The Lean Startup Experiment notes

These are my notes on this chapter from the book The Lean Startup. My original post is here.

Start ups / Teams / departments struggle with the following questions:

  • Which customer opinions should we listen to, if any?
  • Which features are essential to the products success and which are ancillary?
  • What can be changed safely, and what might anger customers?
  • What might please today’s customers at the expense of tomorrows?
  • What should we work on next?

If the plan is to see what happens, a team is guaranteed to succeed – at seeing what happens – but won’t necessarily gain validated learning.

The most important lesson of the scientific method: if you cannot fail, you cannot learn.

Can you answer these four questions:

  • Do consumers recognise that they have the problem you are trying to solve?
  • If there was a solution, would they buy it?
  • Would they buy it from us?
  • Can we build a solution for that problem?

Until you can figure out how to sell and make the product, it isn’t worth spending engineering time on it.

A true experiment begins with a clear hypothesis that makes predictions about what is supposed to happen. If then test those predictions empirically.

The goal of every start up experiment is to discover how to build a sustainable business around that vision.

At the beginning, when testing your vision / strategy, always start with a tiny, simple, product which is designed to answer one question above all: is there already sufficient demand for your vision / idea.

Breaking down your experiments

The first step – break down the grand vision into its component parts. The two most important assumptions are the value hypothesis and the growth hypothesis.

The value hypothesis tests whether a product or service really delivers value to customers once they are using it.

The growth hypothesis tests how new customers will discover a product or service. Once the program is up and running, how will it spread from initial early adopters to mass adoption.

The point is not to find the average customer but to find early adopters: the customers who feel the need for the product most acutely. Those customers team to be more forgiving of mistakes and are especially eager to give feedback.

If the numbers from early experiments don’t look promising, there is clearly a problem with the strategy. That means its time to get some immediate qualitative feedback about how to improve.

An entire experiment could be conducted in a matter of weeks, less that one-tenth the time of the traditional strategic planning process. It can happen in parallel with strategic planning process. It can also happen in parallel with strategic planning.

When experiments produce a negative result, those failures prove instructive and can influence the strategy.

An experiment is more than just a theoretical inquiry; it is also a first product.

By the time a product is ready to be distributed widely, it will already have established customers. It will have solved real problems and offer detailed specifications for what needs to be built. Unlike a traditional strategic planning or market research process, this specification will be rooted in feedback on what is working today rather than in anticipation of what might work tomorrow.

Some example hypothesis’s

It is assumed that customers would want to create albums for some of their photos

It is assumed that event participants would upload photos to event albums created by friends or colleagues

Even though a product is missing features, the product/project is not a failure. The initial product – flaws and all – confirmed that users did have the desire to create event albums, which was extremely valuable information.

Success is not delivering a feature; success is learning how to solve the customers problem


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