How Do You Write a Hypothesis?

A hypothesis is a clear, testable statement. It includes a forecast or prediction based on the assumption. 
Unlike an idea or open question, which are generally vague or speculative, a hypothesis is a precise, verifiable proposition that outlines both the action and expected outcome.

There are several different formats that Scrum Teams can use to write a hypothesis, including:

• General hypothesis template
  • We believe that [specific change or feature] will result in [desired outcome], because [reasoning behind the change].
  • Example(s): 
    "We believe that introducing personalized recommendations will increase user engagement by 20%, because users prefer content that matches their interest.”
     
• Value hypothesis template
  • If we [introduce a feature/change], then [proto-persona] will [expected action], resulting in [benefit].

  • Example(s): 
    "If we add a customer feedback form to the website, then users will provide more insights, resulting in better product improvements."
    "If we implement a loyalty rewards program, then frequent shoppers will increase their purchase frequency by 35%, resulting in higher overall sales by 15% and improved customer retention by 10%."

    (While not every hypothesis needs to include a number or percentage, doing so makes the hypothesis more focused and specific in what you are testing. Incorporate numbers or percentages when you would like to define the expected results clearly.)

• Usability hypothesis template
  • We believe that by [specific change in UI/UX], users will [desired user behavior], because [reasoning related to user experience].
  • Example(s): 
    “We believe that by simplifying the navigation menu, users will find what they need 25% faster, because the interface will be more intuitive.”
     
• Behavioral hypothesis template
  • If [action or change], then [user segment] will [behavior], leading to [outcome].
  • Example:
    "If we send daily notifications, then frequent users of our calorie tracking app will increase their session frequency by 25%, leading to an 15% increase in overall app usage for users to monitor their daily calorie intake for weight gain/loss.”

Hypotheses can be market-related or testing user adoption.