In large companies we have a series of knowns. By contrast, in a startup, it’s a series of unknowns. There is a lot we don’t understand.
So one of the ways to think about what we’re doing in a Lean Startup is the business model canvas is allowing us to articulate hypotheses. But just like scientists, when you have a hypotheses, that is you’re guessing something might happen, you want to actually design experiments to test those hypotheses. Gee, I think if I, you know, have this offer, 49 percent are going to convert on my website. Or if I make these product features, customers will want to grab it out of my hand when I just generally describe the product. These are experiments you’re going to be running.
Doing customer discovery and getting out of the building without collecting data is a real sin. What you really want to do is hypothesis, experiments, get the data, but not just add up the columns of numbers. What you’re really looking for is insight. And let me give you an example of insight. I had some students who talked to 50 customers. And they asked them, you know, would you buy this product for $9.99. They had 47 out of 50 said absolutely, what a great product. And they said, Professor Blank, can we move on to the next experiment. And of course, my question was so what did the other three people say. And they said oh, they were idiots. Well, what did they say? Well they said if we had these two other features they would pay $10,000 for it. And I went what. Well, yeah, they said this should be enterprise software, why are we spending all of our time selling it at $9.99. I said did you ask whether those three people had any more friends. Why no, we just added up the column. And what I also remind my students is this is why accountants don’t run startups. We’re not doing accounting here. We’re getting the data, but your job as scientists, you’re actually doing entrepreneurial science, is looking for the insight in that data.