This article explains how to define a hypothesis in order to run tests to determine the viability of an opportunity. A hypothesis is a statement declaring the expected benefit of your future innovation in a measurable way. To be useful, a hypothesis should be something you could potentially falsify - i.e. prove is not true - through testing.
An example of a good hypothesis might be: "We believe offering customers low cost refillable water bottles will result in a 20% decline in the sales of single-use plastic bottles".
(See our further help on what makes a good hypothesis)
The purpose of creating hypotheses is to guide your testing process and make sure the innovation you are developing is something that your target users want and/or need.
If you are unable to validate your hypothesis, you may be able to pivot your innovation - i.e. change aspects of it to adapt to what you've discovered through testing. If you can't prove your hypotheses or pivot your innovation, this generally means this Test is not worth pursuing any further. The advantage of testing using hypotheses is that you have not yet spent large amounts of money or time on the Test - "fail fast and fail cheap", or "learn fast".
Step by step
- Click on the Hypothesis tab
- Add in the beginning of your hypothesis in one short phrase. It's often helpful to start with:
We believe that followed by the essence of your innovation. For example, "...low cost reusable water bottles...".
For - Who is the target customer or end user? For example, "for our retail customers".
Will achieve - What value will this innovation provide the target customer or end user? What problem or need does it resolve? For example, "...will reduce sales of single use plastic bottles by 20%".
We’ll measure this by - To prove or disprove your hypothesis you must be able to measure it. How will you go about it? For example, "piloting in 12 stores and comparing sales figures over the course of the pilot with stores not running the pilot".