52 Things We Wish Someone Had Told Us about Customer Analytics

52 Things We Wish Someone Had Told Us about Customer Analytics
Author :
Publisher :
Total Pages : 214
Release :
ISBN-10 : 1726601064
ISBN-13 : 9781726601061
Rating : 4/5 (061 Downloads)

Book Synopsis 52 Things We Wish Someone Had Told Us about Customer Analytics by : Mike Sherman

Download or read book 52 Things We Wish Someone Had Told Us about Customer Analytics written by Mike Sherman and published by . This book was released on 2018-09-13 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 52 Things We Wish Someone Had Told Us About Customer Analytics is for anyone who uses customer information to make business decisions: CMOs, CEOs, product owners and the people who provide that information, e.g. data scientists, market researchers, business analysts. By tying impact to tools and techniques, through real-life stories, we hope to help decision makers better understand how to use customer data while helping data analysis providers understand how to create output that end users will value.This book provides 52 real-life anecdotes that illustrate important learnings about customer analytics. It draws from the worlds of big data and customer insights. It is our contribution to help managers do a better job using customer analytics (what to do and what not to do) so that the analytics actually makes a difference.Books on customer analytics (data science, business analysis, market research, whatever you like to call it) primarily exist in two categories: as academic texts, which discuss theoretical approaches to data analysis problems; or as technical texts, which teach the statistics or computer programming required to conduct an analysis. As the focus of these books is on analysis tools and techniques, fictitious examples are often used to explain main topics. Our book fills in the missing gap between these approaches by providing real-life, practical stories, tying analysis directly to business value.---"Essential reading for those who want to cut through all the hype of big data. This book has practical advice on how to have real financial and business impact, from the experienced authors who have done this in real life."John ForsythFormer Principal (Partner), McKinsey, former Head, McKinsey's Global Customer Insights Practice---"Mike and Alex have delivered an entertaining and highly readable romp through many aspects of customer analysis-from qualitative focus groups through to terrabytes of big data; and utilizing many real-world examples to reinforce their points. They employ a relentless focus on the use of analysis to deliver meaningful and impactful business value ... and that should matter to you, too, whether you're the CEO, the product owner or a junior analyst delivering the work."George HaylettFormer Asia Analytics Head for Amex, Citibank and HSBC---"Significance. Reliability. Confidence. These and other such terms can be a mantra for both suppliers and buyers of data and analytics. Whether it be big data, qualitative research or something in between; sampling, statistics and "findings" are often the drivers of customer or business analytic exercises. But what about relevance? If the results cannot direct business decisions, what does it matter how "accurate" they are? Used correctly, such analytics are an enormously powerful driver of business performance and profitability. But only if the findings have business salience or business significance. Otherwise, aren't they just another type of BS? In this book, Mike and Alex Sherman lay out some wonderful examples of how the time and money spent on business analytics can transform decision-making or be a complete waste of time. It contains great lessons for buyers and users of such services. But I would also commend it to consultants and suppliers. We shouldn't need to sell what a computer can do with data. We should be promoting what humans and businesses can do by asking the right questions of the results."Adrian ChedoreFormer CEO of Synovate---"This book thoughtfully and practically reminds us that, as we continue to further automate consumer insight analytics efforts with the newest analytics and AI technology, human thinking and human understanding of the fundamental purpose of the analysis, and of the questions that are essential to understanding that purpose, becomes even more important."Professor Steven MillerVice Provost (Research), Singapore Management University


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