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?
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.
Your goal is to move through the Build-Measure-Learn loop as quickly as possible. Even though the loop has 3 steps, Build...
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The media portrays startup success incorrectly as fatalistic – if you have the right stuff (a good idea, determination, timing, and luck), you will inevitably succeed. If you don’t succeed, it’s because you didn’t have the right stuff. You either have it or you don’t.
This idea is seductive because it both promises easy success and justifies failure. To succeed, all you need is the right stuff – easy! And yet if you fail, you can simply justify failure as not having the right stuff, rather than making poor decisions. This is softer on the ego.
This is the wrong way to think about entrepreneurship. Startup success is NOT fatalistic. There is a rigorous, repeatable method to achieve startup success – the Lean Startup.
The ideas in the book came about when Eric Ries got frustrated working hard on products that failed to get traction. As an engineer, he initially thought they failed due to technical problems, but this was never the right answer. In reality, they just wasted a lot of time building things nobody wanted.
So when he started his new company, IMVU, he wanted to try...
‘Management’ is often a dirty word in startups because it conjures images of grey suits, bureaucracy, and TPS reports. Startups are worried management will squash energy and creativity.
The problem is, startups go too far in the other direction into chaos. They often take a shoot-from-the-hip, hail-Mary, undisciplined approach to company development. This unfortunately often leads to failure, spending years of your life building something no one cares about or remembers.
Startups really do need management, but a new kind of management catering to high-risk innovation - a kind of Entrepreneurial Management. By using this management method, you will be confident you’re moving in the right direction and learning more about your company. Surprise – that method is the Lean Startup.
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Who, exactly, is an entrepreneur?
Entrepreneurs aren’t just startup founders working out of apartments. They can also be general managers in large companies charged with creating new ventures or new product lines.
The author defines a startup as “a human institution designed to create a new product or service under conditions of extreme uncertainty.”
The definition is purposefully broad – it can apply to a non-profit, a government agency, a big company or a small company. The key piece of this definition that makes a startup unique is the condition of “extreme uncertainty.”
In situations of uncertainty, traditional management tools – like forecasts, business plans, and milestones – break down. There’s too much that’s unknown about the world to predict with high accuracy what’s going to work.
The Lean Startup is a set of methods for building a successful startup, wherever it is and whoever is working on it.
In 2009, a startup wanted to automate...
Remember that a startup is trying to build a new product or service in conditions of extreme uncertainty. There are a lot of things you know that you don’t know, and a lot of things you don’t know that you don’t know.
Therefore, a startup’s most important function is learning – in particular, learning what the customers really want and what will lead to a sustainable business.
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.
In 2004, author Eric Ries and his co-founders at IMVU wanted to build a social network around instant messaging (IM), which seemed attractive for its network effects – the more people who join, the more valuable the network is, which makes even more people join....
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Lean Startup treats building a startup as science:
Once again, this stands in stark contrast to the typical “launch and we’ll see” approach. You’re forced to question what your assumptions about your business are, and you’re encouraged to test those assumptions as quickly and cheaply as possible.
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?
We’ll unpack each of these, and how to test them, in the following chapters.
As you learn how to design experiments and test hypotheses,...
Reflect on the principles of Lean Startup.
Do you consider yourself in an entrepreneurial situation – “creating a new product or service under conditions of extreme uncertainty?” Why or why not?
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With your startup, your goal is to learn as quickly as you can with disciplined experiments. Central to Lean Startup is the Build-Measure-Learn feedback loop.
Let’s step through this loop once:
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.
Every startup begins with a set of hypotheses about how the business will work. As stated above, there are typically two core...
Your goal is to move through the Build-Measure-Learn loop as quickly as possible. Even though the loop has 3 steps, Build is often the step where you will waste the most time.
The critical question you need to answer is: what is the MINIMUM product you can build to get reliable data on your hypothesis?
This product is termed the Minimum Viable Product (MVP) and is one of the most important concepts in Lean Startup. This is the product that is the bare minimum to test your hypothesis. Unlike normal product development, you are NOT aiming for product perfection – you’re merely trying to start learning as soon as possible.
The value hypothesis is key to most startups – “does anyone want what we’re building?” The typical wrong route many entrepreneurs make is to simply build their full product, then wait for results. Here’s the problem with that approach – every extra feature you add before testing means wasted time. You might be pointed entirely in the wrong direction. Building features nobody wants means more wasted time before you test and find out you’re in the wrong direction.
Depending on your business, there are a variety of ways to test your hypothesis in the...
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Try to design the minimum product that will test your hypothesis.
What is the key hypothesis you want to test? Often, it’s centered around the question of whether your users will want what you’re building, or whether they have the problem you’re solving.
The job of a startup is to:
Defining the right metrics that actually matter to your business is critical. Before giving examples of good metrics, we’ll define common bad metrics startups choose.
The most insidious kind of metrics, vanity metrics, give you false optimism – it seems like you’re making great progress, but in reality you’re actually stuck.
Often, vanity metrics are metrics that have no choice but to keep increasing over time. One common example is total user count. Let’s say your app adds 1,000 users every week. At the end of 10 weeks of hard work, you have 10,000 users. This is a big number!
Except you aren’t growing any faster – you’re still adding 1,000 users every week. Your hard work actually didn’t change your growth rate.
These vanity metrics are misleading because they keep increasing over time, making you feel good. To give an obviously silly example, think about a metric like number of hours worked. Every day, you and your team each add 10 hours to...
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Don’t be fooled by vanity metrics - focus on the most valuable metrics for your startup.
Have you ever been asked to focus on a metric that you thought was misguided or silly? What was the metric, and why was it bad?
Now when you’re facing the data, you need to decide what to do. Is there still promise in your direction, and should you keep trying to iterate through the Build-Measure-Learn loop? Or have the metrics come back so disappointing so often that it’s time to change your strategy entirely – to pivot?
The answer is often unclear because you will seldom encounter complete, abject failure. The more likely state is when you’re barely limping along, not plummeting to the earth but also feeling like you’re not really making progress. The decision gets hard here.
There are two signs of the need to pivot:
Lean Startup gives the example of Votizen, a company founded to boost participation in politics. Their first product was a social network where voters could unite around causes and mobilize action. They formed hypotheses around 4 metrics: signing up (registration), verifying voters (activation), sticking around and using Votizen (retention), and recruiting friends to join...
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Part 2 is really the core of Lean Startup. You’ve learned about the entire Build-Measure-Learn loop. You know that you need to form hypotheses about your business and test them with MVPs. You know to avoid vanity metrics and focus on the metrics that really tell you the health of your business. You know that you will need to face the question of whether to pivot.
In the concluding section of the book, we’ll learn how to accelerate through the Build-Measure-Learn loop and stay agile as you grow.
The aim of the Build-Measure-Learn loop is to step through it - or iterate - as quickly as you can. This increases your rate of learning.
To support this, try to decrease your batch size. Don’t overinvest in huge feature releases. Release less and more often, and you’ll learn faster.
Imagine you have 100 letters to mail. Each letter needs to be signed, folded, put in an envelope, sealed, and stamped. How would you approach this?
Your intuition is likely to batch each separate step and do all 100 at once. You’ll sign all 100 letters. Then you’ll fold all 100 letters. Then you’ll put 100 letters in 100 envelopes. And so...
A startup is a new company designed to grow. If you’re ambitious about your startup, you want more customers and more revenue sooner. When growth stagnates, it indicates a problem with your growth strategy.
Ideally, you strive for sustainable growth – wherein new customers come from the actions of past customers. This contrasts with unsustainable one-time activities, like a publicity stunt or Super Bowl ad.
How exactly your business grows depends on your industry and product. Eric defines three major engines of growth: Sticky, Viral, and Paid. These aren’t mutually exclusive, and often businesses will use all three at once. But it’s likely one of these will dominate the others.
The Sticky engine relies on retention of customers to grow. When you acquire the user, you want the user to stick around as much as possible.
As a metaphor, think of a leaky bucket with holes. When you pour water in, water flows out the holes. If you fill the bucket with water at the same rate it’s exiting the holes, the water level stays steady – no growth. This is like a startup that loses customers as fast as it’s gaining them - the total number...
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A lean startup faces natural tension between opposites: fast and scrappy vs slow and methodical, hacky and agile vs robust and overdesigned.
Initially, building a product quickly and poorly gets you data faster. But you incur technical debt that will slow development in the future.
How do you decide where on the spectrum to lie? You need a natural feedback loop to tell you when you’re moving too slowly or too quickly by identifying the root cause of problems.
When you face a new problem, root cause analysis tells you precisely why the problem happened, and suggests how to fix it. This prevents overdesign and prevents the problem from happening again.
Find the root cause with the Five Whys method. When you see a problem, ask yourself five Whys in succession.
Here’s an example from Toyota where a machine broke down:
Try to figure out the root cause of a problem.
What problem have you faced recently? Why did it happen?
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The final substantive chapter of Lean Startup discusses innovation in a large company and internal startups.
If growth is your goal and you achieve it, you’ll keep growing your startup to 10, 100, 1,000 people. How do you keep innovating to grow new lines of business while keeping existing products competitive? How do you prevent yourself from being bogged down by process?
The solution is to manage lines of innovation in parallel.
Each product has a life cycle:
Once a company grows past its early stages, it needs to think about what comes next. This means managing multiple products at different stages of the cycle at once. Earlier projects will be sunsetting and losing revenue just as the next major innovation breaks new ground.
Who is the best person to run a product through its lifecycle? A typical answer is to tie the original product team through the entire life cycle of the product. After all, they built it, so they seem like natural candidates to scale it up and to sunset the...
Eric Ries believes a tremendous amount of effort today is wasteful. Over the past century, our bandwidth for production is much larger than our ability to know the right things to build. This problem is compounded by the high rate of change of many industries.
Luckily, this is preventable. The Lean Startup is a framework for figuring out the right things to build. It answers the innovation question: how can we build a sustainable organization around a new...
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