Book SummaryThe Lean Startup, by Eric Ries

1-Page Summary1-Page Book Summary of The Lean Startup

In The Lean Startup, entrepreneur Eric Ries argues that your startup’s primary objective should be discovering what customers actually want and are willing to pay for, in an efficient and cost-effective way. Ries writes that this entails constant experimentation—you put something in front of customers, pay close attention to how they respond, and use that information to decide what to do next. This cycle repeats continuously as you feel your way toward a product people actually want.

In this guide, we’ll explore this repeating cycle of experimentation, covering how to 1) form a hypothesis about your customers, 2) put out a simple version of your product or service to test that hypothesis, 3) collect data and observations from how your customers react, and 4) adjust your strategy based on observed results. As we go through Ries’s experimental cycle, we’ll complement his analysis with insights from other experts in entrepreneurship and startup formation.

Why the Experimental Approach Works

According to Ries, to understand what people want, you have to observe their behavior—you can’t just rely on what they say they want. Thus, purchasing decisions, time investment, and engagement patterns are your windows into your customers’ true needs and desires.

(Shortform note: Some experts write that deeper psychological issues motivate all purchasing decisions, rather than specific product or service benefits. According to Josh Kaufman (The Personal MBA), people make purchases in an attempt to fulfill five basic needs: to feel good about themselves, to connect with others, to grow and learn, to feel safe, and to avoid effort. Therefore, considering which of these five motivations your product or service fulfills will help you appeal to your target market’s innate needs.)

To observe customers’ behavior, writes Ries, you need to get something into their hands and see how they react to it. So, you must create a pilot project and deliver it quickly. The sooner you deliver it to real customers, the sooner you can start getting real feedback and uncover the kinds of unexpected challenges that couldn’t have been anticipated through internal planning alone. This gives you time to course correct, reiterate, and improve on the fly. Crucially, your first experimental cycle almost certainly won’t be your last: You’ll run through multiple rounds of experimentation with your product, each featuring a modified version of your product informed by previous rounds of experimentation.

Further Advice on Researching Your Target Market

In addition to the kind of direct experimentation Ries proposes, marketing experts recommend that you gather relevant data regarding market demand for your product or service. You can do this by:

• Using SEO tools to analyze how many people are searching for similar products and services to yours and what businesses and distribution channels they use to fulfill their needs.

• Signing up for social listening tools that monitor online conversations about products, brands, and consumer needs so you can see where demand already exists and how competitors are positioning themselves.

• Using market and industry reports to understand the broader context your experiment sits within.

Many businesses rely on the strategies above to inspire new marketing campaigns. For example, The Body Shop tracked online conversations to learn more about customer preferences. Discovering that customers cared about refillable products inspired them to launch a global refill program that appeals to eco-aware and value-conscious customers.

Experimental Cycle Step #1: Form Your Hypothesis

Ries writes that you begin your experimental cycle by forming a hypothesis about your customers; like any good hypothesis, it needs to make predictions that can be observed and tested. In this case, your hypothesis (if it’s correct) should predict the behavior of your customers and tell you something valuable about whether your product solves a problem for them. Crucially, it should tell you whether or not your product addresses genuine customer needs and how your customer base will grow beyond early adopters—ensuring the business model can scale sustainably.

For example, imagine you’re building an app that helps people find hiking trails. Your hypothesis is that hikers care most about knowing how crowded a trail will be before they go. If this belief is correct, it should predict something observable about how customers behave. So you make a prediction: If you add a “crowdedness” indicator to your app, users will check the app more frequently before weekend mornings, which is when trails tend to be busiest. If your hypothesis is true, you should see a spike in use during those specific windows. This tests whether you’re solving a real problem that matters to hikers.

Beyond that, you’d also need to test how the app will grow—perhaps hypothesizing that satisfied users will recommend trails to their hiking partners through the app, creating a natural sharing mechanism that expands your user base without heavy marketing spending.

(Shortform note: Ries’s cautionary note that your hypothesis needs to make testable predictions raises an important point: Not all hypotheses are created equal. In The God Delusion, evolutionary biologist Richard Dawkins writes that we...

The Lean Startup Summary Introduction

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.

Origins of 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...

The Lean Startup Summary Part 1: Vision | Chapter 1: Startups Need Managing

‘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.

Startups Need to Learn as...

The Lean Startup Summary Chapter 2: Entrepreneurs Are Everywhere

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.

Startup Example: Snaptax

In 2009, a startup wanted to automate...

The Lean Startup Summary Chapter 3: Learn What Your Users Want

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.

Startup Example: IMVU

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....

The Lean Startup Summary Chapter 4: Experiment like a Scientist

Lean Startup treats building a startup as science:

1. Create a hypothesis. What do you believe that’s important to your business?
2. Design an experiment to directly test that hypothesis. Run the experiment and gather data.
3. Reflect on the data – can you validate or reject your hypothesis?

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.

Startup Hypotheses

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.

Principles of Lean Experimentation

As you learn how to design experiments and test hypotheses,...

Shortform Exercise: Your Startup Beginning

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?

The Lean Startup Summary Part 2: Steer | Chapter 5: Form Your Hypothesis

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.

Startup Hypotheses

Every startup begins with a set of hypotheses about how the business will work. As stated above, there are typically two core...

The Lean Startup Summary Chapter 6: Test with 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 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...

Shortform Exercise: Design Your MVP

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 Lean Startup Summary Chapter 7: Measure

The job of a startup is to:

1. Build an MVP to measure where it is now
2. Experiment to improve the metrics
3. Decide whether to continue in the same direction or pivot in a new direction.

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.

Avoiding Vanity Metrics

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...

Shortform Exercise: Choose the Right Metrics

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?

The Lean Startup Summary Chapter 8: Pivot or Persevere

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:

• Your metrics are not good enough to meet your goals for your startup.
• Your experiments are leading to less and less progress (which is a sign that you’re out of good ideas)

Startup Example: Votizen

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...

The Lean Startup Summary Part 3: Accelerate | Chapter 9: Work in Smaller Batches

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.

Decreasing Batch Sizes

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.

The Envelope Analogy

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...

The Lean Startup Summary Chapter 10: How Your Startup Grows

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 of Growth

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...

The Lean Startup Summary Chapter 11: Slow Down Intelligently

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.

The Five Whys

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:

1. Why did the machine stop? There was a power overload and the fuse blew.
   1. If we stopped here, we would just replace the fuse. The fuse would blow again, and we’d replace it again, and so on. We would treat the symptom, but not the cause.
2. Why? The bearing was not lubricated.
3. Why? The lubrication pump wasn’t...

Shortform Exercise: Try the Five Whys

Try to figure out the root cause of a problem.

What problem have you faced recently? Why did it happen?

The Lean Startup Summary Chapter 12: Startups in Big Organizations

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:

• new product
• growth and scaling
• optimization, operational excellence, and fighting newcomers
• legacy support and cutting costs

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.

Match People with the Product Stage

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...

The Lean Startup Summary Chapter 13: Epilogue

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...