Service Annual Survey


Book Description




Natural Language Processing for Global and Local Business


Book Description

"This book explores the theoretical and practical phenomenon of natural language processing through different languages and platforms in terms of today's conditions"--







Digital Marketing Excellence


Book Description

Now in its sixth edition, the hugely popular Digital Marketing Excellence is a practical guide to creating and executing integrated digital marketing plans, combining established approaches to marketing planning with the creative use of new digital models and digital tools. Written by two highly experienced digital marketing consultants, the book shows you how to: Draw up an outline integrated digital marketing plan Evaluate and apply digital marketing principles and models Integrate online and offline communications Implement customer-driven digital marketing as part of digital transformation Reduce costly trial and error Measure and enhance your digital marketing Learn best practices for reaching and engaging your audiences using the key digital marketing platforms. This new edition has been streamlined to seamlessly integrate the latest developments in digital analytics, ethics and privacy, Predictive Analytics, Machine Learning and Artificial Intelligence. Including new international case studies and up-to-date examples throughout, this book cuts through the jargon to show marketers how to leverage data and digital technologies to their advantage. Offering a highly structured and accessible guide to a critical and far-reaching subject, Digital Marketing Excellence, 6th edition, provides a vital reference point for all digital marketing students, and managers involved in digital marketing strategy and implementation. Online resources have been fully updated for the new edition and include a new set of PowerPoint slides and a full test bank of questions and exercises.




Essentials of Marketing Research


Book Description

Essentials of Marketing Research takes an applied approach to the fundamentals of marketing research by providing examples from the business world of marketing research and showing students how to apply marketing research results. This text focuses on understanding and interpreting marketing research studies. Focusing on the 'how-to' and 'so what' of marketing research helps students understand the value of marketing research and how they can put marketing research into practice. There is a strong emphasis on how to use marketing research to make better management decisions. The unique feature set integrates data analysis, interpretation, application, and decision-making throughout the entire text. The text opens with a discussion of the role of marketing research, along with a breakdown of the marketing research process. The text then moves into a section discussing types of marketing research, including secondary resources, qualitative research, observation research, and survey research. Newer methods (e.g. using blogs or Twitter feeds as secondary resources and using online focus groups) are discussed as extensions of traditional methods such. The third section discusses sampling procedures, measurement methods, marketing scales, and questionnaires. Finally, a section on analyzing and reporting marketing research focuses on the fundamental data analysis skills that students will use in their marketing careers. Features of this text include: - Chapter Openers describe the results of a research study that apply to the topics being presented in that chapter. These are taken from a variety of industries, with a greater emphasis on social media and the Internet. - A Global Concerns section appears in each chapter, helping prepare students to conduct market research on an international scale.This text emphasizes the presentation of research results and uses graphs, tables, and figures extensively. - A Statistics Review section emphasizes the practical interpretation and application of statistical principles being reviewed in each chapter. - Dealing with Data sections in each chapter provide students with opportunities to practice interpreting data and applying results to marketing decisions. Multiple SPSS data sets and step-by-step instructions are available on the companion site to use with this feature. - Each Chapter Summary is tied to the chapter-opening Learning Objectives. - A Continuing Case Study follows a group of students through the research process. It shows potential trade-offs, difficulties and flaws that often occur during the implementation of research project. Accompanying case questions can be used for class discussion, in-class group work, or individual assignments. - End-of-Chapter Critical Thinking Exercises are applied in nature and emphasize key chapter concepts. These can be used as assignments to test students' understanding of marketing research results and how results can be applied to decision-making. - End-of-chapter Your Research Project provides more challenging opportunities for students to apply chapter knowledge on an in-depth basis, and thus olearn by doing.




The Elements of Big Data Value


Book Description

This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.




Big Data for Twenty-First-Century Economic Statistics


Book Description

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.




Statistics for Marketing and Consumer Research


Book Description

Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling







Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner


Book Description

This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --