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 Institute. This piece was written by Mercedes Kraus.