In November 2014 Kellogg Professor Florian Zettelmeyer's led a panel discussion with Facebook CMO Gary Briggs and many other prominent leaders at 'Kellogg Insight Live' event at Facebook headquarters in Menlo Park, California. His argument was "Big Data Doesn't Make Decisions. Leaders Do". I fully concur with his statement. This book is about leaders and customers loyalty & satisfaction based on big data analytics. Achieving customer loyalty is a primary marketing goal, but building loyalty and reaping its rewards remain ongoing challenges. Watson, Beck, Henderson & Palmatier (2015) theory suggests that loyalty comprises attitudes and purchase behaviors that benefit one seller over competitors. Yet researchers examining loyalty adopt widely varying conceptual and operational approaches. The authors examined the consequences of this heterogeneity by empirically mapping current conceptual approaches using an item-level coding of extant loyalty research, then testing how operational and study-specific characteristics moderate the strategy to loyalty to performance process through meta-analytic techniques. The results clarified dissimilarities in loyalty building strategies, how loyalty differentially affects performance and word of mouth, and the consequences of study-specific characteristics. Prescriptive advice based on 163 studies of customer loyalty addresses three seemingly simple but very critical questions: What is customer loyalty? How is it measured? And what actually matters when it comes to customer loyalty? Germann, Lilien, & Rangaswamy (2013) argued that "A few well-documented cases describe how the deployment of marketing analytics produces positive organizational outcomes. However, the deployment of marketing analytics varies widely across firms, and many C-level executives remain skeptical regarding the benefits that they could gain from their marketing analytics efforts. The author's research is based on upper echelons theory and the resource-based view of the firm to develop a conceptual framework that relates the organizational deployment of marketing analytics to firm performance and that also identifies the key antecedents of that deployment. The analysis of a survey of 212 senior executives of Fortune 1000 firms demonstrated that firms attain favorable and apparently sustainable performance outcomes through greater use of marketing analytics. The analysis also reveals important moderators: more intense industry competition and more rapidly changing customer preferences increase the positive impact of the deployment of marketing analytics on firm performance. The results are robust to the choice of performance measures, and, on average, a one-unit increase in the degree of deployment (moving a firm at the median or the 50th percentile of deployment to the 65th percentile) on a 1 to 7 scale is associated with an 8% increase in return on assets. The analysis also demonstrated that support from the top management team, a supportive analytics culture, appropriate data, information technology support, and analytics skills are all necessary for the effective deployment of marketing analytics". Perhaps at some point the big data analytics stops to make any sense unless leaders steps in to make viable decisions