The riskiest assumptions are those that, if proven wrong, can have a devastating impact on your product’s success. Tackling those first saves you time and effort.
Developing a Minimum Viable Product (MVP) is not just about building a smaller version of your product. It starts with identifying the problem, proposing a solution, and then measuring feedback to iterate. Every step involves assumptions—beliefs about your customers, their behaviours, and your business model—that you take as true without yet having proof.
The trap is to treat all assumptions equally. Some are minor and low-risk. Others are critical and can sink your product if wrong. The actual job is to find the riskiest assumptions early and design experiments to test them. This approach saves you from wasting time on less important risks.
A powerful tool to find and prioritize assumptions is the Business Model Canvas. It helps you map out your product’s key components—customer segments, value propositions, channels, revenue streams, costs, and partners. The assumptions often hide in the connections between these blocks: Who your customers really are, whether they will pay the price you set, and whether your distribution channels will reach them effectively.
Assumptions are always lurking in your business model
The Business Model Canvas is more than a planning tool. It is a lens to surface assumptions. Look specifically at:
- Customer segments: Who exactly are your customers? What do you believe about their needs and behaviours?
- Value propositions: What unique value do you think your product delivers to these customers?
- Channels: How do you assume customers will discover and purchase your product?
- Revenue streams: What pricing model do you believe customers will accept?
When you try to link your customer segments to revenue streams through your value propositions, you uncover the assumptions you are making. These form the basis for your MVP hypotheses.
Product discovery workshop with a startup team in Bangalore
You (PM): “Our business model suggests stay-at-home individuals want fresh juices delivered. But how sure are we that they use social media to order?”
Co-founder: “We assumed social media is the best channel because it’s low cost and scalable.”
You (PM): “That’s a risky assumption. What if our target audience isn’t active on social media? We could waste marketing budget with zero sales.”
Co-founder: “So we need to test if social media is an effective distribution channel before scaling.”
This is the moment where assumptions become testable hypotheses that guide your MVP experiments.
Identifying risky assumptions before building saves wasted effort.
The riskiest assumptions determine your MVP focus
Not all assumptions have equal weight. The riskiest assumptions are those that, if proven wrong, would devastate your product’s chance of success. You must detect these quickly and cost-effectively.
How do you spot these riskiest assumptions? The Business Model Canvas helps again:
| Side of Canvas | Assumptions to Watch For |
|---|---|
| Left side (Operational) | - Key partners needed to deliver value - Resources required to create the product - Cost structure assumptions |
| Right side (Customer) | - Customer segments targeted - Distribution channels assumed - Revenue streams expected |
By categorizing assumptions this way, you can rank them by riskiness (how uncertain they are) and consequence (how much damage if wrong). This prioritization lets you focus your MVP tests on the assumptions that matter most.
Real example: Fresh juice delivery in a neighbourhood
Let’s say your identified problem is: There is a need for fresh, healthy afternoon juices delivered to doorsteps in a neighbourhood.
You map the business model:
| Key Partners | Key Activities | Value Proposition | Customer Relationship | Customer Segments |
|---|---|---|---|---|
| Local fruit suppliers | Juice preparation | Fresh, no added sugar, no preservatives | Personalized relationship | Stay-home individuals seeking healthy drinks |
| Key Resources | Channels | Cost Structure | Revenue Streams |
|---|---|---|---|
| Ingredients, equipment | Social media, street cart | Ingredients, equipment, marketing | Juice sales, tips |
From this canvas, you identify assumptions such as:
- Your customers are stay-home individuals who want healthy juices.
- Your customers will buy through social media channels.
- Your customers value freshness and lack of preservatives enough to pay a premium.
Here is the catch: If your target customers are mostly elderly or baby boomers who don’t use social media, your chosen distribution channel may fail. That assumption is risky because it directly affects sales volume.
Building testable hypotheses from assumptions
An assumption is a belief. A hypothesis is a testable statement you can validate with data.
For example, from the assumption "stay-home individuals will buy fresh juice via social media," you create hypotheses like:
- “At least 30% of surveyed stay-home individuals in our target neighbourhood use social media to order food.”
- “Launching a targeted Facebook ad campaign will generate 50 orders within 2 weeks.”
These hypotheses must be measurable and actionable. They become the foundation of your MVP experiments.
Sprint planning meeting
You (PM): “We need to test our hypothesis about social media orders before building the app.”
Engineering Lead: “Can we run a small ad campaign and track clicks and orders?”
You (PM): “Exactly. We will define success criteria and collect data to validate or invalidate our assumptions.”
This scientific approach prevents building products on untested beliefs.
Transforming assumptions into testable hypotheses to reduce risk.
The MVP experiment cycle
- Listen to the voice of the customer. Understand who will buy and why.
- Identify your assumptions. Use tools like the Business Model Canvas.
- Rank assumptions by risk. Focus on those with highest uncertainty and impact.
- Create testable hypotheses. Make them measurable and actionable.
- Design experiments to validate hypotheses. Use surveys, ads, prototypes.
- Collect data and feedback. Measure against success criteria.
- Iterate based on learning. Refine assumptions and product direction.
This cycle repeats until you have confidence in your product-market fit.
- Pick a product idea or MVP you are working on (or a hypothetical one).
- Fill out a Business Model Canvas focusing on customer segments, value propositions, channels, revenue streams, costs, and partners.
- List all assumptions you are making in each of these areas.
- Rank each assumption by its riskiness (uncertainty) and consequence (impact if wrong).
- Identify the top 3 riskiest assumptions to validate first.
- Write a testable hypothesis for each of these assumptions.
- Plan a simple experiment or data collection method to test each hypothesis.
Test yourself: Prioritizing assumptions in a Bangalore juice startup
You are the PM at a seed-stage Bangalore startup building a fresh juice delivery service. Your Business Model Canvas shows customers as stay-home individuals ordering via social media. You suspect this might be wrong.
The call: Which assumptions do you prioritize testing first, and how do you design experiments to validate them?
Your reasoning:
You are the PM at a seed-stage Bangalore startup building a fresh juice delivery service. Your Business Model Canvas shows customers as stay-home individuals ordering via social media. You suspect this might be wrong.
Your task: Which assumptions do you prioritize testing first, and how do you design experiments to validate them?
your reasoning:
When assumptions are wrong: the Uber example
Uber’s founder noticed a specific problem: people wanted to rent premium black cars but found them too expensive. This insight led to proposing a solution—an app connecting riders and drivers.
But this included assumptions such as:
- Timeliness is the most important attribute for office goers.
- Customers are willing to pay a premium for faster rides.
These assumptions were risky because if wrong, the business model would fail.
As Talvinder explained:
"Sometimes time is important; sometimes price is. It depends on the customer's context—whether they are meeting a boss, an investor, or just running errands."
Uber had to test these hypotheses rigorously to ensure product-market fit.
The entire product development process is a continuous learning loop
You create solutions, identify assumptions, convert them into hypotheses, and validate with data. As you learn, new problems surface, and the cycle repeats.
This is what product management is: a scientific experiment to reduce uncertainty and deliver value.
Where to go next
- Build a data-driven product roadmap: Building Your Roadmap (The Journey)
- Write effective testable hypotheses: Hypothesis-Driven Product Development
- Learn methods for customer interviews: User Research Methods
- Understand MVP experiment techniques: Minimum Viable Product Experiments
PL alumni now work at Flipkart, Google, Razorpay, PhonePe, Swiggy, Amazon, Microsoft, and 30+ other companies.