Hypothesis Generation vs. Validation

A lot of people ask me what sort of research they should be doing on their products. There are a lot of factors that go into deciding which sort of information you should be getting from users, but it pretty much boils down to a question of “what do you want to learn.”

Today, I’m going to explore one of the many ways you can go about looking at this: Hypothesis Generation vs. Hypothesis Validation. Don’t worry, it’s not as complicated as I’ve made it sound.

What is Hypothesis Generation

In a nutshell, hypothesis generation is what helps you come up with new ideas for what you need to change. Sure, you can do this by sitting around in a room and brainstorming new features, but reaching out and learning from your users is a much faster way of getting the right data.

Imagine you were building a product to help people buy shoes online. Hypothesis generation might include things like:

  • Talking to people who buy shoes online to explore what their problems are
  • Talking to people who don’t buy shoes online to understand why
  • Watching people attempt to buy shoes both online and offline in order to understand what their problems really are rather than what they tell you they are
  • Watching people use your product to figure out if you’ve done anything particularly confusing that is keeping them from buying shoes from you

As you can see, you can do hypothesis generation at any point in the development of your product. For example, before you have any product at all, you need to do research to learn about your potential users’ habits and problems. Once you have a product, you need to do hypothesis generation to understand how people are using your product and what problems you’ve caused.

To be clear, the research itself does not generate hypotheses. YOU do that. The goal is not to just go out and have people tell you exactly what they want and then build it. The goal is to gain an understanding of your users or your product to help you think up clever ideas for what to build next.

Good hypothesis generation almost always involves qualitative research. At some point, you need to observe people or talk to people in order to understand them better.

However, you can sometimes use data mining or other metrics analyzation to begin to generate a hypothesis. For example, you might look at your registration flow and notice a severe drop off half way through. This might give you a clue that you have some sort of user problem half way through your registration process that you might want to look into with some qualitative research.

What is Hypothesis Validation

Hypothesis validation is different. In this case, you already have an idea of what is wrong, and you have an idea of how you might possibly fix it. You now have to go out and do some research to figure out if your assumptions and decisions were correct.

For our fictional shoe-buying product, hypothesis validation might look something like:

  • Standard usability testing on a proposed new purchase flow to see if it goes more smoothly than the old one
  • Showing mockups to people in a particular persona group to see if a proposed new feature appeals to that specific group of people
  • A/B testing of changes to see if a new feature improves purchase conversion

Hypothesis validation also almost always involves some sort of tangible thing that is getting tested. That thing could be anything from a wireframe to a prototype to an actual feature, but there’s something that you’re testing and getting concrete data about.

You can use both quantitative and qualitative data to validate a hypothesis, but you have to choose carefully to make sure you’re testing the right thing. In fact, sometimes a combination of the two is most effective. I’ve got some information on choosing the right type of test in my post Qual vs. Quant: When to Listen and When to Measure.

Types of Research

Why is this distinction between generation and validation important? Because figuring out whether you’re generating hypotheses or validating them is necessary for deciding which type of research you want to do.

Want to understand why nobody is registering for your site? Generate some hypotheses with observational testing of new users. Want to see if the mockups for your new registration flow are likely to improve matters? Validate your hypothesis with straight usability testing of a prototype.

These aren’t the only factors that go into determining the type of research necessary for your stage of product development, but they’re an important part of deciding how to learn from your users.

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