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Lean Analytics: Use Data to Build a Better Startup Faster (Lean (O'Reilly)) Hardcover – March 26, 2013
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From the Publisher
|Running Lean||Lean Enterprise||Lean UX||UX for Lean Startups||Lean Customer Development||Leading Lean|
|Find further titles in this series||Iterate from Plan A to a Plan That Works||How High Performance Organizations Innovate at Scale||Designing Great Products with Agile Teams||Faster, Smarter User Experience Research and Design||Building Products Your Customers Will Buy||Ensuring Success and Developing a Framework for Leadership|
Q&A with Alistair Croll, coauthor of "Lean Analytics: Use Data to Build a Better Startup Faster"
Q. Why is your book timely-- what makes it important right now?
A. There's been a flurry of startup activity made possible by the lowered barriers to entry of cloud computing, social media, and app platforms. But there's less accountability. If you look at the numbers, it's a bloodbath: you're almost certain to fail. One reason for this is that founders are delusional. But data doesn't lie, and the right data in the right place at the right time can change your business (to steal from Steward Brand.) That's what this book is about-- using data to build a better business faster.
Q. What information do you hope that readers of your book will walk away with?
A. We have a ton of concrete data-- ideas of what's normal; what metric to watch at what time; and so on. But more than any of this, we hope they'll come away with an experimental eye, realizing that they're not building a product. Instead, they're building a tool to figure out what product to build.
Q. What's the most exciting and/ or important thing happening in your space?
A. That nearly every mature industry is ripe for disruption. An entrepreneur, working within a host organization, can absolutely revitalize the business (as Procter & Gamble did when it introduced Swiffer, for example.) And a small business can tackle giants or entrenched competitors by being more agile (as Uber did to taxis, or Airbnb did to hotels.) Mops, taxis, and rentals aren't new. But they're hugely susceptible to change if it's applied in a measured, careful way.
"Your competition will use this book to outgrow you." -- Mike Volpe, Hubspot.
"Alistair and Ben have written a much-needed dose of reality." -- Brad Feld, Foundry Group & Techstars
"This is applicable to organizations of all shapes and sizes, from small business to big government." -- Jennifer Pahlka, Code For America
"No innovator should be without this book." -- Eric Ries, The Lean Startup
"This book is a huge gift to our industry." -- Zach Nies, Rally Software
"As useful for today's multi-billion dollar companies as it is for entrepreneurs." -- John Stormer, Salesforce.com
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This is a really hard problem, and regrettably the book hardly touches on it. Many product methodology books (which adhere to a data driven strategy) cover this question in more detail.
An alternative in the same series is: Lean Customer Development.
I have encountered many GREAT new ideas throughout my career in Technology & Retail that never transitioned to reality, not because of lack of passion, but due to stunted entrepreneurial capability in the captain of the ship. LEAN ANALYTICS Use Data to Build a Better Startup Faster will enable the New to Entrepreneurial-ship, formally educated or not. If you are embarking or are already deep into a Start-Up adVenture, Alistair Croll & Benjamin Yoskovitz share with you what you to incorporate to be successful at reaching that end objective and do it faster, better and in the longer-term cheaper.
Relevant evidence will help build confidence into the Start-Up enterprise; it will assist in validating what you already know, set direction and re-direction when it is needed - it will also help build the confidence of others in you & your Start-up to succeed. Understanding the value of establishing perception in others that will prove to be gateways to your Start-Up's success is a key element within the concepts shared and done in such a way that makes sense to the lay-person; you will not find a similar approach to this message in any of your typical analytics, statistics, performance management or six sigma book.
There appears to be a magical-season for Start-Ups between bootstrapping and initial investment that will make or break the potential for that GREAT new idea to move through infancy; many all-out ignore data to assist in decision making and other become petrified by a drive for data perfection before setting direction. There are real risks to over/under complication; following the step laid out in this book will set you up to have a practical evolution in your relationship with measurable evidence.
The only suggestion that I have (& the reason for 4 versus 5 stars) and that I will be doing for the Start-Ups that I work with is to have a summary map of the book that allows the reader to check-mark what they have already accomplished and move forward to that that section of the book that aligns to where they are in their evolution of their business. This recommendation speaks to the diversity of Start-Up businesses & their entrepreneurial capability that I believe this book was written for; the book is comprehensive in content for the audience, but usability for a population that wants to move fast may not get anchored in Chapter 1 and it would be a tragedy to lose the opportunity to enable the GREAT new ideas and the captains of the ships.
Before going on to explore how metrics can be applied to different business models, the book does a great job in explaining what makes a good metric:
Comparative – Being able to compare a metric to other time periods, groups of users, or competitors, helps you understand which way things are moving.
Understandable – If people can’t remember it and discuss it, it’s much harder to turn a change in the data into a change in the culture.
A ratio or a rate – Ratios or rates tend to be easier to act on, they are inherently comparative (see the first characteristic above) and they are good for comparing opposing factors.
Changes the way you behave – What will you differently based on changes in the metric?
The thing I liked most about Lean Analytics is that all of it makes perfect sense. The book provides a well thought through approach to making sense of something that can be complex and challenging at times: data.
I especially appreciated the clear exposition on key startup types (SaaS, E-Commerce, Media etc.) and the thorough analysis of what a customer funnel looks like for each model. If some of this material covers old ground, it does so in a fresh and easy-to-consume way that is valuable for novices and experienced practitioners alike. The case studies are also excellent and clearly reflect a significant amount of careful and passionate research.
My one gripe for the book is that there is too much time spent on lean startup refresh. I understand the urge to get readers on the same page, but it seems unlikely that many readers of a "lean 2.0" book such as this would not have the basics down, and so some of the material feels a little basic and repetitive. I would have rather seen less intro theory and more deeper dives on advanced issues like different ways to approach cohort analysis.
In any case, it's awesome work and well worth a read for anyone who cares about web analytics and applying lean in a systematic way.
Top international reviews
Running Lean by Ash Maurya is the first in the O'Reilly Lean Startup Series. It is brilliant. Lean Analytics by Alistair Croll and Benjamin Yoskovitz is the second in the series. It is equally brilliant. It is comprehensive and it should change how you do business in your startup. Eric Ries writes a wonderful Foreword to Lean Analytics which he describes as moving beyond the Lean Startup bumper stickers and diving deep into the details of innovation accounting thereby avoiding the perils of vanity metrics. He concludes that the book is a `guide for all practitioners who seek new sources of growth'. I believe that `measuring what you do is critical to achieving success in a new business venture' - this book will help you to figure out what you should be measuring by helping you to ask the most important questions and get clear answers quickly. It is critically important that you can firstly measure your progress and communicate that with your internal and external team.
The Preface explains that Lean Startup helps you identify the riskiest parts of your business plan, then finds ways to reduce those risks in a quick, iterative cycle of learning. Most of its insights boil down to one sentence: Don't sell what you make; make what you can sell. And that means figuring out what people want to buy. Lean Analytics shows you how to figure out your business model and your stage of growth. It explains how to find the One Metric That Matters to you right now, and how to draw a line in the sand so you know when to step on the gas and when to slam on the brakes.
Who the book is for:
The preface acknowledges that the book details tools and techniques which were first applied in consumer web applications, adding that they are now being applied to a much broader audience and that the authors have talked to tiny family businesses, global corporations, fledging startups, and charities, all of whom are applying lean analytical approaches **.
I think Lean Analytics can be read in isolation but armed with knowledge from books such as The Entrepreneur's Guide to Customer Development, The Lean Startup; and of course Running Lean, I think that this book will put you in a frame of mind that you have to take action. The book is broken into four parts. Part 1 summarises (brilliantly) all the building blocks of Lean Startup to include the aforementioned books to prime you for the next 3 parts.
I love the structure of this book. It gives you just enough and then moves on to another area but returning again to build on that knowledge. For the record, Part II looks at six sample business models and the five stages that every startup goes through as it discovers the right product and the best target market. When you are done, you'll know what business you're in, what stage you're at, and what to work on. Part III, looks at what's normal. After reading this part, you'll get some good baselines for key metrics and learn how to set your own targets. Finally, part IV shows you how to apply Lean Analytics to your organisation making the point that data-driven approaches apply to more than just new companies.
The book looks at six sample business models:
- eCommerce chapters 8 and 22;
- SaaS chapters 9 and 23;
- Free Mobile App chapters 10 and 24;
- Media Site chapters 11 and 25;
- User-generated content chapters 12 and 26; and finally
- Two Sided Marketplaces chapters 13 and 27.
** The common denominator is online, and if you are operating in one of these six areas, this book is a Must Read - these are all relatively new areas and this book makes an excellent contribution to understanding success in these domains.
If you are not operating in these areas but have a strong interest in Lean Startup and want to move to the next level, there is plenty of food for thought provided by this book. Chapter 29 deals with enterprise focused B2B software startups. The metrics to measure here are focused on the stages of your Sales funnel with some real nuggets of advice on what to measure and watch out for e.g. ease of customer engagement; integration and support costs; and measuring customer use of your APIs as a strategy for customer retention.
If you are commercialising a physical product I would probably read the Startup Owner's Manual by Steve Blank and Bob Dorf first.
What I really liked about the book
Chapter 2 `How to Keep Score' talks about what makes a good metric and is the best discussion of vanity metrics to include plenty of reference to Donald Rumsfeld, former US Secretary of Defense. This is followed by a great introduction to Leading metrics, Segments, Cohorts and A/B Testing.
Chapter 5 presents a Lean Analytics framework with five distinct stages: Empathy, Stickiness, Virality, Revenue and Scale, that every startup goes through. The model includes the `gating' metrics that indicate that it is time to move to the next stage. The chapter summaries the four primary Lean Startup Frameworks:
- Running Lean Lean Canvas
- Lean Startup by Eric Ries
- Dave McClure Pirate Metrics
- Sean Ellis Growth Pyramid
And on Page 53 presents them visually in one figure along with the Lean Analytics framework thereby adding superb clarity to the discussion. The framework is referenced in the remainder of the book to allow visualisation of business models and user flow through the systems of the business.
The Chapters on eCommerce are particularly illuminating for me as I have limited direct experience in this area.
Finally, I can hardly believe that I have not yet mentioned the Case Examples used in the book. They are interesting and well written and used to illustrate key points - Startup Analytics Lessons Learned.
Overall, Lean Analytics is a fantastic book and definitely value for money!
However I felt the book could have been made shorter as the authors added lots of unrelated information on what I should be doing with my life..etc
It lists the different types of (mainly software) companies: e-commerce; Software as a Service, free mobile app, media site, user-generated content, 2-sided marketplace.
A start-up company goes through 5 stages of growth: Empathy - listening to the customer to learn whether you've got a business or not; Stickiness - making sure you have a product that users will come back to, one that is "sticky", by iterating; Virality - once you've got a sticky product, and not before, think about getting more users. Virality can be inherent, artificial and/or word of mouth. Next, is Revenue, when you start to really concentrate on making money (before, you were getting the product and market fit right); Scale - growing the business.
What is also very useful, and most apt for the title of the book, is knowing what is a good metric. There are lines in the sand for all the business types, and the different growth stages. These can help you know when to move to the next stage, or even whether to pivot, and change company type.
I'm going to read it again, faster this time, and make notes. I think it's well worth a second read.
Some context: I'm focused on ecommerce and therefore parts of the book are relevant, whereas others need to be skipped over.
What I found valuable is the segmentation of metrics based on business model (e.g. what type of ecommerce business should be avoiding loyalty programs and focusing on customer acquisition). Also, the survey guidance alone has saved me hours of trial and error. Finally, the guidance on typical KPIs gave a quick leg up instead of starting with a blank piece of paper.
You won't read this book cover to cover, but it will guide you based on your business model through the book.
The reading style is quite easy going, and isn't laden with academic terminology.
Alistair and Ben have pioneered the idea that you should only track 'one metric that matters' at any given stage in your startup's trajectory. That metric becomes a rallying cry, a call to arms, a focus for your entire company. Startups fail because they try to do too much and can't see the wood for the trees. This will help bring clarity and hopefully success.
These guys are lean mean analytics machines. Saw them talk in person at UCL in 2013 and they were excellent speakers as well, fast on their feet and insightful with the Q&A afterwards too.