Build Measure Learn vs. Learn Measure Build

The first time I saw Kent Beck speak he was going on and on about an itchy goat. I had no idea who he was or why he was talking about this goat or why he was scratching it on the back. But he said something that struck me and keeps coming back.

The Build Measure Learn loop is backwards.

There is a presumption there that if we start building something and slap some analytics on it then we will inevitably learn something.

[UPDATE: Reversing the BML loop is in fact noted in Eric Ries’ book The Lean Startup. I had just always recalled it from Kent’s talk.]

S̶t̶e̶p̶ ̶1̶ Step 3 — Build a Minimum Viable Product

Building an MVP shouldn’t be about minimum effort or just taking out features.

A Minimum Viable Product must be designed for validated learning. -Tweet This

Sure, if you just want to hack something fun together over the weekend, go for it. Release it, see what happens, decide if you want to continue. That’s certainly one way to approach things. (This is affectionately called the “Field of Dreams” approach by some.)

But if our goal is validated learning, the first thing we need to do is decide what to learn. Scientists don’t just start throwing chemicals into a vat and randomly feed it to babies to see what happens. They didn’t build the Large Hadron Collider for the hell of it.

Building random toys to find Product/Market Fit is like paying $80k / year to pick classes by throwing darts at a college catalogue. -Tweet This

A good scientist forms a hypothesis, then carefully designs an experiment with a control group to measure the effect of that experiment. Only then do they implement the experiment and learn something.

Minimum Viable Product is a terrible name. I prefer to build a Minimum Viable Test. -Tweet This

(Parker Thompson also proposed the term Minimum Viable Interaction which we also like tremendously.)

Step 2 — Measure What?

Let’s just throw it out there and see if it works!

Awesome! Do it! How will you know if it works?

Let me guess…you’ll slap google analytics on it, throw up a post on Hacker News, it’ll be voted to the top in meritocratic fashion, and then you’ll be able to tell if people sign up.

Here’s the problem:

  1. Getting to #1 on Hacker News? — A vanity metric.
  2. # of sign ups? — A vanity metric.
Your goal must be validated learning about Product / Market fit. -Tweet This

Product / Market fit does not mean, “does anyone want this thing I built?”

Just knowing that someone, somewhere out in the world wants something you build doesn’t help you.

If there are enough dubiously curious individuals out there who want to buy the shake weight, then we guarantee you that no matter how idiotic your startup idea is, there is at least one individual who is willing to pay for it.

Who is that person? Why do they want it? How are you going to find that person? How many of them are there? Are they willing to pay for it?

At the crux of the biscuit, Product / Market fit asks, “does this specific customer segment desire this specific value proposition?” So at the minimum we need a to measure what % of our target market sign up with a reasonable sample size.

That implies we either restrict our marketing to the customer segment, or we screen them out of our conversion somehow.

In other words, if we’re building a product to target soccer moms, then a viral posting on Hacker News has no bearing on our product, even if we have a 100% conversion rate. (If anything, that would imply that we are targeting the wrong customer segment.)

You can not measure your signup conversion rate without having a clear target market. -Tweet This

(BTW: “Everyone” is not a clear target market. More on that in another post.)

S̶t̶e̶p̶ ̶3̶ Step 1 — Learn

So if you want to start with Build, please do so. I enjoy building random toys myself from time to time. But don’t kid yourself about what you’re learning.

If you really want to learn about your business, start by figuring out what you want to learn.

  1. Establish a hypothesis.
  2. Determine a quantitative or qualitative method to evaluate that hypothesis.
  3. Build an experiment to test that hypothesis.

This post was originally published here on Grasshopper Herder — Lean Startup Blog. Don’t miss a post…Subscribe!