PDF Summary:The Lean Startup, by Eric Ries
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1-Page PDF Summary of The Lean Startup
The Lean Startup by Eric Ries is considered a bible in the tech entrepreneurship community. It’s a methodology for creating businesses that focuses you on finding out what customers actually want. It uses concepts of scientific experimentation to prove that you’re making progress. It encourages you to launch as early and cheaply as possible so you don’t waste time and money.
Learn the critical concepts of the Minimum Viable Product, cohort metrics, A/B testing, virality, and startup pivots.
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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.
Depending on your business, there are a variety of ways to test your hypothesis in the cheapest, fastest way possible. In the more extreme, you don’t need a product at all - you can simply pretend you have a product and collect user behavior.
Here are examples of MVP types:
- Landing Page MVP: create a web page describing the features of the product, before a product actually exists. Track clicks and attempted downloads to gauge how much users want it.
- Video MVP: make a video simulating what the product does. Even without using the actual product, watching the video will give enough info for viewers to decide whether they want the product shown.
- Concierge MVP: instead of building processes that scale, run very manual processes dependent on special white-glove treatment. Often the founders themselves deliver the service. This accelerates learning and allows quick iteration on the product.
- Wizard of Oz MVP: if you plan to build fancy automated technology, try to test it with a human behind the scenes. The human performs the service that the technology does, and the user is none the wiser.
Choosing the Right Metrics
Defining the right metrics that actually matter to your business is critical.
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.
Instead of looking at cumulative vanity metrics over time, the more accurate analysis is to separate users into groups based on the time they joined, then measure your metric for each group independently. Each group of users is called a cohort. For instance, you can measure the signup rate for each week separately to see if that’s increasing over time.
A/B Testing
Let’s say you develop a new feature to your product and you release it to all your users. Suddenly your metrics improve. But how do you know seasonal effects aren’t at play – that the users who joined later aren’t just naturally more engaged? Or that you got a burst of users from an unexpected news article?
An A/B test avoids bias by splitting users into seeing two different versions of your product. By analyzing the metric resulting from both groups, you get strong quantitative evidence about which version users like more.
For example, let’s say you have a landing page MVP listing your potential features and a signup form. You’re not sure which of two features your users will like more. So you set up an A/B test – half of visitors see feature A on your landing page; the other half sees feature B. You measure the difference in signup rate. If feature A gets a 5% signup rate, but feature B gets 2%, this is evidence that your users may prefer feature A!
Another benefit of A/B testing is that it lowers politics. You don’t have to squabble with your team over which features are better – you can put it to the test with an MVP. A/B testing also lets you assign credit where it’s due.
Pivoting Your Startup
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)
To make sure your startup is on the right track, have a regular “pivot or persevere” meeting. The frequency should be between once every few weeks and once every few months, depending on your startup - the more volatile your startup and the less time you have, the more frequent this should be.
Pivots come in multiple flavors. Which type you make depends on what you learn in your experiments about customer needs.
Pivot types include:
- Zoom-in pivot: Customers like a specific feature of your product. You pivot so your product now focuses entirely on delivering this feature.
- Customer need pivot: You know your customers well, and the problem you’re solving for them is not very important. You pivot to target a new customer need, which may entail an entirely new product.
- Business architecture pivot: You pivot to change between two types of businesses: high margin and low volume, or low margin and high volume. This roughly matches to a business to business (B2B) model, or a business to consumer (B2C) model.
- Technology pivot: You want to solve the same problem for the same users, but you pivot to use a different technology to do so. Often, this offers better price or performance.
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PDF Summary Introduction
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2) Entrepreneurship is management. Management shouldn’t be a dirty word in startups. Instead of a chaotic, “do what we feel like” strategy, you need to adopt a principled approach to manage risk and reduce failure.
3) Validated Learning. The job of a startup is to learn who its customer is and what its product should be. This learning should be treated rigorously and scientifically.
4) Build-Measure-Learn (and repeat). First you build, then you measure the results, then you learn what to improve next time. Then you build again. By stepping through this loop, you’ll gain concrete information on your hypotheses about the world and decide whether to change your strategy. The faster you iterate through this loop, the more you’ll learn and the more progress you’ll make.
5) Innovation accounting. It’s critical to treat learning rigorously, which means measuring progress and creating action plans.
Overview of the Book
This book is organized into three sections:
- Vision: We define what an entrepreneur is and how startups learn through experimentation.
- Steer: We step through the Build-Measure-Learn loop in technical detail, covering concepts like the...
PDF Summary Part 1: Vision | Chapter 1: Startups Need Managing
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Unfortunately, some startups avoid this learning cycle. Instead, they essentially point themselves in one direction, put on a blindfold, and then slam their foot on the pedal. To no one’s surprise, they end up in a ditch by the side of the road.
(Shortform example: The failed online grocery company Webvan in the 2000 dot-com bubble is a classic example of this – before fully validating their customer, they spent over a billion dollars building out their infrastructure and delivery fleet. To their chagrin, there weren’t enough customers to justify the investment, and the company folded.)
PDF Summary Chapter 2: Entrepreneurs Are Everywhere
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Intuit: a Giant Startup
Intuit was founded by Scott Cook in 1983, and they dominated the finance and tax prep software industries. But by 2002, its product initiatives were failing. Cook realized the management practices at Intuit couldn’t keep up with the rapidly changing economy.
A decade later, Intuit has built entrepreneurship and risk taking into the backbone of their company. For example, TurboTax, one of their flagship products, used to run on an annual product improvement cycle, where product and marketing teams would package together the year’s changes and push it out in a single big release.
Nowadays, they move in a much more agile way – they’ll run up to 70 different tests on one week, examine the data the next week, and quickly decide what further tests they need to run. Furthermore, because they rely on data to make decisions, good ideas win, rather than politics. This has led to much faster growth of new product lines.
Eric’s major point is that innovation can happen anywhere, not just in college dorm rooms but also in large, experienced organizations. But in the latter, it’s up to the leadership to create the conditions that will stimulate...
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Learn more about our summaries →PDF Summary Chapter 3: Learn What Your Users Want
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The IMVU team labored for 6 months on their prototype product. They worried constantly about the details of their implementation – “how many IM networks should we support?” (over a dozen) “How buggy can the prototype be? Will it make us look bad?”
Finally, with their pride on the line, they launched the product.
And no one joined.
They thought it was a quality problem at first, so they worked on fixing bugs and adding features. This didn’t budge the needle.
Finally, they decided to bring in potential users for interviews. This is where their epiphany happened. IMVU had built the whole game around getting new users to bring in their friends from other IM networks. But users didn’t actually want to invite their friends over before they had a chance to really test it out – if the game was uncool, they’d look bad.
Even more importantly, IMVU found that users actually didn’t mind joining a new IM network. Just like people today have different lives on different social networks (Facebook, Twitter, LinkedIn, Instagram, Pinterest, etc.), IMVU found that their target customer wanted a separate IM network dedicated to this new virtual world. They wanted to make new...
PDF Summary Chapter 4: Experiment like a Scientist
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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.
All these principles are in strict contrast to the usual market research/strategic planning process. Traditionally, you would try to research everything possible about your core user, then build your product to polished perfection, then release with a big launch party. This invites failure when you build something customers actually don’t even want.
We’re going to run through a few examples showing these principles at work. Notice how the same underlying principles apply to vastly different companies and scenarios.
Startup Example: Zappos
During the dot-com boom, it seemed like the internet could be a new commerce platform for everything – books, groceries, even pet supplies. Companies like Webvan started business by building massive infrastructures and supply chains, even before they had proven customer demand.
Zappos founder Nick Swinmurn took the opposite approach. **His first action was...
PDF Summary Part 2: Steer | Chapter 5: Form Your Hypothesis
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- Do people actually have the problem you believe they have?
- Do they actually want what you’re offering?
- Are they willing to pay for it?
The Dangerous Startup by Analogy
One insidious way to frame your business is by analogy to other companies. If there’s a successful company that succeeded because of attribute X, then it’s tempting to say that because you also have attribute X, you’ll naturally succeed.
This superficially looks like sound logic, but in reality it’s very weak and papers over a lot of assumptions that may not hold up on closer inspection.
(Shortform example: for example, when Uber paved the way for on-demand services, a litany of companies cropped up to start the “Uber of [blank].” The logic for an on-demand service was as follows:
We are the Uber of laundry servicing. Uber allows users to request a car on demand using a mobile app, reducing friction far beyond hailing a taxi. Similarly, our users request laundry services on demand, we pick the clothes up and launder in our laundry rooms, and we deliver their laundry to their home 24 hours later. The laundry industry is worth $15 billion. Just as Uber is now larger than the...
PDF Summary Chapter 6: Test with the Minimum Viable Product
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Let’s focus on the hypothesis of the 20% sign up rate (20 signups out of 100 visitors). What is the MVP in this situation? Think about it for a second.
A common answer might be: “a simple prototype that’s light in features – instead of all celebrities, you can only swap faces with Kanye West. And you can only post to one social network, Facebook. We’ll market it and track conversion rate for users who land on our page.”
This is much better than building a fully fledged product over the course of a year. But you can go simpler.
You actually don’t even need to have a working, functional app!
Here’s how. Picture a web page that describes the features of your face swapping app. You show mockups of what it looks like when your face is on Kim Kardashian’s body, or when Donald Trump’s face is on your body. At the bottom of the page, you have a Download button. You track clicks on this Download button.
That’s all you need. You can test your hypothesis without an app at all. If you funnel in 100 users, you can see how many people enter the page, and how many people click the button. You can tell very quickly whether you’re far off from the 20% hypothesis.
If your idea is a...
PDF Summary Chapter 7: Measure
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These common vanity metrics are all problematic:
- Total number of anything – users, sales, actions in product
- Money raised from investors
- Press articles written about your company
- Number of employees hired
- Number of features added to product
- Meetings scheduled
- Emails written
Cohort Analysis
Instead of looking at cumulative vanity metrics over time, the more accurate analysis is to separate users into groups based on the time they joined, then measure your metric for each group independently . Each group of users is called a cohort .
For example, say we wanted to measure engagement in an app by number of photos sent. Each week, we take all the users who joined that week, and then look at the average number of photos each user sends in their first day. We work really hard for 4 weeks, and we hope to see this number rise. Instead we see this:
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| Number of photos sent per user | Vanity metric – total photos sent | |
| Week 1 | 5 | 100 |
| Week 2 | 5 | 200 |
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PDF Summary Chapter 8: Pivot or Persevere
... </td> 90% </tr> Retention Too low to measure 5% 8% Referral Too low to measure 4% 6% </table>
Starting with just the MVP, Votizen was at a good starting point, and without a chance to improve the metrics, it was too early to pivot. The first round of optimization led to major improvements in every single metric. But the second period of optimization, costing much more time and money, led to barely a bump in metrics.
This is a sign to pivot – they had taken the current idea as far as they could go.
From user interviews, Votizen got another idea – pivot to a way to let voters contact their elected representatives easily. Users could write an email or tweet, and Votizen would print a paper letter and send it to their Congressional representative or Senator. Even better, they could charge for this service and start funding the company through revenue.
They called this @2gov, and spent another 4 months and $30,000 to build the prototype. Here were the metrics:
...
PDF Summary Part 3: Accelerate | Chapter 9: Work in Smaller Batches
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This concept maps directly onto building a startup. Instead of releasing a fully-featured product once a year, you could release small batches of features regularly. With smaller batches, you detect problems and measure impact earlier. Most importantly, you might find earlier that customers don’t actually want what you’re building. Would you rather find this out incrementally with 5 small batches in 5 weeks, or 1 big batch in 10 weeks?
Anecdote: Xiaomi
Xiaomi, a Chinese smartphone maker and one of the biggest in the world, is well-known for launching weekly updates to their phones’ operating systems. Engineers scour user forums looking for feature requests. They’re quickly implemented, tested, and rolled out to all its users, sometimes within that week. Users then give feedback on the new release to point out bugs and suggest new features.
Contrast this approach to the monolithic, huge-batch method of Apple, where a new version of iOS is released annually, and minor updates are introduced once every few months.
In comparison to Apple, Xiaomi users feel:
their needs are being listened to. They’re actually getting stuff they requested.
their...
PDF Summary Chapter 10: How Your Startup Grows
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- When your customer keeps paying you
- Merchants like Amazon: Retaining users means they continue to buy from the merchant
- Subscription companies like Netflix or Salesforce – regular subscriptions means the longer a customer stays engaged, the larger lifetime value you get, the more value they get from your service, and the harder it is to leave
Metrics to Care About
- Churn rate is the key metric to care about. This is defined as the fraction of customers who fail to remain engaged with the product in a certain time period.
- Growth rate: defined as new customer acquisition - churn rate.
- For example, you may grow by 50% per month, but churn 30% of users per month. On a base of 100 customers, you gain 50 users but lose 30. You end the month with 120 customers for net 20% growth. If you keep the same growth rate, your userbase will compound over time.
- Engagement: can be defined as the core engagement action you care about, like logins per week, time used per week, messages sent per month, etc.
- AVOID total number of signups. This will always increase, but if you’re churning customers, your revenue will flatline. Your...
PDF Summary Chapter 11: Slow Down Intelligently
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This example can be applied to any recurring problem in your startup, whether it’s a problem in customer service, engineering, accounting, or more.
Make a Proportional Investment
Asking Five Whys lets you figure out the root cause. Depending on how grave the problem is, you can then make a proportional investment to fix it.
This requires you to quantify the size of the problem. You can do this in units of resources – namely, person-hours or dollars.
A problem that occurs once and costs one man-hour to fix doesn’t need a heavy process to fix it.
A problem that occurs weekly and requires ten man-hours to fix will suck up 500 hours in a year – if you can spend 100 hours to solve it completely, it’s well worth it.
This calculus doesn’t have to be exact – often a rough estimate will tell you clearly if fixing the problem is clearly a huge gain, clearly a waste of time, or somewhere on the fence.
And you can solve problems iteratively too. For first-time problems, make a smaller incremental improvement to the root cause. If the problem recurs, then you have more information about whether you want to invest more.
The Five Whys and proportional investments...
PDF Summary Chapter 12: Startups in Big Organizations
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The Three Attributes of Successful Startup Teams
The author suggests that successful innovation requires three structural attributes:
- Limited but secure resources. By their nature, startups are high risk and thus deserve less resources than surefire investments. This is a good thing, since it forces startups to focus on the right questions or perish. But because a sudden change in resources can be catastrophic, internal startups need their funding secured and immune from tampering by other managers.
- Independent decision-making authority. To move faster, startups need to be able to run and execute experiments without passing each one by a review board. Building cross-functional startup teams allows representatives from each stakeholder department to partake in the innovation and sign off quickly on decisions. Of course, this independence needs to be balanced with safeguards – internal startups shouldn’t do anything that can damage the entire brand or hurt customers, for example.
- Incentive in success. Entrepreneurs, internal or independent, are motivated by tying their personal success to their startup’s success. Typically this means equity or...
PDF Summary Chapter 13: Epilogue
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The important goal is validated learning, discovering the truth about the world in a rigorous way. Think about Lean Startup as a mental framework for how to think about building a sustainable business.
What is your value hypothesis or growth hypothesis? What is the fastest, cheapest way you can validate this hypothesis?