Direct answer
In 30 days I would test one question: will US parents of high-school students pay for a math tutoring app when free alternatives exist? I would set stop and go thresholds before collecting data, start with the cheapest tests of the riskiest assumption (willingness to pay), and use interviews and a pilot to learn why. Thirty days can catch a clear no or a promising lead. It cannot give a precise demand figure.
Desk research means reading published material (education data, competitor listings, reviews) instead of collecting new data. Qualified visitors are visitors who match the target buyer, here parents of grades 9-12 reaching the page from a targeted ad. Unit economics means what one paying family earns after the costs of serving and winning them.
Who matters. The student uses the app, a parent usually pays, and a school or teacher might buy. I start with parents as payers because that is the riskiest link.
Plan (four phases)
| Phase | Days | Activities | Output |
|---|
| 1. Frame | 1-7 | Desk research on public education data, competitors, app-store reviews and parent forums. Write hypotheses and stop/go thresholds. | One-page hypotheses and thresholds |
| 2. Listen | 8-14 | 12 parent interviews and 4 teacher or tutor interviews, about past behaviour (what they tried, paid, stopped). | Evidence of past spending |
| 3. Test intent | 15-21 | Priced fake-door landing page (a sign-up page for a product that is not built) with a small ad test aimed at parents of grades 9-12. | Sign-up rate at a shown price |
| 4. Test commitment | 22-30 | Concierge pilot: tutor 6 students by hand and ask parents to pay or commit to a second week. Write the decision memo. | Go, change, or stop decision |
The first test is phase 2 and phase 3 together, because they are cheap and aim at willingness to pay.
Illustrative stop/go thresholds (set before the work; adjust to the unit economics)
- Go: at least 6 of 12 parents describe paying or trying a paid math aid in the past year; fake-door sign-up rate at or above 4% of qualified visitors at the shown price; at least 3 of 6 pilot families commit to continue.
- Stop: fewer than 3 of 12 parents have spent anything, and sign-up under 1%.
- In between: change the buyer (for example teachers or schools) or the problem (test prep) and retest.
Where the thresholds come from (illustrative inputs). Start from unit economics, not from a favourite number:
- Price $12 a month, a family stays about 6 months, so a paying family is worth about $72 (the margin after costs would reduce this; use your own).
- We will spend up to about $30 (roughly 40% of that) to win one paying family.
- Ad budget $600 at $0.60 per qualified visitor buys 1,000 visitors.
- If half of sign-ups pay (the 3 of 6 pilot line), cost per paying family = $0.60 / (sign-up rate x 0.5). At 4%: 0.60 / 0.02 = $30, exactly affordable. At 1%: 0.60 / 0.005 = $120, four times too much.
So 4% sign-up is go (40 sign-ups from 1,000 visitors), and under 1% (fewer than 10) is stop. The interview lines are a judgement: a clear majority (6 of 12) already paying for help, versus fewer than a quarter (under 3 of 12, since 3 of 12 is exactly a quarter and sits in the in-between zone) is a gap too wide for 12 conversations to blur. To set your own, write down the price, the lifetime, and what you can spend to win a customer, then work backwards the same way.
With 12 interviews these are directional. They are built to catch a clear no, not to estimate a percentage.
Things a strong plan accounts for
- Seasonality: demand rises with the school year and exams, so say when the 30 days fall.
- Minors: get parental consent for anyone under 18 and interview parents first.
- Free alternatives: ask what parents use now and why it falls short, because that is your competitor.
Pitfalls
Counting friends and family, measuring praise instead of payment, and moving the thresholds after seeing results.