We all make assumptions.
Entrepreneurs, executives, product managers, innovation teams, board members — no one escapes this.
The problem isn’t making assumptions.
The problem is trusting assumptions as if they were facts. And historically, this is one of the biggest causes of failure in innovation.
This article explains:
- How to identify your assumptions
- How to discover the riskiest ones
- How to prioritize experiments using the Risk/Difficulty Matrix
- Real startup examples
- Practical templates you can use immediately
Let’s begin.
1. Why Assumptions Kill Products
There is one simple rule every innovator must accept:
We don’t know anything until we test it.
You may believe that:
- the customer has the problem,
- the customer wants your solution,
- they are willing to pay,
- there are no satisfactory alternatives,
- the market is large enough,
- behavior will change…
But all of these are assumptions, not facts.
And if one critical assumption is false, the entire product collapses like dominoes.
Real examples of failures caused by false assumptions:
❌ Quibi (2020 – burned $1.75B)
False assumption: “People want to watch 10-minute premium series on their phones.”
Reality: People already had TikTok and YouTube for free.
❌ Juicero (burned $120M)
False assumption: “People want a smart, Wi-Fi juice press.”
Reality: You could squeeze the juice packs with your hands.
❌ Google Glass
False assumption: “People want to wear computers on their faces.”
Reality: It created social discomfort and privacy concerns.
2. How to Identify Your Assumptions
The simplest — and most neglected — step is writing down all your assumptions.
A helpful sentence:
“For this idea to succeed, the following must be true…”
Common assumptions in startups and product development:
- My customer has problem X.
- The problem is important enough to deserve attention.
- Customers will pay for the solution.
- My solution is better than the alternatives.
- The market is large enough.
- My acquisition channel will work as expected.
- Customer behavior will change as imagined.
Real case: Dropbox
Before writing a full product, Drew Houston had one critical assumption:
“People want a simple way to synchronize files across devices.”
He validated this with a simple video, not with full software.
3. Identifying Your Riskiest Assumptions
Not all assumptions carry equal weight.
The riskiest one is:
“My customer truly has the problem I’m trying to solve.”
If the problem doesn’t exist:
- they won’t value your solution,
- they won’t pay,
- they won’t change behavior,
- they won’t return,
- they won’t recommend it.
This kills every business.
Real case: Airbnb
The riskiest assumption was:
“People will be willing to sleep in a stranger’s home.”
They tested this with:
- a simple website,
- three air mattresses,
- photos they took themselves.
The hypothesis proved true — and the rest is history.
4. The Risk/Difficulty Matrix: What to Test First
After listing assumptions and identifying the riskiest ones, you must decide what to test first.
The Risk/Difficulty Matrix helps you prioritize.
RISK: Impact if the assumption is false
DIFFICULTY: How hard it is to test the assumption
This creates four quadrants:
1 — High Risk / Low Difficulty
TOP PRIORITY — test immediately.
Examples:
- Does the customer actually feel this pain?
- Can they describe the problem without prompting?
- Would they use this solution scenario?
2 — High Risk / High Difficulty
Test next.
Requires pilots, prototypes, or more complex experiments.
3 — Low Risk / Low Difficulty
Test if time allows.
4 — Low Risk / High Difficulty
Ignore (not worth the investment).
5. Real Examples of Assumption Testing
Uber
High-risk assumption:
“People will get into a stranger’s car.”
Simple test:
- A basic MVP in a single city
- First drivers were acquaintances
High-risk assumption:
“People want fast, beautiful photo-sharing with filters.”
Test:
- 8-week MVP,
- Only one core behavior: photo → filter → post.
Rappi
High-risk assumption:
“Consumers want ultra-fast delivery of everyday items.”
Test:
- Started delivering chocolate bars and snacks
- Scaled as demand proved real
6. Practical Templates You Can Use Immediately
Template 1 — Assumption List
For this product to succeed, the following must be true:
1. My customer has the problem __________________.
2. This problem matters because __________________.
3. The customer will try to solve it within ______ weeks/months.
4. They are willing to pay $ ________ for a solution.
5. Existing alternatives are not satisfactory because __________.
6. The acquisition channel will work like this: _________________.
7. My sales cycle will be ______ days.
8. Customer behavior will change in the following way: ____________.
9. I can deliver the solution with a cost lower than _____________.
10. The total addressable market is ____________________________.
Template 2 — Riskiest Assumption
Among all assumptions, the riskiest one is:
> _____________________________________________________________
Because if it is not true:
- The product won’t be desired because ________________________.
- The revenue model will fail because __________________________.
- Customer acquisition won’t work because _____________________.
- Retention will fail because __________________________________.
Template 3 — Risk/Difficulty Matrix
Category: _______________________________________________________
Assumption: _____________________________________________________
Classification:
[ ] High Risk / Low Difficulty
[ ] High Risk / High Difficulty
[ ] Low Risk / Low Difficulty
[ ] Low Risk / High Difficulty
Next Steps: _________________________________________________
Template 4 — Lean Experiment Structure
Hypothesis:
“If I ____________________, then customers will ____________________.”
Experiment Type:
[ ] Interview
[ ] Landing page
[ ] Paid ads
[ ] Prototype
[ ] MVP
[ ] Video demo
[ ] Pilot / PoC
Success Criteria:
- At least ______% conversion
- At least ______ sign-ups
- At least ______ discovery calls
- At least ______ pre-payments
Timeline: ______ days
Owner(s): _________________________________________
7. Conclusion: Assumptions Are Inevitable. Failure Isn’t.
Great innovators don’t know more —
they test faster.
Products fail when teams:
- trust assumptions without evidence,
- invest months building without validating,
- ignore customer signals,
- skip early experiments.
Products succeed when teams:
- identify assumptions clearly,
- find the riskiest one,
- design smart, fast experiments,
- iterate relentlessly.
The difference between a good idea and a good business is validation.