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Description
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group.The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in:Ticket pricingSeason ticket member retentionFan engagementSponsorship valuationCustomer relationship managementDigital marketingMarket researchData visualization.This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations.Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. Read more
Publisher : Auerbach Publications; 1st edition (November 21, 2016)
Language : English
Hardcover : 236 pages
ISBN-10 : 1498761267
ISBN-13 : 60
Item Weight : 1.19 pounds
Dimensions : 0.61 x 6.14 x 9.21 inches
Best Sellers Rank: #1,365,759 in Books (See Top 100 in Books) #169 in Business Pricing #582 in Data Mining (Books) #703 in Management Science
#169 in Business Pricing:
#582 in Data Mining (Books):
