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From assumption to hypothesis done right

If I would ask you if the words assumption and hypothesis are synonyms, what would be your answer?

While their meaning is similar, and some dictionaries might list them as synonyms, they are not the same and they should never be used interchangeably. Every day we hear people talk about assumptions and hypothesis and in all kind of contexts. But be aware they are not the same! 

In this article, we will explain you the differences between assumptions and hypotheses and how you can correctly identify the assumptions that will, later on, be turned into experiments.

To have a clear understanding of how the assumption > hypothesis > experiment journey should look like, we will show you how we do it.

Let’s dig into it!

What is an assumption?

On one side, assumptions can be guided by experience and well-established models. On the other side, they may be a product of hope and wishful thinking, or might just be arbitrary.

From a business point of view, an assumption is a general feeling about a problem. In order to test it and see if it is true or not, a sound hypothesis relevant to the assumption and the business problem should be developed.


  • Every individual from a certain target group has the same problem that needs solving.
  • The market is large enough to support my business.
  • People need my product.
  • My audience will pay for a new feature.

What is a hypothesis?

In the scientific environment, a hypothesis is described as the key to a scientific test. Usually, the hypothesis is the statement asserting what a researcher assumes is the correct answer to whatever empirical question is motivating the research. Hence, it can be described as a proposed model of a cause, classification, or localisation, which can potentially be eliminated by experimental contradiction.

From a growth marketing perspective, a hypothesis is an educated guess for what you expect to happen in a given experiment.

Assumption vs hypothesis

Assumption  Hypothesis 
Belief  Prediction
Axiomatic  An educated guess
No evidence  Supported by reasoning 
Unmeasurable Measurable 
Don’t require any verification Needs to be validated/rejected 
Vague, optimistic, and untestable Specific and testable 

Actually, a hypothesis is a more on-point version of an assumption and it is formulated in such a way that it can be tested and its outcome(s) can easily be measured.

In its simplest form, a (testable) hypothesis incorporates 3 main elements: assumption, condition, and prediction. Therefore, its basic structure looks like this:

If <assumption> then <condition>, because <prediction>. 

If you find the previous form too complicated, here is another structure you could use:

Changing <problem> into <solution> will <anticipated result>. 

This second structure is focused on the same 3 elements: presumed problem (assumption), proposed solution (condition) and the anticipated result (prediction).

Testable hypothesis

A testable hypothesis is one that can be used as the basis for an experiment design and thus an experiment.

How to create them: (1) Ask a question. (2) Do background research and discover your assumptions. (3) Construct a hypothesis. (4) Test your hypothesis by doing an experiment. (5) Analyse your data and draw a conclusion. (6) Communicate your results.

In order for it to be considered testable (feasible), two criteria must be met: (1) It must be possible to prove that the hypothesis is true/false. (2) It must be possible to test it and measure its results.


1. If I replace the “learn more” CTA on my page with a “request a demo” button, then the number of clicks will increase by 10% in one month because it will make it clear for my audience what the outcome of clicking on the CTA is.

2. Changing the number of form fields from 10 to 30 will increase the number of leads by 20% in one month.

To sum it up, an assumption is a statement that you’re going to suppose is true (without necessarily attempting to prove), whereas a hypothesis is more a statement that you’re actually attempting to prove as opposed to merely assuming.

How to get from assumption to hypothesis – the right way

In order to be more specific for your experiments, you need to convert the assumptions into more concrete hypotheses. How can you do this?

The first step is to identify the assumptions in your arguments and see which ones are worth being tested. Because assumptions are statements whose truth is being speculated but not proven, it is easy to fall into the trap of trying to test them all – and this can go horribly wrong and make you waste a lot of resources for 0 results.

So, after identifying your assumptions you need to separate them into risky and irrelevant ones. Your riskiest assumptions will then be transformed into hypotheses.

Turning assumptions into hypotheses can be hard and confusing. But it shouldn’t be, because, in the end, a hypothesis is a statement you believe to be true about the riskiest assumption. In order to make it easier for you to formulate your marketing hypotheses, you should follow the following simple steps. 


Properly identify the risky assumptions:

  1. Be specific.
  2. Make sure your hypothesis is measurable. Don’t use ambiguous words and convert to a if-then-because  statement.
  3. Clearly state the desired outcome and tested variables.
  4. Ask yourself if you need to test that hypothesis. If it didn’t start from a risky assumption, then it might not be as solid as you think it is and you should not move forward testing it.
Assumption  Hypothesis
People don’t click on CTA buttons. If I change the “learn more” CTA on my page with a “request a demo” button, then the number of clicks will increase by 10% in one month because it will make it clear for my audience what the outcome of clicking on the CTA is.
People will pay for this new product. If I show my already existing clients a prototype of the new product, then 30% of them will commit to paying for it via an email of intent.
People will sign up for my newsletter. If I give away an ebook (for free) when asking my website visitors to subscribe to my newsletter, then 20% of them will give their email address and agree to join my email list.
Form fields  don’t bring leads. By changing the number of form fields on our website from 20 to 30, we will increase the number of leads by 30% in 6 months.

To have a better understanding of how this works, I’ll show you how we do it!

First, we come up with ideas and assumptions. How? Well, there are multiple ways to do it, depending on what you are focusing on. You can start by having a brainstorming session with your team to come up with new business ideas, use a buyer persona map in order to make assumptions about your clients, interview your customers, etc. Here it’s important to choose your focus and take the next steps accordingly.

After completing the first step, the elimination game begins. You need to analyse your ideas and pick the best ones that you can turn into a testing-worthy assumption. 

There are multiple ways to go from here, but what we like to do is to use the assumption mapper to prioritise and map the assumptions. This tool helps us to categorise our assumptions based on importance and ease of implementation. After using this map we will be able to differentiate the critical assumptions from the not so critical ones and know which ones we can validate with ease.

After eliminating the unimportant and difficult to validate assumptions, it is time to translate them into hypotheses, so they can be tested.

We use the experiment card to break down the assumptions into more clear statements. Afterwards, we translate them into experiments. The purpose of the experiment card is to help us design the right experiments at the right time. It makes it easy to identify the riskiest assumptions, then transform them into clear, falsifiable hypothesis so that, in the end, you can set up your experiments. After running your experiments, all that’s left to do is check the results and plan your next steps.

Now that we know what hypothesis we need to test and we have an idea about what experiments we could run, we use an experiment design matrix to choose the most relevant tactics for this particular case. 

Last, but not least, we use an experimentation map to map out the different activities that lead to the validation of the experiment and that will further on lead to the execution of the project.

Long story short, the road from assumption to hypothesis to experiment is a long one and it can sometimes be difficult to keep on the right track. What is important important to keep in mind:

  1. Assumptions/hypotheses are not absolute truths. They are educated guesses, unknowns or risks and should be treated accordingly.
  2. Only the riskiest assumptions should be considered and turned into hypotheses.
  3. Before deciding to move on and build something, you need to first validate/invalidate your hypothesis.

Need help turning your assumptions into experiments? We’re here to support you with your experiment design. Feel free to reach out, we are eager to help!