Experiment Canvas

30 minutes
Creative Commons CC BY-SA 4.0

Once you’ve found your riskiest assumptions you’ll need a way to figure out how best to test and measure them in a quantitative way. The experiment canvas, created by Ash Maurya, provides a straightforward way to break down your assumptions into measurable, observable, experiments.


  • Regular size (A4) PDF

How To Use the Experiment Canvas

The purpose of the experiment canvas is to design the right experiment at the right time, facilitating a team to have the right conversation. With the experiment canvas, it is easy to design a well-defined experiment: starting with identifying the current Riskiest Assumption, then specifying a clear, falsifiable hypothesis and experiment setup. After running the experiment, check the results and plan your next steps.

Your hypothesis is a statement you believe to be true about your riskiest assumption. Write it down before you run the experiment. It is too easy to change the conditions afterward to make the data fit, and this robs you of valuable insight.

Quantify your hypothesis. How many customers will do it? How many times? In what timeframe? It’s okay to use a bandwidth for this, as long as you specify it upfront. The metrics you define need to be actionable (i.e., they need to directly relate to the hypothesis) and, accessible (i.e., you need to be able to see the results).

Link the numbers back to the assumption you are testing. Why does having 10 positive results validate your assumption? Specify any qualitative outcomes and variables. What different answers you are expecting? How will you cluster them?

Armed with this hypothesis you’re ready to start your experiment. Track the data immediately and write everything down, so that later you can check if you interpreted the results correctly.

Use the hypothesis formula: "We believe (specific testable action) will drive (specific measurable outcome) within (timeframe)"

Tool Overview

  1. Riskiest Assumption

    What is the riskiest assumption you want to validate? And why is it so important?

  2. Falsifiable Hypothesis

    Declare the expected outcome beforehand. Try to have a good estimate rather than fake precision!

  3. Experiment Setup

    What is the prototype you will use to test with? What are the important variables and metrics? Is it quantitative or qualitative?

  4. Results

    Enter the qualitative and/or quantitative data resulting from your experiment.

  5. Conclusion

    Summarize your findings. Did your result validate or invalidate the hypothesis? Or was it inconclusive?

  6. Next Steps

    Do you need to pivot, persevere, or redo the experiment?

Step by Step Guide

1 Before you start

Arrange for a comfortable environment. Definitely not a meeting room. Make sure you have already found your Riskiest Assumption.


  • Arrange a relaxed, positive and private environment
  • Have markers (fine tip) and paper for everybody
  • Print or draw the canvas on a big sheet of paper
  • Have plenty of sticky notes and markers ready
  • Allow yourself 45 minutes of undisturbed time

2 Define the Experiment

Go over the sections on the left side of the canvas. Come up with a hypothesis first, and then try to figure out what you need (in terms of a prototype setup) to test that hypothesis. Have a look at the Prototype Canvas for inspiration.


  • You have created a falsifiable hypothesis to test the Riskiest Assumption with
  • Your hypothesis fits the template
  • You defined measurable outcomes
  • You created a prototype

3 Run the experiment

Run the experiment for the time you specified, and collect the data.

4 Draw your conclusions

Based on the data, decide if your hypothesis was validated or invalidated - or that your experiment was inconclusive.

5 Next Steps


Additional Resources

2 day DBB masterclass by the authors and designers!

October 10/11 2018 at Hotel Zoku Amsterdam