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[Croll, Alistair, Yoskovitz, Benjamin]のLean Analytics: Use Data to Build a Better Startup Faster (Lean Series)
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紙の本の長さ: 409ページ Word Wise: 有効 言語: 英語
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内容紹介

Marc Andreesen once said that "markets that don't exist don't care how smart you are." Whether you're a startup founder trying to disrupt an industry, or an intrapreneur trying to provoke change from within, your biggest risk is building something nobody wants.

Lean Analytics can help. By measuring and analyzing as you grow, you can validate whether a problem is real, find the right customers, and decide what to build, how to monetize it, and how to spread the word. Focusing on the One Metric That Matters to your business right now gives you the focus you need to move ahead--and the discipline to know when to change course.

Written by Alistair Croll (Coradiant, CloudOps, Startupfest) and Ben Yoskovitz (Year One Labs, GoInstant), the book lays out practical, proven steps to take your startup from initial idea to product/market fit and beyond. Packed with over 30 case studies, and based on a year of interviews with over a hundred founders and investors, the book is an invaluable, practical guide for Lean Startup practitioners everywhere.

著者について

Alistair Croll has been an entrepreneur, author, and public speaker for nearly 20 years. He's worked on a variety of topics, from web performance, to big data, to cloud computing, to startups, in that time.
In 2001, he co-founded web performance startup Coradiant, and since that time has also launched Rednod, CloudOps, Bitcurrent, Year One Labs, the Bitnorth conference, the International Startup Festival and several other early-stage companies.
Alistair is the author of three books on web performance, analytics, and IT operations, including "Lean Analytics" http: //leananalyticsbook.com/, a book on using data to build a better business faster that's due out in March from O'Reilly Media. He lives in Montreal, Canada and tries to mitigate chronic ADD by writing about far too many things at "Solve For Interesting": http: //www.solveforinteresting.com. Alistair chairs O'Reilly's Strata Conference.

Benjamin Yoskovitz is a serial entrepreneur with over 15 years of experience in web businesses. The co-founder of Standout Jobs and Year One Labs, he is also an active mentor to numerous startups and startup accelerators. Ben is the author of "Instigator Blog" (instigatorblog.com), and regularly speaks at startup conferences. He's currently VP Product at GoInstant, which was acquired by Salesforce in 2012.


登録情報

  • フォーマット: Kindle版
  • ファイルサイズ: 17291 KB
  • 紙の本の長さ: 440 ページ
  • 同時に利用できる端末数: 無制限
  • 出版社: O'Reilly Media; 1版 (2013/3/8)
  • 販売: Amazon Services International, Inc.
  • 言語: 英語
  • ASIN: B00AG66LTM
  • Text-to-Speech(テキスト読み上げ機能): 有効
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  • Word Wise: 有効
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現場改善でのリーンをイメージするところですが、この書籍はデーターのリーンです。現場改善型コンサルの自分にとっては参考程度になる内容でした。
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Amazon.com: 5つ星のうち 4.6 115 件のカスタマーレビュー
7 人中、7人の方が、「このレビューが参考になった」と投票しています。
5つ星のうち 4.0 Perfect Menu for the New to Entrepreneurial-ship 2013/3/24
投稿者 Margue L. Hunt - (Amazon.com)
形式: ハードカバー Amazonで購入
Perfect Menu for the New to Entrepreneurial-ship ...

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.
4 人中、4人の方が、「このレビューが参考になった」と投票しています。
5つ星のうち 4.0 Lean Startup Keeps Growing Up 2013/3/28
投稿者 I. Souweine - (Amazon.com)
形式: ハードカバー Amazonで購入
The lean startup movement is entering an exciting new phase, with big picture theory + evocative anecdotes giving way to careful case studies and more refined analysis of how to apply lean as a management discipline. The O'Reilly Lean Series is of course central to this transformation, and this Lean Analytics book in particular is a fantastic contribution.

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.
1 人中、1人の方が、「このレビューが参考になった」と投票しています。
5つ星のうち 5.0 Making data less complex and daunting 2014/6/27
投稿者 Marc Abraham - (Amazon.com)
形式: ハードカバー Amazonで購入
Lean Analytics is a great fit within the “Lean Startup” movement. The book provides a very comprehensive overview of the different metrics worth tracking and – most importantly – offers a clear rationale as to why certain metrics should be tracked for a specific business model at a given stage.

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.
1 人中、1人の方が、「このレビューが参考になった」と投票しています。
5つ星のうち 5.0 This is a must read for all startup-ers 2014/4/10
投稿者 Derek M Skaletsky - (Amazon.com)
形式: Kindle版 Amazonで購入
Very often the "Lean Startup" movement can be very theoretical and academic, but Lean Analytics give is some teeth and meaning.

IMO, the most important concept that this book promotes is the pairing of metrics with business stage. Way too often companies define their key metrics without taking their stage into account (ie - the board will say, "We have to focus on Cost of Acquisition!" when the company is still trying to figure out product/market fit).

I also love how they broke the book down by business-type, allowing the reader to quickly access the most relevant parts without having to weed through topics that don't relate to their business.

Bottom-line, this is a book that I recommend to all my startup friends. It's super helpful and presents concepts that you come back to over-and-over as you grow your business...
1 人中、1人の方が、「このレビューが参考になった」と投票しています。
5つ星のうち 5.0 Overwhelming at times, but great to use as reference for performance management 2015/3/4
投稿者 Vlad Zamfirescu - (Amazon.com)
形式: Kindle版 Amazonで購入
I found it to be one of the most complete books on business performance management. From page one, you find yourself immersed in KPIs, metrics, various scenarios, giving you all the information that you need if you are serious about getting a business on the road. What I found to be the most valuable resource offered by this book was the way it presented the applicability of the LEAN methodology to performance management through real world case studies. Still, I would recommend this book as a reference, as you will most likely have to come back to certain parts due to its overwhelming amount of data and information that it contains.
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