Hybrid CRM Deployment Model

Due to the rapid growth in the electronic business, information technology has become very necessary for building up efficiency and effective transactions among organizations. Consequently, Cloud Computing (CC) becomes a very important area to achieve the organization's performance. The process of integration between Cloud Computing (CC) and the Customer Relationship Management (CRM) is a new research area. Therefore, scientific research and literature review related to Cloud Computing and CRM processes are limited. Yet, the impact of Cloud Computing on CRM processes remains under exploration and investigation. To this effect, this paper takes on a holistic approach that examines the combined effects of Cloud Computing Benefits (cost and ease of use) and CRM processes (customer acquisition, customer retention and customer expansion) on organization's performance. It also presents a conceptual framework for Cloud Computing and CRM processes, based on the analysis of various models presented in Cloud Computing and CRM processes. The main emphasis is focused on the concept of Cloud Computing Benefits (cost and ease of use) and CRM processes (customer acquisition, customer retention and customer expansion) by examining some reasons that make the organization interested in using this modern technology from one hand and how Cloud Computing can encourage organizations to implement CRM to improve their performance on the other. Therefore, this paper contributes to develop three models: Cloud Computing Benefits, CRM process, and integration between the Cloud Computing and CRM process to improve organization performance model. Also, it describes more valid factors to identify how an organization deals with its performance in the future by providing an advice for the Information Technology (IT) industry as how an analytical integration between Cloud Computing Benefits and CRM process improves organization's performance – something that should be taken into account in developing countries to attain a competitive advantage. This study is divided in three sections: Literature Review, Research Model, and Conclusion.

Due to the rapid growth in the electronic business, information technology has become necessary for building efficiency and effective transactions among organizations. Consequently, Cloud Computing (CC) becomes a very important area to achieve the organization's performance. The process of integration between Cloud Computing (CC) and the Customer Relationship Management (CRM) is a new research area. Therefore, scientific research and literature review related to Cloud Computing and CRM processes are limited. This paper takes a holistic approach that examines the combined effects of Cloud Computing Benefits (cost and ease of use) and CRM processes (customer acquisition, customer retention and customer expansion) on organization's performance. It also presents a conceptual framework for Cloud Computing and CRM processes, based on the analysis of various models presented in Cloud Computing and CRM processes. The main emphasis is focused on the concept of Cloud Computing Benefits and CRM processes by examining some reasons that make the organization interested in using this modern technology from one hand and how Cloud Computing can encourage organizations to implement CRM to improve their performance on the other. This paper contributes to develop three models: Cloud Computing Benefits, CRM process, and integration between the Cloud Computing and CRM process to improve organization performance model. Also, it describes more valid factors to identify how an organization deals with its performance in the future by providing an advice for the Information Technology (IT) industry as how an analytical integration between Cloud Computing Benefits and CRM process improves organization's performance – something that should be taken into account in developing countries to attain a competitive advantage. This study is divided in three sections: Literature Review, Research Model, and Conclusion.

Customer Relationship Management (CRM) systems are essential for businesses to manage customer interactions, enhance engagement, and drive customer satisfaction. Traditional CRM solutions face challenges such as data security risks, inefficiencies in processing customer data, and limitations in providing personalized experiences. Emerging technologies like blockchain and machine learning offer promising solutions to address these challenges. Blockchain enhances CRM by providing decentralized, secure, and tamper-proof data storage, ensuring transparency and reducing the risk of fraud. Machine learning improves CRM by enabling predictive analytics, customer segmentation, and automation of customer interactions. This paper provides a comprehensive survey of existing techniques that integrate blockchain and machine learning in CRM, analyzing their impact on security, efficiency, and customer engagement. The study compares various approaches, highlighting their advantages and limitations while assessing their practical applications in real-world CRM systems. Additionally, this paper examines how these technologies enhance decision-making, optimize customer management strategies, and ensure compliance with data protection regulations. The findings suggest that while blockchain strengthens data security and trust, machine learning enhances automation and personalization, making CRM systems more intelligent and efficient. This survey provides insights into the evolving landscape of CRM technologies and offers a comparative analysis of how blockchain and machine learning are shaping the future of customer relationship management. By reviewing current methodologies and their effectiveness, this paper aims to guide businesses and researchers in understanding the potential and challenges of these technologies in CRM applications.

This research paper delves into the integration of Artificial Intelligence (AI) in Customer Relationship Management (CRM) systems within Enterprise Resource Planning (ERP) frameworks, with a focus on personalized interactions, predictive modeling, and service automation. The primary objective was to empirically investigate how AI enhancements in CRM functionalities can contribute to more efficient and effective customer relationship management within ERP systems. A quantitative research design was adopted, utilizing a structured questionnaire distributed among CRM managers and IT professionals across various industries, with the data analyzed using the Statistical Package for the Social Sciences (SPSS). Key findings from the study reveal significant positive impacts of AI integration on CRM functionalities, notably in personalized customer interactions, predictive modeling accuracy, and service automation efficiency. These enhancements were found to contribute to improved customer satisfaction and operational efficiency, suggesting that AI - driven CRM strategies within ERP systems offer substantial benefits to organizations. The research fills a critical gap in existing literature by providing empirical evidence of the specific benefits of AI in CRM and underscores the strategic value of AI integration in enhancing CRM functionalities. The broader implications of this study highlight the transformative potential of AI in CRM, encouraging organizations to leverage AI technologies to gain a competitive edge in customer relationship management.

This work describes the main characteristics of Customer Relationship Management (CRM) and the new environment where the CRM has been in use from for several years now: Cloud Computing. In the rest of the work the specific features of cloud CRM are described, trends and predictions in its usage, a new trend in development of cloud CRM: the binding thread with social networking, weakness and selection strategy, and the first benchmarks on many of different configurations available to cloud consumers.

This study aims to determine the effect of Customer Relationship Management (CRM) on customer loyalty at PT Menara Agung in West Sumatra. The research method used is a quantitative approach with data collection techniques using direct telephone interviews with 100 customers who have interacted with the dealer CRM system to obtain direct information and assessments from customers. In an effort to measure the effect of Customer Relationship Management (CRM) on customer loyalty, data analysis was carried out using a simple linear regression method. The results of the study showed that CRM has a significant positive effect on customer loyalty, with a correlation coefficient of 0.654, this means that the correlation relationship between CRM and customer loyalty is in the strong category. In the determination correlation, the figure was 0.428 which means 42.8%, which means that customer loyalty is influenced by the effectiveness of CRM implementation. This study emphasizes the importance of an effective CRM strategy in increasing customer loyalty in the automotive industry, especially at PT Menara Agung, West Sumatra. The recommendation from this study is for PT Menara Agung to continue to strengthen and optimize its CRM strategy to maintain and increase customer loyalty.

PurposeDue to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.Design/methodology/approachA total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.FindingsOutcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.Originality/valueTo the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.

An Empirical Investigation into the Effects of Customer Relationship Management on Bank Performance in Nigeria

The service industry is highly competitive. In order to provide value-added services, many companies rely on customers as powerful tools for solidifying company performance through discourse, participation, and social presence. In this Research, the main purpose was to study the effect of Customer Relationship Management on customer behaviors with the mediating role of customer value creation in the insurance industry (Case Study: Karafarin Insurance). The research method employed in this study was a descriptive-survey, and the statistical population consisted of 800 employees from branches of Karafarin Insurance. A sample of 260 individuals was selected as the statistical sample using the simple random sampling method, with appropriate allocation determined by referring to the Morgan Table. For data collection, the Customer Relationship Management questionnaire by Sin et al. [1], the Customer Value Creation questionnaire by Kalra & Kalra (2010), and the Consumer Behavior questionnaire by Lerman (2006) were employed. Data was analyzed using descriptive and inferential statistics, and utilizing the SPSS and PLS softwires. The analysis showed that Customer Relationship Management and its components (focusing on key customers, organizational Customer Relationship Management, knowledge management, technology-based Customer Relationship Management) have an effect on customer behaviors and customer value creation. The Findings demonstrate that customer value creation have effect on customer behaviors. The Sobel test results also indicate that customer value creation plays a mediating role between Customer Relationship Management and customer behaviors.

The purpose of this study is to describe: (1) Customer Relationship Management (CRM) at Andalas University Library; (2) user loyalty at Andalas University Library; (3) the effect of Customer Relationship Management (CRM) on user loyalty at Andalas University Library. This type of research is quantitative with a descriptive method. The population in this study were all visitors to Andalas University Library as of 2023, totaling 140,928 and a sample of 100 people. Sampling using simple random sampling technique. Data analysis was carried out through the stages of examination, tabulation, and drawing conclusions. The results of the study indicate that: (1) the implementation of Customer Relationship Management (CRM) at Andalas University Library has been implemented well, this can be seen from the responses given by respondents who stated that the completeness of technology-based services at Andalas University Library is relatively complete and makes it easier for users to get the books or references they need. In addition, the service process involving officers and users can be carried out quickly and accurately, in addition, the Andalas University library has also been supported by officers who are creative, responsive and able to serve the needs of users; (2) the level of loyalty of users who visit the Andalas University library is also relatively high, this can be seen from the existence of repeat purchases that occur repeatedly, in addition, users have a high level of retention, this can be seen from their actions to always want to visit the library almost every day, in addition, users are also concluded to have a high level of referrals, this can be seen from the number of respondents who choose to agree to invite friends to come and read books at the Andalas University Library; (3) according to the results of the hypothesis testing through the t-statistic test, it was found that Customer Relationship Management (CRM) has a positive and significant effect on user loyalty in visiting the Andalas University Library. These findings indicate that the better the implementation of Customer Relationship Management (CRM) felt by users, the more their loyalty will increase. The results obtained at the first hypothesis testing stage are in line with the proposed hypothesis, so the first hypothesis is accepted.

Cloud computing is a state-of-the-art Internet technology being recently adapted by enterprises. The cloud computing models are implemented by business to improve existing practices. With improvement in the standards of the Web and affordability of mobile devises, the customer has accepted the online way of shopping. Cloud computing has been extensively used to deliver e-commerce, Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP). E-commerce models have undergone considerable changes in order to attract customers online. This chapter showcases the requirement of e-commerce model to integrate cloud computing technology. This chapter puts forward cloud computing applications for E-commerce, CRM and ERP by describing the significant characteristics of the cloud. For enterprises to bring into play cloud based e-commerce, CRM and ERP, certain significant issues need to be handled. These issues are the points of discussion in the chapter. In addition, the chapter introduces big data framework for building efficient e-commerce framework.

With the rapid development of modern economy, which regards satisfying customer demands as its basis, enterprises urgently need to operate effective Customer Relationship Management (CRM) to gain their market and increase their profit or competitive power. To provide enterprises managers with valuable views on customer management, in this paper we discussed on operation design of CRM, and proposed six operation tactics of CRM, including senior enterprise leaders support CRM application, integrate CRM strategies with corporate culture, customer-oriented management system, train staff to learn CRM knowledge, enhance data quality of CRM and protect customer information privacy. The proposed tactics will be helpful for practical operation of customer management system effectively.

This study is aiming at determining the effect of customer relationship management on the customer loyalty, the effect of customer relationship management on brand trust, the effect of brand trust on customer loyalty and the mediating effect of brand trust on the relationship between customer relationship management and customer loyalty. This research is explanatory research with the population of undergraduate students (S1) in five faculties at Budi Luhur University, Jakarta who are at least sophomores. Data collected using questionnaire. The research sample is using purposive sampling with total of 110 respondents. The data were analyzed by path analysis using SPSS. Based on the results of research it can be seen that customer relationship management did not affect customer loyalty, customer relationship management did not affect brand trust, brand trust affected customer loyalty, and brand trust did not mediate the effect of customer relationship management to customer loyalty.

Background: Decline in epidemiology cohort response rates has been documented over decades, with precipitous declines in recent years. Incentives and repeated contact attempts have been shown to increase retention to varying degrees, but the effects of the different types of incentives and methods of contact—details necessary for reliable replication—remain poorly understood. Numerous factors related to study implementation and participant characteristics likely affect response rates, but few cohort studies have published the detailed empirical data that would be necessary to assess their effect. The small number of cohort studies that have published analyses of their recruitment protocols raises the question of how many studies are systematically and rigorously examining their methods. A 2011 review suggested that cohort studies may be less likely to engage in these activities due to concerns of risk to participant loyalty and the cost of assessment. Epidemiology cohorts often involve many concurrent activities and overlapping projects, which may also contribute to the complexity of the task. Considering the long duration of cohort studies, some may perceive that study staff can accurately intuit best practices. However, these challenges are not unique to epidemiology cohorts. The private sector is also concerned with attracting and retaining customers, and as such, companies have developed tools that enable rapid, low-cost reporting on their methods. In the field of marketing, customer relationship management (CRM) systems facilitate both the desired outcome (a customer buying a product) and the collection of data to identify factors that influenced the outcome. Aspects of these targeted marketing approaches and their related software tools provide both a model and a means by which epidemiology cohorts can better understand the constellation of factors that affect attrition among their own populations. Methods: The California Teachers Study (CTS) is a large prospective cancer epidemiology cohort that began in 1995. Since 2013, the CTS has used a commercially available CRM platform, modified with a variety of native applications (apps) and integrations, to manage participant recruitment and data collection for multiple projects. To manage a large-scale biobanking project and multiple tissue collection projects, we began with the platform’s standard contact data management and activity tracking features. We added an app for geolocation fieldwork management and a custom mobile app for surveys and biospecimen chain-of-custody tracking. To manage two follow-up questionnaires, we used available integrations for survey development, email marketing automation, a cloud-based call center with automated activity logging, and a web form for participants to submit information securely from our study website. Central features of all projects have included native reports and dashboards, workflow automations that reduce data entry, and data security measures. Results: The CRM platform has scaled to meet the needs of multiple concurrent projects with highly varied study designs and staffing requirements. By conducting our recruitment activities within the CRM, each interaction with the system (an incoming call from a participant, a blood collection, an automated survey reminder) passively generates useful metadata. These metadata, in concert with structured and unstructured data from participants and staff, enable timely monitoring and retrospective analysis using native reporting tools within the system. The ability to view and analyze clean data from the outset of each project revealed key—and sometimes unexpected—factors that were influencing response. Analysis of data across projects has revealed that characteristics of participants, staff, protocol decisions, technology, and equipment all influence outcomes in distinct ways. Conclusion: Existing commercially available tools, such as a CRM system, can be readily configured to meet the specific research, process, and security requirements of population sciences research. In the CTS, using a CRM system helped reveal that different factors affected participation differently, even within the same project. This presentation will discuss these factors, the approaches studies can use to collect data about these factors, and lessons learned about ways to further improve response rates. Broader adoption of CRM tools could enable the type of data collection and analysis necessary to more precisely define the factors that affect participation and develop more targeted and successful recruitment methods. Citation Format: Jennifer Benbow. Data-driven recruitment: Implementation of digital marketing strategies for improved participant response rates and retention [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA04.

Customers, being important assets to an enterprise, directly relate to the latter’s profitability and survival. Customers buy products to generate revenue. Their feedbacks also promote the improvement of products and drive an enterprise to develop forward. With or without an information system, good CRM (customer relationship management) is extremely important for an enterprise to achieve its profit targets. Though a non-profit organization (NPO) does not pursue profits, it has service objects, concrete products or services for achieving its vision, or supporters of its vision. The spirit and practice of making every effort possible to know their customers which is usually adopted by an enterprise in order to achieve its business objectives could also be seen to exist in non-profit organizations. It’s just such spirit and practice that is slightly different in form or the goal. If adjusted, the application of CRM in enterprises could also effectively help non-profit organizations to understand more clearly the practice they have to take in order to achieve their visions and understand the objects of their services or supporters. Exampled with the church, this study explores whether CRM helps the church and how should churches apply CRM. Leaders at all levels in the church pastoral relationship could be compared to managers at all levels in a corporate organization, while PRM (pastoral relationship management) applied to churches via CRM could generate specific impacts on group pastoral care, group development strategies, equipment of true believers, business as mission, family as mission, church planting and preaching.