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Author: Katarzyna Tarnowska
Publisher: Springer
ISBN: 3030134385
Category : Technology & Engineering
Languages : en
Pages : 133
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Book Description
This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience. The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to “learn” from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to “weigh” these actions and determine which ones would have a greater impact.
Author: Katarzyna Tarnowska
Publisher: Springer
ISBN: 3030134385
Category : Technology & Engineering
Languages : en
Pages : 133
Get Book Here
Book Description
This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience. The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to “learn” from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to “weigh” these actions and determine which ones would have a greater impact.
Author: Katarzyna A. Tarnowska
Publisher:
ISBN: 9783030134396
Category : COMPUTERS
Languages : en
Pages : 124
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Book Description
This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience. The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to "learn" from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to "weigh" these actions and determine which ones would have a greater impac t.
Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
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Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Author: Michael J. Shaw
Publisher: Springer Science & Business Media
ISBN: 0306475480
Category : Computers
Languages : en
Pages : 463
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Book Description
E-Business Management: Integration of Web Technologies with Business Models contains a collection of articles by leading information systems researchers on important topics related to the development of e-business. The goal is to enhance the understanding of the state of the art in e-business, including the most current and forward-looking research. The book emphasizes both business practices and academic research made possible by the recent rapid advances in the applications of e-business technology. The book should help graduate students, researchers, and practitioners understand major e-business developments, how they will transform businesses, and the strategic implications to be drawn.
Author: Prathmesh Yelne
Publisher: Codegyan
ISBN:
Category : Education
Languages : en
Pages : 250
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Book Description
Discover the extraordinary possibilities of machine learning and artificial intelligence in this groundbreaking exploration. From self-driving cars to virtual assistants, this book delves into the fascinating world of algorithms and how they are transforming industries and revolutionizing our lives. Explore the inner workings of neural networks, deep learning models, and predictive analytics, and witness the profound impact they have on decision-making, problem-solving, and data analysis. Whether you're a novice or an expert in the field, prepare to be captivated by the limitless potential of machine learning and AI.
Author: Xin-She Yang
Publisher: Springer Nature
ISBN: 9819932432
Category : Technology & Engineering
Languages : en
Pages : 1102
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Book Description
This book gathers selected high-quality research papers presented at the Eighth International Congress on Information and Communication Technology, held at Brunel University, London, on 20–23 February 2023. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.
Author: Kim Normann Andersen
Publisher: Springer
ISBN: 3642229611
Category : Computers
Languages : en
Pages : 422
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Book Description
This book constitutes the refereed proceedings of the Second International Conference on Electronic Government and the Information Systems Perspective, EGOVIS 2011, held in Toulouse, France, in August/September 2011. The 30 revised full papers presented were carefully reviewed and selected from numerous submissions. Among the topics addressed are aspects of security, reliability, privacy and anonymity of e-government systems, knowledge processing, service-oriented computing, and case studies of e-government systems in several countries.
Author: Alessia Paglialonga
Publisher: Frontiers Media SA
ISBN: 2832527221
Category : Science
Languages : en
Pages : 215
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Book Description
Author: Michael Johnson & Andres Gustafsson
Publisher: John Wiley & Sons
ISBN: 9788126509393
Category :
Languages : en
Pages : 240
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Book Description
Author: Juan D. Velásquez
Publisher: Springer
ISBN: 3642333265
Category : Technology & Engineering
Languages : en
Pages : 191
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Book Description
This research volume focuses on analyzing the web user browsing behaviour and preferences in traditional web-based environments, social networks and web 2.0 applications, by using advanced techniques in data acquisition, data processing, pattern extraction and cognitive science for modeling the human actions. The book is directed to graduate students, researchers/scientists and engineers interested in updating their knowledge with the recent trends in web user analysis, for developing the next generation of web-based systems and applications.
