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Lean Analytics: Use Data to Build a Better Startup Faster (Lean Series) Hardcover – March 21, 2013
"Rebound" by Kwame Alexander
Don't miss best-selling author Kwame Alexander's "Rebound," a new companion novel to his Newbery Award-winner, "The Crossover," illustrated with striking graphic novel panels. Learn more
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From the Publisher
|Running Lean||Lean Enterprise||Lean UX||UX for Lean Startups||Lean Customer Development||Lean Branding|
|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||Creating Dynamic Brands to Generate Conversion|
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
Top customer reviews
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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.
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.
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.