FIELD GUIDE
Customer discovery is not a hunt for compliments. It is a controlled way to replace one risky assumption with evidence from people who recently experienced the problem.
This guide takes you from a testable assumption to a clear next move: keep learning, narrow the segment, reframe the problem, run a stronger behavioral test, or stop. If the term is new to you, start with what customer discovery is.
01
Choose one assumption
02
Recruit the right people
03
Interview without pitching
04
Record the evidence
05
Choose the next test
STEP 01
Do not begin with “Is my idea good?” That question is too broad to test. Choose the belief that would damage the idea most if it were wrong—usually who has the problem, how painful it is, or what they already do about it.
ASSUMPTION TEMPLATE
We believe [specific segment] struggles with [problem] when [trigger]. Today they [work around it], which costs [time, money, or risk].
FICTIONAL B2B EXAMPLE
We believe finance leads at multi-entity marketing agencies struggle to reconcile invoices at month-end. Today they export data into spreadsheets and chase approvals in Slack, costing several hours per close.
Contradicted if: qualifying teams close quickly without manual reconciliation, a costly delay, or an active workaround.
FICTIONAL CONSUMER EXAMPLE
We believe parents of children with food allergies struggle to plan safe school lunches each Sunday. Today they cross-check labels and keep scattered notes, costing time and creating avoidable uncertainty.
Contradicted if: families reuse a stable meal list, rarely check labels, and do not see planning as a recurring problem.
Write down what would contradict the assumption before you speak to anyone. Otherwise, every polite answer will start looking like support.
STEP 02
Interview people who match the segment and have experienced the situation recently. Friends, generic “founders,” and people who merely like the idea are weak substitutes.
COPYABLE OUTREACH
“Hi [name] — I saw [relevant signal]. I’m speaking with [segment] to understand how they handle [situation]. Would you be open to a 20-minute conversation about the last time this came up and what you did?”
Track where qualified conversations come from. If the segment is almost impossible for you to reach, that is early evidence about distribution—not merely a recruiting problem.
STEP 03
Your job is to reconstruct real behavior, not sell the solution. Ask for specific stories, then follow the sequence of events, decisions, workarounds, and consequences.
DON’T ASK
“Would you pay €30 per month for this?”
ASK INSTEAD
“What did you spend the last time you tried to solve this?”
This past-behavior approach follows practical guidance from Y Combinator: learn from users before pitching to them.
STEP 04
Write up every conversation while it is fresh. Keep conclusions tied to a participant and a concrete incident so a memorable quote cannot overpower the rest of the evidence.
| FIELD | WHAT TO CAPTURE |
|---|---|
| Participant | Segment, role, and user/buyer status |
| Incident | The most recent specific event and its trigger |
| Consequence | Frequency and cost in time, money, delay, or risk |
| Behavior | Workaround, spending, switching attempt, or inaction |
| Counterevidence | Facts that weaken or contradict your assumption |
| Next step | Retest, narrow, prototype, pause, or stop |
Compare evidence only within the same segment. Look for recurring behavior and contradictions; do not convert a few enthusiastic quotes into a fake scientific score.
STEP 05
There is no universal interview count that validates a startup. Decide from the quality and consistency of evidence, the gaps that remain, and the cost of the next experiment.
New themes are still appearing or important buyer roles remain unknown.
Pain clusters in a smaller segment, or the incidents are real but your assumed cause is wrong.
Repeated behavior supports the problem. Test a concierge service, paid pilot, deposit, preorder, or priced landing page next.
Good interviews in the exact segment reveal no recurring incident, costly consequence, workaround, or meaningful commitment.
A positive result does not mean “build everything.” It means the idea earned a stronger, more expensive test.
FICTIONAL EXAMPLE
A founder assumes that small agencies struggle with month-end invoice reconciliation. Interviews with single-entity agencies reveal annoyance but no serious workaround or budget. That is counterevidence—not a reason to improve the pitch.
The pattern changes among multi-entity agencies. Finance leads describe repeated delays, spreadsheet checks, approval bottlenecks, and several hours of manual work every month. The pain is narrower than expected, but more consequential.
NEXT DECISION
Resegment around multi-entity agencies and manually deliver one reconciliation cycle before building software. Measure access to the required data, time saved, and willingness to pay for the next cycle.
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