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Value Hypothesis & Growth Hypothesis: lean startup validation
Posted on September 16, 2021 |
You’ve come up with a fantastic idea for a startup and you need to discuss the hypothesis and its value? But you’re not sure if it’s a viable one or not. What do you do next? It’s essential to get your ideas right before you start developing them. 95% of new products fail in their first year of launch. Or to put it another way, only one in twenty product ideas succeed. In this article, we’ll be taking a look at why it’s so important to validate your startup idea before you start spending a lot of time and money developing it. And that’s where the Lean Startup Validation process gets into, alongside the growth hypothesis and value hypothesis. We’ll also be looking at the questions that you need to ask.
Table of contents
The lean startup validation methodology, the benefits of validating your startup idea, the value hypothesis, the growth hypothesis, recommendations and questions for creating and running a good hypothesis, in conclusion – take the time to validate your product.
What does it mean to validate a lean startup?
Validating your lean startup idea may sound like a complicated process, but it’s a lot simpler than you may think. It may be the case that you were already planning on carrying out some of the work.
Essentially, validating your startup when you check your idea to see if it solves a problem that your prospective customers have. You can do this by creating hypotheses and then carrying out research to see if these hypotheses are true or false.
The best startups have always been about finding a gap in the market and offering a product or service that solves the problem. For example, take Airbnb . Before Airbnb launched, people only had the option of staying in hotels. Airbnb opened up the hospitality industry, offering cheaper accommodation to people who could not afford to stay inexpensive hotels.
“Don’t be in a rush to get big. Be in a rush to have a great product” – Eric Ries
Validation is a crucial part of the lean startup methodology, which was devised by entrepreneur Eric Ries. The lean startup methodology is all about optimizing the amount of time that is needed to ensure a product or service is viable.
Lean Startup Validation is a critical part of the lean startup process as it helps make sure that an idea will be successful before time is spent developing the final product.
As an example of a failed idea where more validation could have helped, take Google Glass . It sounded like a good idea on paper, but the technology failed spectacularly. Customer research would have shown that $1,500 was too much money, that people were worried about health and safety, and most importantly… there was no apparent benefit to the product.
Find out more about lean startup methodology on our blog
How to create a mobile app using lean startup methodology
The key benefit of validating your lean startup idea is to make sure that the idea you have is a viable one before you start using resources to build and promote it.
There are other less obvious benefits too:
- It can help you fine-tune your idea. So, it may be the case that you wanted your idea to go in a particular direction, but user research shows that pivoting may be the best thing to do
- It can help you get funding. Investors may be more likely to invest in your startup idea if you have evidence that your idea is a viable one
The value hypothesis and the growth hypothesis – are two ways to validate your idea
“To grow a successful business, validate your idea with customers” – Chad Boyda
In Eric Rie’s book ‘ The Lean Startup’ , he identifies two different types of hypotheses that entrepreneurs can use to validate their startup idea – the growth hypothesis and the value hypothesis.
Let’s look at the two different ideas, how they compare, and how you can use them to see if your startup idea could work.
The value hypothesis tests whether your product or service provides customers with enough value and most importantly, whether they are prepared to pay for this value.
For example, let’s say that you want to develop a mobile app to help dog owners find people to help walk their dogs while they are at work. Before you start spending serious time and money developing the app, you’ll want to see if it is something of interest to your target audience.
Your value hypothesis could say, “we believe that 60% of dog owners aged between 30 and 40 would be willing to pay upwards of €10 a month for this service.”
You then find dog owners in this age range and ask them the question. You’re pleased to see that 75% say that they would be willing to pay this amount! Your hypothesis has worked! This means that you should focus your app and your advertising on this target audience.
If the data comes back and says your prospective target audience isn’t willing to pay, then it means you have to rethink and reframe your app before running another hypothesis. For example, you may want to focus on another demographic, or look at reducing the price of the subscription.
Shoe retailer Zappos used a value hypothesis when starting out. Founder Nick Swinmurn went to local shoe stores, taking photos of the shoes and posting them on the Zappos website. Then, if customers bought the shoes, he’d buy them from the store and send them out to them. This allowed him to see if there was interest in his website, without having to spend lots of money on stock.
The growth hypothesis tests how your customers will find your product or service and shows how your potential product could grow over the years.
Let’s go back to the dog-walking app we talked about earlier. You think that 80% of app downloads will come from word-of-mouth recommendations.
You create a minimal viable product ( MVP for short ) – this is a basic version of your app that may not contain all of the features just yet. So, you then upload it to the app stores and wait for people to start downloading it. When you have a baseline of customers, you send them an email asking them how they heard of your app.
When the feedback comes back, it shows that only 30% of downloads have come from word-of-mouth recommendations. This means that your growth hypothesis has not been successful in this scenario.
Does this mean that your idea is a bad one? Not necessarily. It just means that you may have to look at other ways of promoting your app. If you are relying on word-of-mouth recommendations to advertise it, then it could potentially fail.
Dropbox used growth hypotheses to its advantage when creating its software. The file-storage company constantly tweaked its website, running A/B tests to see which features and changes were most popular with customers, using them in the final product.
Like any good science experiment, there are things that you need to bear in mind when running your hypotheses. Here are our recommendations:
- You may be wondering which type of hypothesis you should carry out first – a growth hypothesis or a value hypothesis. Eric Ries recommends carrying out a value hypothesis first, as it makes sense to see if there is interest before seeing how many people are interested. However, the precise order may depend on the type of product or service you want to sell;
- You will probably need to run multiple hypotheses to validate your product or service. If you do this, be sure to only test one hypothesis at a time. If you end up testing multiple ones in one go, you may not be sure which hypothesis has had which result;
- Test your most critical assumption first – this is one that you are most worried about, and could affect your idea the most. It may be that solving this issue makes your product or service a viable one;
- Specific – is your hypothesis simple? If it’s jumbled or confusing, you’re not going to get the best results from it. If you’re struggling to put together a clear hypothesis, it’s probably a sign to go back to the drawing board.
- Measurable – can your hypothesis be measured? You’ll want to get tangible results so you can check if the changes you have made have worked.
- Achievable – is your hypothesis attainable? If not, you may want to break it down into smaller goals.
- Relevant – will your hypothesis prove the validity of your product or service?
- Timely – can your hypothesis be measured in a set amount of time? You don’t want a goal that will take years to monitor and measure!
- Be as critical as possible. If you have created an idea, it is only natural that you want it to succeed. However, being objective rather than subjective will help your startup most in the long term;
- When you are carrying out customer research, use as vast a pool of people as time and money will allow. This will result in more accurate data. The great news is that you can use social media and other networking sites to reach out to potential customers and ask them their opinions;
- When carrying out customer research, be sure to ask the questions that matter. Bear in mind that liking your product or service isn’t the same as buying it. If a customer is enthusiastic about your idea, be sure to ask follow-on questions about why they like it, or if they would be willing to spend money on it. Otherwise, your data may end up being useless;
- While it is essential to have as many relevant hypotheses as possible, be careful not to have too many. While it may sound like a good idea to try out lots of different ideas, it can actually be counter-productive. As Eric Ries said:
“Don’t bog new teams down with too much information about falsifiable hypotheses. Because if we load our teams up with too much theory, they can easily get stuck in analysis paralysis. I’ve worked with teams that have come up with hundreds of leap-of-faith assumptions. They listed so many assumptions that were so detailed and complicated that they couldn’t decide what to do next. They were paralyzed by the just sheer quantity of the list.”
“We must learn what customers really want, not what they say they want or what we think they should want.” – Eric Ries
According to CB Insights , the number one reason why startups fail is that there is no demand for the product. Many entrepreneurs have gone ahead and launched a product that they think people want, only to find that there is no market at all.
Lean Startup Validation is essential in helping your business idea to succeed. While it may seem like extra work, the additional work you do in the beginning will be of a critical advantage later down the line.
Still not 100% convinced? Take HubSpot . Before HubSpot launched its sales and marketing services, it started off as a blog. Co-founders Dharmesh Shah and Brian Halligan used this blog to validate their ideas and see what their visitors wanted. This helped them confirm that their concept was on the right lines and meant they could launch a product that people actually wanted to use.
Validating a startup idea before development is crucial because it ensures that the idea is viable and addresses a real problem that customers have. With a high failure rate of new products, validation helps avoid wasting time and resources on ideas that might not succeed.
The value hypothesis tests whether customers find enough value in a product or service to pay for it. The growth hypothesis examines how customers will discover and adopt the product over time. Both hypotheses are essential for validating the viability of a startup idea.
Eric Ries recommends starting with a value hypothesis before a growth hypothesis. Validating whether the idea provides value is crucial before considering how to promote and grow it.
When creating and running a hypothesis, consider the following: 1. Focus on testing one hypothesis at a time. 2. Test your most critical assumptions first. 3. Ensure your hypothesis follows SMART goals (Specific, Measurable, Achievable, Relevant, Timely). 4. Use a wide pool of potential customers for accurate data. 5. Ask relevant and probing questions during customer research. 6. Avoid overwhelming your team with excessive hypotheses.
Validating your product idea before development helps you avoid the top reason for startup failure—lack of demand for the product. By confirming that there is a market need and interest in your idea, you increase the chances of building a successful product.
Lean Startup Validation helps entrepreneurs avoid the mistake of launching a product that doesn’t address a genuine need. By gathering evidence and feedback early, you can make informed decisions about pivoting or refining your idea before investing significant time and resources.
Certainly. Suppose you’re developing a mobile app for dog owners to find dog-walking services. Your value hypothesis could be: “We believe that 60% of dog owners aged between 30 and 40 would be willing to pay upwards of €10 a month for this service.” You then validate this hypothesis by surveying dog owners in that age range and analyzing their responses.
The growth hypothesis examines how customers will discover and adopt your product. If, for example, you expect 80% of app downloads to come from word-of-mouth recommendations, but feedback shows only 30% are from this source, you may need to reevaluate your promotion strategy.
Yes, Lean Startup Validation can be applied to startups across various industries. Whether you’re offering a product or service, the process of testing hypotheses and gathering evidence applies universally to ensure the viability of your idea.
To gather accurate data, focus on reaching a diverse pool of potential customers through various channels, including social media and networking sites. Ask relevant questions about their preferences, willingness to pay, and potential pain points related to your idea
Being critical and objective during validation helps you avoid confirmation bias and wishful thinking. Objectivity allows you to assess whether your idea truly addresses a problem and resonates with customers, ensuring that your startup’s foundation is built on solid evidence.
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Creating a Growth Hypothesis for Your Financial Projections
So you’ve got a great idea for a business, and you have thought up a brilliant product for that business to sell. You have done your research, identified your target markets, and come up with an ideal customer profile. Maybe you even have started the wheels rolling on development, and you are on your way to dishing out a Minimum Viable Product (MVP). Business is good and things should be smooth sailing from here on out, right?
Now all you need is for customers to realize how amazing your product is and come rushing to buy!
Hold on, where are all the customers?
Unfortunately, your customers do not just magically appear out of nowhere. Building a growth strategy means building a plan for how you will acquire customers. The great thing about customers is they pay you for your product (or at least they should), and getting customers to pay for your product is one of the core reasons for why you created your business. You may have some great technology, but the reality is you built your product for others, not for yourself. You need to figure out how you are going to attract others to your product and grow your customer base. Determining a plan for growth and creating the assumptions for growth is called a Growth Hypothesis .
What is a Growth Hypothesis?
Eric Ries first pioneered the idea of the growth hypothesis in his book, The Lean Startup . By definition, a growth hypothesis “tests how new customers will discover a product or service”. Your growth hypothesis needs to explain your business’s strategy in obtaining and retaining customers, so it can eventually transform those customers into a sustainable source of cash flow.
Ries lays out three separate engines of growth for a startup to determine how customers are going to buy their product:
- The Sticky Engine of Growth . This concept is maintaining a greater organic customer growth rate than your customer churn. Basically, customers gained > customers lost, therefore net new customers increases.
- The Viral Engine of Growth . Here we have relying on existing customers and word of mouth to spread news of your product and essentially carry out your advertising for you.
- The Paid Engine of Growth . Lastly, we have paid advertising. TV commercials, billboards, magazine ads, etc. Enough said.
(More detail on growth drivers at https://sivers.org/book/LeanStartup )
A business can rely on any one, two, or even all three of these drivers when formulating their growth hypotheses. For your startup, however, it’s probably easiest to stick to the one engine that would yield the most potential for your business and worry about the others later. After doing some research, look at some companies in your industry and determine what they are doing right to grow their business.
Cool Growth Story: How Dropbox Hacked Growth to Become a $4 Billion Company
Another Cool Growth Story: Airbnb: The Growth Story You Didn’t Know
Once you have an idea of where you are headed with your growth hypothesis, you then need to decide on the most suitable revenue model for your type of business. Unless you have a truly new and disruptive business model, getting your customers to change their behavior in how they purchase is going to be a very challenging task.
The Right Revenue Model for Your Business
It is also essential to know how you are going to sell your product to your target market. Enter, the Revenue Model . While your growth hypothesis gives detail to gaining customers, your revenue model explains how to make money from them. Afterall, that’s the ultimate goal of your business, right?
It can be easy to get caught up in the numerous amounts of revenue models available to businesses, so let’s go through a few models that are fundamental to startups.
- Recurring . Also known as subscription-based, this model is where a customer pays for your product in installments (typically monthly or yearly) (e.g. Salesforce)
- Transactional . A one-time sale of goods or a service (e.g. Coffee Shop, Clothing Retailer)
- Project . A one-time project, typically completed over a specific time period (e.g. construction)
- Service . Services provided to a customer. The customer pays for time, expertise, material (e.g. Consulting, Lawyer)
- Freemium . Offered for free with additional features available for purchase (e.g. Dropbox, Free Trials)
- Advertisements . Selling adspace on fixed or digital media (e.g. Google)
- Marketplace . Platform to connect buyers and sellers (e.g. Ebay, Etsy)
See: Carnegie Mellon Center for Innovation and Entrepreneurship – Revenue Models
By no means is this list comprehensive, it is merely a starting point for you to begin visualizing your possible revenue streams. There are countless resources available for aiding you in developing your model if you are still unsure with how your company will derive its revenues.
Related: The 10 Most Popular Startup Revenue Models
Putting it all together in a Financial Model
You have your Growth Hypothesis. You have decided on the best-fitting Revenue Model. Now let’s figure out how to put it all together and lay out the groundwork for your business to start earning some actual money. At this point, most businesses would probably open up an Excel spreadsheet, and begin desperately attempting to forecast out their revenues based on their newly formulated hypothesis and model.
See our post: STOP CREATING FINANCIAL MODELS USING SPREADSHEETS!
Let’s face it, modeling out a long-term growth strategy in a spreadsheet is more trouble than it is worth, so most businesses just default to some nice round number like 5%. Yes, 5% growth looks nice… 5% per month looks even better! This seems like a masterful plan.
Unfortunately, this new growth strategy is rooted in a few very basic and flawed assumptions since properly modeling growth became too difficult in a spreadsheet. You know that your revenue model is more complex than a simple spreadsheet, and you have multiple strategies and tactics for how your business earns its revenue.
At Hivemetric , we understand your revenue model consists of multiple unique components. How you manage free trials, monthly vs annual subscribers, one-time setup fees, special promotions – these are variables that are incapable of being simulated over time on a spreadsheet. Hivemetric’s dynamic revenue modeling system can help you to forecast your revenue with the detail it needs to show how it can evolve into something much bigger if based on a strategic growth plan. Forecast upsell and cross-sell opportunities, model changes in staffing plans and the effect on revenue, and build various pricing scenarios to see the impact on your business. We do not want you to just model a single source of growth for your business, we want you to be able to provide a level of detail that was previously missing from you and your stakeholders. We want you to see the future the Hivemetric way.
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Understanding Lean Startup Validation: What Is a Value Hypothesis?
Understanding Lean Startup Principles in Relation to Value Hypothesis
When exploring the Lean Startup methodology and its relationship with the value hypothesis , it's essential to understand how these principles intertwine. By integrating lean principles with the value hypothesis , entrepreneurs can effectively validate their startup ideas and drive sustainable business development.
Lean Startup Methodology and Value Hypothesis
Integrating lean principles with value hypothesis.
Incorporating the core tenets of lean startup methodology, such as rapid iteration and validated learning, into the formulation of a value hypothesis is crucial for refining and validating a startup idea.
Lean Startup Benefits for Value Hypothesis
The lean startup approach offers invaluable benefits for shaping a robust value hypothesis, including efficient resource allocation, risk mitigation, and accelerated product-market fit.
Aligning Lean Principles with Value Hypothesis
Aligning lean principles with the value hypothesis ensures that startups remain customer-centric, adaptable, and responsive to market dynamics.
Importance of Lean Startup Validation for Value Hypothesis
Reducing business risks through value hypothesis.
Validating a value hypothesis through lean principles minimizes the inherent risks associated with untested assumptions, thereby safeguarding business resources.
Enhancing Product Market Fit with Value Hypothesis
By leveraging lean startup validation processes, entrepreneurs can enhance their product-market fit by aligning their offerings closely with customer needs and preferences.
Accelerating Business Growth with Value Hypothesis
A well-validated value hypothesis paves the way for accelerated business growth by fostering innovation, customer satisfaction, and competitive differentiation.
Lean Startup Validation process: The integration of lean principles into the validation process is instrumental in ensuring that startups develop viable solutions that resonate with their target audience.
Understanding the Value Hypothesis
In the realm of lean startup methodology , a value hypothesis plays a pivotal role in shaping the trajectory of a new venture. It serves as a foundational premise that guides entrepreneurs in developing products or services that resonate with their target audience, thereby increasing the likelihood of success.
Defining a Value Hypothesis
Components of a value hypothesis.
A value hypothesis comprises several essential components, including the identification of customer pain points, an articulation of how the proposed solution addresses these pain points, and an estimation of how customers will perceive and adopt the solution.
Importance of a Clear Value Hypothesis
Crafting a clear and concise value hypothesis is crucial for aligning internal teams, investors, and stakeholders around a common understanding of the problem being solved and the proposed solution. It provides clarity and direction for all subsequent product development efforts.
Crafting an Effective Value Hypothesis
An effective value hypothesis is not only specific but also measurable. It should articulate clear success criteria that can be objectively evaluated to determine whether the proposed solution has indeed created value for its intended users.
The Role of a Value Hypothesis in Lean Startup
Aligning with customer needs.
The value hypothesis makes explicit assumptions about what customers truly value and how those values can be addressed through innovative solutions. This alignment ensures that startups remain focused on delivering tangible benefits to their customers.
Iterative Product Development
Embracing a value hypothesis within lean startup principles fosters iterative product development, where each iteration is designed to test and validate specific aspects of the value proposition. This iterative approach allows for continuous refinement based on real-time feedback from customers.
Behind the Scenes
Historical Examples:
Eric Ries' first company, Catalyst Recruiting , failed because he and his colleagues did not understand the wants of their target customers, focusing too much time and energy on the initial product launch. Ries later published “ The Lean Startup ” book in 2011, aiming to improve upon what had been going on with startups and tech companies. He was inspired by his own company's failure due to not understanding customer needs.
Expert Testimony:
"Lean startup emphasizes customer feedback over intuition and flexibility over planning."
"Testing and validating your hypotheses is an essential part of startup development as it helps you reduce uncertainty, avoid failure, and create value for your customers."
Importance of a Value Hypothesis
In the realm of startup development, a value hypothesis serves as the compass guiding entrepreneurs toward creating products or services that resonate with their target audience. Understanding the significance of a value hypothesis entails embracing a customer-centric approach and leveraging market differentiation strategies.
Customer-Centric Approach to Value Hypothesis
Understanding customer pain points for value hypothesis.
A fundamental aspect of a value hypothesis involves delving into the pain points experienced by customers . By comprehensively understanding these pain points, entrepreneurs can tailor their solutions to directly address the specific needs and challenges faced by their target audience.
Tailoring Products to Customer Needs with Value Hypothesis
The essence of a value hypothesis lies in its ability to steer product development efforts toward catering to the unique requirements and preferences of customers . This tailored approach ensures that the resulting offerings align closely with what customers truly value, thereby increasing the likelihood of widespread adoption and satisfaction.
Building Customer Loyalty through Value Hypothesis
Statistical data highlights that at least one-third of respondents emphasize human interaction as crucial for their loyalty, while more than half express a preference for an enjoyable online shopping experience. A well-crafted value hypothesis enables entrepreneurs to build customer loyalty by addressing these key aspects that influence consumer allegiance.
Market Differentiation and Value Hypothesis
Identifying unique value propositions.
An effective value hypothesis aids in identifying and articulating unique value propositions that set a venture apart from competitors. By pinpointing what makes their offerings distinct, entrepreneurs can effectively communicate this differentiation to potential customers, fostering brand loyalty and preference.
Creating Competitive Advantage through Value Hypothesis
The strategic formulation and validation of a robust value hypothesis empower startups to create sustainable competitive advantages within their respective markets. This advantage stems from aligning products or services with customer needs in ways that outperform existing alternatives, positioning the venture for long-term success.
Validating the Value Hypothesis
In the realm of lean startup methodology, validating the value hypothesis is a critical phase that involves leveraging various methods and tools to ensure that a product or service genuinely delivers value to the customer. This process not only reduces uncertainty but also paves the way for creating solutions that address real needs and preferences.
Research and Data Analysis for Value Hypothesis
Conducting market research for value hypothesis.
Market research serves as a foundational step in validating the value hypothesis. It involves gathering insights into consumer behavior, market trends, and competitor offerings to assess the potential reception of the proposed solution.
Analyzing User Feedback for Value Hypothesis
User feedback analysis provides invaluable qualitative data regarding how customers perceive and interact with a product or service. This analysis helps in refining the value hypothesis based on authentic user experiences and preferences.
Iterative Testing of Value Hypothesis
Prototyping and mvp testing for value hypothesis.
Prototyping and minimum viable product (MVP) testing are instrumental in validating the value hypothesis. These methods allow entrepreneurs to gather real-world feedback on early versions of their offerings, enabling iterative refinement based on user responses.
A/B Testing and Experiments for Value Hypothesis
A/B testing involves comparing different versions of a product or feature to determine which resonates best with users. By conducting experiments through A/B testing, startups can validate their value hypotheses by identifying features that drive meaningful engagement and satisfaction.
Measuring Customer Value with Value Hypothesis
Key metrics for value assessment with value hypothesis.
Key metrics, such as customer acquisition cost, lifetime value, and retention rates, provide quantifiable indicators of customer value. Measuring these metrics allows startups to gauge how well their offerings align with customer needs and expectations.
Customer Satisfaction Surveys for Value Hypothesis
Customer satisfaction surveys offer direct insights into how customers perceive the value delivered by a product or service. These surveys help in understanding areas of strength and improvement within the value proposition.
Long-Term Value Measurement with Value Hypothesis
Long-term measurement involves tracking customer satisfaction, loyalty, and advocacy over extended periods. This longitudinal assessment provides a comprehensive view of how well a product or service continues to deliver value over time.
By employing these validation methods , startups can systematically refine their value hypotheses based on empirical evidence gathered from market dynamics and user interactions.
Key Recommendations for Value Hypothesis
When formulating a value hypothesis , several key recommendations can significantly impact its effectiveness and the subsequent validation process.
Crafting a Good Hypothesis for Value Hypothesis
Clarity and specificity in value hypothesis.
A well-crafted value hypothesis should be clear, specific, and unambiguous. It must articulate the problem being addressed, the proposed solution, and the expected outcomes with precision to guide subsequent product development efforts effectively.
Testability and Measurability of Value Hypothesis
An effective value hypothesis should be testable and measurable. It should define success criteria that can be objectively evaluated, allowing startups to gather empirical evidence to validate whether their proposed solution genuinely creates value for their target audience.
Lean Startup Principles and Value Hypothesis
Embracing iterative development for value hypothesis.
Incorporating lean startup principles into the formulation of a value hypothesis involves embracing iterative development. This approach advocates rapid iteration, constant feedback loops, and validated learning to refine the value proposition based on real-time insights from users.
Customer-Centric Mindset in Value Hypothesis
A customer-centric mindset is pivotal when crafting a value hypothesis . Startups must prioritize understanding customer needs, preferences, and pain points to tailor their solutions effectively while aligning with lean principles of continuous improvement through user feedback.
Time and Resource Allocation for Value Hypothesis
Efficient resource management for value hypothesis.
Efficient resource allocation is crucial when validating a value hypothesis within the lean startup framework. Startups need to optimize resource allocation by focusing on high-impact activities that contribute to refining the value proposition based on validated learning.
Balancing Speed and Quality in Value Hypothesis
Balancing speed with quality is essential when validating a value hypothesis . While rapid iteration is encouraged within lean principles, startups must ensure that speed does not compromise the quality of insights gathered or the refinement process based on accurate data analysis.
Growth Hypothesis in Relation to Value Hypothesis
Establishing scalable sales strategies for value hypothesis.
The growth hypothesis examines how validated value propositions can impact product sales at scale. It focuses on identifying opportunities for sustainable revenue generation by leveraging a well-validated value hypothesis as an integral part of scalable sales strategies.
Repeatable Revenue Generation with Value Hypothesis
Validating a value hypothesis also involves testing its impact on repeatable revenue generation. By understanding how well the value proposition resonates with customers over time, startups can refine their offerings to ensure consistent revenue streams through sustained customer satisfaction.
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Value Hypothesis 101: A Product Manager's Guide
Talk to Sales
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
Your value hypothesis focuses on the value of your product to customers. This type of hypothesis can apply to a product or company and is a building block of product-market fit .
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.
Heather Tipton
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