Assumption Testing: 9 Methods, Questions & Examples

Ever made a decision thinking, “This just makes sense,” only to realize later that reality doesn’t quite agree? That’s because we often operate on assumptions – things we believe to be true without actual proof.

Some of these assumptions turn out to be right, but others can lead to wasted time, money, and effort. Before you invest in a new feature, launch a product, or overhaul a design, you need to test those assumptions.

Because what seems obvious to you might not be obvious to your users.

This article will walk you through nine proven methods for assumption testing, the right questions to ask, and real-world examples to help you make informed decisions.

What is an assumption

An assumption is basically a guess you’re treating as a fact, whether you realize it or not. It’s something you believe about your users, product, or market without solid proof (yet).

Some assumptions turn out to be right, but others can lead you down the wrong path if you don’t test them.

And that’s a big deal—because according to a study by CB Insights, about 35% of startups fail because there is “no market need” for their products. In other words, they assumed demand that didn’t exist.

For example, thinking “People will totally use this feature because I would” is an assumption. The only way to know for sure? Put it in front of real users and see what happens.

Opinion vs assumption

An opinion is a personal belief or perspective, often influenced by emotions or experiences, while an assumption is something you take for granted as true without evidence.

Opinions are subjective (“Dark mode looks better”), whereas assumptions often shape decisions (“Users prefer dark mode”). The key difference? Assumptions can and should be tested, while opinions remain personal viewpoints.

In product development, relying on assumptions without validation can lead to costly mistakes.

Types of assumptions we make

Brian Tracy said it best:

When building a product or strategy, we assume we know what users want, how they’ll behave, or what will work. But unchecked assumptions can lead us astray.

Let’s break down the key types of assumptions and why they matter.

Usability assumptions

These are the assumptions we make about how easy and intuitive something will be for the end user.

Think of them like assuming everyone knows how to use a TV remote, but then realizing your grandma keeps hitting the ‘mute’ button instead of ‘volume up’.

Example: Assuming that users will immediately understand how to navigate your app without any tutorials or guidance.

You might think, “It’s so obvious! The ‘next’ button is right there.” But then… users click on the logo instead of the button and wonder why nothing happens. Oops!

Feasibility assumptions

These are the assumptions about how possible something is to create or implement—basically, can we pull it off?

It’s like assuming you can make a 5-tier cake with zero baking experience. Spoiler alert: it might not end well.

Example: Assuming your team can develop a complex feature within a week because you saw it done in a tutorial.

You might think, “Hey, it’s just a tiny tweak to the code, no biggie.” But then reality hits, and you realize it needs a complete redesign.

Viability assumptions

These assumptions are all about whether something will actually work in the real world and make a profit.

It’s like assuming your new unicorn-themed coffee shop will be the next big thing, but forgetting that the rent is sky-high and unicorns don’t drink coffee.

Example: Assuming that a new feature will instantly attract paying customers.

You launch your shiny new feature but customers weren’t as excited about it as you thought they would.

Desirability assumptions

These are the assumptions about whether people will actually want what you’re offering. Think of it like assuming everyone loves pineapple on pizza.

Surprise! Not everyone does.

Example: Assuming your users will love your design overhaul because you think it’s super sleek and modern.

You might love it, but your users? Not so much. They preferred the old, cozy design that felt like home. Turns out, what’s desirable to you isn’t always desirable to them.

What is assumption testing

Assumption testing is the process of challenging what you believe to be true about your users, product, or market before making big decisions.

You might think users will love a new feature, instinctively know how to use it, or happily pay for your product—but until you test those beliefs, they’re just hopeful guesses.

As Elizabeth Thornton puts it:

Instead of building on gut feelings, you put your assumptions to the test with real users.

Will they actually use it? Does it solve a real problem? Is it even worth building? The sooner you find out, the fewer expensive mistakes you’ll make.

Assumption testing VS assumption mapping

Think of assumption mapping as the planning stage and assumption testing as the action stage.

Assumption mapping helps you identify and prioritize your assumptions before you test them. It’s about laying everything out, spotting the riskiest ones, and deciding what needs validation first.

A common approach is using an impact-uncertainty matrix—high-impact, high-uncertainty assumptions are the ones you should test first.

Assumption testing, on the other hand, is where you actually validate those assumptions through real-world experiments like user interviews, A/B testing, or smoke tests.

It’s how you separate fact from fiction before investing too much time or money. Both go hand in hand: map your assumptions first, then test the ones that matter most.

9 key assumption testing methods

When building a product or launching a new initiative, you’re making assumptions about what customers want, how they’ll behave, and whether your solution will work.

Instead of blindly moving forward, you need to test these assumptions before investing too much time and money. That’s where these methods come in.

Let’s break them down with examples of when to use them.

1. User interviews

Talking directly to users is one of the best ways to uncover what they need, how they think, and what problems they face. As Marty Cagan says:

User interviews help validate assumptions about customer pain points, motivations, and behaviors before you invest in building solutions.

✅ Use when:

• You’re developing a new product and need to validate if there’s a real problem worth solving
• You have an existing product and want to understand why users aren’t engaging
• You’re exploring a rebrand and need insights into how your audience perceives you

Unsure of how to get started? Start with our list of user interview questions and build upon them gradually.

2. Usability testing

Even the best-designed products can be confusing to users. Usability testing helps you spot roadblocks by watching real people interact with your product. Instead of assuming your design is intuitive, you see firsthand where users struggle, hesitate, or drop off.

✅ Use when:

• You’re launching a new app or website and want to ensure it’s intuitive
• Conversion rates are low, and you suspect design issues are causing drop-offs
• A feature isn’t being used as expected, and you need to understand why’

Consider a travel booking site noticing that users abandon their carts frequently. Usability testing reveals that they struggle to find the baggage policy, making them hesitant to complete the purchase. A simple UI fix increases conversions.

3. A/B testing

Sometimes, small changes can have a big impact. A/B testing lets you test two variations of a feature, page, or message to see which one performs better. Instead of guessing, you make data-driven decisions on what resonates with users.

✅ Use when:

• You’re optimizing a landing page and want to test different headlines or CTAs
• You’re running paid ads and want to compare different visuals
• You’re sending emails and want to see which subject line gets more opens

Consider a SaaS company testing two CTAs: “Start Free Trial” vs. “Get Started.” The second one results in a 15% higher conversion rate, proving small changes can have big impacts.

4. Smoke testing

Before investing heavily in development, you need to check if there’s actual demand for your product or feature. A smoke test does just that by putting a basic version (like a landing page or ad) in front of users to see if they engage.

If people click, sign up, or show interest, your assumption might be right. If not, it’s back to the drawing board.

✅ Use when:

• You have a new business idea and want to test demand before building
• You’re considering a major feature and want to validate if users care
• You want to see if people will pay for something before investing in production

5. Wizard of Oz testing

What if you could test a feature without actually building it? Wizard of Oz testing lets you fake the backend while giving users the illusion that a system is fully functional. It’s a great way to validate interest before investing in automation.

It’s often referred to as a Wizard of Oz prototype, where users interact with what feels like a real product, but the core functionality is manually handled.

✅ Use when:

• You’re testing a new AI-powered feature but don’t want to build the full model yet
• You want to see if users will pay for a service before developing it
• You need to observe real user behavior before committing resources

6. Field studies

Sometimes, the best insights come from observing users in their natural environment. Field studies involve watching people use your product in real-world settings to uncover behaviors, challenges, and needs that wouldn’t surface in a lab setting.

✅ Use when:

• You’re building a tool for frontline workers and need to see how they operate
• You suspect there’s a gap between how users say they behave and what they actually do
• You want to understand cultural or environmental factors affecting product use

For instance, a fintech startup observing small business owners managing expenses. They discover that most track finances on paper, showing the need for an easy digital alternative.

7. Concierge testing

Instead of automating everything from the start, concierge testing lets you manually provide a service to test demand and gather insights. It’s a way to validate a concept before investing in tech-heavy solutions.

✅ Use when:

• You’re launching a subscription service and want to test user interest before automating
• You need direct feedback before scaling a product
• You want to refine your offering based on early interactions

For example, a fitness startup offers personalized workout plans via email instead of developing an app. If users love it, they build the full product.

8. Fake door testing

What if you could test demand for a feature before building it? Fake door testing involves adding a button, page, or signup option for a feature that doesn’t exist yet. If users engage, you know it’s worth developing.

But remember to be transparent. If users click, let them know the feature is coming soon instead of leaving them confused.

✅ Use when:

• You want to gauge interest in a new feature before investing resources
• You need real user data to justify building something
• You’re testing different product directions before committing

A SaaS company adds a “Request Demo” button for a not-yet-built integration. If enough users click, they move forward with development.

9. Riskiest assumption test

Not all assumptions are created equal. Riskiest Assumption Testing (RAT) focuses on identifying and testing the assumptions that could cause your entire idea to fail.

Instead of testing everything, you prioritize what could make or break your product.

✅ Use when:

• You’re in the early stages of product development and need to de-risk your idea
• You want to validate the biggest unknowns before committing time and money
• You need to quickly determine if your idea is viable

For intance, a founder assumes people will pay for a self-driving grocery cart. Instead of building it, they survey users and find that most prefer personal shopping assistance over automation.

How to prepare for assumption testing

Before you start testing, you need to be clear on what you’re testing and why. Jumping in without proper preparation can lead to misleading results. Or worse, wasting time on the wrong assumptions.

Here’s how to do it right:

Identify assumptions to test  

Not all assumptions need testing. Some are obvious, while others are critical but uncertain. Start by mapping out your assumptions to see which ones could make or break your idea.

This is where assumption mapping comes in. It helps you categorize assumptions based on how much they impact your success and how uncertain they are.

This should always be the step before assumption testing. Otherwise, you risk testing things that don’t really matter.

Focus on the riskiest assumptions

The best use of your time is testing the assumptions that could completely derail your product if they’re wrong. A simple way to find them is by using the Impact-Uncertainty Matrix.

Plot your assumptions on a grid:

• High impact, low uncertainty → No need to test (you already know the answer).
• Low impact, high uncertainty → Not worth testing.
• High impact, high uncertainty → These are the ones to focus on

This way, you’re not just testing for the sake of testing, you’re reducing the biggest risks upfront.

Choose your testing method & success metrics

Different assumptions require different testing methods. If you’re unsure about demand, a smoke test works well. If you want to test usability, a prototype with usability testing is better.

So define what success looks like before you start. Here are some metrics to consider based on your testing method:

• Fake Door Test – Percentage of users who click on the feature or sign-up button
• A/B Testing – Conversion rate difference between variations
• Smoke Testing – Sign-ups or pre-orders before the product exists
• User Interviews – Number of users who express a strong pain point (look for patterns, not just individual opinions)
• Usability Testing – Task success rate, time taken to complete tasks, and number of errors
• Concierge Testing – User engagement and willingness to continue using the manual version

Setting clear success metrics ensures you don’t rely on gut feelings. It helps you decide whether to move forward, iterate, or scrap an idea altogether.

Find and recruit participants

Who you test with matters just as much as how you test. Your results will only be useful if they come from the right audience.

Ways to find and recruit participants:

• Tap into existing customers – If you have a user base, reach out directly. Customers who already engage with your product can give deep insights
• Leverage LinkedIn and online communities – If you’re testing a B2B product, LinkedIn is gold. For B2C, Reddit, Facebook groups, and Slack communities are great places to find relevant users
• Ask for referrals – Sometimes the best participants come through word of mouth. If you’ve interviewed someone relevant, ask if they know others who face the same challenges
• Use a research panel if you don’t want to source manually – Platforms like UXtweak’s User Panel let you access participants from over 130 countries without the hassle of recruitment.

Recruiting the right participants ensures your findings are meaningful. Testing with random people might feel productive, but if they don’t match your ideal user, their feedback could send you in the wrong direction.

Prepare your questions and other materials

A well-structured test is only as good as the questions you ask. Whether you’re running interviews, usability tests, or A/B experiments, your questions should be designed to uncover real insights—not just confirm what you already believe.

Sample Questions for Assumption Testing

📌 For User Interviews:

• “Can you walk me through the last time you experienced [problem]?”
• “How are you currently solving this issue? What’s frustrating about it?”
• “What would make you switch to a new solution?”

📌 For Usability Testing:

• “What do you expect to happen when you click this button?”
• “Can you complete [task] without any guidance? What’s confusing?”
• “If you could change one thing about this interface, what would it be?”

📌 For Fake Door or Smoke Testing:

• “What made you click on this feature?”
• “What were you expecting to see after signing up?”
• “Would you be willing to pay for this feature? Why or why not?”

How to write assumption testing questions for user interviews

User interviews are a goldmine for testing assumptions—if you ask the right questions. The key is to keep them open-ended, avoid leading the user, and dig into their real experiences.

Here’s how to do it right:

Focus on open-ended questions

If you frame your question around your assumption, you’re leading the user toward a biased response. Instead, explore their natural behavior before introducing solutions.

Example: Instead of “Would a dashboard help you track progress?”, ask “How do you currently keep track of progress? What challenges do you face?”

Also, remember to let the user lead. If they bring up a solution similar to your assumption on their own, that’s a strong validation. If they don’t, your assumption may be off.

Don’t mention your assumption to avoid bias

If you frame your question around your assumption, you’re leading the user toward a biased response. Instead, explore their natural behavior before introducing solutions.

Example: Instead of “Would a dashboard help you track progress?”, ask “How do you currently keep track of progress? What challenges do you face?”

This way, users describe their real workflow rather than being influenced by the way you present your idea.

If they naturally bring up a solution similar to your assumption, that’s strong validation. If they don’t, your assumption may need rethinking.

Put effort into understanding the context

Users don’t always think about their own habits critically, so you need to dig into the details. Asking about a specific past experience helps you see what they actually do, not just what they think they do.

Example: Instead of “Do you struggle with this?”, ask “Can you walk me through the last time you encountered this issue?” When users recall real moments, their responses are more detailed and honest.

If multiple users describe the same frustration, that’s a strong signal worth paying attention to.

How to write assumption testing questions for usability testing

The goal of usability testing is to see how real users interact with your product—not to guide them toward the “right” answer. Your tasks should feel natural, challenge their expectations, and reveal usability issues you might not have considered.

Tasks should mirror real users’ jobs

Instead of generic tasks like “Find the pricing page,” frame it as a real-world scenario:

“You’re considering purchasing this tool for your team. Where would you go to compare pricing plans?”

Use the funnel technique

The funnel technique focuses on starting with broad, open-ended questions and gradually narrowing down to specifics. Here’s how:

• “What do you think this page is for?” (broad)
• “How would you complete [specific task]?” (narrower)
• “Why did you take that approach?” (deep dive)

Include uncommon scenarios

Edge cases reveal usability gaps that standard tests might miss:

• “You forgot your password and need to reset it. What would you do?”
• “You’re shopping for a friend and need to send a gift receipt. Where would you find that option?”

Analyzing assumption testing results

Once your tests are complete, it’s time to break down the results and decide your next move. Here’s how to approach it:

📌Spot the patterns – Are certain results recurring? Do they vary significantly between groups? Identifying trends will help determine whether your assumption holds up.

📌Gauge reliability – A single test isn’t enough. Check for consistency across multiple data points. If the results are all over the place, you might need to refine your testing method or gather more data.

📌Compare with expectations – Did the results confirm what you assumed, or was there a surprise? If your hypothesis was wrong, figure out why. Maybe the assumption itself was flawed, or perhaps external factors influenced the test.

📌Break It down by segments – Not all results apply universally. Analyze by different user groups, behaviors, or time periods to see where the assumption holds true and where it doesn’t. This prevents broad, misleading conclusions.

📌Turn findings into next steps – What do the results tell you to do? If your assumption is validated, how can you scale or optimize? If it’s disproven, should you tweak the idea, test again, or move on? Make the insights actionable.

📌Keep a record – Every test teaches you something. Document what was tested, what you learned, and what you did next. This avoids repeating mistakes and makes future testing faster and more effective.

Assumption testing example

Ever heard of Convo? They’re a Deaf-owned company making sign language interpretation services more accessible. But in 2024, they hit a challenge: How do you improve communication services without just guessing what users need?

Instead of assuming, they put their ideas to the test—literally. Here’s what they did:

🔍 Listened first, built later – Instead of diving into development, Convo’s team sat down with Deaf users and businesses to understand their real struggles.

🧠 Mapped their assumptions – They wrote down everything they thought was true about user behavior, needs, and potential solutions; then poked holes in those ideas.

🤝 Got the whole squad involved – Product managers, designers, engineers, and stakeholders teamed up to challenge assumptions and refine ideas before committing to any big changes.

🔄 Tested, tweaked, and tested Again – They rolled out features (like QR codes for instant interpretation access), gathered real-world feedback, and adjusted as needed.

Testing instead of assuming helped Convo launched features that actually worked. Businesses could now offer interpretation services effortlessly, and Deaf users got a frictionless, on-the-go experience.

The result? Happier users, growing revenue, and a new industry standard for accessibility.

Wrapping up

Every product decision is built on assumptions—some right, some wrong. The only way to know for sure is to test them. Skipping assumption testing can lead to wasted time, budget, and effort on features nobody needs or understands.

But when you validate your ideas early, you reduce risk, improve user experience, and make smarter choices.

And if you want a seamless way to do it, UXtweak has got you covered!

From assumption mapping to user interviews, usability testing, A/B testing, and more, it’s a platform to recruit, conduct, analyze, and share research all-in-one place.

Want to see it in action? Book a demo today!

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