Live Prototyping

Purpose

To test how an innovation would work if it became a reality.

When To Run This

You want to test and measure your innovation against your hypotheses.

Time

As long as it takes to get significant results.

Input

  • Hypotheses

Materials

  • A Minimum Viable Product (MVP) - a version of your innovation with enough features that it’s able to do the task it was built for

TheSteps

Prepare:Prepare:

  • Create your hypotheses. Use the Hypothesis Creation tool to figure out what you want to test in your Live Prototype.

  • Define your MVP. What features or capabilities does the innovation need before it’s useful? To help you decide, you can use the Impact/Effort Matrix tool or the Feature Bucket model. 

    1. For the Feature Bucket model, sort your features out into these 3 buckets
      1. Must have (MVP feature set)
      2. Nice to have 
      3. Not needed
  • Decide how you’ll collect results or feedback. Think about which metrics make sense for your test, such as tracking data, the amount of users, or their satisfaction scores. You could also do a survey at the end of the Live Prototype.

  • Prepare the test. Organise everything you’ll need to run your Live Prototype. Does it need a physical test space or a server? Will you need to promote the MVP to get people to use it?

Action It:Action It:

  • Run the test. If it’s possible, you can save time by doing a few Live Prototypes simultaneously to compare a variety of ideas and see how they work together

Next Steps:Next Steps:

  • Analyse the results.

    1. How well did your Live Prototype work? 
    2. What was the user feedback? 
    3. Did it prove or disprove your hypothesis?
  • Keep improving. Live Prototypes are all about learning and fixing problems quickly so that you can push your solution to its best version. If something didn’t work on Day 1, try a new approach on Day 2.

Considerations

Considerations

  • Your innovation doesn’t have to be perfect for launch, the sooner you test it in the real world, the quicker you’ll be able to improve it.
  • Don’t be afraid to change things during the test, but make sure you’re following the right feedback, not the outlying data.
Signals

Signals

It's Going Well When:

  • The results you’re getting clearly answer your hypothesis, i.e. proving or disproving it. 
  • You are gathering a lot of meaningful feedback 
  • You know how to improve your innovation

Watch Out For:

  • Your Live Prototype didn’t help your users complete their task - it doesn’t answer your hypothesis - Supply the missing parts and repeat your prototype.

Whatsnext?