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| customer relationship management dataset: Customer Relationship Management V. Kumar, Werner J. Reinartz, 2006 Customer relationship management (CRM) offers the potential of maximised profits for todays highly competitive businesses. This title describes the methods and structures for integrating CRM principles into the workplace, so that a strong customer relationship can be achieved. |
| customer relationship management dataset: Building the Customer-Centric Enterprise Claudia Imhoff, Lisa Loftis, Jonathan G. Geiger, 2001 Strategies for leveraging information technologies to improve customer relationships With E-business comes the opportunity for companies to really get to know their customers--who they are and their buying patterns. Business managers need an integrated strategy that supports customers from the moment they enter the front door--or Web site--right through to fulfillment, support, and promotion of new products and services. Along the way, IT managers need an integrated set of technologies--from Web sites to databases and data mining tools--to make all of this work. This book shows both IT and business managers how to match business strategies to the technologies needed to make them work. Claudia Imhoff helped pioneer this set of technologies, called the Corporate Information Factory (CIF). She and her coauthors take readers step-by-step through the process of using the CIF for creating a customer-focused enterprise in which the end results are increased market share and improved customer satisfaction and retention. They show how the CIF can be used to ensure accuracy, identify customer needs, tailor promotions, and more. |
| customer relationship management dataset: Customer Relationship Management Francis Buttle, 2009 This title presents an holistic view of CRM, arguing that its essence concerns basic business strategy - developing and maintaining long-term, mutually beneficial relationships with strategically significant customers - rather than the operational tools which achieve these aims. |
| customer relationship management dataset: Data Mining Techniques Michael J. A. Berry, Gordon S. Linoff, 2004-04-09 Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information. |
| customer relationship management dataset: MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT Michael J. A. Berry, Gordon S. Linoff, 2008-09-01 Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers. |
| customer relationship management dataset: Data Mining Techniques in CRM Konstantinos K. Tsiptsis, Antonios Chorianopoulos, 2011-08-24 This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process. |
| customer relationship management dataset: Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0 Ammari, Nedra Bahri, 2022-06-24 The advent of Web 2.0 has led to a rebalancing of power between the customer and the company through the consumer's voice about the brand and referral behavior via electronic word of mouth. Customer opinions within the virtual brand communities can have a vast impact on a company’s sales and image. It is crucial for companies to promote and use customer contributions in order to enhance their brand image, retain customers, and develop their marketing strategy. Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0 provides relevant theoretical frameworks and the latest results of empirical research on the strategic role of marketing 2.0, digital customer experience, and social customer relationship management on social networks. Covering a range of topics such as disruptive marketing, artificial intelligence, and customer behavior, this reference work is ideal for marketers, IT practitioners, CRM specialists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students. |
| customer relationship management dataset: Customer Relationship Management Dr. Pallavi (Joshi)Kapooria, 2017-08-14 In this era of customer sovereignty, the key to success is to be customer-centric to the core and divert optimum resources towards identifying the right customers and catering to their service needs so as to leverage the relationship with a long-term perspective. In the fierce marketplace, the prime factor that will prove to be a sustainable differentiator is customer loyalty. Marketers must connect with the customers – inform, engaging and energizing them in the process to capture the customers and win over the competition. This book will give an insight into such aspects of CRM and help an organization to develop an apt strategy and build an infrastructure that absolutely must be in place before they can begin to understand the customers and start delivering effective loyalty programs. It emphasizes on the fact that the loyalty is built on trust which results from the total experience that a customer has with your organization throughout the customer lifecycle. This book will primarily cater to the management students who are aspiring managers keen to explore the world of endless opportunities of Marketing & Brand Management. It will provide them with an insight into the core concepts of CRM and equip them to successfully mark their corporate debut. This book also intends to cater to the corporate professionals who are planning to invest in a Customer Relationship Management program. I hope that we will be able to build a relationship through my investment in writing this book and your investment in reading it. Since a relationship is two-way, I hope that we can benefit from each other’s experiences. I would be glad to hear from you, please do share your experience and feedback at pallavikapooria@gmail.com |
| customer relationship management dataset: Customer Relationship Management Daniel D. Prior, Francis Buttle, Stan Maklan, 2024-01-23 This highly regarded textbook provides the definitive account of Customer Relationship Management (CRM) concepts, applications, and technologies, focusing on how companies can create and maintain mutually beneficial relationships with customers. Readers will gain a thorough understanding of the conceptual foundations of CRM, see CRM in practice through illustrative case examples and exercises, and understand how to organise customer data gathering, analysis, and presentation for decision making. The book achieves these outcomes by first considering strategic CRM before moving into operational CRM and, finally, onto analytical aspects of CRM. The fifth edition has been fully updated to include: A series of new case examples to illustrate CRM within various regional and industrial contexts, including those relevant to large, medium, and small enterprises A series of new exercises and discussion questions to help readers understand CRM concepts and to support pedagogical processes, particularly in higher education environments A greater emphasis on managerial applications of CRM through new content to help guide managers An updated account of new and emerging technologies relevant to CRM Expanded coverage of customer experience (CX), customer engagement (CE), and customer journey management (CJM) Customer Relationship Management is essential reading for advanced undergraduate and postgraduate students studying CRM, Sales Management, Customer Experience Management, and Relationship Marketing, as well as executives who oversee CRM functions. Online resources include an Instructor’s Manual, chapter-by-chapter PowerPoint slides, and a bank of exam questions. |
| customer relationship management dataset: Mastering Data Mining Berry, Michael J. A. Berry, Gordon Linoff, 2000 |
| customer relationship management dataset: Customer Relationship Management Srivastava Mallika, With the aim of developing a successful CRM program this book begins with defining CRM and describing the elements of total customer experience, focusing on the front-end organizations that directly touch the customer. The book further discusses dynamics in CRM in services, business market, human resource and rural market. It also discusses the technology aspects of CRM like data mining, technological tools and most importantly social CRM. The book can serve as a guide for deploying CRM in an organization stating the critical success factors. KEY FEATURES • Basic concepts of CRM and environmental changes that lead to CRM adoption • Technological advancements that have served as catalyst for managing relationships • Customer strategy as a necessary and important element for managing every successful organization • CRM is not about developing a friendly relationship with the customers but involves developing strategies for retention, and using them for achieving very high levels of customer satisfaction • The concept of customer loyalty management as an important business strategy • The role of CRM in business market • The importance of people factor for the organization from the customer's perspective • Central role of customer related databases to successfully deliver CRM objectives • Data, people, infrastructure, and budget are the four main areas that support the desired CRM strategy |
| customer relationship management dataset: Customer Relationship Management V. Kumar, Werner Reinartz, 2018-05-15 This book presents an extensive discussion of the strategic and tactical aspects of customer relationship management as we know it today. It helps readers obtain a comprehensive grasp of CRM strategy, concepts and tools and provides all the necessary steps in managing profitable customer relationships. Throughout, the book stresses a clear understanding of economic customer value as the guiding concept for marketing decisions. Exhaustive case studies, mini cases and real-world illustrations under the title “CRM at Work” all ensure that the material is both highly accessible and applicable, and help to address key managerial issues, stimulate thinking, and encourage problem solving. The book is a comprehensive and up-to-date learning companion for advanced undergraduate students, master's degree students, and executives who want a detailed and conceptually sound insight into the field of CRM. The new edition provides an updated perspective on the latest research results and incorporates the impact of the digital transformation on the CRM domain. |
| customer relationship management dataset: Artificial Intelligence for Customer Relationship Management Boris Galitsky, 2020-12-23 The second volume of this research monograph describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer. After we learn to detect fake content, deception and hypocrisy, we examine the domain of customer complaints. We simulate mental states, attitudes and emotions of a complainant and try to predict his behavior. Having suggested graph-based formal representations of complaint scenarios, we machine-learn them to identify the best action the customer support organization can chose to retain the complainant as a customer. |
| customer relationship management dataset: Customer Relationship Management: A Step H. Peeru Mohamed, 2003-01-01 This book succinctly explains the cardinal principles of effective customer relationship management (CRM) acquiring, retaining and expanding customer base. The concepts, process, techniques, significance and architectural aspects of CRM are dealt in comprehensive manner. The book would serve as a useful source of reference for designing, developing and implementing CRM in any organization. |
| customer relationship management dataset: Customer Relationship Management (CRM) for Medium and Small Enterprises Antonio Specchia, 2022-04-07 Customer Relationship Management (CRM) systems are a growing topic among small- and medium-sized enterprises, entrepreneurs, and solopreneurs, and it is completely clear that CRM is a tool that businesses should have in place to manage sales processes. Teams of salespeople must have a system to run their daily activities, and small businesses and solopreneurs must track their marketing effort, a functioning structure for maintaining their contacts with prospects and clients to improve the effectiveness of their sales effort. CRM, once only available to large corporations, is now powerful technology for small and medium businesses. Small and medium businesses are now able to implement CRM solutions under a more cost-effective balance as an alternative to traditional tools like Salesforce, Dynamics, or Oracle. The reason for the success is mainly the simplicity of the new tools and solutions that have been developed for the management of sales processes. This book discusses how to implement a CRM from the perspective of the businessperson—not the more typical IT consultant or the technical staff. It benefits business development, sales management, and sales process control. Small business owners must understand why and how implementing a CRM will create value for their business—how it will focus on business development, sales management, and how sales leads develop into happy customers. Small business owners must first understand what a CRM system is, how it works, what its main functions are, and how it serves to manage workflows in the company’s sales department. Generally, entrepreneurs struggle to find the time to read and study complex and fully comprehensive books. This book provides direct operational guidelines to those who need easy-to-read information about how to use CRM effectively. Business professionals must be able to set up CRM systems and avoid mistakes and wasting time. This book provides an overview of what can be done with CRM and how it happens to empower businesspeople to find new customers and win business opportunities. This book discusses the logic of CRM in sales, giving tips and explanations on why and what happens when CRM is implemented in a specific way. Essentially, this book gives the entrepreneur the know-how behind CRM in sales in general terms, supporting enhanced customer relationships. |
| customer relationship management dataset: The Organisation of Tomorrow Mark Van Rijmenam, 2019-07-19 The Organisation of Tomorrow presents a new model of doing business and explains how big data analytics, blockchain and artificial intelligence force us to rethink existing business models and develop organisations that will be ready for human-machine interactions. It also asks us to consider the impacts of these emerging information technologies on people and society. Big data analytics empowers consumers and employees. This can result in an open strategy and a better understanding of the changing environment. Blockchain enables peer-to-peer collaboration and trustless interactions governed by cryptography and smart contracts. Meanwhile, artificial intelligence allows for new and different levels of intensity and involvement among human and artificial actors. With that, new modes of organising are emerging: where technology facilitates collaboration between stakeholders; and where human-to-human interactions are increasingly replaced with human-to-machine and even machine-to-machine interactions. This book offers dozens of examples of industry leaders such as Walmart, Telstra, Alibaba, Microsoft and T-Mobile, before presenting the D2 + A2 model – a new model to help organisations datafy their business, distribute their data, analyse it for insights and automate processes and customer touchpoints to be ready for the data-driven and exponentially-changing society that is upon us This book offers governments, professional services, manufacturing, finance, retail and other industries a clear approach for how to develop products and services that are ready for the twenty-first century. It is a must-read for every organisation that wants to remain competitive in our fast-changing world. |
| customer relationship management dataset: Augmenting Customer Retention Through Big Data Analytics Reena Malik, Ambuj Sharma, Prashant Chaudhary, 2024-12-06 Most businesses today are embracing digital transformation and automation, deploying the processes of data analytics in combination with advanced technologies for customer retention using such techniques as marketing automation, digital marketing, machine learning (ML), blockchain, generative AI, and robotics. This new book discusses a wide range of topics related to big data customer analytics and its application for customer retention. It covers important topics on the use of big data in business, including personalization and customization of products and services, segmentation, digital marketing, customer relationship management, loyalty programs, and customer loyalty and retention and more. The book provides examples and case studies that demonstrate how big data is changing the customer loyalty scenario in a highly digitalized world. The book also addresses using big data analytics in areas such as metaverse, government bodies, and fashion retail. Key features: Provides valuable insights on formulating customer retention strategies using big data analytics Discusses the application of big data for reducing churn rate Demonstrates strategies for using big data analytics to improve efficiency and customer service With its diverse and comprehensive coverage, this book offers academics, marketers, human resource managers, students, as well as industrial practitioners a guide to using the exciting technology of big data for customer retention. |
| customer relationship management dataset: Social Customer Relationship Management Rainer Alt, Olaf Reinhold, 2019-08-29 Social media has received considerable attention, and many potential benefits, as well as concerns, are now being discussed. This book explores how social media can successfully support business processes in marketing, sales and service in the context of customer relationship management (CRM). It presents the fundamentals of Social CRM and shows how small and large companies alike have implemented it. In turn, the book presents analytic and operational software tools that offer features for enhancing and streamlining interactions with customers. The book concludes with an overview of essential design areas that businesses need to bear in mind when introducing social media into their CRM strategies. In this regard, it also points out key success factors, limitations, and data protection aspects. |
| customer relationship management dataset: Building a Brand Image Through Electronic Customer Relationship Management Naim, Arshi, Kautish, Sandeep Kumar, 2022-06-30 Effective e-customer relationship management is imperative for increasing customer satisfaction, online sales, website patronage, loyalty, and retention. To understand exactly how this business strategy can be applied to enhance business operations, further study on its various benefits, opportunities, and challenges is required. Building a Brand Image Through Electronic Customer Relationship Management develops electronic customer relationship management strategies for achieving customer satisfaction and explains the concepts and uses of electronic customer relationship management to meet strategic objectives, improve customer loyalty, and build brand image. Covering topics such as marketing, brand equity, customer loyalty, and social media, this reference work is ideal for business owners, managers, entrepreneurs, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students. |
| customer relationship management dataset: Strategic Customer Relationship Management in the Age of Social Media Khanlari, Amir, 2015-07-16 In today's society, organizations are looking to optimize potential social interactions and increase familiarity with customers by developing relationships with various stakeholders through social media platforms. Strategic Customer Relationship Management in the Age of Social Media provides a variety of strategies, applications, tools, and techniques for corporate success in social media in a coherent and conceptual framework. In this book, upper-level students, interdisciplinary researchers, academicians, professionals, practitioners, scientists, executive managers, and consultants of marketing and CRM in profit and non-profit organizations will find the resources necessary to adopt and implement social CRM strategies within their organizations. This publication provides an advanced and categorized variety of strategies, applications, and tools for successful Customer Relationship Management including, but not limited to, social CRM strategies and technologies, creation and management of customers' networks, customer dynamics, social media analytics, customer intelligence, word of mouth advertising, customer value models, and social media channel management. |
| customer relationship management dataset: Applications of Emerging Technologies and AI/ML Algorithms Manoj Kumar Tiwari, Madhu Ranjan Kumar, Rofin T. M., Rony Mitra, 2023-07-01 This book provides practical insights into applications of the state-of-the-art of Machine Learning and Artificial Intelligence (AI) for solving intriguing and complex problems in procurement and supply chain management. The application domain includes perishable food supply chain, steel price prediction, electric vehicle charging infrastructure design, contract price negotiation, reverse logistics network design, and demand forecasting. Further, the book highlights the advanced topics in the procurement field, like AI in green procurement and e-procurement in the pharma sector. Furthermore, the book covers applications of well-established methodologies such as heuristics, optimization, game theory, and MCDM based on the nature of the problem. The inclusion of the vaccine supply chain digital twin and blockchain-based procurement signals the significance of the book. This book is a comprehensive guide for industry professionals to understand the power of data analytics, enabling them to improve efficiency and effectiveness in the procurement and supply chain sectors. |
| customer relationship management dataset: Applied Predictive Modeling Max Kuhn, Kjell Johnson, 2013-05-17 Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. |
| customer relationship management dataset: Mastering Data Mining : the Art and Science of Customer Relationship Management Michael J. A. Berry, 2000 |
| customer relationship management dataset: Advances in Customer Relationship Management Daniel Catalan-Matamoros, 2012-04-11 Customer relationship management (CRM) strategies have become increasingly important worldwide due to changes in expectations from customers as well as changes in the nature of markets. This book puts forth a conceptualization that attempts to not only outline CRM's domain but also to reconcile the divergent perspectives found in the academic and popular literature. Readers can see through measurable data-containing examples how the theory is applied with great success by various real-life examples. This book presents innovative proven methods for determining whether a CRM strategy for changing the way a company provides service (by adding new technology, processes, and procedures) will realize the return on the investment projected. It could be a great help to CRM personnel, student, managers and any one that works directly or indirectly with customers. |
| customer relationship management dataset: Consumer-Centered Computer-Supported Care for Healthy People H.-A. Park, P.J. Murray, C. Delaney, 2006-06 This publication, initiated by the Korean Society of Medical Informatics (KOSMI) and its Nursing Informatics Specialist Group, and the Special Interest Group in Nursing Informatics of the International Medical Informatics Association (IMIA-NI), is published for nurses and informatics experts working with informatics applications in nursing care, administration, research and education, bringing together the worlds of nursing informatics community. Korea is well known for having the highest level of Information and Communication Technology (ICT) accessibility in the world. Advances in ICT in Korea have lead Korean health care sectors to fully utilize the benefit of ICT for health care. The theme of the book, ‘Consumer-Centered Computer-Supported Care for Healthy People’, emphasizes the central role of the consumer and the function of information technology in health care. It reflects the major challenge in our time, which is developing and using information technology for the improvement of consumer oriented health care. I would seriously recommend that this book – in text form – should be available in all nursing libraries as a resource for study and reference in the expanding area of nursing and health care.”--Paula M. Procter, Reader in Informatics and Telematics in Nursing, The University of Sheffield, United Kingdom. |
| customer relationship management dataset: Customer Relationship Management Systems Handbook Duane E. Sharp, 2002-07-19 This handbook provides a detailed description and analysis of the concepts, processes, and technologies used in the development and implementation of an effective customer relationship (CRM) strategy. It takes readers through the evolution of CRM- from its early beginning to today's sophisticated data warehouse-based systems. Illustrations enhance the textual presentation. Case studies provide insight and lessons-to-be-learned and describe the benefits of successful CRM implementations. The chapter on privacy issues covers the processes companies use to ensure the privacy of their customer data, the last chapter explores the benefits of a well-conceived CRM strategy. |
| customer relationship management dataset: Statistical Methods in Customer Relationship Management V. Kumar, J. Andrew Petersen, 2012-07-26 Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back. Statistical Methods in Customer Relationship Management: Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models. Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies. Explores each model in detail, from investigating the need for CRM models to looking at the future of the models. Presents models and concepts that span across the introductory, advanced, and specialist levels. Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book. |
| customer relationship management dataset: Frontier Computing on Industrial Applications Volume 1 Jason C. Hung, Neil Yen, Jia-Wei Chang, 2024-02-21 This book gathers the proceedings of the 13th International Conference on Frontier Computing, held in Tokyo, on July 10–13, 2023, and provides comprehensive coverage of the latest advances and trends in information technology, science, and engineering. It addresses a number of broad themes, including communication networks, business intelligence and knowledge management, Web intelligence, and related fields that inspire the development of information technology. The respective contributions cover a wide range of topics: database and data mining, networking and communications, Web and Internet of things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. Many of the papers outline promising future research directions, and the book benefits students, researchers, and professionals alike. Further, it offers a useful reference guide for newcomers to the field. |
| customer relationship management dataset: Building Data Mining Applications for CRM Alex Berson, Stephen Smith, Kurt Thearling, 2000 Learn how to use customer relationship management (CRM) techniques to give your company an edge in the competitive marketplace. -- |
| customer relationship management dataset: Data Management, Analytics and Innovation Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic, 2020-09-18 This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. |
| customer relationship management dataset: Think Bigger Mark Van Rijmenam, 2014-04-03 Offering real-world insight and explanations, this book provides a roadmap for organizations looking to develop a profitable big data strategy and reveals why it's not something they can leave to the I.T. department. Big data--the enormous amount of data that is created as virtually every movement, transaction, and choice we make becomes digitized--is revolutionizing business. Sharing best practices from companies that have implemented a big data strategy including Walmart, InterContinental Hotel Group, Walt Disney, and Shell, this helpful resource covers the most important big data trends affecting organizations, as well as key technologies like Hadoop and MapReduce, and several crucial types of analyses. In Think Bigger, you will find guidance on topics such as: how to ensure security, respecting the privacy rights of consumers, and how big data is impacting specific industries--and where opportunities can be found. Big data is changing the way businesses--and even governments--are operated and managed. Think Bigger is an essential resource for anyone who wants to ensure that their company isn't left in the dust. |
| customer relationship management dataset: Computer Networks and Inventive Communication Technologies S. Smys, Ram Palanisamy, Álvaro Rocha, Grigorios N. Beligiannis, 2021-06-02 This book is a collection of peer-reviewed best selected research papers presented at 3rd International Conference on Computer Networks and Inventive Communication Technologies (ICCNCT 2020). The book covers new results in theory, methodology, and applications of computer networks and data communications. It includes original papers on computer networks, network protocols and wireless networks, data communication technologies, and network security. The proceedings of this conference is a valuable resource, dealing with both the important core and the specialized issues in the areas of next generation wireless network design, control, and management, as well as in the areas of protection, assurance, and trust in information security practice. It is a reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners for advance work in the area. |
| customer relationship management dataset: Power BI Data Analysis and Visualization Suren Machiraju, Suraj Gaurav, 2018 Power BI Data Analysis and Visualization provides a roadmap to vendor choices and highlights why Microsoft's Power BI is a very viable, cost effective option for data visualization. The book covers the fundamentals and most commonly used features of Power BI, but also includes an in-depth discussion of advanced Power BI features such as natural language queries; embedding Power BI dashboards; and live streaming data. It discusses real solutions to extract data from the ERP application, Microsoft Dynamics CRM, and also offers ways to host the Power BI Dashboard as an Azure application, extracting data from popular data sources like Microsoft SQL Server and open-source PostgreSQL. Authored by Microsoft experts, this book uses real-world coding samples and screenshots to spotlight how to create reports, embed them in a webpage, view them across multiple platforms, and more. Business owners, IT professionals, data scientists, and analysts will benefit from this thorough presentation of Power BI and its functions. |
| customer relationship management dataset: Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications Meier, Andreas, 2012-01-31 This book explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies--Provided by publisher. |
| customer relationship management dataset: Big Data Analytics Kiran Chaudhary, Mansaf Alam, 2021-12-27 Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics. |
| customer relationship management dataset: Accelerating Customer Relationships Ronald S. Swift, 2001 Preface Corporations that achieve high customer retention and high customer profitability aim for: The right product (or service), to the right customer, at the right price, at the right time, through the right channel, to satisfy the customer's need or desire. Information Technology—in the form of sophisticated databases fed by electronic commerce, point-of-sale devices, ATMs, and other customer touch points—is changing the roles of marketing and managing customers. Information and knowledge bases abound and are being leveraged to drive new profitability and manage changing relationships with customers. The creation of knowledge bases, sometimes called data warehouses or Info-Structures, provides profitable opportunities for business managers to define and analyze their customers' behavior to develop and better manage short- and long-term relationships. Relationship Technology will become the new norm for the use of information and customer knowledge bases to forge more meaningful relationships. This will be accomplished through advanced technology, processes centered on the customers and channels, as well as methodologies and software combined to affect the behaviors of organizations (internally) and their customers/channels (externally). We are quickly moving from Information Technology to Relationship Technology. The positive effect will be astounding and highly profitable for those that also foster CRM. At the turn of the century, merchants and bankers knew their customers; they lived in the same neighborhoods and understood the individual shopping and banking needs of each of their customers. They practiced the purest form of Customer Relationship Management (CRM). With mass merchandising and franchising, customer relationships became distant. As the new millennium begins, companies are beginning to leverage IT to return to the CRM principles of the neighborhood store and bank. The customer should be the primary focus for most organizations. Yet customer information in a form suitable for marketing or management purposes either is not available, or becomes available long after a market opportunity passes, therefore CRM opportunities are lost. Understanding customers today is accomplished by maintaining and acting on historical and very detailed data, obtained from numerous computing and point-of-contact devices. The data is merged, enriched, and transformed into meaningful information in a specialized database. In a world of powerful computers, personal software applications, and easy-to-use analytical end-user software tools, managers have the power to segment and directly address marketing opportunities through well managed processes and marketing strategies. This book is written for business executives and managers interested in gaining advantage by using advanced customer information and marketing process techniques. Managers charged with managing and enhancing relationships with their customers will find this book a profitable guide for many years. Many of today's managers are also charged with cutting the cost of sales to increase profitability. All managers need to identify and focus on those customers who are the most profitable, while, possibly, withdrawing from supporting customers who are unprofitable. The goal of this book is to help you: identify actions to categorize and address your customers much more effectively through the use of information and technology, define the benefits of knowing customers more intimately, and show how you can use information to increase turnover/revenues, satisfaction, and profitability. The level of detailed information that companies can build about a single customer now enables them to market through knowledge-based relationships. By defining processes and providing activities, this book will accelerate your CRM learning curve, and provide an effective framework that will enable your organization to tap into the best practices and experiences of CRM-driven companies (in Chapter 14). In Chapter 6, you will have the opportunity to learn how to (in less than 100 days) start or advance, your customer database or data warehouse environment. This book also provides a wider managerial perspective on the implications of obtaining better information about the whole business. The customer-centric knowledge-based info-structure changes the way that companies do business, and it is likely to alter the structure of the organization, the way it is staffed, and, even, how its management and employees behave. Organizational changes affect the way the marketing department works and the way that it is perceived within the organization. Effective communications with prospects, customers, alliance partners, competitors, the media, and through individualized feedback mechanisms creates a whole new image for marketing and new opportunities for marketing successes. Chapter 14 provides examples of companies that have transformed their marketing principles into CRM practices and are engaging more and more customers in long-term satisfaction and higher per-customer profitability. In the title of this book and throughout its pages I have used the phrase Relationship Technologies to describe the increasingly sophisticated data warehousing and business intelligence technologies that are helping companies create lasting customer relationships, therefore improving business performance. I want to acknowledge that this phrase was created and protected by NCR Corporation and I use this trademark throughout this book with the company's permission. Special thanks and credit for developing the Relationship Technologies concept goes to Dr. Stephen Emmott of NCR's acclaimed Knowledge Lab in London. As time marches on, there is an ever-increasing velocity with which we communicate, interact, position, and involve our selves and our customers in relationships. To increase your Return on Investment (ROI), the right information and relationship technologies are critical for effective Customer Relationship Management. It is now possible to: know who your customers are and who your best customers are stimulate what they buy or know what they won't buy time when and how they buy learn customers' preferences and make them loyal customers define characteristics that make up a great/profitable customer model channels are best to address a customer's needs predict what they may or will buy in the future keep your best customers for many years This book features many companies using CRM, decision-support, marketing databases, and data-warehousing techniques to achieve a positive ROI, using customer-centric knowledge-bases. Success begins with understanding the scope and processes involved in true CRM and then initiating appropriate actions to create and move forward into the future. Walking the talk differentiates the perennial ongoing winners. Reinvestment in success generates growth and opportunity. Success is in our ability to learn from the past, adopt new ideas and actions in the present, and to challenge the future. Respectfully, Ronald S. Swift Dallas, Texas June 2000 |
| customer relationship management dataset: Monetizing Data Andrea Ahlemeyer-Stubbe, Shirley Coleman, 2018-02-01 Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors — noted experts in the field — show how to generate extra benefit from data already collected and how to use it to solve business problems. In accessible terms, the book details ways to extract data to enhance business practices and offers information on important topics such as data handling and management, statistical methods, graphics and business issues. The text presents a wide range of illustrative case studies and examples to demonstrate how to adapt the ideas towards monetisation, no matter the size or type of organisation. The authors explain on a general level how data is cleaned and matched between data sets and how we learn from data analytics to address vital business issues. The book clearly shows how to analyse and organise data to identify people and follow and interact with them through the customer lifecycle. Monetising Data is an important resource: Focuses on different business scenarios and opportunities to turn data into value Gives an overview on how to store, manage and maintain data Presents mechanisms for using knowledge from data analytics to improve the business and increase profits Includes practical suggestions for identifying business issues from the data Written for everyone engaged in improving the performance of a company, including managers and students, Monetising Data is an essential guide for understanding and using data to enrich business practice. |
| customer relationship management dataset: Proceedings of Data Analytics and Management Abhishek Swaroop, Zdzislaw Polkowski, Sérgio Duarte Correia, Bal Virdee, 2024-01-29 This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes. |
| customer relationship management dataset: Fuzzy Data Matching with SQL Jim Lehmer, 2023-10-03 If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code. You'll learn how to: Identity and remove duplicates in two different datasets using SQL Regularize data and achieve data quality using SQL Extract data from XML and JSON Generate SQL using SQL to increase your productivity Prepare datasets for import, merging, and better analysis using SQL Report results using SQL Apply data quality and ETL approaches to finding similarities and differences between various expressions of the same data |
| customer relationship management dataset: Proactive Data Mining with Decision Trees Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon, 2014-02-14 This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students. |
Customer Relationship Management (CRM) - Kaggle
Explore and run machine learning code with Kaggle Notebooks | Using data from Online Retail II Data Set from ML Repository
CRM Data Analysis: Metrics for Better Customer Relationships
Sep 19, 2024 · Exploring the CRM Analytics Dataset. The CRM analytics dataset is the backbone of CRM data analysis. It consists of all the data collected about customers, such as: Customer …
Dataset for the electronic customer relationship management …
Mar 12, 2022 · The stimulus–organism–response (SOR) model, developed by Mehrabian and Russell [5], is a well-known paradigm for describing buyer–seller interaction and is widely used …
CRM Sales Analysis - GitHub
This project involves the analysis of sales opportunities data from a Customer Relationship Management (CRM) system. The dataset, sourced from Maven Analytics1, contains detailed …
Salesforce Customer Relationship Manager - Catalog
Jun 25, 2024 · Traditionally Customer Relationship Management has been a sales tool but now CRM systems, like Salesforce, allow people to do more. Access & Use Information Public: …
Dataset for the electronic customer relationship management
Mar 12, 2022 · The dataset presents the survey data including three factors as electronic loyalty, perceived mental benefits, hedonic value. The quantitative data is based on 48 … Dataset for …
(PDF) Dataset for the electronic customer relationship management …
Mar 1, 2022 · The dataset presents the survey data including three factors as electronic loyalty, perceived mental benefits, hedonic value. The quantitative data is based on 485 participants …
Customer Relationship Management for Supermarkets Using …
Jun 19, 2022 · Customer Relationship Management (CRM) is a process in which a business manages its interactions with customers using data analysis regarding the customers’ beh ...
Dataset for the electronic customer relationship management …
Customer loyalty is difficult to establish because of the danger of online transactions, which causes risk in all transaction procedures. The dataset presents the survey data including three …
4 CRM Data Types & How To Use Them – Forbes Advisor
Jun 14, 2024 · A customer relationship management, or CRM, is a software platform that helps you organize and manage essential prospect and customer data. Marketers, customer service …
Customer Relationship Management (CRM) - Kaggle
Explore and run machine learning code with Kaggle Notebooks | Using data from Online Retail II Data Set from ML Repository
CRM Data Analysis: Metrics for Better Customer Relationships
Sep 19, 2024 · Exploring the CRM Analytics Dataset. The CRM analytics dataset is the backbone of CRM data analysis. It consists of all the data collected about customers, such as: Customer …
Dataset for the electronic customer relationship management …
Mar 12, 2022 · The stimulus–organism–response (SOR) model, developed by Mehrabian and Russell [5], is a well-known paradigm for describing buyer–seller interaction and is widely used …
CRM Sales Analysis - GitHub
This project involves the analysis of sales opportunities data from a Customer Relationship Management (CRM) system. The dataset, sourced from Maven Analytics1, contains detailed …
Salesforce Customer Relationship Manager - Catalog
Jun 25, 2024 · Traditionally Customer Relationship Management has been a sales tool but now CRM systems, like Salesforce, allow people to do more. Access & Use Information Public: …
Dataset for the electronic customer relationship management
Mar 12, 2022 · The dataset presents the survey data including three factors as electronic loyalty, perceived mental benefits, hedonic value. The quantitative data is based on 48 … Dataset for …
(PDF) Dataset for the electronic customer relationship management …
Mar 1, 2022 · The dataset presents the survey data including three factors as electronic loyalty, perceived mental benefits, hedonic value. The quantitative data is based on 485 participants …
Customer Relationship Management for Supermarkets Using …
Jun 19, 2022 · Customer Relationship Management (CRM) is a process in which a business manages its interactions with customers using data analysis regarding the customers’ beh ...
Dataset for the electronic customer relationship management …
Customer loyalty is difficult to establish because of the danger of online transactions, which causes risk in all transaction procedures. The dataset presents the survey data including three …
4 CRM Data Types & How To Use Them – Forbes Advisor
Jun 14, 2024 · A customer relationship management, or CRM, is a software platform that helps you organize and manage essential prospect and customer data. Marketers, customer service …
