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, they 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 their contribution to helping 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. This 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 terabytes 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 layout 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. They shouldn’t need to sell what a computer can do with data.
