| customer service sentiment analysis: Sentiment Analysis in Social Networks Federico Alberto Pozzi, Elisabetta Fersini, Enza Messina, Bing Liu, 2016-10-06 The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics |
| customer service sentiment 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 service sentiment analysis: Sentiment Analysis and Opinion Mining Bing Liu, 2012 Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography |
| customer service sentiment analysis: Sentiment Analysis Bing Liu, 2020-10-15 Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis. |
| customer service sentiment analysis: Deep Learning-Based Approaches for Sentiment Analysis Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik, 2020-01-24 This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field. |
| customer service sentiment analysis: Opinion Mining and Sentiment Analysis Bo Pang, Lillian Lee, 2008 This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. |
| customer service sentiment analysis: Sentiment Analysis for Social Media Carlos A. Iglesias, Antonio Moreno, 2020-04-02 Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection. |
| customer service sentiment analysis: The AI Revolution in Customer Service and Support Ross Smith, Mayte Cubino, Emily McKeon, 2024-07-16 In the rapidly evolving AI landscape, customer service and support professionals find themselves in a prime position to take advantage of this innovative technology to drive customer success. The AI Revolution in Customer Service and Support is a practical guide for professionals who want to harness the power of generative AI within their organizations to create more powerful customer and employee experiences. This book is designed to equip you with the knowledge and confidence to embrace the AI revolution and integrate the technology, such as large language models (LLMs), machine learning, predictive analytics, and gamified learning, into the customer experience. Start your journey toward leveraging this technology effectively to optimize organizational productivity. A portion of the book’s proceeds will be donated to the nonprofit Future World Alliance, dedicated to K-12 AI ethics education. IN THIS BOOK YOU’LL LEARN About AI, machine learning, and data science How to develop an AI vision for your organization How and where to incorporate AI technology in your customer experience fl ow About new roles and responsibilities for your organization How to improve customer experience while optimizing productivity How to implement responsible AI practices How to strengthen your culture across all generations in the workplace How to address concerns and build strategies for reskilling and upskilling your people How to incorporate games, play, and other techniques to engage your agents with AI Explore thought experiments for the future of support in your organization “Insightful & comprehensive—if you run a service & support operation, put this book on your essential reading list right now!” —PHIL WOLFENDEN, Cisco, VP, Customer Experience “This book is both timely and relevant as we enter an unprecedented period in our industry and the broader world driven by Generative AI. The magnitude and speed of change we’re experiencing is astounding and this book does an outstanding job balancing technical knowledge with the people and ethical considerations we must also keep front of mind.” —BRYAN BELMONT, Microsoft, Corporate VP, Customer Service & Support “The authors of this book are undoubtedly on the front lines of operationalizing Gen AI implementations in customer support environments... and they know undoubtedly that at its core, support is about people and genuine human connections. This book walks you through their journey to keep people at the center of this technical tsunami.” —PHAEDRA BOINODIRIS, Author, AI for the Rest of Us |
| customer service sentiment analysis: Exploring the Power of Electronic Word-Of-Mouth in the Services Industry Hans Ruediger Kaufmann, Sandra Maria Correia Loureiro, 2019-08 This book examines the importance and the effective utilization of eWOM content for the positioning of products and services that illustrate the value of user generated content for influencing customer decision making in diverse business sectors-- |
| customer service sentiment analysis: The Conversational Interface Michael McTear, Zoraida Callejas, David Griol, 2016-05-19 This book provides a comprehensive introduction to the conversational interface, which is becoming the main mode of interaction with virtual personal assistants, smart devices, various types of wearable, and social robots. The book consists of four parts. Part I presents the background to conversational interfaces, examining past and present work on spoken language interaction with computers. Part II covers the various technologies that are required to build a conversational interface along with practical chapters and exercises using open source tools. Part III looks at interactions with smart devices, wearables, and robots, and discusses the role of emotion and personality in the conversational interface. Part IV examines methods for evaluating conversational interfaces and discusses future directions. |
| customer service sentiment analysis: Sentiment Analysis and Knowledge Discovery in Contemporary Business Rajput, Dharmendra Singh, Thakur, Ramjeevan Singh, Basha, S. Muzamil, 2018-08-31 In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit. |
| customer service sentiment analysis: Handbook of Natural Language Processing Nitin Indurkhya, Fred J. Damerau, 2010-02-22 The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater |
| customer service sentiment analysis: The Discourse of Customer Service Tweets Ursula Lutzky, 2021-10-21 The Discourse of Customer Service Tweets studies the discursive and pragmatic features of customer service interactions, making use of a corpus of over 1.5 million tweets from more than thirty different companies. With Twitter being used as a professional service channel by many transport operators, this book features an empirical analysis of British and Irish train companies and airlines that provide updates and travel assistance on the platform, often on a 24/7 basis. From managing crises in the midst of strike action to ensuring passengers feel comfortable on board, Twitter allows transport operators to communicate with their customers in real time. Analysing patterns of language use as well as platform specific features for their communicative functions, Ursula Lutzky enhances our understanding of customers' linguistic expectations on Twitter and of what makes for successful or unsuccessful interaction. Of interest to anyone researching discourse analysis, business communication and social media, this book's findings pave the way for practical applications in customer service. |
| customer service sentiment analysis: MarketPsych Richard L. Peterson, Frank F. Murtha, 2010-07-30 An investor's guide to understanding the most elusive (yet most important) aspect of successful investing - yourself. Why is it that the investing performance of so many smart people reliably and predictably falls short? The answer is not that they know too little about the markets. In fact, they know too little about themselves. Combining the latest findings from the academic fields of behavioral finance and experimental psychology with the down-and-dirty real-world wisdom of successful investors, Drs. Richard Peterson and Frank Murtha guide both new and experienced investors through the psychological learning process necessary to achieve their financial goals. In an easy and entertaining style that masks the book’s scientific rigor, the authors make complex scientific insights readily understandable and actionable, shattering a number of investing myths along the way. You will gain understanding of your true investing motivations, learn to avoid the unseen forces that subvert your performance, and build your investor identity - the foundation for long-lasting investing success. Replete with humorous games, insightful self-assessments, entertaining exercises, and concrete planning tools, this book goes beyond mere education. MarketPsych: How to Manage Fear and Build Your Investor Identity functions as a psychological outfitter for your unique investing journey, providing the tools, training and equipment to help you navigate the right paths, stay on them, and see your journey through to success. |
| customer service sentiment analysis: AI in Customer Service: Transforming Customer Experience for the Digital Age Dizzy Davidson, 2024-08-26 Are you struggling to fully understand how AI can revolutionize your customer service? Are you looking for ways to enhance customer interactions and boost satisfaction? Look no further! “AI in Customer Service: Transforming Customer Experience for the Digital Age” is your ultimate guide to harnessing the power of AI to elevate your customer service game. This book provides a comprehensive overview of how AI technologies can be integrated into customer service operations to deliver exceptional experiences. Benefits of Reading This Book: Unlock the potential of AI to automate and streamline customer support. Learn how to personalize customer interactions using AI-driven insights. Discover tools and techniques for sentiment analysis and predictive analytics. Implement AI-powered chatbots and virtual assistants to provide 24/7 support. Enhance security with AI-based fraud detection systems. Expand your reach with multilingual support capabilities. This book is packed with practical examples, case studies, and actionable strategies that will help you understand and apply AI concepts effectively. Whether you’re a business owner, customer service manager, or tech enthusiast, this book offers valuable insights to stay ahead in the digital age. Why This Book is a Must-Read: Comprehensive Coverage From chatbots to predictive analytics, this book covers all essential AI applications in customer service. Real-World Examples to Learn from successful implementations and case studies. Actionable Insights to Get practical tips and strategies to apply AI concepts in your business. Future-Proof Your Skills to Stay updated with the latest trends and technologies in AI. Don’t miss out on the opportunity to transform your customer service with AI! Get your copy of “AI in Customer Service: Transforming Customer Experience for the Digital Age” today and start reaping the benefits of cutting-edge technology. Become knowledgeable about AI and lead your business into the future! Bullet Points 24/7 AI-Powered Support Personalized Customer Interactions Sentiment Analysis Tools Predictive Analytics for Proactive Support Voice and Virtual Assistants Self-Service Portals Fraud Detection Systems Multilingual Support Get this book now to unlock the full potential of AI in customer service and transform your customer experience for the digital age. Become an AI-savvy leader and drive your business to new heights. |
| customer service sentiment analysis: Text Mining and Analysis Dr. Goutam Chakraborty, Murali Pagolu, Satish Garla, 2014-11-22 Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program. |
| customer service sentiment analysis: TEXT PROCESSING AND SENTIMENT ANALYSIS USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-06-26 In this book, we explored a code implementation for sentiment analysis using machine learning models, including XGBoost, LightGBM, and LSTM. The code aimed to build, train, and evaluate these models on Twitter data to classify sentiments. Throughout the project, we gained insights into the key steps involved and observed the findings and functionalities of the code. Sentiment analysis is a vital task in natural language processing, and the code was to give a comprehensive approach to tackle it. The implementation began by checking if pre-trained models for XGBoost and LightGBM existed. If available, the models were loaded; otherwise, new models were built and trained. This approach allowed for reusability of trained models, saving time and effort in subsequent runs. Similarly, the code checked if preprocessed data for LSTM existed. If not, it performed tokenization and padding on the text data, splitting it into train, test, and validation sets. The preprocessed data was saved for future use. The code also provided a function to build and train the LSTM model. It defined the model architecture using the Keras Sequential API, incorporating layers like embedding, convolutional, max pooling, bidirectional LSTM, dropout, and dense output. The model was compiled with appropriate loss and optimization functions. Training was carried out, with early stopping implemented to prevent overfitting. After training, the model summary was printed, and both the model and training history were saved for future reference. The train_lstm function ensured that the LSTM model was ready for prediction by checking the existence of preprocessed data and trained models. If necessary, it performed the required preprocessing and model building steps. The pred_lstm() function was responsible for loading the LSTM model and generating predictions for the test data. The function returned the predicted sentiment labels, allowing for further analysis and evaluation. To facilitate user interaction, the code included a functionality to choose the LSTM model for prediction. The choose_prediction_lstm() function was triggered when the user selected the LSTM option from a dropdown menu. It called the pred_lstm() function, performed evaluation tasks, and visualized the results. Confusion matrices and true vs. predicted value plots were generated to assess the model's performance. Additionally, the loss and accuracy history from training were plotted, providing insights into the model's learning process. In conclusion, this project provided a comprehensive overview of sentiment analysis using machine learning models. The code implementation showcased the steps involved in building, training, and evaluating models like XGBoost, LightGBM, and LSTM. It emphasized the importance of data preprocessing, model building, and evaluation in sentiment analysis tasks. The code also demonstrated functionalities for reusing pre-trained models and saving preprocessed data, enhancing efficiency and ease of use. Through visualization techniques, such as confusion matrices and accuracy/loss curves, the code enabled a better understanding of the model's performance and learning dynamics. Overall, this project highlighted the practical aspects of sentiment analysis and illustrated how different machine learning models can be employed to tackle this task effectively. |
| customer service sentiment analysis: Natural Language Processing: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2019-11-01 As technology continues to become more sophisticated, a computer’s ability to understand, interpret, and manipulate natural language is also accelerating. Persistent research in the field of natural language processing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror natural language processes that have existed for centuries. Natural Language Processing: Concepts, Methodologies, Tools, and Applications is a vital reference source on the latest concepts, processes, and techniques for communication between computers and humans. Highlighting a range of topics such as machine learning, computational linguistics, and semantic analysis, this multi-volume book is ideally designed for computer engineers, computer and software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of natural language processing. |
| customer service sentiment analysis: Computing Attitude and Affect in Text: Theory and Applications James G. Shanahan, Yan Qu, Janyce Wiebe, 2006-01-17 Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the “factual” aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author’s reports from reports of other people’s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers’ aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an “NLP”-complete problem. |
| customer service sentiment analysis: Fun with Data Analysis and BI Nitin Sethi, 2024-08-29 DESCRIPTION Fun with Data Analysis and BI teaches you how to turn raw data into actionable insights using business intelligence tools. It equips you with essential skills to make data-driven decisions and effectively communicate findings. This book is designed to guide you through learning SQL from the ground up. Starting with installation and environment setup, it covers everything from building databases and creating tables to mastering SQL queries. Alongside theoretical concepts, you will engage in hands-on projects that demonstrate practical applications, including market analysis using Python to track stock trends and churn analysis to understand customer behavior. Each chapter concludes with MCQs to test your knowledge. The book also introduces you to Tableau, a powerful tool for creating visualizations without writing code, with step-by-step instructions on how to use it for your data projects. By the end of this book, you will be equipped with the skills to extract valuable insights from complex datasets, visualize data in compelling ways, and make data-driven decisions that positively impact your organization. KEY FEATURES ● In-depth coverage of SQL, Python, ML, and Tableau for all skill levels. ● Hands-on projects to transform raw information into valuable data insights. ● Practical examples and end-to-end solutions for mastering data science concepts. WHAT YOU WILL LEARN ● Install and set up SQL environments, create databases, develop tables, and write effective SQL queries. ● Use Python to analyze stock market data, create clusters, and support data-driven decisions. ● Apply ML to understand consumer behavior, predict churn, and improve retention. ● Design striking data visuals with Tableau, enhancing data presentation skills without coding. ● Gain hands-on experience by working on complete projects, from data preparation to final output. WHO THIS BOOK IS FOR Whether you are a business analyst, data scientist, or aspiring data professional, this book provides the essential knowledge and practical guidance to excel in the field of data analysis. TABLE OF CONTENTS 1. E-Ticket Booking 2. Creating Games on Python 3. Introduction to Sentiment Analysis 4. Sentiment Analysis on E-Commerce: Product Reviews 5. Sentiment Analysis on X 6. Stroke Prediction 7. Movie Review Sentiment Analysis 8. Stock Market Data Analysis 9. Customer Data Analysis 10. Analyzing Sports Data in Tableau 11. Office Supplies Dashboard Using Tableau 12. COVID Dashboard Using Tableau |
| customer service sentiment analysis: The Three C's: Communication, Customer Service, & Chatbots I. Edmondson, 2024-01-05 The world that our forefathers knew no longer exists, and the world in which most of us grew up is no longer here either. Science has taken us into a new world in which humans and their activities are now augmented by robots that can perform many of the functions that were previously believed to be only possible for humans to perform. The total impact of these changes is as yet unknown, but we do know that every facet of human existence has been and will continue to be impacted. There are many who fear for the future of mankind while others see possibilities for changes that will improve all facets of our lives. The one thing we do know -- life will never be the same again! |
| customer service sentiment analysis: Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines Management Association, Information Resources, 2022-06-10 The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians. |
| customer service sentiment analysis: ICDSMLA 2019 Amit Kumar, Marcin Paprzycki, Vinit Kumar Gunjan, 2020-05-19 This book gathers selected high-impact articles from the 1st International Conference on Data Science, Machine Learning & Applications 2019. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human–Computer Interaction and various data science & machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise. |
| customer service sentiment analysis: The Effortless Experience Matthew Dixon, Nick Toman, Rick DeLisi, 2013-09-12 Everyone knows that the best way to create customer loyalty is with service so good, so over the top, that it surprises and delights. But what if everyone is wrong? In their acclaimed bestseller The Challenger Sale, Matthew Dixon and his colleagues at CEB busted many longstanding myths about sales. Now they’ve turned their research and analysis to a new vital business subject—customer loyalty—with a new book that turns the conventional wisdom on its head. The idea that companies must delight customers by exceeding service expectations is so entrenched that managers rarely even question it. They devote untold time, energy, and resources to trying to dazzle people and inspire their undying loyalty. Yet CEB’s careful research over five years and tens of thousands of respondents proves that the “dazzle factor” is wildly overrated—it simply doesn’t predict repeat sales, share of wallet, or positive wordof-mouth. The reality: Loyalty is driven by how well a company delivers on its basic promises and solves day-to-day problems, not on how spectacular its service experience might be. Most customers don’t want to be “wowed”; they want an effortless experience. And they are far more likely to punish you for bad service than to reward you for good service. If you put on your customer hat rather than your manager or marketer hat, this makes a lot of sense. What do you really want from your cable company, a free month of HBO when it screws up or a fast, painless restoration of your connection? What about your bank—do you want free cookies and a cheerful smile, even a personal relationship with your teller? Or just a quick in-and-out transaction and an easy way to get a refund when it accidentally overcharges on fees? The Effortless Experience takes readers on a fascinating journey deep inside the customer experience to reveal what really makes customers loyal—and disloyal. The authors lay out the four key pillars of a low-effort customer experience, along the way delivering robust data, shocking insights and profiles of companies that are already using the principles revealed by CEB’s research, with great results. And they include many tools and templates you can start applying right away to improve service, reduce costs, decrease customer churn, and ultimately generate the elusive loyalty that the “dazzle factor” fails to deliver. The rewards are there for the taking, and the pathway to achieving them is now clearly marked. |
| customer service sentiment analysis: Artificial Intelligence in Customer Service Jagdish N. Sheth, Varsha Jain, Emmanuel Mogaji, Anupama Ambika, 2023-08-17 This edited volume elucidates how artificial intelligence (AI) can enable customer service to achieve higher customer engagement, superior user experiences, and increased well-being among customers and employees. As customer expectations dictate 24/7 availability from service departments and market pressures call for lower costs with higher efficiency, businesses have accepted that AI is vital in maintaining customer satisfaction. Yet, firms face tough challenges in choosing the right tool, optimizing integration, and striking the appropriate balance between AI systems and human efforts. In this context, chapters in this book capture the latest advancements in AI-enabled customer service through real-world examples. This volume offers a global perspective on this contemporary issue, covering topics such as the use of AI in enhancing customer well-being, data and technology integration, and customer engagement. |
| customer service sentiment analysis: Learn Emotion Analysis with R Partha Majumdar, 2021-06-02 Learn to assess textual data and extract sentiments using various text analysis R packages KEY FEATURES ● In-depth coverage on core principles, challenges, and application of Emotion Analysis. ● Includes real-world examples to simplify practical uses of R, Shiny, and various popular NLP techniques. ● Covers different strategies used in Sentiment and Emotion Analysis. DESCRIPTION This book covers how to conduct Emotion Analysis based on Lexicons. Through a detailed code walkthrough, the book will explain how to develop systems for Sentiment and Emotion Analysis from popular sources of data, including WhatsApp, Twitter, etc. The book starts with a discussion on R programming and Shiny programming as these will lay the foundation for the system to be developed for Emotion Analysis. Then, the book discusses essentials of Sentiment Analysis and Emotion Analysis. The book then proceeds to build Shiny applications for Emotion Analysis. The book rounds off with creating a tool for Emotion Analysis from the data obtained from Twitter and WhatsApp. Emotion Analysis can be also performed using Machine Learning. However, this requires labeled data. This is a logical next step after reading this book. WHAT YOU WILL LEARN ● Learn the essentials of Sentiment Analysis. ● Learn the essentials of Emotion Analysis. ● Conducting Emotion Analysis using Lexicons. ● Learn to develop Shiny applications. ● Understanding the essentials of R programming for developing systems for Emotion Analysis. WHO THIS BOOK IS FOR This book aspires to teach NLP users, ML engineers, and AI engineers who want to develop a strong understanding of Emotion and Sentiment Analysis. No prior knowledge of R programming is needed. All you need is just an open mind to learn and explore this concept. TABLE OF CONTENTS Section 1 Introduction to R Programming 1 Getting Started with R 2 Simple Operations using R 3 Developing Simple Applications in R Section 2 Introduction to Shiny Programming 4 Structure of Shiny Applications 5 Shiny Application 1 6 Shiny Application 2 Section 3 Emotion Analysis 7 Sentiment Analysis 8 Emotion Analysis 9 ZEUSg Section 4 Twitter Data Analysis 10 Introduction to Twitter Data Analysis 11 Emotion Analysis on Twitter Data 12 Chidiya BONUS CHAPTER WhatsApp Chat Analysis |
| customer service sentiment analysis: Managing Customer Relationships Using Customer Care Techniques Anna Brzozowska, Stanisław Brzeziński, Arnold Pabian, Barbara Pabian, 2024-05-15 In today’s global business environment, Customer Relationship Management (CRM) has become key to the success of many international enterprises. Managing Customer Relationships Using Customer Care Techniques: Strategy Development of an International Enterprise offers a comprehensive analysis of this crucial business aspect, focusing on how companies can effectively manage their customer relationships in the context of global expansion. This book stands out with its unique approach to CRM, blending theory with practice and providing readers with a deep understanding of how CRM influences the strategies of international enterprises. The book is divided into four main parts, each focusing on a different aspect of customer relationship management. The first part focuses on creating strategies in the context of customer relationships in international enterprises, the second part discusses the essence of the CRM concept in companies, the third part delves into the strategy of a global enterprise from the customer relationship perspective, and the fourth part centers on the evaluation and optimization of customer care strategy in modern business. Key Features: • In-depth analysis of the CRM concept in the context of international business. • Discussion on the evolution of the CRM idea over the years. • Introduction to integrated customer relationship management systems in global enterprises. • Analysis of the impact of social media on CRM. • Practical insights on measuring the effectiveness of customer care activities. Managing Customer Relationships Using Customer Care Techniques: Strategy Development of an International Enterprise is a must-read for managers, business consultants, business students, and anyone wanting to understand how to effectively manage customer relationships in an international business environment. |
| customer service sentiment analysis: Data-Driven Marketing for Strategic Success Rosário, Albérico Travassos, Cruz, Rui Nunes, Moniz, Luis Bettencourt, 2024-08-09 In the field of modern marketing, a pivotal challenge emerges as traditional strategies grapple with the complexities of an increasingly data-centric world. Marketers, researchers, and business consultants find themselves at a crossroads, navigating the intricate intersection of data science and strategic marketing practices. This challenge serves as the catalyst for Data-Driven Marketing for Strategic Success, a guide designed to address the pressing issues faced by academic scholars and professionals alike. This comprehensive exploration unveils the transformative power of data in reshaping marketing strategies, offering a beacon of strategic success in a sea of uncertainty. This book transcends the realm of traditional marketing literature. It stands as a useful resource, not merely adding elements to ongoing research but shaping the very future of how researchers, practitioners, and students engage with the dynamic world of data-driven marketing. It is strategically tailored to reach a diverse audience, offering valuable insights to academics and researchers exploring advanced topics, practitioners in the marketing industry seeking practical applications, and graduate students studying data science, marketing, and business analytics. Policymakers, ethicists, and industry regulators will find the dedicated section on ethical considerations particularly relevant, emphasizing the importance of responsible practices in the data-driven marketing landscape. |
| customer service sentiment analysis: A First Course in Artificial Intelligence Osondu Oguike, 2021-07-14 The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes. A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning. The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence. |
| customer service sentiment analysis: ISCONTOUR 2020 Tourism Research Perspectives Christian Maurer, Hubert J. Siller, 2020-04-30 The International Student Conference in Tourism Research (ISCONTOUR) offers students a unique platform to present their research and establish a mutual knowledge transfer forum for attendees from academia, industry, government and other organisations. The annual conference, which is jointly organized by the IMC University of Applied Sciences Krems and the Management Center Innsbruck, takes place alternatively at the locations Krems and Innsbruck. The conference research chairs are Prof. (FH) Mag. Christian Maurer (University of Applied Sciences Krems) and Prof. (FH) Mag. Hubert Siller (Management Center Innsbruck). The target audience include international bachelor, master and PhD students, graduates, lecturers and professors from the field of tourism and leisure management as well as businesses and anyone interested in cutting-edge research of the conference topic areas. The proceedings of the 8th International Student Conference in Tourism Research include a wide variety of research topics, ranging from consumer behaviour, tourist experience, information and communication technologies, marketing, destination management, and sustainable tourism management. |
| customer service sentiment analysis: New Technologies, Development and Application VII Isak Karabegovic, |
| customer service sentiment analysis: 13 Keys to Grow Your Business with ChatGPT Vision Tree Psychology and Technology Education Center, 2024-06-21 Are you ready to revolutionize your business with cutting-edge AI technology? In 13 Keys to Grow Your Business with ChatGPT, we provide a comprehensive guide to leveraging ChatGPT for business growth. This book is a must-read for entrepreneurs, business owners, and professionals looking to harness the power of AI to achieve unprecedented success. Inside this Book: Understanding ChatGPT: Learn the fundamentals of ChatGPT and how it can be integrated into various aspects of your business. Practical Applications: Discover practical, real-world applications of ChatGPT in customer service, marketing, sales, and more. Strategies for Success: Explore 13 proven strategies to enhance your business operations, improve customer engagement, and boost profitability. Case Studies: Gain insights from detailed case studies of businesses that have successfully implemented ChatGPT. Future Trends: Stay ahead of the curve with a look at the future of AI in business and how you can prepare for upcoming trends. Why Read This Book? Actionable Insights: Get step-by-step instructions and actionable tips that you can implement immediately. Expert Advice: Benefit from the extensive experience and expertise of Vision Tree Psychology and Technology Education Center. Comprehensive Guide: Whether you are a novice or an expert, this book provides valuable insights for all levels of AI understanding. Unlock the full potential of your business with the transformative power of ChatGPT. Order your copy of 13 Keys to Grow Your Business with ChatGPT today and take the first step towards achieving your business goals. About the Organization: Vision Tree Psychology and Technology Education Center is one of the leading authority in AI and business strategy, with professionals over 10 years of experience helping businesses of all sizes achieve their goals. Located in Brussels, Belgium, Vision Tree continues to innovate and lead in the fields of AI and business development. For more information, visit www.visiontree.be. |
| customer service sentiment analysis: The Financial Services Guide to Fintech Devie Mohan, 2020-01-03 Fintech has emerged as one of the fastest growing sectors in the financial services industry and has radically disrupted traditional banking. However, it has become clear that for both to thrive, the culture between fintech and incumbent firms must change from one of competition to collaboration. The Financial Services Guide to Fintech looks at this trend in detail, using case studies of successful partnerships to show how banks and fintech organizations can work together to innovate faster and increase profitability. Written by an experienced fintech advisor and influencer, this book explains the fundamental concepts of this exciting space and the key segments to have emerged, including regtech, robo-advisory, blockchain and personal finance management. It looks at the successes and failures of bank-fintech collaboration, focusing on technologies and start-ups that are highly relevant to banks' product and business areas such as cash management, compliance and tax. With international coverage of key markets, The Financial Services Guide to Fintech offers practical guidance, use cases and business models for banks and financial services firms to use when working with fintech companies. |
| customer service sentiment analysis: Advances in Artificial Intelligence Sabine Bergler, 2008-05-20 This book constitutes the refereed proceedings of the 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008, held in Windsor, Canada, in May 2008. The 30 revised full papers presented together with 5 revised short papers were carefully reviewed and selected from 75 submissions. The papers present original high-quality research in all areas of Artificial Intelligence and apply historical AI techniques to modern problem domains as well as recent techniques to historical problem settings. |
| customer service sentiment analysis: Data Dynamo: Unleashing the Power of Big Data Analytics Mothiram Rajasekaran, 2024-04-26 Mothiram Rajasekaran,Senior Solution Consultant, Cloudera, USA. |
| customer service sentiment analysis: United States Code United States, 1989 |
| customer service sentiment analysis: AI-Driven Marketing Research and Data Analytics Masengu, Reason, Chiwaridzo, Option Takunda, Dube, Mercy, Ruzive, Benson, 2024-04-22 The surge in technological advancements, coupled with the exponential growth of data, has left marketers grappling with the need for a paradigm shift. The once-established methods of consumer engagement are now overshadowed by the complexities of the digital age, demanding a profound understanding of artificial intelligence (AI) and data analytics. The gap between academic knowledge and practical applications in the field of marketing has widened, leaving industry professionals, educators, and students seeking a comprehensive resource to navigate the intricacies of this transformative era. AI-Driven Marketing Research and Data Analytics is a groundbreaking book that serves as a beacon for marketers, educators, and industry leaders alike. With a keen focus on the symbiotic relationship between AI, data analytics, and marketing research, this book bridges the gap between theory and practice. It not only explores the historical evolution of marketing but also provides an innovative examination of how AI and data analytics are reshaping the landscape. Through real-time case studies, ethical considerations, and in-depth insights, the book offers a holistic solution to the challenges faced by marketing professionals in the digital age. |
| customer service sentiment analysis: Intelligent Systems and Sustainable Computational Models Rajganesh Nagarajan, Senthil Kumar Narayanasamy, Ramkumar Thirunavukarasu, Pethuru Raj, 2024-06-03 The fields of intelligent systems and sustainability have been gaining momentum in the research community. They have drawn interest in such research fields as computer science, information technology, electrical engineering, and other associated engineering disciples. The promise of intelligent systems applied to sustainability is becoming a reality due to the recent advancements in the Internet of Things (IoT), Artificial Intelligence, Big Data, blockchain, deep learning, and machine learning. The emergence of intelligent systems has given rise to a wide range of techniques and algorithms using an ensemble approach to implement novel solutions for complex problems associated with sustainability. Intelligent Systems and Sustainable Computational Models: Concepts, Architecture, and Practical Applications explores this ensemble approach towards building a sustainable future. It explores novel solutions for such pressing problems as smart healthcare ecosystems, energy efficient distributed computing, affordable renewable resources, mitigating financial risks, monitoring environmental degradation, and balancing climate conditions. The book helps researchers to apply intelligent systems to computational sustainability models to propose efficient methods, techniques, and tools. The book covers such areas as: Intelligent and adaptive computing for sustainable energy, water, and transportation networks Blockchain for decentralized systems for sustainable applications, systems, and infrastructure IoT for sustainable critical infrastructure Explainable AI (XAI) and decision-making models for computational sustainability Sustainable development using edge computing, fog computing and cloud computing Cognitive intelligent systems for e-learning Artificial Intelligence and machine learning for large scale data Green computing and cyber physical systems Real-time applications in healthcare, agriculture, smart cities, and smart governance. By examining how intelligent systems can build a sustainable society, the book presents systems solutions that can benefit researchers and professionals in such fields as information technology, health, energy, agricultural, manufacturing, and environmental protection. |
| customer service sentiment analysis: Marketing with AI For Dummies Shiv Singh, 2024-08-22 Stay ahead in the marketing game by harnessing the power of artificial intelligence Marketing with AI For Dummies is your introduction to the revolution that’s occurring in the marketing industry, thanks to artificial intelligence tools that can create text, images, audio, video, websites, and beyond. This book captures the insight of leading marketing executive Shiv Singh on how AI will change marketing, helping new and experienced marketers tackle AI marketing plans, content, creative assets, and localized campaigns. You’ll also learn to manage SEO and customer personalization with powerful new technologies. Peek at the inner workings of AI marketing tools to see how you can best leverage their capabilities Identify customers, create content, customize outreach, and personalize customer experience with AI Consider how your team, department, or organization can be retooled to thrive in an AI-enabled world Learn from valuable case studies that show how large organizations are using AI in their campaigns This easy-to-understand Dummies guide is perfect for marketers at all levels, as well as those who only wear a marketing hat occasionally. Whatever your professional background, Marketing with AI For Dummies will usher you into the future of marketing. |
| customer service sentiment analysis: The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics Teixeira, Sandrina, Remondes, Jorge, 2023-11-17 In today's rapidly evolving landscape, AI has become an indispensable tool for organizations seeking to enhance their understanding of customers, boost productivity, and foster stronger connections with their target audience. The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics is a comprehensive and timely exploration of the integration of artificial intelligence (AI) into the field of digital marketing. Authored by experts in the field, this book delves into the profound and far-reaching changes that AI is bringing to the digital marketing arena. It provides a detailed examination of how organizations can leverage AI technologies to gain a competitive edge in the market. By mastering these new technologies, companies can effectively navigate the dynamic digital landscape, optimize their marketing strategies, and deliver highly personalized content to their customers. Ideal for a wide range of audiences, including researchers, teachers, students, and executives, this book serves as a vital resource for those seeking to stay ahead of the curve in the ever-evolving world of digital marketing. Through its comprehensive coverage of AI applications in the field, it equips readers with the knowledge and insights necessary to make informed decisions, develop effective marketing strategies, and drive business growth. |
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 …
