Assumption Testing

An assumption is something we believe is true without having proof. In product discovery, assumptions can shape the direction of what we create. For example, you might assume people want a new app to track their fitness because you’ve noticed a trend in health apps. But what if people actually want something simpler, like a daily reminder to stay active? If you build based on your assumption without testing it, you could miss what users really need. That’s why assumption testing is important. It helps you check if your ideas match what users actually want before moving forward.

In product discovery, teams make assumptions in five key areas:

• Desirability: Do we believe customers want this solution, and will they take the steps needed to get value from it?
• Viability: Will this solution be good for our business and help us reach our goals?
• Feasibility: Can we realistically build and deliver this solution with the resources we have?
• Usability: Will customers easily understand how to use the product and find it helpful?
• Ethical: Could building this solution cause harm to users or society?

Each type of assumption can affect the success of a product, so it’s important to test them before moving forward with development.^[1]

There are several ways to generate assumptions:

• One effective method is user story mapping, which breaks down each step of a user journey. This helps you spot assumptions about desirability, usability, and feasibility.^[2]
• Another approach is walking through your opportunity solution tree. Ask yourself why you believe your solution will address each opportunity and achieve the desired outcome. Each step in this thinking process will reveal important assumptions.
• You can also define your ideal customer profile and list assumptions about what they need, want, and value.
• Brainstorming sessions with your team can be a great way to generate assumptions. Encourage diverse perspectives and use techniques like "What if?" scenarios to uncover hidden assumptions about your product or market.^[3]
• Analyzing competitor products and user reviews can also help you form assumptions about what features or experiences your target audience might expect or value.

How you phrase assumptions is crucial for making them testable. Here are two tips:

• Phrase assumptions in a way that they need to be true for your idea to succeed. For example, if you're building a shopping app, a good assumption is: "Users will finish checking out in less than 5 minutes." Avoid phrasing it negatively, like “Users won’t abandon their carts,” since it’s easier to test what users will do than what they won’t.
• Be specific. The more detailed your assumption, the quicker you can test it. Instead of saying, “Users will like the app,” a more testable assumption is: “Users will rate their shopping experience 4 stars or higher.” This allows you to create targeted tests and gather actionable feedback.

There are different types of assumption tests you can use to check if your ideas are right:

• Surveys or interviews: Ask potential users questions to test if they want or need your product. This helps with desirability assumptions.
• Prototypes: Create a simple version of your product to test both desirability and usability. It helps see if users are interested in the product and can use it easily.
• Landing pages: This tests desirability and viability by gauging user interest (e.g., sign-ups) and showing whether there’s enough demand for the product to be successful for the business.
• Data analysis: Look at existing data, like user behavior, sales figures, or website analytics, to see patterns. For example, if data shows users are leaving your site quickly, it might challenge your assumption about usability.
• A/B testing: This tests usability and desirability, showing which version of a product users prefer and whether they’re engaging with it as expected.

Assumption mapping is a simple way to organize and prioritize your assumptions before testing them. It helps you focus on the most important ones. You start by listing all your assumptions, then place them on a two-axis grid: certainty (how confident you are that the assumption is true) and importance (how crucial the assumption is for your idea to succeed). For example, if you assume users will love a feature but aren’t sure, and it's critical for success, that assumption would go in the high-importance, low-certainty area. These are the assumptions you should test first because they carry the most risk.

By mapping assumptions this way, you can clearly see which ones need immediate attention and testing, helping you make smarter, faster decisions.

Run assumption tests as early as possible, ideally before you invest too much time and money into building your product. Assumption tests help you check if the key things you believe about your users, product, or market are actually true. The earlier you test, the sooner you can avoid mistakes and make better decisions. It’s a good idea to run assumption tests after you’ve identified a target opportunity and selected a few ideas to explore. This helps you figure out which idea has the best chance of success.

Also run tests after choosing a final solution, especially if there are still questions about how it will work or if there are risks you need to manage. Since assumption testing helps teams make smarter decisions, it should be done continuously throughout the discovery process as you explore what to build. Regular testing ensures you're always learning and improving your product ideas.

Assumption testing tools make it easier to test your product ideas quickly and effectively. Here are some useful types:

• Prototyping tools: Platforms like Figma, Sketch, or Balsamiq make it easy to create simple mockups for testing before building the full product.
• Testing platforms: Tools like UserTesting or Maze, let you upload a prototype and get video feedback from users, without having to be there in real time.
• In-product survey tools: Tools like Qualaroo and Typeform, let you embed short surveys directly in your product to collect quick feedback from users.
• User behavior analytics tools: Tools like Amplitude, Mixpanel, or Heap track what users are doing in your product, helping you see how they interact with it.
• Data synthesis tools: Tools like Dovetail help you organize and understand data from different sources, such as customer feedback and support tickets, to inform your decisions.

Before running your assumption tests, define success with your team. Decide what results would show that your solution is working. For example, if you're testing usability, agree on how many users need to complete a task easily for the solution to succeed.

After the test, compare the results against the success criteria you set. If multiple solutions were tested, look at which one performed the best based on average across all your defined standards. This helps you make clearer, more confident decisions about which solution to move forward with.

Documenting test results is an important step to keep track of what you learned:

• Start by noting the assumption you tested and the goal or success criteria you set before the test.
• Then, clearly describe the test method you used, such as a survey, prototype, or user behavior tracking.
• Next, write down the results — what happened during the test. Include any data or feedback, like how many users completed a task or gave positive responses.
• Highlight any patterns or key findings.
• Finally, explain what you learned from the results. Did the test confirm or challenge your assumption?
• Include any next steps, such as running more tests, making changes to the product, or moving forward with confidence.

Keeping everything clear and organized helps your team make better decisions and refer back to past tests when needed.