Who actually has your problem?
You can't sell to "someone who needs this."
You know your research has commercial potential.
You can see the applications. The problems it could solve. The industries it could transform.
But here’s the question that stops most academic entrepreneurs dead in their tracks:
Who would actually pay for this?
Not in theory. Not “eventually.” Not “lots of people could benefit from this.”
Who specifically, by name and job title, has the problem your research solves badly enough that they’d pay to fix it?
Most academics answer this question by listing possibilities: “Healthcare systems, manufacturers, government agencies, research labs...”
That’s not a customer segment. That’s a brainstorming session.
And the longer you stay in brainstorming mode, the longer your research stays on the shelf.
Here’s what’s actually happening: you’re skipping the hardest question in academic entrepreneurship. You’re trying to build a solution before you’ve identified who has the problem.
This isn’t bad. It’s just training.
Academic research starts with a gap in the literature, not a gap in someone’s budget. You were taught to ask “What hasn’t been studied?” not “Who’s losing money because this doesn’t exist yet?”
Commercial work flips that entirely. You can’t validate a market by pointing to potential applications. You have to find actual people who will tell you, “Yes, this is a problem I have right now, and here’s what I’m currently doing about it.”
That specificity is terrifying for academics. Because it means you might be wrong. And being wrong means pivoting, reframing, or in the worst case, discovering there’s no market for what you’ve built.
But here’s the paradox: the faster you get specific, the faster you learn whether you’re right.
Vague customer hypotheses keep you stuck in perpetual “market research” mode. Specific customer segments let you test, learn, and move forward.
So let’s fix this.
The Three Questions That Narrow Your Focus
Most academics try to identify customers by starting broad and getting narrower. “Anyone in healthcare” becomes “hospital administrators” becomes “hospital administrators in oncology departments.”
That’s backwards.
Start with these three questions instead:
1. Who has this problem right now, badly enough that they’re already trying to solve it?
Not “who might benefit from this someday.” Not “who would be interested if they knew about it.”
Who is actively spending time, money, or political capital trying to fix the problem your research addresses even if their current solution is terrible?
If nobody’s trying to solve it, you don’t have a market. You have an idea.
Example: You’ve developed a machine learning model that predicts equipment failure in manufacturing. Don’t ask “Who uses manufacturing equipment?” Ask “Who’s already tracking equipment failure and getting frustrated with their current approach?”
That’s a much smaller, much more actionable list.
2. Who has budget authority to purchase a solution?
Academic entrepreneurs waste months talking to people who love their solution but can’t buy it.
The lab manager who says “This would save us so much time!” doesn’t have purchasing authority. Neither does the junior engineer, the postdoc, or the program coordinator.
You need to talk to the person who controls the budget line where your solution would sit. That’s often 2-3 levels higher than the person who experiences the problem daily.
Example: Your AI tool helps researchers analyze genomic data faster. The grad students and postdocs would use it. But the PI decides whether to pay for it. And the PI’s decision is influenced by whether it helps them publish more, win more grants, or reduce labor costs.
Your customer isn’t “researchers.” It’s “PIs who are bottlenecked by data analysis and need to increase throughput.”
3. Who can you actually reach in the next 30 days?
This is the filter most academics skip, and it’s the most important one.
You might have a perfect customer segment, but if you can’t get meetings with them, it doesn’t matter.
Who do you already have access to? Who’s one connection away? Who’s active in communities you’re part of?
Start there. Not because they’re the ultimate target market, but because they’re reachable, and reachable customers let you test your hypotheses fast.
Example: You’ve identified hospital CFOs as your ideal customer. But you don’t know any hospital CFOs, and cold emails aren’t working.
Who DO you know? Maybe you know doctors. Maybe one of them has a spouse who works in hospital administration. Maybe your university has a healthcare MBA program with students who work in hospital operations.
Start with whoever you can reach. Learn from those conversations. Refine your pitch. Then work your way to the CFOs.
The First 10 Conversations Framework
Once you’ve answered those three questions, here’s how to build your first target list:
Step 1: List 5-7 specific organizations or people who fit your criteria.
Not “hospital administrators.” Not “manufacturing companies.”
Names. Organizations. LinkedIn profiles.
Example:
John Smith, VP of Operations at ABC Manufacturing
Jane Doe, Director of Clinical Operations at XYZ Hospital
Dr. Sarah Lee, PI at University Lab focused on [relevant area]
Step 2: Categorize them by access level.
Tier 1 (Immediate access): People you already know or can reach through one warm intro
Tier 2 (Two degrees away): People you can reach through a connection’s connection
Tier 3 (Cold outreach): People you’ll need to email or message directly
Start with Tier 1. Always.
Step 3: Write down your hypothesis for each person.
What problem do you think they have? Why do you think your research solves it?
You’re not trying to be right yet. You’re trying to be specific enough that the conversation can prove you wrong.
Example hypothesis: “I think John Smith’s manufacturing plant is losing money due to unplanned equipment downtime, and he’s currently using reactive maintenance schedules that don’t prevent failures.”
Step 4: Reach out to 3 people this week.
Not next month. Not after you’ve “refined your pitch.”
This week.
Your goal isn’t to sell them anything. It’s to test whether your hypothesis is even close to reality.
What You’re Actually Testing
When you talk to these first 10 people, you’re not pitching. You’re learning.
Here’s what you’re trying to figure out:
✅ Do they actually have the problem you think they have?
(Or are you solving a problem that only exists in academic papers?)
✅ How are they currently trying to solve it?
(What’s their existing workaround, and why is it lackluster?)
✅ How much does this problem cost them?
(Time? Money? Reputation? Career advancement?)
✅ Would they pay to solve it?
(Or is it annoying but not urgent?)
Most of your hypotheses will be wrong. That’s the point.
The faster you learn what’s wrong, the faster you can adjust your approach and find the customers who actually exist.
The Mistake You’re About to Make (And How to Avoid It)
Here’s where most academic entrepreneurs go sideways:
They have 3 good conversations with people who validate the problem. Those people say things like “Yeah, this is definitely an issue for us” and “I’d be interested in hearing more.”
So the academic goes back to the lab and spends 6 months building a product.
Then they come back to those 3 people and hear: “Oh, we ended up solving that a different way” or “Our budget got cut” or “I left that role.”
Don’t build yet.
Have 10 conversations. Then have 10 more.
Your goal in the first 20 conversations isn’t to close deals. It’s to figure out whether you’ve actually identified a customer segment that’s reachable, has budget, and feels the problem urgently enough to act.
If 15 out of 20 conversations confirm your hypothesis, you’re onto something.
If 5 out of 20 do, you need to adjust.
Where This Leaves You
Your research has potential. But potential doesn’t become traction until you get specific about who needs it.
Not “industries that could benefit.” Not “anyone who works in X sector.”
Names. Titles. Organizations. People you can email this week.
The faster you move from “lots of people could use this” to “here are 10 specific people I’m going to talk to,” the faster you’ll learn whether you’re building something the market actually wants.
And if the first 10 conversations don’t validate your hypothesis?
Good. You just saved yourself 6 months of building the wrong thing.
Adjust your customer segment and try again.
That’s not failure. That’s how research works.
You already know how to test hypotheses. You already know how to iterate based on data.
This is the same process. Just a different lab.
Next step: Write down 10 names by the end of this week. Then reach out to 3 of them.
Not someday. This week.
Your research deserves to find the people who actually need it.