| customer segmentation using rfm analysis: Global Perspective for Competitive Enterprise, Economy and Ecology Shuo-Yan Chou, Amy J. C. Trappey, Jerzy Pokojski, Shana Smith, 2009-07-01 Global Perspective for Competitive Enterprise, Economy and Ecology addresses the general theme of the Concurrent Engineering (CE) 2009 Conference – the need for global advancements in the areas of competitive enterprise, economy and ecology. The proceedings contain 84 papers, which vary from the theoretical and conceptual to the practical and industrial. The content of this volume reflects the genuine variety of issues related to current CE methods and phenomena. Global Perspective for Competitive Enterprise, Economy and Ecology will therefore enable researchers, industry practitioners, postgraduate students and advanced undergraduates to build their own view of the inherent problems and methods in CE. |
| customer segmentation using rfm analysis: Applications of Big Data and Business Analytics in Management Sneha Kumari, K. K. Tripathy, Vidya Kumbhar, 2020-12-04 Applications of Big Data and Business Analytics in Management uses advanced analytic tools to explore the solutions to problems in society, environment and industry. The chapters within bring together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field. |
| customer segmentation using rfm analysis: Database Marketing Robert C. Blattberg, Byung-Do Kim, Scott A. Neslin, 2010-02-26 Database marketing is at the crossroads of technology, business strategy, and customer relationship management. Enabled by sophisticated information and communication systems, today’s organizations have the capacity to analyze customer data to inform and enhance every facet of the enterprise—from branding and promotion campaigns to supply chain management to employee training to new product development. Based on decades of collective research, teaching, and application in the field, the authors present the most comprehensive treatment to date of database marketing, integrating theory and practice. Presenting rigorous models, methodologies, and techniques (including data collection, field testing, and predictive modeling), and illustrating them through dozens of examples, the authors cover the full spectrum of principles and topics related to database marketing. This is an excellent in-depth overview of both well-known and very recent topics in customer management models. It is an absolute must for marketers who want to enrich their knowledge on customer analytics. (Peter C. Verhoef, Professor of Marketing, Faculty of Economics and Business, University of Groningen) A marvelous combination of relevance and sophisticated yet understandable analytical material. It should be a standard reference in the area for many years. (Don Lehmann, George E. Warren Professor of Business, Columbia Business School) The title tells a lot about the book's approach—though the cover reads, database, the content is mostly about customers and that's where the real-world action is. Most enjoyable is the comprehensive story – in case after case – which clearly explains what the analysis and concepts really mean. This is an essential read for those interested in database marketing, customer relationship management and customer optimization. (Richard Hochhauser, President and CEO, Harte-Hanks, Inc.) In this tour de force of careful scholarship, the authors canvass the ever expanding literature on database marketing. This book will become an invaluable reference or text for anyone practicing, researching, teaching or studying the subject. (Edward C. Malthouse, Theodore R. and Annie Laurie Sills Associate Professor of Integrated Marketing Communications, Northwestern University) |
| customer segmentation using rfm analysis: Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari, 2021-08-23 This book presents recent research in intelligent and fuzzy techniques. Emerging conditions such as pandemic, wars, natural disasters and various high technologies force people for significant changes in business and social life. The adoption of digital technologies to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technologies through intelligent systems is the main scope of this book. It focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent and fuzzy systems. The latest intelligent and fuzzy methods and techniques on digital transformation are introduced by theory and applications. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying digital transformation. Usage of ordinary fuzzy sets and their extensions, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management makes the book an excellent source for researchers. |
| customer segmentation using rfm analysis: Drilling Down: Turning Customer Data into Profits with a Spreadsheet Jim Novo, 2004-06-18 I spend a lot of time in marketing-oriented discussion lists. If you do, you probably also sense the incredible frustration of people who keep asking about using their customer data to retain customers and increase profits. Everybody knows they should be doing it, but can't find out how to do it. Consultants and agencies make this process sound like some kind of black magic, something you can't possibly do yourself. I disagree. I think the average business owner can do a perfectly decent job creating profiles and using them to retain customers and drive profits. Thus the book. The examples provided are Internet specific, but the methods can be used in any business where customer data is available. This book is about the down-and-dirty, nitty-gritty art of taking chunks of data generated by your customers and making sense of it, getting it to speak to you, creating insight into what types of marketing or general business actions you can take to make your business more profitable. We'll be talking about action-oriented ideas you can generate on your own to drive sales and profits, ideas that will reveal themselves by analyzing your own customer data, using only a spreadsheet. We have all heard how important it is to collect customer data, to know your customer. What I don't hear much about is what exactly you DO with all that data once you have collected it. How is it used? What exactly is Drilling Down into the data supposed to tell me, and what am I looking for when I get there? For that matter, what data should I be collecting and how will I use it when I have it? And how much is this process going to cost me? The following list outlines what you will learn and be able to do after reading the Drilling Down book: --What data is important to collect about a customer and what data is not --How to create action-oriented customer profiles with an Excel spreadsheet --How to use these profiles to plan marketing promotions --How to use these profiles to define the future value of your customers --How to use these profiles to measure the general health of your business --How to use these profiles to encourage customers to do what you want them to --How to predict when a customer is about to defect and leave you --How to increase your profits while decreasing your marketing costs --How to design high ROI (Return on Investment) marketing promotions How to blow away investors with predictions of the future profitability of your business Table of Contents Chapter 1: What's a Customer Profile? Chapter 2: Data-Driven Marketing - Customer Retention Basics Chapter 3: The Language of Data, The Science of Profit Chapter 4: Interactivity Changes the Rules of the Game Chapter 5: How to Build a Customer Profiling Spreadsheet Chapter 6: How to Profile (Score) Your Customers Chapter 7: Marketing Using Customer Scores - Basic Approach Chapter 8: Using Customer Characteristics and Multiple Scores Chapter 9: Watching Scores over Time - Customer LifeCycles Chapter 10: Customer Scoring Grids - Profiling on Steroids Chapter 11: Calculating and Using LifeTime Value in Promotions Chapter 12: Turning Profiles into Profits - the Staging Area Chapter 13: Turning Profiles into Profits - the Financial Model Chapter 14: Turning Profiles into Profits - Financial Tweaks Chapter 15: Measuring Success in Best Customer Promotions Chapter 16: Some Final Thoughts Seasonal Adjustments to Marketing Promotions Don't Fight Customer Behavior CRM Software and Customer Scoring Data-Driven Marketing Program Descriptions There's more! Automate the basic customer scoring process on large groups of customers. Use the software included free with this edition! Windows OS and MS Access and Excel required to run the software. |
| customer segmentation using rfm analysis: Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition Randall S. Collica, 2017-03-23 Résumé : A working guide that uses real-world data, this step-by-step resource will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. -- |
| customer segmentation using rfm analysis: Industrial and Managerial Solutions for Tourism Enterprises Akbaba, Atilla, Alt?nta?, Volkan, 2020-02-07 The tourism and hospitality industries are seeing continued success, which is why so many new businesses are trying to find a foothold in the field. However, the functions and responsibilities of management differ heavily between organizations within the tourism industry, such as the differences faced by big chain hotels, family owned hotels, and individually owned hotels. Understanding the methods of managing such companies is vital to ensuring their success. Industrial and Managerial Solutions for Tourism Enterprises is a pivotal reference source that focuses on the latest developments on management in the tourism and hospitality industries. Highlighting a range of topics including core competency, customer relationship management, and departmental relationships, this book is ideally designed for managers, restaurateurs, tour developers, destination management professionals, travel agencies, tourism media journalists, hotel managers, management consulting companies, human resources professionals, performance evaluators, researchers, academicians, and students. |
| customer segmentation using rfm analysis: Application of Intelligent Systems in Multi-modal Information Analytics Vijayan Sugumaran, Zheng Xu, Huiyu Zhou, 2020-07-23 This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18–19, 2020. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. |
| customer segmentation using rfm analysis: Data Mining: Concepts and Techniques Jiawei Han, Micheline Kamber, Jian Pei, 2011-06-09 Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data |
| customer segmentation using rfm analysis: Advances in Computing and Communications, Part I Ajith Abraham, Jaime Lloret Mauri, John Buford, Junichi Suzuki, Sabu M. Thampi, 2011-07-08 This volume is the first part of a four-volume set (CCIS 190, CCIS 191, CCIS 192, CCIS 193), which constitutes the refereed proceedings of the First International Conference on Computing and Communications, ACC 2011, held in Kochi, India, in July 2011. The 68 revised full papers presented in this volume were carefully reviewed and selected from a large number of submissions. The papers are organized in topical sections on ad hoc networks; advanced micro architecture techniques; autonomic and context-aware computing; bioinformatics and bio-computing; cloud, cluster, grid and P2P computing; cognitive radio and cognitive networks; cyber forensics; database and information systems. |
| customer segmentation using rfm analysis: 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 segmentation using rfm analysis: SAS For Dummies Stephen McDaniel, Chris Hemedinger, 2010-03-16 The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business. SAS allows any business or enterprise to improve data delivery, analysis, reporting, movement across a company, data mining, forecasting, statistical analysis, and more. SAS For Dummies, 2nd Edition gives you the necessary background on what SAS can do for you and explains how to use the Enterprise Guide. SAS provides statistical and data analysis tools to help you deal with all kinds of data: operational, financial, performance, and more Places special emphasis on Enterprise Guide and other analytical tools, covering all commonly used features Covers all commonly used features and shows you the practical applications you can put to work in your business Explores how to get various types of data into the software and how to work with databases Covers producing reports and Web reporting tools, analytics, macros, and working with your data In the easy-to-follow, no-nonsense For Dummies format, SAS For Dummies gives you the knowledge and the confidence to get SAS working for your organization. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| customer segmentation using rfm analysis: Advanced Theory and Practice in Sport Marketing Eric C. Schwarz, Jason D. Hunter, 2017-12-18 Effective marketing is essential for any successful sport organization, from elite international teams to local leagues. Now in a fully revised and updated third edition, Advanced Theory and Practice in Sport Marketing is still the only text to introduce key theory and best practice at an advanced level. This new edition goes beyond the introductory marketing course by exploring advanced marketing theories related to social responsibility, global issues, information systems, consumer behavior, product management, logistics, sales, promotions, and social/digital/mobile media. New to the edition are sections on branding, destination marketing, and performance evaluation that demonstrate how to measure impacts through sport marketing and how to use analytics to determine sport marketing success. Every chapter contains extended case studies and theory-to-practice insights from marketing professionals around the world and a companion website includes an impressive array of additional teaching and learning resources. Advanced Theory and Practice in Sport Marketing goes further than any other textbook to prepare students for the real world of sport marketing. It is essential reading for any upper-level undergraduate or postgraduate course in sport marketing or sport business. |
| customer segmentation using rfm analysis: Intelligent Computing Methodologies De-Shuang Huang, Zhi-Kai Huang, Abir Hussain, 2019-07-24 This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology. |
| customer segmentation using rfm analysis: Knowledge-Oriented Applications in Data Mining Kimito Funatsu, 2011-01-21 The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining. |
| customer segmentation using rfm analysis: Optimal Database Marketing Ronald G Drozdenko, Perry D Drake, 2002-03-26 Destined to be the definitive guide to database marketing applications, analytical strategies and test design. - Brian Kurtz, Executive Vice President, Boardroom Inc., 2000 DMA List Leader of the Year and DMA Circulation Hall of Fame Inductee This book is well written with interesting examples and case studies that both illustrate complex techniques and tie the chapters together. The level of detail and treatment of statistical tools and methods provides both understanding and enough detail to begin to use them immediately to target marketing efforts efficiently and effectively. It is perfect for a course in database marketing or as a handy reference for those in the industry. - C. Samuel Craig, New York University, Stern School of Business This book should be studied by all who aspire to have a career in direct marketing. It provides a thorough overview of all essential aspects of using customer databases to improve direct marketing results. The material is presented in a style that renders even the technical subjects understandable to the novice direct marketer Kari Regan, Vice President, Database Marketing Services, The Reader′s Digest Association Finally, practical information on database marketing that tackles this complex subject but makes it clear enough for the novice to understand. This book serves as more than a primer for any senior manager who needs to know the whole story. As one who has spent over 20 years of his career involved in publishing and database marketing, I have a real appreciation for how difficult it is to explain the finer points of this discipline, while keeping it understandable. This book does that admirably. Well done! - Patrick E. Kenny, Executive Vice President, Qiosk.com This book is especially effective in describing the breadth and impact of the database marketing field. I highly recommend this book to anyone who has anything to do with database marketing! -- works in or with this dynamic area. - Naomi Bernstein, Vice President, BMG Direct Ron Drozdenko and Perry Drake have written a guide to database marketing that is thorough and that covers the subject in considerable depth. It presents both the concepts underlying database marketing efforts and the all-important quantitative reasoning behind it. The material is accessible to students and practitioners alike and will be an important contribution to improved understanding of this important marketing discipline. Mary Lou Roberts, Boston University and author of Direct Marketing Management I think it is a terrific database marketing book, it′s got it all in clear and logical steps. The benefit to the marketing student and professional is that complex database concepts are carefully developed and thoroughly explained. This book is a must for all marketing managers in understanding database issues to successfully manage and structure marketing programs and achieve maximum results. - Dante Cirille, DMEF Board Member and Retired President, Grolier Direct Marketing An excellent book on the principles of Direct Marketing and utilization of the customer database to maximize profits. It is one of the best direct marketing books I have seen in years in that it is broad with specific examples. I am going to require new hires to read this (book) to get a better understanding of the techniques used in Database Marketing. - Peter Mueller, Assistant Vice President of Analysis, Scholastic, Grolier Division This is an amazingly useful book for direct marketers on how to organize and analyze database information. It′s full of practical examples that make the technical material easy to understand and apply by yourself. I strongly recommend this book to direct and interactive marketers who want to be able to perform professional database analyses themselves, or be better equipped to review the work of analysts. - Pierre A. Passavant, Professor of Direct Marketing, Mercy College and Past Director, Center for Direct Marketing, New York University The most useful database marketing reference guide published today. The authors do an excellent job of laying out all the steps required to plan and implement an effective database marketing strategy in a clear and concise manner. A must have for academics, marketing managers and business executives. - Dave Heneberry, Director, Direct Marketing Certificate programs, Western Connecticut State University and Past Chair, Direct Marketing Association This book is essential for all direct marketers. It serves as a great introduction to the technical and statistical side of database marketing. It provides the reader with enough information on database marketing and statistics to effectively apply the techniques discussed or manage others in the environment - Richard Hochhauser, President, Harte-Hanks Direct Marketing Ronald G. Drozdenko, Ph.D., is Professor and Chair of the Marketing Department, Ancell School of Business, Western Connecticut State University. He is also the founding Director of the Center for Business Research at the Ancell School. He has more than 25 years of teaching experience. The courses he teaches include Strategic Marketing Databases, Interactive/Direct Marketing Management, Product Management, Marketing Research, and Consumer Behavior. He is collaborating with the Direct Marketing Education foundation to develop a model curriculum for universities pursing the area of interactive or direct marketing. Working with an advisory board of industry experts, he co-developed the Marketing Database course in model curriculum. Dr. Drozdenko has co-directed more than 100 proprietary research projects since 1978 for the marketing and research and development of several corporations, including major multinationals. These projects were in the areas of strategic planning, marketing research, product development, direct marketing, and marketing database analysis. He also has published several articles and book chapters. He holds a Ph.D. in Experimental Psychology from the University of Missouri and is a member of the American Marketing Association, the Society for Consumer Psychology, and the Academy of Marketing Sciences. He is also the co-inventor on three U.S. patents. Perry D. Drake has been involved in the direct marketing industry for nearly 15 years. He is currently the Vice President of Drake Direct, a database marketing consulting firm specializing in response modeling, customer file segmentation, lifetime value analysis, customer profiling, database consulting, and market research. Prior to this, Perry worked for approximately 11 years in a variety of quantitative roles at The Reader′s Digest Association, most recently as the Director of Marketing Services. In addition to consulting, Perry has taught at New York University in the Direct Marketing Master′s Degree program since Fall, 1998, currently teaching Statistics for Direct Marketers and Database Modeling. Perry was the recipient of the NYU Center for Direct and Interactive Marketing′s 1998-1999 Outstanding Master′s Faculty Award. Perry also lectures on testing and marketing financials for Western Connecticut State University′s Interactive Direct Marketing Certificate Program. Along with Ron, he is collaborating with the Direct Marketing Education Foundation to develop a model curriculum for universities pursuing the area of interactive or direct marketing. Perry earned a Masters of Science in Applied Statistics from the University of Iowa and a Bachelor of Science in Economics from the University of Missouri. The book evolved from an outlined developed by an advisory board of industry experts that was established by the Direct Marketing Educational Foundation. Contemporary direct marketing and e-commerce could not exist without marketing databases. Databases allow marketers to reach customers and cultivate relationships more effectively and efficiently. While databases provide a means to establish and enhance relationships, they can also be used incorrectly, inefficiently, and unethically. This book looks beyond the temptation of the quick sale to consider the long-term impact of database marketing techniques on the organization, customers, prospective customers, and society in general. Ron Drozdenko and Perry Drake help the reader gain a thorough understanding of how to properly establish and use databases in order to build strong relationships with customers. There is not another book on the market today that reveals the level of detail regarding database marketing applications - the how′s, why′s and when′s. Features/Benefits: Draws on numerous examples from real businesses Includes applications to all direct marketing media including the Internet Describes in step-by-step detail how databases are developed, maintained, and mined Considers both business and social issues of marketing databases Contains a sample database allowing the reader to apply the mining techniques Offers access to comprehensive package of academic support materials |
| customer segmentation using rfm analysis: Predictive Marketing Omer Artun, Dominique Levin, 2015-08-06 Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience. |
| customer segmentation using rfm analysis: Marketing Analytics Wayne L. Winston, 2014-01-08 Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel. |
| customer segmentation using rfm analysis: Customer Relationship Management: A Databased Approach Kumar, 2009-07 Customer Relationship Management: A Data based Approach offers the promise of maximized profits for today s highly competitive businesses. This innovative book provides readers with the tools and techniques to effectively use CRM. It emphasizes the utilization of database marketing in order to build strong and profitable customer relationships. Kumar first describes how to implement database marketing and then looks at recent advances in CRM applications. Critical marketing issues like optimum resource allocation, purchase sequence, and the link between acquisition, retentions, and profitability are also examined on the basis of empirical findings.· CRM, Database Marketing, and Customer Value· CRM Industry Landscape· Strategic CRM· Implementing the CRM Strategy· Introduction to Customer-Based Marketing Metrics· Customer Value Metrics-Concepts and Practices· Using Databases· Designing Loyalty Programs· Effectiveness of Loyalty Programs· Data Mining· Campaign Management· Applications of Database Marketing in B-to-C and B-to-B Scenarios· Application of the Customer Value Framework to Marketing Decisions· Impact of CRM on Marketing Channels |
| customer segmentation using rfm analysis: Intelligent Systems Information Resources Management Association, 2018 Ongoing advancements in modern technology have led to significant developments in intelligent systems. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Intelligent Systems: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on the latest breakthroughs and recent progress in intelligent systems. Including innovative studies on information retrieval, artificial intelligence, and software engineering, this multi-volume book is an ideal source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of intelligent systems. |
| customer segmentation using rfm analysis: Market Segmentation Michel Wedel, Wagner A. Kamakura, 2012-12-06 Modern marketing techniques in industrialized countries cannot be implemented without segmentation of the potential market. Goods are no longer produced and sold without a significant consideration of customer needs combined with a recognition that these needs are heterogeneous. Since first emerging in the late 1950s, the concept of segmentation has been one of the most researched topics in the marketing literature. Segmentation has become a central topic to both the theory and practice of marketing, particularly in the recent development of finite mixture models to better identify market segments. This second edition of Market Segmentation updates and extends the integrated examination of segmentation theory and methodology begun in the first edition. A chapter on mixture model analysis of paired comparison data has been added, together with a new chapter on the pros and cons of the mixture model. The book starts with a framework for considering the various bases and methods available for conducting segmentation studies. The second section contains a more detailed discussion of the methodology for market segmentation, from traditional clustering algorithms to more recent developments in finite mixtures and latent class models. Three types of finite mixture models are discussed in this second section: simple mixtures, mixtures of regressions and mixtures of unfolding models. The third main section is devoted to special topics in market segmentation such as joint segmentation, segmentation using tailored interviewing and segmentation with structural equation models. The fourth part covers four major approaches to applied market segmentation: geo-demographic, lifestyle, response-based, and conjoint analysis. The final concluding section discusses directions for further research. |
| customer segmentation using rfm analysis: Effective CRM using Predictive Analytics Antonios Chorianopoulos, 2016-01-19 A step-by-step guide to data mining applications in CRM. Following a handbook approach, this book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques. The book is organized into three parts. Part one provides a methodological roadmap, covering both the business and the technical aspects. The data mining process is presented in detail along with specific guidelines for the development of optimized acquisition, cross/ deep/ up selling and retention campaigns, as well as effective customer segmentation schemes. In part two, some of the most useful data mining algorithms are explained in a simple and comprehensive way for business users with no technical expertise. Part three is packed with real world case studies which employ the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Case studies from industries including banking, retail and telecommunications are presented in detail so as to serve as templates for developing similar applications. Key Features: Includes numerous real-world case studies which are presented step by step, demystifying the usage of data mining models and clarifying all the methodological issues. Topics are presented with the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Accompanied by a website featuring material from each case study, including datasets and relevant code. Combining data mining and business knowledge, this practical book provides all the necessary information for designing, setting up, executing and deploying data mining techniques in CRM. Effective CRM using Predictive Analytics will benefit data mining practitioners and consultants, data analysts, statisticians, and CRM officers. The book will also be useful to academics and students interested in applied data mining. |
| customer segmentation using rfm analysis: Practical Machine Learning with Python Dipanjan Sarkar, Raghav Bali, Tushar Sharma, 2017-12-20 Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students |
| customer segmentation using rfm analysis: DAX Patterns Marco Russo, Alberto Ferrari, 2020-08-10 A pattern is a general, reusable solution to a frequent or common challenge. This book is the second edition of the most comprehensive collection of ready-to-use solutions in DAX, that you can use in Microsoft Power BI, Analysis Services Tabular, and Power Pivot for Excel. The book includes the following patterns: Time-related calculations, Standard time-related calculations, Month-related calculations, Week-related calculations, Custom time-related calculations, Comparing different time periods, Semi-additive calculations, Cumulative total, Parameter table, Static segmentation, Dynamic segmentation, ABC classification, New and returning customers, Related distinct count, Events in progress, Ranking, Hierarchies, Parent-child hierarchies, Like-for-like comparison, Transition matrix, Survey, Basket analysis, Currency conversion, Budget. |
| customer segmentation using rfm analysis: Successful Direct Marketing Methods Bob Stone, 1984 |
| customer segmentation using rfm analysis: Scaling the Revenue Engine Tom Mohr, 2018 Tom Mohr's book, Scaling the Revenue Engine, has already garnered over 12,000 online readers. This is the book author Geoffrey Moore (Crossing the Chasm) has challenged execs to read (You really want to read this...). Same with Tien Tzuo, the CEO of Zuora (...read this book). So too with Victor Ho, CEO of FiveStars (...the most complete resource on driving real growth I've ever seen.). And many more. In Scaling the Revenue Engine, the revenue engine is seen as a whole system, bounded by unit economics. It stretches beyond marketing and sales to also incorporate product, technology, and even accounting. At every stage of revenue engine growth, you uplift maturity by leveraging your deployment of people, tools, workflows and metrics-- always working outward from a clear understanding of customer value. |
| customer segmentation using rfm analysis: Marketing Analytics Robert W. Palmatier, J. Andrew Petersen, Frank Germann, 2022-03-24 Using data analytics and big data in marketing and strategic decision-making is a key priority at many organisations and subsequently a vital part of the skills set for a successful marketing professional operating today. Authored by world-leading authorities in the field, Marketing Analytics provides a thoroughly contemporary overview of marketing analytics and coverage of a wide range of cutting edge data analytics techniques. It offers a powerful framework, organising data analysis techniques around solving four underlying marketing problems: the 'First Principles of Marketing'. In this way, it offers an action-oriented, applied approach to managing marketing complexities and issues, and a sound grounding in making effective decisions based on strong evidence. It is supported by vivid international cases and examples, and applied pedagogical features. The companion website offers comprehensive classroom instruction slides, videos including walk throughs on all the examples and methods in the book, data sets, a test bank and a solution guide for instructors. |
| customer segmentation using rfm analysis: Marketing Strategy Robert W. Palmatier, Shrihari Sridhar, 2020-12-31 Marketing Strategy offers a unique and dynamic approach based on four underlying principles that underpin marketing today: All customers differ; All customers change; All competitors react; and All resources are limited. The structured framework of this acclaimed textbook allows marketers to develop effective and flexible strategies to deal with diverse marketing problems under varying circumstances. Uniquely integrating marketing analytics and data driven techniques with fundamental strategic pillars the book exemplifies a contemporary, evidence-based approach. This base toolkit will support students' decision-making processes and equip them for a world driven by big data. The second edition builds on the first's successful core foundation, with additional pedagogy and key updates. Research-based, action-oriented, and authored by world-leading experts, Marketing Strategy is the ideal resource for advanced undergraduate, MBA, and EMBA students of marketing, and executives looking to bring a more systematic approach to corporate marketing strategies. New to this Edition: - Revised and updated throughout to reflect new research and industry developments, including expanded coverage of digital marketing, influencer marketing and social media strategies - Enhanced pedagogy including new Worked Examples of Data Analytics Techniques and unsolved Analytics Driven Case Exercises, to offer students hands-on practice of data manipulation as well as classroom activities to stimulate peer-to-peer discussion - Expanded range of examples to cover over 250 diverse companies from 25 countries and most industry segments - Vibrant visual presentation with a new full colour design |
| customer segmentation using rfm analysis: Stop Marketing, Start Selling Shaun Tinney, Jon MacDonald, 2015-09-04 Your guide to doubling online leads, customers, and revenue. The basic value proposition of any business is to help people get what they want. A website is no different. Nobody watches TV for the commercials, or visits your website to check out your latest marketing campaigns. If they're on your site, your marketing worked. Now it's time to help them get what they came for. The partners at The Good (http: //thegood.com), an ecommerce and lead generation advisory, have condensed their learnings from over a decade in the ecommerce space. Their battle tested process for growing online revenues for brands large and small is shared in this comprehensive and actionable path to doubling online leads, customers and revenue. This book offers a step by step guide to making websites that convert. In the age of empowered customers the best possible business case is to put the needs of your customers first. This book is a practical, no-nonsense approach to doing just that. It may not always tell you what you want to hear, but it certainly tells you what you need to hear. -Gerry McGovern, Author, CEO of Customer Carewords When you invite guests to your house, you want them to enjoy themselves and leave happy. You should have the same mindset with your website. In this book, The Good shows you how to create a customer experience that converts. -Stephen Lease, Founder, Simplify & Go |
| customer segmentation using rfm analysis: Big Data and Analytics Vincenzo Morabito, 2015-01-31 This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics. |
| customer segmentation using rfm analysis: Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics Kumar, Anil, Dash, Manoj Kumar, Trivedi, Shrawan Kumar, Panda, Tapan Kumar, 2016-10-25 The success of any organization is largely dependent on positive feedback and repeat business from patrons. By utilizing acquired marketing data, business professionals can more accurately assess practices, services, and products that their customers find appealing. The Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics features innovative research and implementation practices of analytics in marketing research. Highlighting various techniques in acquiring and deciphering marketing data, this publication is a pivotal reference for professionals, managers, market researchers, and practitioners interested in the observation and utilization of data on marketing trends to promote positive business practices. |
| customer segmentation using rfm analysis: Principles of Data Mining Max Bramer, 2016-11-09 This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift. |
| customer segmentation using rfm analysis: Customer Winback Jill Griffin, Michael W. Lowenstein, 2002-02-28 Most firms consider the lost customer a lost cause. But in this ground breaking book, Jill Griffin and Michael Lowenstein provide you with step-by-step solutions for winning back lost customers, saving customers on the brink of defection, and making your firm defection proof. Whether your business is small or large, product- or service-based, retail or wholesale, this book offers proven strategies for recognizing which lost customers have the highest win-back value and implementing a sure-fire plan to recover them. It includes the techniques of hundreds of innovative companies who are already working to recapture lost customers and keep them loyal. In today's hyper-competitive marketplace, no customer retention program can be entirely foolproof, but with this guide gives you today's best methods for winning back those customers you simply can't afford to let go. |
| customer segmentation using rfm analysis: Intelligent Information Processing IX Zhongzhi Shi, Eunika Mercier-Laurent, Jiuyong Li, 2018 This book constitutes the refereed proceedings of the 10th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018. The 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. They are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding. |
| customer segmentation using rfm analysis: Economics for Business John Sloman, Mark Sutcliffe, 2004 The third EDITION of this highly successful textbook is direct and readable, with a firm focus on applying economic principles to the real world of business. It has been thoroughly revised and updated to reflect current issues and is therefore ideal for a first course in economics taking a business perspective. Features bull; bull; bull;Contains a wealth of applied material and case studies which demonstrate how economics can be used to understand real business situations. bull;Covers all the major topics of economics, as well as several specialist business chapters and sections. bull;Provides a balanced coverage of microeconomic, macroeconomic and international economic issues. bull;'FT Reports' throughout which include articles from the Financial Times examining topical news stories. bull;A range of pedagogical features to aid learning, including review questions and a web appENDix. New to this EDITION bull; bull;Use of icons throughout to highlight and explain key ideas. bull;'Pause for thought' questions integrated throughout encourage reflective learning. Answers are on the Companion Website. bull;New chapter on strategic management and a new section on globalisation. bull;Extensive web references which can be hotlinked from the book's excellent Companion Website. Student supplements This textbook is accompanied by an outstanding Companion Website, full of resources for students. These include: multiple-choice questions for each chapter; monthly updated links to news articles, with questions and commentary; hotlinks to related websites; case studies referenced in the main text; and answers to questions in the text. Visit www.booksites.net/sloman About the AUTHORs John Sloman lectures in the School of Economics at the University of the West of England. He is also Director of the Economics Subject Centre of the UK government-funded Learning and Teaching Support Network (LTSN) for higher education. Economics LTSN is based at the University of Bristol. Mark Sutcliffe is based at Bristol Business School at the University of the West of England and has many years of experience teaching economics to business studies students. |
| customer segmentation using rfm analysis: Customer Centricity Peter Fader, 2012 Not all customers are created equal. Despite what the tired old adage says, the customer is not always right. Not all customers deserve your best efforts: in the world of customer centricity, there are good customers...and then there is pretty much everybody else. Upending some of our most fundamental beliefs, renowned behavioral data expert Peter Fader, Co-Director of The Wharton Customer Analytics Initiative, helps businesses radically rethink how they relate to customers. He provides insights to help you revamp your performance metrics, product development, customer relationship management and organization in order to make sure you focus directly on the needs of your most valuable customers and increase profits for the long term. |
| customer segmentation using rfm analysis: Market Segmentation Analysis Sara Dolnicar, Bettina Grün, Friedrich Leisch, 2018-07-20 This book is published open access under a CC BY 4.0 license. This open access book offers something for everyone working with market segmentation: practical guidance for users of market segmentation solutions; organisational guidance on implementation issues; guidance for market researchers in charge of collecting suitable data; and guidance for data analysts with respect to the technical and statistical aspects of market segmentation analysis. Even market segmentation experts will find something new, including an approach to exploring data structure and choosing a suitable number of market segments, and a vast array of useful visualisation techniques that make interpretation of market segments and selection of target segments easier. The book talks the reader through every single step, every single potential pitfall, and every single decision that needs to be made to ensure market segmentation analysis is conducted as well as possible. All calculations are accompanied not only with a detailed explanation, but also with R code that allows readers to replicate any aspect of what is being covered in the book using R, the open-source environment for statistical computing and graphics. |
| customer segmentation using rfm analysis: Advances in Computer Science and Ubiquitous Computing James J. Park, Vincenzo Loia, Gangman Yi, Yunsick Sung, 2017-12-19 This book presents the combined proceedings of the 12th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2017) and the 9th International Conference on Computer Science and its Applications (CSA2017), both held in Taichung, Taiwan, December 18 - 20, 2017. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing. James J. (Jong Hyuk) Park received Ph.D. degrees in Graduate School of Information Security from Korea University, Korea and Graduate School of Human Sciences from Waseda University, Japan. From December, 2002 to July, 2007, Dr. Park had been a research scientist of R&D Institute, Hanwha S&C Co., Ltd., Korea. From September, 2007 to August, 2009, He had been a professor at the Department of Computer Science and Engineering, Kyungnam University, Korea. He is now a professor at the Department of Computer Science and Engineering and Department of Interdisciplinary Bio IT Materials, Seoul National University of Science and Technology (SeoulTech), Korea. Dr. Park has published about 200 research papers in international journals and conferences. He has been serving as chair, program committee, or organizing committee chair for many international conferences and workshops. He is a steering chair of international conferences – MUE, FutureTech, CSA, CUTE, UCAWSN, World IT Congress-Jeju. He is editor-in-chief of Human-centric Computing and Information Sciences (HCIS) by Springer, The Journal of Information Processing Systems (JIPS) by KIPS, and Journal of Convergence (JoC) by KIPS CSWRG. He is Associate Editor / Editor of 14 international journals including JoS, JNCA, SCN, CJ, and so on. In addition, he has been serving as a Guest Editor for international journals by some publishers: Springer, Elsevier, John Wiley, Oxford Univ. press, Emerald, Inderscience, MDPI. He got the best paper awards from ISA-08 and ITCS-11 conferences and the outstanding leadership awards from IEEE HPCC-09, ICA3PP-10, IEE ISPA-11, PDCAT-11, IEEE AINA-15. Furthermore, he got the outstanding research awards from the SeoulTech, 2014. His research interests include IoT, Human-centric Ubiquitous Computing, Information Security, Digital Forensics, Vehicular Cloud Computing, Multimedia Computing, etc. He is a member of the IEEE, IEEE Computer Society, KIPS, and KMMS. Vincenzo Loia (BS ‘85, MS ‘87, PhD ‘89) is Full Professor of Computer Science. His research interests include Intelligent Agents, Ambient intelligence, Computational Intelligence. Currently he is Founder & Editor-in-chief of “Ambient Intelligence and Humanized Computing”, and Co-Editor-in-Chief of “Softcomputing”, Springer-Verlag. He is Chair of the Task Forces “Intelligent Agents” and “Ambient Intelligence” IEEE CIS ETTC. He has been Chair the Emergent Technical Committe Emergent Technology, IEEE CIS Society and Vice-Chair of Intelligent Systems Applications Technical Committee. He has been author of more than 200 scientific works, Editor/co-editor of 4 Books, 64 journal papers, 25 book chapters, and 100 conference papers. He is Senior member of the IEEE, Associate Editor of IEEE Transactions on Industrial Informatics, and Associate Editor of IEEE Transactions on Systems, Man, and Cybernetics: Systems. Many times reviewers for national and international projects, Dr. Loia is active in the research domain of agents, ambient intelligence, computational intelligence, smartgrids, distributed platform for enrich added value. Gangman Yi in Computer Sciences at Texas A&M University, USA in 2007, and doctorate in Computer Sciences at Texas A&M University, USA in 2011. In May 2011, he joined System S/W group in Samsung Electronics, Suwon, Korea. He joined the Department of Computer Science & Engineering, Gangneung-Wonju National University, Korea, since March 2012. Dr. Yi has been researched in an interdisciplinary field of researches. His research focuses especially on the development of computational methods to improve understanding of biological systems and its big data. Dr. Yi actively serves as a managing editor and reviewer for international journals, and chair of international conferences and workshops. Yunsick Sung received his B.S. degree in division of electrical and computer engineering from Pusan National University, Busan, Korea, in 2004, his M.S. degree in computer engineering from Dongguk University, Seoul, Korea, in 2006, and his Ph.D. degree in game engineering from Dongguk University, Seoul, Korea, in 2012. He was employed as a member of the researcher at Samsung Electronics between 2006 and 2009. He was the plural professor at Shinheung College in 2009 and at Dongguk University in 2010. His main research interests are many topics in brain-computer Interface, programming by demonstration, ubiquitous computing and reinforcement learning. His Journal Service Experiences is Associate Editor at Human-centric Computing and Information Sciences, Springer (2015- Current). |
| customer segmentation using rfm analysis: RFM ANALYSIS AND K-MEANS CLUSTERING: A CASE STUDY ANALYSIS, CLUSTERING, AND PREDICTION ON RETAIL STORE TRANSACTIONS WITH PYTHON GUI Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-07-07 In this case study, we will explore RFM (Recency, Frequency, Monetary) analysis and K-means clustering techniques for retail store transaction data. RFM analysis is a powerful method for understanding customer behavior by segmenting them based on their transaction history. K-means clustering is a popular unsupervised machine learning algorithm used for grouping similar data points. We will leverage these techniques to gain insights, perform customer segmentation, and make predictions on retail store transactions. The case study involves a retail store dataset that contains transaction records, including customer IDs, transaction dates, purchase amounts, and other relevant information. This dataset serves as the foundation for our RFM analysis and clustering. RFM analysis involves evaluating three key aspects of customer behavior: recency, frequency, and monetary value. Recency refers to the time since a customer's last transaction, frequency measures the number of transactions made by a customer, and monetary value represents the total amount spent by a customer. By analyzing these dimensions, we can segment customers into different groups based on their purchasing patterns. Before conducting RFM analysis, we need to preprocess and transform the raw transaction data. This includes cleaning the data, aggregating it at the customer level, and calculating the recency, frequency, and monetary metrics for each customer. These transformed RFM metrics will be used for segmentation and clustering. Using the RFM metrics, we can apply clustering algorithms such as K-means to group customers with similar behaviors together. K-means clustering aims to partition the data into a predefined number of clusters based on their feature similarities. By clustering customers, we can identify distinct groups with different purchasing behaviors and tailor marketing strategies accordingly. K-means is an iterative algorithm that assigns data points to clusters in a way that minimizes the within-cluster sum of squares. It starts by randomly initializing cluster centers and then iteratively updates them until convergence. The resulting clusters represent distinct customer segments based on their RFM metrics. To determine the optimal number of clusters for our K-means analysis, we can employ elbow method. This method help us identify the number of clusters that provide the best balance between intra-cluster similarity and inter-cluster dissimilarity. Once the K-means algorithm has assigned customers to clusters, we can analyze the characteristics of each cluster. This involves examining the RFM metrics and other relevant customer attributes within each cluster. By understanding the distinct behavior patterns of each cluster, we can tailor marketing strategies and make targeted business decisions. Visualizations play a crucial role in presenting the results of RFM analysis and K-means clustering. We can create various visual representations, such as scatter plots, bar charts, and heatmaps, to showcase the distribution of customers across clusters and the differences in RFM metrics between clusters. These visualizations provide intuitive insights into customer segmentation. The objective of this data science project is to analyze and predict customer behavior in the groceries market using Python and create a graphical user interface (GUI) using PyQt. The project encompasses various stages, starting from exploring the dataset and visualizing the distribution of features to RFM analysis, K-means clustering, predicting clusters with machine learning algorithms, and implementing a GUI for user interaction. Once we have the clusters, we can utilize machine learning algorithms to predict the cluster for new or unseen customers. We train various models, including logistic regression, support vector machines, decision trees, k-nearest neighbors, random forests, gradient boosting, naive Bayes, adaboost, XGBoost, and LightGBM, on the clustered data. These models learn the patterns and relationships between customer features and their assigned clusters, enabling us to predict the cluster for new customers accurately. To evaluate the performance of our models, we utilize metrics such as accuracy, precision, recall, and F1-score. These metrics allow us to measure the models' predictive capabilities and compare their performance across different algorithms and preprocessing techniques. By assessing the models' performance, we can select the most suitable model for cluster prediction in the groceries market analysis. In addition to the analysis and prediction components, this project aims to provide a user-friendly interface for interaction and visualization. To achieve this, we implement a GUI using PyQt, a Python library for creating desktop applications. The GUI allows users to input new customer data and predict the corresponding cluster based on the trained models. It provides visualizations of the analysis results, including cluster distributions, confusion matrices, and decision boundaries. The GUI allows users to select different machine learning models and preprocessing techniques through radio buttons or dropdown menus. This flexibility empowers users to explore and compare the performance of various models, enabling them to choose the most suitable approach for their specific needs. The GUI's interactive nature enhances the usability of the project and promotes effective decision-making based on the analysis results. |
| customer segmentation using rfm analysis: Informatics and Cybernetics in Intelligent Systems Radek Silhavy, 2021-07-15 This book constitutes the refereed proceedings of the informatics and cybernetics in intelligent systems section of the 10th Computer Science Online Conference 2021 (CSOC 2021), held online in April 2021. Modern cybernetics and computer engineering papers in the scope of intelligent systems are an essential part of actual research topics. In this book, a discussion of modern algorithms approaches techniques is held. |
consumer、customer、client 有何区别？ - 知乎
对于customer和consumer，我上marketing的课的时候区分过这两个定义。 customer behavior：a broad term that covers individual consumers who buy goods and services for their own use …
Consumer与customer有区别吗？具体作什么区别？ - 知乎
Mar 18, 2014 · 一般把 customer 翻译做 “客户“ 比如你是杜蕾斯的生产商，那么中国总代，上海曼伦商贸有限公司，就是你的customer，然后从曼伦进货的全家就是曼伦的customer，然后隔 …
Windows 10 business 和 consumer 中的专业版有什么不同？ - 知乎
Mar 14, 2020 · Windows10 有business editions 和 consumer editions 版。其中每个都有 专业工作站版，可这2个专业工作…
想问一下大家web of science文献检索点不动 只能用作者检索怎么 …
手机电脑打开都是这样 我想用文献检索 不想用作者检索啊啊啊啊啊
什么是CRM系统？它的作用是什么？ - 知乎
CRM（Customer Relationship Management），即客户关系管理系统.。 是指利用软件、硬件和网络技术，为企业建立一个客户信息收集、管理、分析和利用的信息系统。通俗地讲， CRM就 …
请问金融系统中提到的KYC是做什么用的？ - 知乎
KYC看着高端，其实我们每个人都经历过。例如，当你去银行开户的时候，都必须要提交身份证件，甚至有时候还要提交家庭住址证明。这便是一个最简单的KYC。(也叫做CIP - Customer …
什么是SCRM？为什么企业要做SCRM？ - 知乎
SCRM翻译后的全程是：Social Customer Relationship Management ，可以看到这里的“S”原来是“Social”，也就是“社交”的意思。 尽管只是多了一个S，却将原先CRM呈现的客户管理行为转 …
什么是跨境电商，你们了解多少？ - 知乎
跨境电子商务是指不同国度或地域的买卖双方经过互联网以邮件或者快递等方式通关，将传统贸易中的展现、洽谈和成交环节数字化，完成产品进口的的新型贸易方式，当前主流的跨境电商形 …
有大神公布一下Nature Communications从投出去到Online的审稿 …
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
新媒体的KOL、KOC是什么? - 知乎
KOC有双重身份，即Customer和Creator，KOC是消费者的同时也是创作者，是对消费者的消费决策起到关键作用的群体。 KOL与KOC在本质上截然不同，是两个群体。前者是推，而KOC是 …
consumer、customer、client 有何区别？ - 知乎
对于customer和consumer，我上marketing的课的时候区分过这两个定义。 customer behavior：a broad term that covers individual consumers who buy goods and services for their own use …
Consumer与customer有区别吗？具体作什么区别？ - 知乎
Mar 18, 2014 · 一般把 customer 翻译做 “客户“ 比如你是杜蕾斯的生产商，那么中国总代，上海曼伦商贸有限公司，就是你的customer，然后从曼伦进货的全家就是曼伦的customer，然后隔 …
Windows 10 business 和 consumer 中的专业版有什么不同？ - 知乎
Mar 14, 2020 · Windows10 有business editions 和 consumer editions 版。其中每个都有 专业工作站版，可这2个专业工作…
想问一下大家web of science文献检索点不动 只能用作者检索怎么 …
手机电脑打开都是这样 我想用文献检索 不想用作者检索啊啊啊啊啊
什么是CRM系统？它的作用是什么？ - 知乎
CRM（Customer Relationship Management），即客户关系管理系统.。 是指利用软件、硬件和网络技术，为企业建立一个客户信息收集、管理、分析和利用的信息系统。通俗地讲， CRM就 …
请问金融系统中提到的KYC是做什么用的？ - 知乎
KYC看着高端，其实我们每个人都经历过。例如，当你去银行开户的时候，都必须要提交身份证件，甚至有时候还要提交家庭住址证明。这便是一个最简单的KYC。(也叫做CIP - Customer …
什么是SCRM？为什么企业要做SCRM？ - 知乎
SCRM翻译后的全程是：Social Customer Relationship Management ，可以看到这里的“S”原来是“Social”，也就是“社交”的意思。 尽管只是多了一个S，却将原先CRM呈现的客户管理行为转 …
什么是跨境电商，你们了解多少？ - 知乎
跨境电子商务是指不同国度或地域的买卖双方经过互联网以邮件或者快递等方式通关，将传统贸易中的展现、洽谈和成交环节数字化，完成产品进口的的新型贸易方式，当前主流的跨境电商形 …
有大神公布一下Nature Communications从投出去到Online的审稿 …
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
新媒体的KOL、KOC是什么? - 知乎
KOC有双重身份，即Customer和Creator，KOC是消费者的同时也是创作者，是对消费者的消费决策起到关键作用的群体。 KOL与KOC在本质上截然不同，是两个群体。前者是推，而KOC是 …
