1-Page Summary1-Page Book Summary of The Lean Startup
The goal of a startup is to learn what their customers want and will pay for, as quickly as possible. Because startups face so much uncertainty, you have to make continuous adjustments to your startup plan, based on the information you get back. This is Build-Measure-Learn.
Think about it like driving a car. When you get on the road, you make constant adjustments to the steering wheel, based on where you see yourself on the road. Veer a little right, and you turn to the left before you go offroad.
A startup’s the same way. You collect information about your customer, just like seeing where you are on the road. Based on this new information, you adjust your strategy, like turning the steering wheel. You keep repeating this and making progress.
But you need to approach learning with discipline, a process called “validated learning.”
Bad learning is executing a plan without much prior thought, seeing it work or fail, and giving a post-hoc rationalization. (“Well of course X didn’t work, that means we should do Y!”)
Validated learning is having testable hypotheses about the world, designing experiments to test those hypotheses, and analyzing the data to evaluate your hypotheses. You have real, quantitative data to show what you have learned.
How can you learn what your users want, as quickly as possible, and with as few resources as possible? The strategies of Lean Startup answer this question.
First, you set your hypothesis. What do you believe about your customers that is vital to your business? How are you going to measure this?
Next, you build the MINIMAL product necessary to test the hypothesis.
Next, you run the experiment. Often this means exposing users to the product and collecting data on their behavior.
Finally, you analyze the data and reflect – how far off was your hypothesis? What do you need to change about your strategy? Should you actually change your entire direction?
Then you update the hypothesis or set a new one. Then you build the minimal product to test that hypothesis, and so on.
The faster you move through this loop, the faster you’ll learn, and the more progress you’ll make. Imagine how much you’d learn from 10 steadily improving prototypes vs 1 giant, fully-featured prototype.
What are hypotheses in a startup? Your hypotheses should revolve around the most important problem of a startup – how to build a sustainable business around your vision.
Commonly, there are two critical hypotheses:
Value hypothesis: does the customer have the problem you’re trying to solve? Does the product actually deliver value to the customer?
Growth hypothesis: how will the company grow once people start using the product?
Principles of Lean Experimentation
The best way to understand human preferences is to track behavior of real people, not ask for opinions. People often can’t verbalize what they actually want – cue the classic Henry Ford quote, “If you asked people what they wanted, they’d have said faster horses.” The better way to measure what people want is by their real behavior – what they click on, what they spend time looking at, what they choose to pay for.
Think about the cheapest, fastest experiment you can run to validate the hypothesis. Simplify the product to the core essentials needed to run the experiment. Resist the urge to build more than is absolutely necessary – as you’ll learn, sometimes you can fake it ‘til you make it without a real product.
Launching early gives you customer information earlier. The earlier you learn if customers actually want what you’re building, the more time you have to change your plan and run more experiments. You also discover customer concerns you couldn’t have predicted in a vacuum.
The Minimum Viable Product
Your goal is to move through the Build-Measure-Learn loop as quickly as possible. Even though the loop has 3 steps, Build…