Customer Discovery for Biotech Founders
Biotech founders sometimes assume customer discovery is less relevant because the science is complex or the product is years from market. The opposite is often true. Long development cycles make early commercial mistakes more expensive.
Who Is the Customer?
In healthcare, the user, buyer, payer, beneficiary, and decision-maker may all be different. Customer discovery should map the ecosystem rather than interview one convenient stakeholder.
- Clinicians and end users
- Patients or caregivers where appropriate
- Laboratory or technical operators
- Hospital administrators and procurement
- Payers and reimbursement experts
- Pharma or strategic partners
- Distributors or channel partners
- Technology-transfer and licensing stakeholders
Ask about Behavior, Not Praise
'Would you use this?' produces weak evidence. Better questions uncover current workflow, unmet need, cost, decision criteria, switching barriers, and the consequences of the problem.
- How is this problem handled today?
- What is most frustrating or expensive about the current approach?
- When does the problem become important enough to act?
- Who approves a change?
- What evidence would be required before adoption?
- What would prevent use even if the technology worked?
Do Not Pitch during Discovery
The purpose is to learn, not to persuade. If the founder spends most of the call explaining the technology, the interview often confirms the founder's assumptions rather than testing them.
Turn Interviews into Development Decisions
Customer discovery becomes valuable when findings change something: the initial indication, product features, comparator, endpoint, workflow, price hypothesis, evidence plan, or business model.
Look for Patterns, Not Compliments
One enthusiastic expert is not a market. Repeated evidence across stakeholders is more important than a single strong reaction. Document assumptions before interviews and record what changed afterward.
BYB Takeaway
Customer discovery is an R&D activity for the business model. It should reduce commercial uncertainty just as experiments reduce scientific uncertainty.
The earlier you discover that the market needs something different, the cheaper it is to change.
