3 Steps to Identifying Where Hypothesis Testing is Critical

As a follow on to our last blog post, we wanted to provide an excerpt that revealed how to identify the areas of the business for which you need to formulate hypotheses in order to test and build confidence in your product direction or pivot where you need to earlier rather than later. Check this out.

The following excerpt is from Groundwork: Get Better at Making Better Products by Vidya Dinamani and Heather Samarin. 

As product leaders, we spend a lot of time in meetings sharing opinions when we review customer research. We make a lot of assumptions, and we tend to hear what we want to hear. We’re sure you’ve been in more than one meeting like this. Many companies are so execution-focused that they move from one activity to another, without taking the time to help teams align, ask the right questions, and facilitate real collaboration.

Instead of just providing feedback on a hypothesis (or rejecting it outright), we’ve created three easy steps to help you coach your team to getting to a strong hypothesis: 

1. Identify What You Don’t Know

The best way to avoid some of the pitfalls we described earlier is to think about what you truly don’t know about the customer or problem. 

  • What are you guessing at or making assumptions about, with regard to their behaviors, their needs or the problem they’re facing? 
  • What conditions would have to be true for a new feature to work? 
  • If this is a new market, then what conditions need to be true for you to launch? 
  • If this is for a physical product, what conditions must exist for a customer to successfully use it?
  • What assumptions are you making about your persona, that if proven false, would dramatically change your course of action? 
  • Have you accurately translated what a customer has told you they wanted into a need?

Each of these questions represent the types of assumptions we make every day. Most of the time we jump straight from idea or insight, right into development. This stage requires you to painstakingly face everything that might go wrong. We often start with asking ourselves the question “What would make this idea fail?”

Now write down everything you don’t know as a question. Here are two assumptions we made based on our fitness app Melanie Persona:

● Melanie loves to try new forms of exercise.

● Melanie won’t care if she can’t go to the same studio more than three times a month.

Those assumptions matter. We believe them to be true because we spent a lot of time talking with her, to develop our Actionable Persona. Both of these assumptions were driving major design decisions. We’re taking this head-on, leaning into the biggest assumptions that will impact our business model. What we learn will help us make an important product decision.

2. Prioritize Assumptions.

If you do step one thoroughly, you’re going to end up with a lot of assumptions. Not all of the assumptions are critical and you want to know which will have the most impact on your business. We turn to a design thinking technique called a “bullseye diagram” to help sort through and classify all these assumptions. We like to make this a visual exercise that the entire team can participate in. On a large whiteboard draw three concentric circles, each one bigger than the last. Write each of your assumptions on separate Post-it Notes so you can move them around easily. Now it’s time to prioritize.

You can place one assumption in the innermost circle. In the next circle, you get to place three assumptions, and in the outermost ring, you get a choice of five assumptions. As you pick up each assumption, ask “how important is it to know this?” You can also set up multiple bullseye diagrams and have each member of your team run through the prioritization process individually, and then gather to compare results. 

We’ve even invited key stakeholders in our business to participate so that we get to hear their thoughts and concerns. Consider what different perspectives you may want as you try to understand what’s most important for you to learn. As an added benefit, it keeps everyone on the same page and increases commitment to, and interest in, the research you’re about to start. With this exercise, you’ll have a list of prioritized assumptions—and a clear winner. This winning assumption is used for the first hypothesis you write.

3. Convert Assumptions to Hypotheses

This step converts the prioritized assumption into a hypothesis. Here’s a hypothesis format you can use:

If… [specific, repeatable action]

Then… [expected, measurable outcome]

Because… [clearly stated assumption]

The easiest way we’ve found to create a strong hypothesis is to start with your desired outcome. What needs to be true to resolve your assumption? 

  • Do you want 10% more sign-ups to your site? 
  • Do you want 25% fewer customer calls? 
  • Do you want to increase your NPS by 5 points? 

Whether it’s 5 points or 10 points of NPS you’re trying to impact, or 25% less customer contacts; pick a figure that is meaningful to the business and will make a difference. Start with your desired outcome and then pick the appropriate measurement.

Next, move to the clearly stated, highest-priority assumption. This is where you can rewrite and reshape your assumption. If you truly believe you can’t make a significant difference by addressing this assumption, then move to your next ring of assumptions. There is no point in trying to create a test for an assumption that you don’t believe you can tackle. This is where you need a strong understanding of your business, your customers, and your market. Know what is important, and drive to make an impact where it counts.

Finally, consider the test itself. What action do you believe will create a significant result? Do you need to make a change to how people sign-up for your service? Do you need to introduce a new offering? Do you need to increase loyalty with existing customers?

Going back to the Melanie persona, share your highest prioritized assumption. One that we believe is critical to our business is: Melanie loves to try new forms of exercise.

We believe that Melanie will love to try new forms of exercise. If that is true, we’re going to give her many different classes to choose from. This will dictate how quickly we need to bring on new partners and it will dictate the design of our application. We want to make sure the assumption is true, so let’s turn this into a hypothesis that we can test given what’s important for our business: 

1. Desired Measurable Outcome: We want Melanie to love trying new exercises so much that she will purchase at least one class a week. That will give us enough revenue based on our projected number of customers.

2. Clearly Stated Assumption: Choice is the primary driver of purchase.

3. Specific, Repeatable Action: We will display different classes every week to keep her interested and engaged. 

This creates a hypothesis we can test:

If…we offer different classes per week to choose from

Then…we’ll get at least one purchase

Because…choice is the primary driver of purchase

After developing this hypothesis, we created three different prototypes on paper to test the different ways that the Melanie persona could choose classes and our hypothesis was validated. Remember, your assumption is always derived from something you don’t know and your hypothesis is based on your belief that a specific action will deliver the outcome your business is looking for. We told you to start with the measurable, desired outcome. When you start with what matters most for the business, whether that’s retention, or growth. Perhaps it’s revenue. Home in on the metric you most want to impact.

Like any practice, getting results requires constant feeding and nurturing. Starting to build a hypothesis-driven organization is going to be ugly and painful at the beginning. At first, you won’t get hypotheses that are elegantly formed and perfectly clear. A lot of them will be quite confusing and badly written and that’s okay. Pretty soon you’ll find yourself in a hypothesis-driven culture, with a team that’s always focusing on the riskiest assumptions, ready to make the biggest business impact.


If you like what you see, there’s more where that came from. Pick up Groundwork: Get Better at Making Better Products by Vidya Dinamani and Heather Samarin from Amazon.

Product Rebels is a product management training and coaching firm run by long term product executives for companies like Intuit and Mitchell International. We have trained over 200 companies, small and enterprise level, in the skills and frameworks that help product management leaders and product managers deliver kick-ass customer experiences. We have a passion for finding efficient ways of infusing customer insight into everything product teams do in pursuit of experiences that customers love …and that drive growth.  Join us in the Product Rebels Community on Facebook or the Product Rebels Community on LinkedIn.

Take a look at our very practical training courses and coaching programs that give you practical tools, frameworks, and support you can use tomorrow in becoming a more effective product leader.  www.productrebels.com

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