out of the user rows themselves — which also means a channel that has never produced a signup is invisible here.
users — one row per registered user. source is the acquisition channel that brought them in.
| id | name | source | signup_date |
|---|---|---|---|
| 1 | Aiden Cole | organic | 2023-05-01 |
| 2 | Bianca Reyes | paid_search | 2023-05-02 |
| 3 | Carlos Mora | organic | 2023-05-03 |
| 4 | Delia Frank | referral | 2023-05-04 |
| 5 | Ewan Blake | paid_search | 2023-05-05 |
| 6 | Fiona Grey | organic | 2023-05-06 |
| 7 | Gus Herrera | referral | 2023-05-07 |
| 8 | Hana Ito | paid_search | 2023-05-08 |
The table already exists in the database — there is nothing to create or load.
Task: Write a query returning two columns, source and num_users, with one row for each channel that appears in the table. A channel with no signups produces no row. Rows come back in alphabetical order of source.
Example output — shape only; the figures below are invented, not this data's answer.
| source | num_users |
|---|---|
| organic | 12 |
| paid_search | 5 |
| referral | 9 |
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