Download Free Statistical Methods In Customer Relationship Management Book in PDF and EPUB Free Download. You can read online Statistical Methods In Customer Relationship Management and write the review.

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.
Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9781119993209 .
All of us enjoy individually specific service or a product that is delivered for us only. Customer relationship management (CRM) is the area of expertise that helps companies to work with customers based on their specific needs or requirements. To reach success CRM systems implement the most powerful math and IT tools such as statistical analysis, artificial neural nets, and graph systems. This book deals with the practical implementation and meta-analysis of CRM experience in various locations and business areas. The authors have produced a great book and provided meta-analysis of the latest CRM systems and a roadmap of their development. In the chapters, our readers will find descriptive analysis of CRM models, applied tools, and methods.
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.
Packed with more than forty percent new and updated material,this edition shows business managers, marketing analysts, and datamining specialists how to harness fundamental data mining methodsand techniques to solve common types of business problems Each chapter covers a new data mining technique, and then showsreaders how to apply the technique for improved marketing, sales,and customer support The authors build on their reputation for concise, clear, andpractical explanations of complex concepts, making this book theperfect introduction to data mining More advanced chapters cover such topics as how to prepare datafor analysis and how to create the necessary infrastructure fordata mining Covers core data mining techniques, including decision trees,neural networks, collaborative filtering, association rules, linkanalysis, clustering, and survival analysis
This text provides step-by-step guidelines for implementing customer relationship management (CRM) throughout an organization. This book explains: the benefits of CRM, the planning, change management, business metrics and analytics, systems and technology, and measuring the impact of CRM.
Understand customer relationship management in no time! Find out everything you need to know about this powerful tool with this practical and accessible guide. Customer relationship management is a valuable tool in an increasingly competitive business world. It allows companies to find out who their customers are and what they want, which enables them to tailor their communication and offers to their clients. No matter what your sector of activity, an effective CRM strategy will boost customer satisfaction, increase performance and give you a valuable edge over the competition. In 50 minutes you will be able to: • Understand the wide range of tools and techniques used in customer relationship management • Tailor your communications to your customers’ needs and expectations • Evaluate the success of your CRM strategy based on a number of key performance indicators ABOUT 50MINUTES.COM | MANAGEMENT AND MARKETING The Management and Marketing series from the 50Minutes collection provides the tools to quickly understand the main theories and concepts that shape the economic world of today. Our publications will give you elements of theory, definitions of key terms and case studies in a clear and easily digestible format, making them the ideal starting point for readers looking to develop their skills and expertise.
This dissertation, "Stochastic Models for Customer Relationship Management" by Ka-kuen, Wong, 黃嘉權, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled STOCHASTIC MODELS FOR CUSTOMER RELATIONSHIP MANAGEMENT submitted by WONG Ka-Kuen for the degree of Master of Philosophy at The University of Hong Kong in July 2004 Customer relationship management is the development and maintenance of a long-term relationship with the customers. It is a crucial factor for surviving in a competitive market. Classication of customers and promotion budget allocation arethecoreissuesinrelationshipmarketing. Deterministicmodelshavebeenused in customer relationship management. In practice, however, most of them are not suitable because of the stochastic nature of the problem. In this thesis, a series of stochastic models and numerical algorithms are proposed and evaluated. Classication of customers plays an important role in promotion planning and budget setting. Apart from many available tools for classication, one poten- tial tool is the Hidden Markov Models (HMMs) and it can be implemented in a Microsoft Excel worksheet. Ecient parameter estimation methods with fast numerical algorithms for HMMs are also proposed. Numerical examples are given to demonstrate the model's e(R)ectiveness and eciency of the estimation method. Promotionbudgetallocationisdesignedtoattractandkeepcustomers. Stochas- tic dynamic programming models with the Markov chain techniques are proposed for capturing the customer behaviour. The model can be implemented easily and eciently in a Microsoft Excel worksheet, and precise implementation is also demonstrated and discussed in details. Furthermore, a higher-order Markov chain modelisafurtherwayofcapturingthedynamicsofpracticaldata. Ahigher-order Markov decision process is proposed. Practical data of a computer servicecompanyisusedtoillustratethee(R)ectivenessoftheproposedhigher-orderMarkov model. Aremarkableimprovementinpredictingthecustomerbehaviorisobserved. DOI: 10.5353/th_b3028996 Subjects: Customer relations - Management - Statistical methods Stochastic processes
This research monograph brings AI to the field of Customer Relationship Management (CRM) to make a customer experience with a product or service smart and enjoyable. AI is here to help customers to get a refund for a canceled flight, unfreeze a banking account or get a health test result. Today, CRM has evolved from storing and analyzing customers’ data to predicting and understanding their behavior by putting a CRM system in a customers’ shoes. Hence advanced reasoning with learning from small data, about customers’ attitudes, introspection, reading between the lines of customer communication and explainability need to come into play. Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers’ frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently. Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.