Full Product Details
Author: Ron Kohavi ,
Diane Tang ,
Ya Xu
Publisher: Cambridge University Press
Imprint: Cambridge University Press
Dimensions:
Width: 15.20cm
, Height: 1.40cm
, Length: 22.60cm
Weight: 0.420kg
ISBN: 9781108724265
ISBN 10: 1108724264
Pages: 288
Publication Date: 02 April 2020
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Available To Order
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Reviews
'This book is a great resource for executives, leaders, researchers or engineers looking to use online controlled experiments to optimize product features, project efficiency or revenue. I know firsthand the impact that Ronny's work had on Bing and Microsoft, and I'm excited that these learnings can now reach a wider audience.' Harry Shum, Executive Vice President, Microsoft Artificial Intelligence and Research Group 'The secret sauce for a successful online business is experimentation. But it is a secret no longer. Here three masters of the art describe the ABCs of A/B testing so that you too can continuously improve your online services.' Hal Varian, Chief Economist at Google and author of Intermediate Microeconomics: A Modern Approach 'Experiments are the best tool for online products and services. This book is full of practical knowledge derived from years of successful testing at Microsoft, Google and LinkedIn. Insights and best practices are explained with real examples, and pitfalls, their markers and solutions identified. I strongly recommend this book!' Preston McAfee, former Chief Economist and VP of Microsoft 'A great book that is both rigorous and accessible. Readers will learn how to bring trustworthy controlled experiments, which have revolutionized internet product development, to their organizations.' Adam D'Angelo, Co-founder and CEO of Quora and prior CTO of Facebook 'Online experiments have fueled the success of Amazon, Microsoft, LinkedIn and other leading digital companies. This practical book gives the reader rare access to decades of experimentation experience at these companies and should be on the bookshelf of every data scientist, software engineer and product manager.' Stefan Thomke, William Barclay Harding Professor, Harvard Business School and author of Experimentation Works: The Surprising Power of Business Experiments 'An extremely useful how-to book for running online experiments that combines analytical sophistication, clear exposition and the hard-won lessons of practical experience.' Jim Manzi, Founder of Foundry.ai, Prior founder, CEO and Chairman of Applied Predictive Technologies and author of Uncontrolled: The Surprising Payoff of Trial-and-Error for Business, Politics, and Society 'Kohavi, Tang, and Xu are pioneers of online experimentation. The platforms they've built and the experiments they've enabled have transformed some of the largest internet brands. Their research and talks have inspired teams across the industry to adopt experimentation. This book is the authoritative yet practical text that the industry has been waiting for.' Adil Aijaz, Co-founder and CEO, Split Software
Author Information
Ron Kohavi is a Technical Fellow and corporate VP of Microsoft's Analysis and Experimentation, and was previously director of data mining and personalization at Amazon. He received his Ph.D. in Computer Science from Stanford University. His papers have over 40,000 citations and three of them are in the top 1,000 most-cited papers in Computer Science. Diane Tang is a Google Fellow, with expertise in large-scale data analysis and infrastructure, online controlled experiments, and ads systems. She has an A.B. from Harvard and an M.S./Ph.D. from Stanford University, with patents and publications in mobile networking, information visualization, experiment methodology, data infrastructure, data mining, and large data. Ya Xu heads Data Science and Experimentation at LinkedIn. She has published several papers on experimentation and is a frequent speaker at top-tier conferences and universities. She previously worked at Microsoft and received her Ph.D. in Statistics from Stanford University.
