How to not waste $40K on a startup idea
Case study on going from zero to one
Every so often, I read an article that hooks me from the start. This is the story of a guy with a fantastic startup idea whose dreams were crushed by the market.
Our protagonist, Tom, is clearly smart, which makes his story a useful example of how even the best of us can wind up building the wrong thing. The good news: his fatal mistakes are preventable. So let’s retrace them, find alternatives, and not waste $40K.
What risks are you taking?
Like many origin stories, it starts with a personal anecdote, a sprinkle of data, and that magical aha moment.
Tom has a splitting headache. He instinctively turns to Google for the best pain reliever, but meets a wall of SEO fluff. It dawns on him that he’s not alone. 60% of Americans search online for health information. Yet despite thousands of clinical trials to draw from, the results are usually flooded with useless links.
Enter the fantastic startup idea: a database of clinical trials to power reliable answers to common medical questions.
To prove the concept, Tom builds a spreadsheet by hand. So far, so good:
Here was a problem that
Could help people
I knew how to solve
His points 2 and 3 presciently cover the two big risks in building something new:
Market risk: do people want this enough to support a business?
Execution risk: can we build this within a realistic timeline?
It also marks the scene of the first fatal mistake: Tom saw his spreadsheet as a promising proof-of-concept. I have the opposite take.
With the exception of notorious execution flameouts (*cough* Theranos), market risk is the more deadly idea killer. There’s a deep graveyard filled with ideas that were buildable but never viable businesses. So the first mission is to de-risk the market.
Reduce market risk
Here’s how I would approach it. First, pressure-test the main stat: 60% of Americans search online for health information. But what does that mean? Is it searching for “pain reliever” or something like “keto diet”? Former is right in our target market; latter not so much.
Pop these into search tools like Ubersuggest or Ahrefs, and we find that “keto” is ~6X more popular than “pain reliever”. And comically, pain reliever for dogs is the most popular query in its category:
This confirms our suspicion that our 60% “addressable” market is surely inflated.
Next, get a more realistic estimate of demand based on popular medical-related searches. Are we talking 1M+ monthly searches, 100K+, or more like 10K+? Comb the search results of top searches to see if there’s room for major quality improvement across the board, or only in certain niches.
Assuming strong search volumes and low-quality results, find relevant online forums (FB groups, subreddits, WebMD) to check if people have shared frustrations around unreliable answers. Chat up at least 5 people to explore and validate the problem.
How often do they find good enough answers vs. not? Ideal to see recurring issue
When the answers are not good enough, what do they do? Turn to their doctor? Pick the first answer? Ideal to see that they’re motivated to solve the problem
Do they currently pay for more reliable answers? Would they pay to have clinical evidence translated into digestible nuggets? Do their doctors basically already do this?
If people are willing to pay, what’s the best way to reach them?
You get the point. De-risking the market is a grind — far from the glamor of pitching a grand vision. But it’s also the kind of vital, meticulous work that uncovers what people are doing and why, and how they would use your product (if at all)! The more resources it takes to build, the more upfront research pays off.
Separate claims vs. bets
Back to Tom’s story. He’s guns blazing and ready to quit his job. Even his boss is supportive:
“That’s an awesome idea,” said Carl. “It sounds like something worth working on.”
This makes Tom more bullish. Who can blame him? We all stand a little taller when someone we respect believes in us. The hidden caveat is that there’s a universe of difference between a claim vs. a bet.
Claim = words. Bet = actions with stakes. A bet would be: Real talk: would you invest money in this? Would you pay to use this? Would you recommend this to so-and-so?
Claims are kind on the ego, but bets tell you everything worth knowing.
Tom dives headfirst into coding and hires a small team of contractors. Before long, the first crack appears:
My friends and family all tell me they love the site. Even some strangers on the internet love it. “I know right,” I tell them. “So how much would you pay for this?
“Hahahahah,” they say in unison. “Good one!”
I forgot that the first law of consumer tech is nobody pays for consumer tech.
While there are lucrative exceptions: MasterClass (education), Sweat (fitness), Tinder Plus (dating), the latest iPhone, the consumer pocket is fiercely competitive. Realizing this, Tom pivots to doctors, but now the wheels start coming off:
“I don’t know if we can spare the budget here, to be honest. It’s very fun…but I’m not sure if our practice can justify this cost.”
If you read enough sales books, most of them tell you that when people say your product is too expensive, what they really mean is your product isn’t valuable enough.
Taking it further, there are several shades of not valuable enough:
This is a low-priority problem — what are their high-priority problems?
This is a high-priority problem, but I have no budget — who controls their budget?
I don’t get why this would help me — can you make them a hero?
When Tom presses on the value point, he sees the final nail in the coffin:
“Of course I always have the best interests of my patients in mind, but, you know, it’s not like they’ll pay more if I prescribe Lexapro instead of Zoloft. They won’t come back more often or refer more friends. So I’d sorta just be, like, donating this money if I paid you for this thing, right?”
Bingo. The doctor’s ROI is based on getting patients to come back more often or refer their friends. The former is dicey; the latter is actionable, but nowhere close to what he’s been solving.
Contrary to the popular YC advice “make something people want”, it’s more useful to have an idea of who you’re selling to early on. That initial market shapes what you build, not the other way around. Knowing every line-item of their budget, how it’s allocated and why helps you figure out how to fit into their world.
This is also why an effective way to come up with (B2B) ideas is to look at your company’s P&L and follow the expenses. Are there better solutions to be made?
The idea maze continues
Tom ran out of time, but that doesn’t mean the idea is dead. For instance:
Google is notoriously bad for certain types of searches — could there be a segment of consumers willing to pay for clinically validated answers?
Possible profiles: athletes that need the latest findings on treating pain and injuries; people seeking top-notch care for their dogs — the point is to build a sharp wedge into the market, not a blunt one-size-fits-all instrument
Trend towards pay-for-performance may have incentivized more providers to get the best results — could they use a convenient digest of clinical findings?
Instead of spending 9 months and $40K building the product, I would’ve redirected half the time to figuring out the market, and the rest to testing promising niches.
There’s a saying that first-time founders take on more market risk, and experienced founders take on more execution risk. I would argue that execution risk is inherent in everything we do. But we can all spend more time upfront to:
Separate claims vs. bets
Clarify who we’re delivering value to, who’s paying, and their constellation of influences
Engineers tend to think: can we build it, and how do we do it? Product people tend to think: should we build it, and why? To take an idea from zero to one, we gotta fuse the engineering mindset with the product mindset. Here’s to thinking across disciplines!
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