hello and welcome to the bottom-up skills podcast. I'm Mike Parsons. I'm the CEO of tents. And we are continuing our journey, our adventure into the world of lean startup. And today we're going to talk about the mill build measure, learn loop. Yes. It's going to get pretty loopy and it's really important to get into this idea of the loop that is inside of the lean startup, because, you know, if you think about a completed product, that's shiny polished.

It's been through all sorts of prototyping, MVP, it's the full deal. And if you actually look at it, it's actually, you can break it down into literally hundreds of small little tests that have been done since day one. And the [00:01:00] power of this loop is that if you learn each time you build something, you measure it.

Actually, you know, what the product gets better. Uh, you de-risk mistakes, you don't make assumptions. You start to shift from guessing to knowing you're more confident you have more insight. And you know, at the heart of this is the opportunity to, um, really. Enjoy the process because let's be honest, building a product with very, very complex.

So together on this episode of the bottom-up skills podcast, let's decode this scientific method that's behind it all. And let's see how we can continually test hypotheses and, you know, really embraced data, uh, in the use of these little kinds of experiments you could call them. So that we can really, uh, be onto a good thing to know what users desire what's technically feasible.

And honestly, let's make [00:02:00] sure that we've got a viable business offering too. This is all at the heart of the build measure, learn loop. Okay. So let's think about, um, this loop, this loop is something that you could do. Uh, from everything to some of the core functionality inside the app, to the name of the service, everything you can build something, put it through some sort of test with users.

That's that's really, really important. Then you say, okay, let's look at the data and ask, what did we learn? And then once we've worked out, what we've learned, we can then start to inform our next decision. So this is the build measure, learn loop, and you just keep doing this. And I think a great signal inside of any product team is how much they're learning.

So they don't have to hit the home run from day one, but you can be really sure that I'll get that if they're learning. And so using this [00:03:00] loop as the key tool to do it. So you got to start with, you know, obviously a fundamentally good idea, and then you've got to structure that into a hypothesis and I'm going to.

Yeah. Tell you a little bit about how to do that in a second. And then you've got to go, okay. Let's work out. Um, how are we going to measure it? You collect some data after you've tested it. Now it's really important that you always test with users. Um, don't test with yourselves as product owner, because you're going to be full of bias.

Now you've got to really, really test with real users. And then you're going to have to make some, some decisions based on the data and, you know, challenge yourselves about what you've learned. Um, Ask yourself, do we revise? Do we stop? Do we persevere? Do we pivot? There's all sorts of, um, ideas here. Now.

Here's the thing. You can do that with each, uh, core feature each, uh, user story. Uh, or you can start to zoom [00:04:00] out and apply this to the business itself. And so you can see some really significant pivots, uh, have happened from businesses that end up winning, uh, providing a service that was, looks nothing like where they started because they used this loop and they kept learning all the time.

And actually they abandoned their early ideas. In fact, most successful startups end up succeeding. In an idea or a version of the product that is radically different to where they started. So it shows you how much learning is really crucial because we often don't really start with the best ideas, even though no matter how good and no matter how talented we are.

In fact, sometimes we've got some pretty rotten ideas, but actually if you use this loop, You can look at your, whether it's a logo idea, product idea, or venture idea, just look at it as a starting point. And if you continue to learn, you should get incrementally better. [00:05:00] Now there's a lot inside of this loop and I want to focus on something that's going to come back a lot in this series, which is like, what's the hypothesis.

And I really like this because it just helps me simply structure a product idea and its proposition to the customer and to the user. And inside of this hypothesis can be certain. Parts, uh, elements or aspects of the product or service that we can test and will change a lot. And I'm just going to take you through what this might look like, so you can get a good sense of, okay.

I know there's a loop. I know we're going to build, we're going to measure, we're going to learn, but I'm going to give you, um, the structure of, uh, of the venture hypothesis. So you can start to wrap your mind around it. So this is an example of our structure or template that you could use yourself. So I want you to imagine this is a venture hypothesis, a [00:06:00] business idea, a product idea, and here we go, a certain persona exists and they have a certain problem scenario, situation.

And currently they're using certain alternatives to kind of get this job done. But if we offer our time target value proposition, our solution, right? Then we'll observe success through key metrics such as onboarding engagement, et cetera. So this would be. Basically your idea in a nutshell, and let's just break it down and see what is inside of the hypothesis and see how we could break this apart and test it.

So the first thing you'll notice I mentioned is a certain persona exists. They said differently, a certain customer, a certain customer segment exists. Well, that's something that B can be tested because you're going to want to go for [00:07:00] a. Let's say health obsessed 40 year old men. Let's just say, that's your persona where you need to go out and actually validate that th there are a lot of health obsessed, 40 plus men in the world, and then you'd have to go to the next part of your hypothesis and they have a certain problem.

Okay. So you can go in test the problem. So you can do a lot of, uh, very, um, simple interviews and surveys to actually qualify. Does this problem exist? Is it the biggest problem and is it a problem that they really want to solve and therefore would be prepared to pay for this problem scenarios? The next part of your hypothesis that you can test.

And again, this is, remember this is all inside the loop. You're going to build, measure, learn. Each one of these things, you build something you actually measure and test it with the user, ask yourself what you've learned, and then that informed what you build next. But [00:08:00] we're not done with the hypothesis because you'll remember that the third part, after we say a certain persona exists and they have these problems, we then say, currently they are using these alternatives.

And in here are lots of clues to either what you should do. What you could do better than what's currently on offer, or you might have to go radically beyond because they're currently meeting the needs of users. So understanding how people get the job done today, even if it's far from perfect, really essential as part of your hypothesis, and really, really crucial to go into test, to learn, um, put it through that loop.

And then you say, if we offer our value proposition, what it's, what's going to relieve their pain, what's going to create their gains. This is our hypothesis. Now you can test this ...