This comprehensive article explores the transformative role of Customer Relationship Management (CRM) systems in modern healthcare delivery. The article examines how CRM platforms revolutionize patient care through enhanced engagement, streamlined operations, and data-driven decision-making capabilities. It investigates the significant impact of healthcare CRM on personalized care delivery, patient experience, and operational efficiency while addressing the technical and organizational implementation challenges. The article demonstrates how CRM systems facilitate better care coordination, improve patient outcomes, and contribute to financial sustainability in healthcare organizations. (...) Special attention is given to the unique features of healthcare CRM systems that differentiate them from traditional CRM platforms, highlighting their crucial role in advancing patient-centered care models and supporting healthcare providers in delivering more effective, efficient, personalized medical services. (shrink)

Customer Relationship Management has become one of the most valuable tools in business, with the help of predictive analyzes organizations can identify their customer’s needs and improve business results. This research focuses on using of predictive analytics in Salesforce, the prominent CRM system that helps to gain insights from large volumes of data with the help of deep learning approaches. Using current advanced models like Recurrent Neural Networks and the transformer connections, companies can gain deep insights into such patterns and (...) trends as customer buying behavior, sales anticipation, and customer lifetime value. It is not only effective in improving decision making but also useful in the customization of the marketing strategy involving the delivery of messages that the customer might be interested. Integrating deep learning into Salesforce’s analytics is a revolution in the CRM system function. Former approaches in data analysis could not deal with unstructured data or analyses customer paths, as mentioned before. However, thanks to deep learning, large-scale customer data and aspects of previously hidden patterns have become changer for business interpretation. This research demonstrates the potential of using deep learning for predictive analytics to inform customer-oriented initiatives and increase the proportion of customers amongst leads and stability of client base. Thus, by focusing on Salesforce as an example, this study gives a clear vision of how artificial intelligence revolutionizes the approach to CRM, serves as the reference point for data-driven businesses in the digital environment. (shrink)

Today every organization is acting in a dynamic environment and in a world characterised by turbulent change and fierce competition due to technological advancement and the knowledge based economy, an organization must always ready to adapt and transform themselves so as to be able to confront the shifting needs of the new environment, more demanding customers, smarter workers, anticipating ability to changes, accelerating the development of new products, processes and services, changing technologies and customer expectations, businesses have realised the importance (...) of Customer Relationship Management in acquiring new customers, retain existing ones and maximize their lifetime value. The wide spread availability of the internet across the world has led airlines to use their corporate web-sites to bypass travel intermediaries and focus on online communication, information and transaction. The paper considers five dimensions of Web site quality-usability, web site design, service quality, information quality and enjoyment on a sample of 150 respondents from four airlines namely, Air India, Spicejet, Indigo and Jet Airways. Respondents consisted of 40 employed, 80 business men and 30 students. Overall, the majority of respondents are frequent, experienced Internet users and likely to be relatively good judges of Web quality. Analysis of results shows that customers’ priority about airlines website are changing. As the self-service, no-frills and low-cost trend for air travel has grown in recent years, so consumers have been driven less by service quality and more by easy access to good information packaged in an entertaining and fun "wrapper'. More over the airlines have pursued different strategies for their Web sites over the period of study .Air India rated badly for service quality and Jet Airways and Spice jet scored high on service and information quality. The paper suggests that careful management and selection of subjects to be placed on web site can retain the customers and reduce switching intentions. (shrink)

The dynamics of using CRM have changed rapidly due to the advances in AI technology, which has allowed for the use of intelligent and informatics technology in handling customers. It is crucial to understand that oldfashioned techniques of using CRM systems for data storage and achieving simple analytical capabilities have evolved with the incorporation of AI to become a powerful tool capable of predicting customer needs and automating communication processes. Salesforce Einstein is one of the best artificial intelligence CRM solutions, (...) and it uses machine learning, NLP, deep learning, and predictive analytics to improve the customer engagement approach. One of the significant advantages of employing artificial intelligence in sales and customer service is the discovery and analysis of immense amounts of customer data and its application in making effective decisions in an organization. As a result, businesses can gain such advanced knowledge of the customers, making it possible to engage them through highly targeted marketing and sales methods that enhance customer satisfaction and loyalty. This paper aims to explore the basic structures of Salesforce Einstein and introduce it as the tool that revolutionizes customers’ interactions in sales, marketing, service, and analytics. In this literature review, we discuss the development of AI technology in CRM solutions and its correlation with performance metrics. The measure and analysis sections describe the evaluation approach to planted Einstein’s effectiveness, supported by data from real practice implementation. Overall, the findings herein reveal positive customer-oriented, financial, and organizational outcomes, thus verifying the potential of AI in CRM. Therefore, it assesses the impediments to implementing AI features of CRM systems in businesses and outlines relevant lines of research for advancing AI-based CRM systems in the future. Thus, this study aims to explain how AI is transforming the CRM landscape by showcasing the features and values of Salesforce Einstein. (shrink)

Lograr beneficios económicos a partir de la satisfacción de las necesidades de los clientes, es y será el objetivo principal de cualquier empresa en el sentido de ser una organización que busca crear valor. -/- En el entorno actual parece casi imposible satisfacer las necesidades de los clientes y es grande la dificultad de obtener beneficios en economías abiertas. Los sistemas de manejo de las relaciones con los clientes (CRM) constituyen una pieza clave al momento de brindar herramientas para la (...) segmentación, fidelización y análisis de los datos que surgen en el contacto con el cliente. -/- Aquí se presentan conceptos relacionados con esta estrategia, la visión de especialistas y usuarios, así como el análisis de algunos productos. Además se presentan tres casos de empresas uruguayas, donde los sistemas de atención de clientes se han llevado adelante de maneras diferentes. -/- Finalmente se resumen una serie de recomendaciones en cuanto al tipo de herramienta que se ha de utilizar en cada caso, la forma de evaluar productos, el análisis del retorno de la inversión, y los principales elementos que se deben tomar en cuenta para llevar adelante un sistema de mejora continua en su uso y aplicación al objetivo inicial de crear valor. (shrink)

Customer Relationship Management (CRM) is a new technique in marketing where the marketer tries to develop long term relationship with the customers to develop them as life time customers. This research check the impact of customer relationship management activities on bank’s customer retention in The Nainital Bank Ltd.,Vikasnagar . For the purpose of study, a sampling analysis was conducted among (400) customers selected with the help of a structured questionnaire. (370) questionnaires were usable. Statistical answers give support on the high (...) positive relationship between customer relationship management (CRM) and customer satisfaction. Thus, this paper aims to identify the reasons for the customers to prefer The Nainital Bank Ltd. at Vikasnagar. Further, this paper focuses the service provided by the staff in the bank. This paper is an attempt to find out CRM role in The Nainital bank Ltd. Few recommendations were suggested from this study were to create an awareness of loan facility, internet banking and locker service. (shrink)

The Internet of Things (IoT), Artificial Intelligence (AI), and Big Data are shaping the new evolving customer experience landscape. This transition points to the very important role that Salesforce, the world’s leading Customer Relationship Management (CRM) platform, will play. This paper talks about how Salesforce uses these technologies to reinvent customer engagement, personalize and predict. And by connecting devices and systems in real time, IoT lets businesses collect actionable data about their customer’s behavior and preferences. With the combination of AI (...) inside Salesforce, delivered via tools like Einstein, processes can be automated and predictive analytics; recommendations are provided by this data. It also allows us to integrate big data and analyze massive datasets to find trends, improve decision making, and deliver hyper personalization experiences. The practical applications considered in the paper include predictive maintenance, real time customer support, and targeted marketing campaigns. Second, it discusses the problems of including IoT, AI, and Big Data in existing systems, including data privacy issues, technological complexities and organizational blockades. This paper features key trends, takes stock of innovations and serves as a roadmap for organizations looking to redefine customer experiences in the hyper digital world. It’s no wonder Salesforce plays a pivotal marketing role in this future of customer-centric strategies. (shrink)

dolce, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, (...) and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases. (shrink)

Abstract: The study investigated the impact of Customer Relationship Management (CRM) on performance of deposit money banks in Abia State. The study adopted a random sampling technique which made it possible for all the workers to have equal opportunity to being selected as the representative sample based on the total population of the two hundred and ten (210), a normal confidence level of 95% and error tolerance of 5% was used. ANOVA showed a large F-statistics of 509.23 coupled with a (...) significant value of less than 0.005 which indicated that there was a 95% confidence interval that the difference was accepted. The regression gave the value 0.564. The value using 2-tailed analysis was flagged as being significant with a 0.001 sig. value. Equally implied that there was a more than 95% confidence interval. More so, Since the p-value 0.154 was greater than 0.059 that was (real 0.154 > rtab 0,059). Therefore, the researcher found that there was relationship between CRM practice and customer satisfaction of First bank and GT Bank Plc. in Abia state. Also that there was an influence of CRM practice on profitability in First Bank and GT Bank Plc. in Abia state. Finally that there was an influence of CRM practice on the market share of First bank and GT bank plc in Abia state. (shrink)

The COVID-19 pandemic that began in 2020 has significantly impacted businesses, regardless of size or industry. The hybrid and remote working models have moved all meetings with potential and existing suppliers to an online environment. This also applies to small- and medium-sized enterprises (SMEs), which have had to adapt themselves to the new situation and implement the solutions necessary to survive on the market. On the other hand, clients have become more aware of the environment and its changes. Customers are (...) trying to be more eco-friendly, by choosing and moving towards Green IT. Thus, this needs to be considered. The acquisition of management information systems (MIS) in the pandemic era is based only on virtual meetings. The main goals of this paper were the identification of the changes in the negotiations caused by the COVID-19 pandemic, the transformation of this process into virtual environment, discussion of the possibility of using Green IT in addition to Management Information Systems, and the changes caused by the pandemic. The article was prepared based on the results of qualitative research using the case study method. The comparative analysis includes purposely selected cloud-based Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems’ acquisition processes, presented from the clients’ perspective. The research was conducted in 2021, based on the authors’ practical experience, and presents four cases. This research illustrates the negotiations concerning an acquisition transaction pre-pandemic and during the pandemic. Finally, the conclusions and main differences caused by the pandemic in the acquisition transaction process of management information systems (MIS) are presented. (shrink)

Customer retention is a significant issue and one of the most pressing issues for big businesses. Companies are working to create methods to anticipate future customer churn since it has such a direct impact on their revenues, particularly in the telecom industry. As a result, identifying factors that contribute to customer turnover is critical in order to take the required steps to minimise churn. Our work's primary contribution is the development of a churn prediction model that helps telecom carriers forecast (...) which customers are most likely to churn. The model created in this paper employs machine learning methods on a large data platform to provide a novel approach to feature engineering and selection. This study also established churn variables that are critical in identifying the underlying causes of churn in order to evaluate the model's success. CRM may increase productivity, suggest appropriate promotions to a group of probable churn customers based on similar behaviour patterns, and vastly improve the company's marketing efforts by understanding the major churn causes from customer data. The accuracy, precision, recall, f-measure, and receiving operating characteristics (ROC) area of the suggested churn prediction model are all assessed. Furthermore, via the rules produced by the attribute-selected classifier algorithm, it offers reasons behind the churning of churn consumers. (shrink)

Simulación del proceso de implantación de un sistema IT (ERP, CRM, BI,..) en una empresa.

Odată cu creșterea volumului de date pe Internet, în media socială, cloud computing, dispozitive mobile și date guvernamentale, Big Data devine în același timp o amenințare și o oportunitate în ceea ce privește gestionarea și utilizarea acestor date, menținând în același timp drepturile persoanelor implicate. În fiecare zi, folosim și generăm tone de date, alimentând bazele de date ale agențiilor guvernamentale, companiilor private și chiar cetățenilor privați. Beneficiem în multe feluri de existența și utilizarea Big Data, dar trebuie să ne (...) amintim de asemenea că „nu există nimic gratuit”. Există riscuri în utilizarea Big Data, un fel de parte întunecată. Schimbările de piață pot fi obținute prin utilizarea Big Data: în timp ce acestea pot fi pozitive pentru cineva, ele pot dăuna altcuiva. Riscurile potențiale provin și de la agențiile publice. Este clar că datele mari pot aduce beneficii cetățenilor și companiilor, dar trebuie să fie echilibrate de o conștientizare sporită a „părții întunecate” a Big Data în exploatarea noilor capacități și oportunități pe care le oferă tuturor . -/- CUPRINS -/- 1. Big Data - Definiție - Caracteristici - Clasificarea datelor mari - Arhitectura - Tehnologii - Oportunități - Provocări - Critici - - Criticile paradigmei Big Data - - Criticile modelului "V" - - Criticile de noutate - - Criticile execuției Big Data - 1.1 Viața datelor mari - - Nașterea - - Copilăria - - - Educație - - - Divertisment - - Adolescența - - - Servicii online - - - Comunicații mobile - - - Servicii de streaming - - Adulți tineri - - - Căutarea de locuri de muncă - - - Servicii bancare și asigurări - - - Utilități - - - Dating online și pornografie - - Vârsta medie - - - Servicii de sănătate - - - Aplicații pentru îngrijire și aplicații pentru sănătate și fitness - - - Căutarea de locuri de muncă - - - Dating online - - Bătrânețea - - - Îngrijirea sănătății - - Moartea - 1.2 Aplicații - - Guvern - - Dezvoltare internațională - - Fabrici - - Sănătate - - Educaţie - - Mass-media - - Asigurare - - Internetul obiectelor (IoT) - - Tehnologia informației - 1.3 Studii de caz - - Guvern - - - China - - - India - - - Israel - - - Regatul Unit - - - Statele Unite ale Americii - - Cu amănuntul - - Ştiinţă - - Sport - - Tehnologie - - Activități de cercetare - - - Prelevarea de date mari - 1.4 Agenda europeană privind societatea digitală - - Cadrul juridic - - Peisajul opiniei părților interesate - 1.5 GDPR - - Etapele procesării datelor personale - - Principiile procesării datelor - - Politica de confidențialitate și transparența - - Scopurile procesării datelor - - Confidențialitate prin design și implicită - - - Paradoxul (legal) al Big Data - - Domeniul teritorial al GDPR - - Definirea datelor mari, a datelor personale și a datelor anonime - - Etapele procesării datelor cu caracter personal - - Principii de prelucrare a datelor - - Politica de confidențialitate și Transparența - - Scopuri de prelucrare a datelor - - Confidențialitate prin design și confidențialitate în mod implicit - - Paradoxul (legal) al datelor mari 2. Analiza Big Data - 2.1 Analitica - - Analitica vs. analiză - - Aplicații ale analiticii - - - Optimizarea marketingului - - - Analiza oamenilor - - - Analiza portofoliului - - - Analitica riscurilor - - - Analitica digitală - - - Analitica securității - - - Analitica software-ului - - Provocări - - Riscuri - 2.2 Analitica predictivă - - Definiție - - Procesul de analitica predictivă - - Tipuri - - - Modele predictive - - - Modele descriptive - - - Modele de decizie - - Aplicații - - - Managementul relațiilor cu clienții analitic (CRM) - - - Protecția copilului - - - Sisteme de suport decizional clinic - - - Analiticile colecțiilor - - - Vânzări încrucișate - - - Retenția clienților - - - Marketing direct - - - Detectarea fraudelor - - - Prezicerea rezultatelor deciziilor legale - - - Previziuni privind portofoliul, produsele sau economia - - - Managementul riscului de proiect - - - Acceptanța (Underwriting) - - Tehnologia și influențele big data - - Tehnici analitice - - - Tehnici de regresie - - - - Model de regresie liniară - - - - Modele de alegere discretă - - - - Regresie logistică - - - - Regresie logistică multinomială - - - - Regresie probit - - - - Logit versus probit - - - - Modele pentru serii de timp - - - - Analiza supraviețuirii sau a duratei - - - - Arborele de clasificare și regresie (CART) - - - - Funcții spline adaptive de regresie multivariate - - - Tehnici de învățare automată - - - - Rețele neuronale - - - - Perceptron multistrat (MLP) - - - - Funcții radiale de bază - - - - Mașini cu vectori de suport - - - - Bayesiene naive - - - - Vecinul k-cel mai apropiat - - - - Modelarea predictivă geospațială - - Instrumente - - - PMML - - Critici - 2.3 Analitica prescriptivă - - Istorie - 2.4 Studiul critic al datelor - - Perspective critice - - Abordare: Pragmatismul și etica discursului 3. Etica Big Data - Datele personale ale copiilor - Rolul instituțiilor - - State naționale - - Bănci - Articole relevante de știri despre etica datelor - Legislație relevantă privind etica datelor - 3.1 Principii ale eticii Big Data - - Etica în cercetare - - Conștientizarea - - Consimţământul - - Controlul - - Transparența - - Încrederea - - Proprietatea - - Supravegherea și securitatea - - Identitatea digitală - - Realitatea ajustată - - De-anonimizarea - - Inegalitatea digitală - - Confidențialitatea - - Financiar - - - Cât de mult merită datele? - - Deschidere - 3.2 Probleme etice în cercetare - - Etica cercetării pentru cercetarea socială - - Principalele aspecte etice ale cercetării sociale - - - Intimitate - - - Consimțământ informat - - - De-identificarea - - - Inegalitate – Diviziune digitală - - Integritatea cercetării - - Probleme emergente - - Aviz legal - 3.3 Aspecte filosofice - 3.4 10 reguli de bază în lucrul cu Big Data - - Concluzie Referințe Despre autor - Nicolae Sfetcu - - De același autor - - Contact Editura - MultiMedia Publishing . 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Organizations are increasingly relying on data to inform decision making, as we progress to ever more advanced digital economy and a world where data creates competitive advantages. This may be challenging in the presence of data siloes—that is, having the data stored and managed in isolation by departments as opposed to on a centralized database. This approach leads to inefficiencies, duplications and lost opportunities for a more integrated picture. This causes challenges both in having aligned strategies across departments but it (...) is also severely limiting the capacity of organisations to actualise the transformative potential that data and data innovation has to offer their customers. Data, a separate source, is evolving into a contiguous environment that nurtures and merges its findings, overcoming its silos. Data silos pose an Albatross because they lead to an information asymmetry and have become the new norm thanks to legacy systems, the independence of individual departments and lapses in governance practices. Thus resulting in jagged data architectures where useful insights are being locked in these silos and out of reach for the relevant stake holders. Addressing these problems will require a coordinated effort that includes technological innovation and organizational change. Data lakes, data meshes and advanced analytics technologies allow businesses to aggregate heterogenous data sources to create a single source of truth across the organization. Structured and unstructured information storing in data lakes for business scalability and access Data meshes, on the other hand, emphasize decentralized ownership and domainoriented architectures so that teams can treat data like a product. Likewise, at a higher-level analytics and AI enhance the ability to converge data from various sources, automate insights and enable pre-decision making. The analysis offers a detailed overview of the problem of data silos, outlining their implications for operational efficiency, collaboration and regulatory compliance. It also suggests effective integration approaches, which include both technical fixes and cultural changes. Organizational buy-in is noted as a key enabler of success as IT hardware/software is no real remedy for the deeper root cause of silos created by human and cultural factors. To promote adoption, training programs, collaboration and communication of the advantages of integration are vital. Real-world case studies and quantitative analyses illustrate key benefits of unified data insights. For instance, 20-30% improvement in operational efficiency, decision-making agility, and better customer experience seems to be the new norm for organizations embarking on their journey with unified data platforms. With unified insights, organizations can recognize trends, anticipate changes in the market, and react accordingly, providing them with a competitive advantage as data-driven worlds continue to emerge. Unified data platforms also bring value to regulatory compliance, especially to audits before bodies such as the GDPR; they also ensure compliance with data protection laws (i.e. protecting private data from being leaked). Unified data platforms require technology and can be challenging, but we'll also see their revolutionary potential illustrated by real-world case studies. Moreover, a case in point is a multinational company that leveraged a data lake approach that led to 25% savings in recurring operational expenses and reduced time taken to drive data-based decisions. One such case study shows that silo breaking through aggregating customer relationship management (CRM) across business units resulted in 15% increased customer retention, making it clear how data synergy can translate directly to business objective. (shrink)

Customer relationship management has been signed up as an integral part of the organization and is widely implemented within Salesforce, which operates globally. Such modern CRM systems are a must-have for data governance and consent management. As such, they must follow regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the like. To remedy this problem, in this paper, we will discuss the intricacies of data governance as well as the other side of (...) obtaining consent in Salesforce, how regulatory laws play into the situation, and what challenges exist with regard to Salesforce for data governance and consent management and what does not exist to replace them in terms of data governance and consent management provided by Salesforce specifically. We then describe how we approach the IAC and describe a structured approach using automated consent tracking, role-based access control, data classification, encryption mechanisms, and audit logs. We also dive deep into how Artificial Intelligence (AI) and Machine Learning (ML) influence salesforce data governance. Industry case studies show empirical results of improvement in compliance and operational efficiency. Finally, this paper provides recommendations and future directions to those organizations trying to build resilient data governance for their Salesforce organization. (shrink)