Experimentation 101: So You’re Ready to Write a Hypothesis

To get the most clear results out of your tests, marketing experts Cindy Alvarez, Alistair Croll and Anita Newton all emphasize the importance of creating a constrained hypothesis before you start experimenting. But don’t just come up with it, write it down!


A hypothesis is what you think will happen when customers come into contact with your product, and the basic structure of an experiment hypothesis looks like this: I believe [customers like this] will [behave like this] in [this measurable way] in [this time period].

The most effective hypotheses ones are usually quantitative because they give you a clear way to see whether your assumptions were right (i.e., people will spend at least three minutes per page reading articles on our new site; or, one of ten sales calls in the next month will lead to a signed contract for our new product). “Validating a hypothesis” means you’re running experiments that prove it true; “invalidating a hypothesis” means your experiments are proving it false. Ben Yoskovitz has a clear write-up on how to craft a useful hypothesis.


When you create a hypothesis, it can be around either the value potential or the growth potential for a product. A value hypothesis tests whether a product delivers value to customers once they’re using it, whereas a growth hypothesis tests how new customers discover a product.

This week, the Lean Startup is taking over the blog on Intuit Labs with original stories and a fresh perspective. Centered around experimentation and investigating all parts of a business or product idea, this week’s posts include case studies, tips, Q&As, startup stories and more.  If you want to learn more about Lean Startup and how it’s applied at Intuit, visit the Intuit Innovation InstituteThis piece was written by Mercedes Kraus.


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