Adoption And Implementation Of Ai In Customer Relationship Management

Integration of artificial intelligence (AI) into customer relationship management (CRM) automates the sales, marketing, and services in organizations. An AI-powered CRM is capable of learning from past decisions and historical patterns to score the best leads for sales. AI will also be able to predict future customer behavior. These tactics lead to better and more effective marketing strategies and increases the scope of customer services, which allow businesses to build healthier relationships with their consumer base. Adoption and Implementation of AI in Customer Relationship Management is a critical reference source that informs readers about the transformations that AI-powered CRM can bring to organizations in order to build better services that create more productive relationships. This book uses the experience of past decisions and historical patterns to discuss the ways in which AI and CRM lead to better analytics and better decisions. Discussing topics such as personalization, quality of services, and CRM in the context of diverse industries, this book is an important resource for marketers, brand managers, IT specialists, sales specialists, managers, students, researchers, professors, academicians, and stakeholders.

This research monograph brings AI to the field of Customer Relationship Management (CRM) to make a customer experience with a product or service smart and enjoyable. AI is here to help customers to get a refund for a canceled flight, unfreeze a banking account or get a health test result. Today, CRM has evolved from storing and analyzing customers’ data to predicting and understanding their behavior by putting a CRM system in a customers’ shoes. Hence advanced reasoning with learning from small data, about customers’ attitudes, introspection, reading between the lines of customer communication and explainability need to come into play. Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers’ frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently. Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.

Artificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.

The advent of Web 2.0 has led to a rebalancing of power between the customer and the company through the consumer's voice about the brand and referral behavior via electronic word of mouth. Customer opinions within the virtual brand communities can have a vast impact on a company’s sales and image. It is crucial for companies to promote and use customer contributions in order to enhance their brand image, retain customers, and develop their marketing strategy. Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0 provides relevant theoretical frameworks and the latest results of empirical research on the strategic role of marketing 2.0, digital customer experience, and social customer relationship management on social networks. Covering a range of topics such as disruptive marketing, artificial intelligence, and customer behavior, this reference work is ideal for marketers, IT practitioners, CRM specialists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference "Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation" on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020. The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems

Masterarbeit aus dem Fachbereich Informatik - Künstliche Intelligenz, , Sprache: Deutsch, Abstract: The aim of the research of this present work is to answer which criteria make an AI-driven CRM successful, what opportunities and challenges there are, and how the general population assesses this topic. Furthermore, it is important to see that the corona pandemic is having an impact on the use of AI. For this purpose, the following two research questions were asked. How does AI strengthen the customer relationship CRM? Will the Corona pandemic accelerate the use of AI? To answer the research questions, a quantitative study on people's current opinions and attitudes towards AI and how it will change as a part of the outbreak of the pandemic was conducted. Specifically, the study deals with artificial intelligence in customer service, the change of AI in companies due to Covid-19 and how people generally view the topic of AI. The participants surveyed were anonymous, of different age groups, occupations, and origins, as this topic affects everyone today and it is important to pay attention to the opinion of the general population. The targeted use of artificial intelligence in customer relationship management to make the work of companies and their employees more efficient and of higher quality, also about the customer, is on the rise. More and more sales are generated by this technology and more and more AI-controlled tools are being developed which make customer management more successful and thus intensify the relationship between customers and companies. Thus, it is necessary to understand such technologies and how they are designed, but also what opinion the general society has on this rather revolutionary technology.

The second volume of this research monograph describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer. After we learn to detect fake content, deception and hypocrisy, we examine the domain of customer complaints. We simulate mental states, attitudes and emotions of a complainant and try to predict his behavior. Having suggested graph-based formal representations of complaint scenarios, we machine-learn them to identify the best action the customer support organization can chose to retain the complainant as a customer.