Value Hypothesis 101: A Product Manager's Guide
Humans make assumptions every day—it’s our brain’s way of making sense of the world around us, but assumptions are only valuable if they're verifiable. That’s where a value hypothesis comes in as your starting point.
A good hypothesis goes a step beyond an assumption. It’s a verifiable and validated guess based on the value your product brings to your real-life customers. When you verify your hypothesis, you confirm that the product has real-world value, thus you have a higher chance of product success.
What Is a Verifiable Value Hypothesis?
A value hypothesis is an educated guess about the value proposition of your product. When you verify your hypothesis, you're using evidence to prove that your assumption is correct. A hypothesis is verifiable if it does not prove false through experimentation or is shown to have rational justification through data, experiments, observation, or tests.
The most significant benefit of verifying a hypothesis is that it helps you avoid product failure and helps you build your product to your customers’ (and potential customers’) needs.
Verifying your assumptions is all about collecting data. Without data obtained through experiments, observations, or tests, your hypothesis is unverifiable, and you can’t be sure there will be a market need for your product.
A Verifiable Value Hypothesis Minimizes Risk and Saves Money
When you verify your hypothesis, you’re less likely to release a product that doesn’t meet customer expectations—a waste of your company’s resources. Harvard Business School explains that verifying a business hypothesis “...allows an organization to verify its analysis is correct before committing resources to implement a broader strategy.”
If you verify your hypothesis upfront, you’ll lower risk and have time to work out product issues.
UserVoice Validation makes product validation accessible to everyone. Consider using its research feature to speed up your hypothesis verification process.
Value Hypotheses vs. Growth Hypotheses
A growth hypothesis is a guess at how your business idea may develop in the long term based on how potential customers may find your product. It’s meant for estimating business model growth rather than individual products.
Because your value hypothesis is really the foundation for your growth hypothesis, you should focus on value hypothesis tests first and complete growth hypothesis tests to estimate business growth as a whole once you have a viable product.
4 Tips to Create and Test a Verifiable Value Hypothesis
A verifiable hypothesis needs to be based on a logical structure, customer feedback data, and objective safeguards like creating a minimum viable product. Validating your value significantly reduces risk. You can prevent wasting money, time, and resources by verifying your hypothesis in early-stage development.
A good value hypothesis utilizes a framework (like the template below), data, and checks/balances to avoid bias.
1. Use a Template to Structure Your Value Hypothesis
By using a template structure, you can create an educated guess that includes the most important elements of a hypothesis—the who, what, where, when, and why. If you don’t structure your hypothesis correctly, you may only end up with a flimsy or leap-of-faith assumption that you can’t verify.
A true hypothesis uses a few guesses about your product and organizes them so that you can verify or falsify your assumptions. Using a template to structure your hypothesis can ensure that you’re not missing the specifics.
You can’t just throw a hypothesis together and think it will answer the question of whether your product is valuable or not. If you do, you could end up with faulty data informed by bias, a skewed significance level from polling the wrong people, or only a vague idea of what your customer would actually pay for your product.
A template will help keep your hypothesis on track by standardizing the structure of the hypothesis so that each new hypothesis always includes the specifics of your client personas, the cost of your product, and client or customer pain points.
A value hypothesis template might look like:
[Client] will spend [cost] to purchase and use our [title of product/service] to solve their [specific problem] OR help them overcome [specific obstacle].
An example of your hypothesis might look like:
B2B startups will spend $500/mo to purchase our resource planning software to solve resource over-allocation and employee burnout.
By organizing your ideas and the important elements (who, what, where, when, and why), you can come up with a hypothesis that actually answers the question of whether your product is useful and valuable to your ideal customer.
2. Turn Customer Feedback into Data to Support Your Hypothesis
Once you have your hypothesis, it’s time to figure out whether it’s true—or, more accurately, prove that it’s valid. Since a hypothesis is never considered “100% proven,” it’s referred to as either valid or invalid based on the information you discover in your experiments or tests. Additionally, your results could lead to an alternative hypothesis, which is helpful in refining your core idea.
To support value hypothesis testing, you need data. To do that, you'll want to collect customer feedback. A customer feedback management tool can also make it easier for your team to access the feedback and create strategies to implement or improve customer concerns.
If you find that potential clients are not expressing pain points that could be solved with your product or you’re not seeing an interest in the features you hope to add, you can adjust your hypothesis and absorb a lower risk. Because you didn’t invest a lot of time and money into creating the product yet, you should have more resources to put toward the product once you work out the kinks.
On the other hand, if you find that customers are requesting features your product offers or pain points your product could solve, then you can move forward with product development, confident that your future customers will value (and spend money on) the product you’re creating.
A customer feedback management tool like UserVoice can empower you to challenge assumptions from your colleagues (often based on anecdotal information) which find their way into team decision making. Having data to reevaluate an assumption helps with prioritization, and it confirms that you’re focusing on the right things as an organization.
3. Validate Your Product
Since you have a clear idea of who your ideal customer is at this point and have verified their need for your product, it’s time to validate your product and decide if it’s better than your competitors’.
At this point, simply asking your customers if they would buy your product (or spend more on your product) instead of a competitor’s isn’t enough confirmation that you should move forward, and customers may be biased or reluctant to provide critical feedback.
Instead, create a minimum viable product (MVP). An MVP is a working, bare-bones version of the product that you can test out without risking your whole budget. Hypothesis testing with an MVP simulates the product experience for customers and, based on their actions and usage, validates that the full product will generate revenue and be successful.
If you take the steps to first verify and then validate your hypothesis using data, your product is more likely to do well. Your focus will be on the aspect that matters most—whether your customer actually wants and would invest money in purchasing the product.
4. Use Safeguards to Remain Objective
One of the pitfalls of believing in your product and attempting to validate it is that you’re subject to confirmation bias. Because you want your product to succeed, you may pay more attention to the answers in the collected data that affirm the value of your product and gloss over the information that may lead you to conclude that your hypothesis is actually false. Confirmation bias could easily cloud your vision or skew your metrics without you even realizing it.
Since it’s hard to know when you’re engaging in confirmation bias, it’s good to have safeguards in place to keep you in check and aligned with the purpose of objectively evaluating your value hypothesis.
Safeguards include sharing your findings with third-party experts or simply putting yourself in the customer’s shoes.
Third-party experts are the business version of seeking a peer review. External parties don’t stand to benefit from the outcome of your verification and validation process, so your work is verified and validated objectively. You gain the benefit of knowing whether your hypothesis is valid in the eyes of the people who aren’t stakeholders without the risk of confirmation bias.
In addition to seeking out objective minds, look into potential counter-arguments, such as customer objections (explicit or imagined). What might your customer think about investing the time to learn how to use your product? Will they think the value is commensurate with the monetary cost of the product?
When running an experiment on validating your hypothesis, it’s important not to elevate the importance of your beliefs over the objective data you collect. While it can be exciting to push for the validity of your idea, it can lead to false assumptions and the permission of weak evidence.
Validation Is the Key to Product Success
With your new value hypothesis in hand, you can confidently move forward, knowing that there’s a true need, desire, and market for your product.
Because you’ve verified and validated your guesses, there’s less of a chance that you’re wrong about the value of your product, and there are fewer financial and resource risks for your company. With this strong foundation and the new information you’ve uncovered about your customers, you can add even more value to your product or use it to make more products that fit the market and user needs.
If you think customer feedback management software would be useful in your hypothesis validation process, consider opting into our free trial to see how UserVoice can help.