Customer Relationship Management Research Articles

Artificial Intelligeence in Construction Industry

Abstract: The construction industry is currently experiencing an increasing skill shortage due to which, many businesses are pressurized. Artificial Intelligence is bringing transformation in construction industry through automation and in finance by implementing business models. Artificial Intelligence is providing novel solutions to the problems faced in construction industry. Artificial Intelligence when implemented in Construction Industry is expected to alter Business Models in logistics, customer relationship management, and support. Artificial Intelligence helps in providing amicable realistic solutions to situations, training, reducing injuries, and costly construction industry. Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. Implementation of artificial intelligence in the construction industry and analysis of existing technologies. Here, the research is done on the applications which are done on Artificial intelligence. The study used fuzzy logic methods and machine learning to mark visual data and analyze it for potential threats and to reduce all possible risks. This technology allows users to explore different construction plans in real time and understand the impact of key building decisions on the various factors especially cost and duration of a project. The study highlights the potential of artificial intelligence and machine learning technology in the construction industry. The implementation of the proposed approaches will improve the efficiency of construction, its safety and quality. The results of the study will be useful in the standardization of construction processes and the processing of data on construction projects.

Customer Segmentation Using the K-means Clustering Algorithm and Recency Frequency Monetary Model at Pharmaceutical Product Wholesaler

PT Kimia Farma Trading and Distribution (KFTD) is a company engaged in the distribution and trading services of Indonesian health products, on a national scale. In 2022, the company aims to increase sales to be awarded as one of the top 3 national pharmaceutical product distributors by 2024. Their current strategy is to provide customers with delayed payment permission and integrated complaint services. However, the offers and services are the same for all customers which does not consider customer track record hence it is not cost-effective. One way to increase sales is by enhancing customer satisfaction and loyalty by implementing Customer Relationship Management (CRM) strategies. Several strategies can be carried out, namely analysis of associations related to pharmaceutical products, and analysis of customer segmentation and clustering of products. The method used in this study was the K-means clustering algorithm combined with the Recency Frequency Monetary (RFM) model. Experiments showed that the optimal clustering results are 4 therefore they are categorized into 4 customer segments, namely Superstar, Golden, Typical, and Occasional Customers.

The Influence of Customer Relationship Management and Promotion from Digital Marketing on Visitor Satisfaction through Purchase Decisions as Intervening Variables at Matan Andau Agro Tourism Objects in Central Borneo - Indonesia

The Influence of Customer Relationship Management and Promotion from Digital Marketing on Visitor Satisfaction through Purchase Decisions as Intervening Variables at Matan Andau Agro Tourism Objects in Central Borneo - Indonesia

Developing Scalable APIs for Data Synchronization in Salesforce Environments

In the modern business landscape, Salesforce has become an essential platform for managing customer relationships, driving sales, and fostering business growth. However, as organizations grow and their data volumes increase, the need for efficient and scalable data synchronization across various systems becomes paramount. Developing scalable APIs for data synchronization in Salesforce environments presents a significant challenge due to the complexity of integrating multiple data sources, ensuring real-time updates, and maintaining data integrity across diverse systems. This paper explores the design and implementation of scalable APIs specifically tailored for data synchronization within Salesforce environments. It delves into the architectural considerations necessary for creating robust, high-performance APIs capable of handling large volumes of data while ensuring consistency and reliability. The discussion begins with an overview of Salesforce’s ecosystem, highlighting the importance of data synchronization in maintaining seamless operations across various departments and systems. A critical component of this study is the examination of different API design patterns that support scalability, such as RESTful services, GraphQL, and event-driven architectures. Each approach is analyzed for its suitability in handling the unique challenges of Salesforce data synchronization, such as managing API limits, optimizing data transfer, and ensuring that data synchronization processes do not disrupt ongoing business activities. The paper also explores the role of middleware solutions, like Enterprise Service Bus (ESB) and API gateways, in facilitating seamless data flow between Salesforce and other systems.

The Role of Apttus CPQ in Modern CRM Systems: Implementation Challenges and Solutions

The advent of Configure, Price, Quote (CPQ) solutions has significantly transformed the landscape of Customer Relationship Management (CRM) systems, enhancing their ability to streamline sales processes, improve accuracy, and boost overall efficiency. Apttus CPQ, a prominent player in the CPQ market, offers a robust solution that integrates seamlessly with modern CRM systems to address complex pricing and quoting challenges. This research paper explores the role of Apttus CPQ in contemporary CRM environments, focusing on its implementation challenges and potential solutions. Apttus CPQ provides an advanced framework for managing product configurations, pricing strategies, and quote generation processes. By automating these critical aspects, Apttus CPQ aims to reduce manual errors, accelerate sales cycles, and improve the accuracy of quotes. Its integration with CRM systems, such as Salesforce, leverages existing customer data to generate accurate and customized quotes, enhancing the overall sales experience. However, despite its advanced capabilities, the implementation of Apttus CPQ presents several challenges that organizations must navigate.

Digital marketing and small and medium-sized enterprises’ business performance in emerging markets

Purpose This study aims to investigate the comprehensive conceptualization how digital marketing and its adoption increase the productivity of small and medium-sized enterprises (SMEs), as well as the impact of technological orientation, customer relationship management and digital marketing on SMEs’ business performance in emerging markets (EMs). Design/methodology/approach Anchored by social network theory, 178 SMEs were conveniently drawn from the National Board for Small Scale Industries now Ghana enterprise agencies in Ghana. The hypotheses were analysed using the SPSS package tool, and structural equation modelling was used, as well. Findings This study reveals that the conceptualization and adoption of digital marketing positively affect the performance of SMEs’ business management in EMs. In addition, a positive moderating effect of dynamism is observed in the relationship between digital marketing and SMEs’ business performance. Research limitations/implications This study focuses only on SMEs from the Greater Accra and Ashanti regions of Ghana as an EM, and it proposes priorities for future research streams in both developed and emerging countries. Practical implications The findings encourage SMEs to develop quality digital marketing technologies, good customer relationships and technological orientation and customer relationship management competencies in EMs to maximise profit. Originality/value This paper fills considerable knowledge, evidence and contextual gaps in the literature on SMEs, entrepreneurship and marketing in EMs by presenting a comprehensive overview of how SMEs can use digital marketing in an EM context to achieve the following: customer acquisitions, satisfaction and retention; increased profitability; quality service delivery; value creation; and cost reductions.

Exploring customer retention dynamics: A comparative investigation of factors affecting customer retention in the banking sector using mediation-moderation approach

The purpose of this research is to explore the impact of service quality, customer trust, and cultural disparities on customer satisfaction within the banking sector. Additionally, the study examined the mediating effect of customer satisfaction and the moderating effect of financial technology. Data for this investigation were gathered from customers utilizing services offered by public banks in Pakistan and China. The analysis was conducted using the Smart-PLS software, with 281 samples from Pakistan and 312 samples from China being included in the study. Results show that service quality, customer trust, and cultural differences positively affect customer satisfaction in the context of Pakistan and China. Results also reveal that service quality and customer trust have a positive effect on customer retention behavior in China, but customer trust has an insignificant impact on customer retention behavior in Pakistan. Analysis specifies that customer satisfaction positively mediated the relationship between service quality, customer trust, cultural differences, and customer retention behavior in Pakistan and China. More importantly, financial technology moderated the relationship between customer satisfaction and customer retention behavior, but it was insignificant in the context of China and Pakistan. The study seeks to provide significant insights for strategic decision-making and improve customer relationship management techniques in the dynamic field of financial services by including mediating and moderating elements.

Technological Integration in CRM: A Case Study of Madurai's Hospitality Sector

This study examines the role of technological integration in Customer Relationship Management (CRM) within Madurai's hospitality sector, focusing on how digital tools and software solutions enhance customer engagement and service delivery. As the tourism and hospitality industry in Madurai continues to grow, driven by its cultural significance and heritage, effective CRM practices have become essential for maintaining competitive advantage. This case study investigates how hotels, restaurants, and tour operators in Madurai leverage CRM technologies to streamline operations, personalize guest experiences, and foster long-term relationships. The research analyses the adoption of CRM software, mobile applications, and data analytics in enhancing customer satisfaction, increasing retention rates, and improving operational efficiency. Findings reveal that while the use of technology in CRM has significantly improved service standards and customer interactions, challenges such as system integration, staff training, and cost constraints remain. This study offers insights into the potential of technological CRM solutions to transform the hospitality landscape in Madurai, contributing to both academic literature and practical applications in the tourism and hospitality industries.

Parameters Identification Related to Design of Customer Relationship Management Structure for Health Tourism Facilitators in Iran: A Case Study of Iran

The Health Tourism Industry is burgeoning within Iran, presenting promising opportunities. Despite its relative infancy in the country, this sector predominantly comprises Small and Medium Enterprises (SMEs). These entities encounter a spectrum of challenges as they navigate the path to growth, with Customer Relationship Management (CRM) emerging as a prominent concern. Effective management of customer relations necessitates a comprehensive understanding of their diverse needs and challenges, spanning from initial engagement to the culmination of the relationship. Designing an effective CRM structure requires a meticulous exploration of these facets throughout the customer journey. In our study, we conducted a literature review to explore these challenges and employed a qualitative approach, conducting semi-structured interviews with seven Iranian health tourism facilitators. Through framework analysis, we identified key insights into CRM challenges and strategies. Our thematic analysis revealed seven pivotal themes germane to CRM within Iranian health tourism facilitation: Initial customer engagement; Transformation of information between customers and health tourism facilitator; Data assessment and Challenges in information exchange; Perception of service quality factors; Cultural and national considerations; Monitoring and oversight; and Stress mitigation strategies Keywords: customer relationship management, health tourism, health tourism facilitators, health care, customer journey

An Exploratory Study of the Use of ICT for Control Measures in Organization Across Industries

In business management, a control function refers to the process of monitoring, measuring, and regulating various aspects of an organization's activities to ensure that they align with the established goals and objectives. This function is crucial for achieving efficiency, effectiveness, and accountability within an organization. Information and Communication Technology (ICT) has had a profound impact on the control functions of various industries. These control functions encompass a range of activities including monitoring, automation, decision-making, and overall management of industrial processes. For the sake the research paper and better understanding for the readers we have divided Control Function into 5 components that are – Quality Control, Feedback, Finance, Supply Chain,Market and Competitor Analysis and Customer Relationship Management The paper will attempt to explain how each of the given components are impacted by ICT and provide a Real-life industry example for each.

The Use of E-CRM as a Means of Selling Groceries

Customer Relationship Management (CRM) is a type of management regarding the management of a company with its customers to improve relationships with customers to maximize company growth. To implement Electronic-Customer Relationship Management (E-CRM), the role of information technology and human resources of the company is needed. E-CRM can make it easier for customers to get the necessary information from the company. Wholesale Berkat Doa is one of the basic food distributors that sells various kinds of basic necessities such as rice, oil and sugar which are the most demanded needs. To see these basic food products, customers must come directly to the store because there is no intermediary media to convey and provide product information to customers. The purpose of this research is to create an E-CRM system so that sales at Wholesale Blessing Doa can be done online. By implementing the E-CRM system, it can help Wholesir Berkat Doa to market and sell basic food products to customers. Customers know product information in detail and with CRM features namely members, discounts, promos, live chat, points, vouchers and reviews can maintain relationships with new and old customers which makes loyal customers to keep shopping at Wholesale Berkat Doa

Influence of Big Data Analytics on Decision-Making Processes in Financial Firms in South Africa

Purpose: The aim of the study was to assess the influence of big data analytics on decision-making processes in financial firms in South Africa. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: By harnessing vast volumes of structured and unstructured data, these firms can derive valuable insights into market trends, customer behavior, and risk assessment with unprecedented accuracy and speed. This capability enables more informed and data-driven decision-making across various facets of financial operations, including investment strategies, risk management, and customer relationship management. Moreover, big data analytics facilitates the identification of previously hidden patterns and correlations within financial data, enhancing predictive modeling and forecasting capabilities. This proactive approach allows firms to anticipate market shifts, optimize portfolio performance, and mitigate potential risks effectively. Additionally, the adoption of advanced analytics techniques, such as machine learning and artificial intelligence, further enhances decision-making by automating processes and refining predictive accuracy. Implications to Theory, Practice and Policy: Diffusion of innovation theory, technology acceptance model and resource-based view may be used to anchor future studies on assessing influence of big data analytics on decision-making processes in financial firms in South Africa. In practice, financial firms should establish robust data governance frameworks to ensure data accuracy, privacy, and security. Policymakers should develop and enforce regulatory frameworks that support the ethical and effective use of BDA in financial firms.

Role of Machine Learning Algorithms in Enhancing Customer Relationship Management Systems in Rwanda

Purpose: The aim of the study was to assess the role of machine learning algorithms in enhancing customer relationship management systems in Rwanda. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Algorithms analyze vast amounts of data, allowing businesses to personalize interactions and anticipate customer needs more effectively. For instance, predictive analytics can forecast customer churn, prompting proactive retention strategies. Moreover, sentiment analysis tools gauge customer emotions from feedback, enabling tailored responses and improved service delivery. Machine learning also automates routine tasks like email marketing segmentation, optimizing resource allocation and enhancing overall efficiency. Consequently, CRM systems empowered by machine learning algorithms foster stronger customer relationships, driving business growth through enhanced customer satisfaction and loyalty. Implications to Theory, Practice and Policy: Technology acceptance model (TAM), resource-based view and diffusion of innovations theory may be used to anchor future studies on assessing the role of machine learning algorithms in enhancing customer relationship management systems in Rwanda. Businesses should adopt advanced ML techniques, such as Long Short-Term Memory (LSTM) models and ensemble learning, to enhance the accuracy of customer segmentation and churn prediction, leading to more personalized marketing strategies and improved customer retention. Policymakers should develop and enforce stringent data privacy and security regulations to protect customer data used in ML-enhanced CRM systems.

The Influence of Corporate Social Responsibility and Customer Retention on Customer Relationship Management Performance with the Mediating Effect of Customer Trust in SMEs of Ningxia Province, China

In recent years, e-commerce has experienced rapid expansion and developed as the mainstream business practice in small and medium-sized enterprises (SMEs) in developing areas of China. There are a variety of channels for consumers to purchase from. Therefore, maintaining customers is increasingly important. In the meantime, companies expect to gain more significant insights into their consumers’ demands to earn customer trust, thus achieving customer relationship management (CRM) performance. This study develops based on trust theory and consists of four latent variables: corporate social responsibility (CSR), customer retention, customer trust, and customer relationship management performance. The current study used probability and random sampling techniques. It conducted the questionnaire survey to collect data form managers of SMEs in Ningxia province of China. The Partial least square structural equation modeling (PLS-SEM) technique was used for this study. As a result, a total of 150 respondents were usable for these questionnaires. The study revealed that corporate social responsibility and customer retention have a positive effect on customer relationship management performance. Moreover, customer trust has been examined that it had a positive effect on customer relationship management performance. In addition, customer trust was discovered as a partial mediation between the relationship of corporate social responsibility, customer retention, and customer relationship management performance. Furthermore, based on the samples analyzed, the proposed model seems to be fitted considerably well. Therefore, this study intends to contribute to a better understanding of factors influencing customer relationship management performance in Chinese SMEs, thereby providing companies with practical ideas to improve overall performance.

The Role of Cloud Computing in Transforming Sales Force Customer Engagement Strategies

This research paper explores the transformative role of cloud computing in sales force management, focusing on its impact on customer engagement strategies. It examines the benefits of cloud-based Customer Relationship Management (CRM) systems, Sales Force Automation (SFA) tools, and AI-driven analytics in enhancing sales productivity, customer satisfaction, and operational efficiency. Through a detailed analysis of industry case studies, including Salesforce, IBM, Siemens, and Amazon, the paper highlights the significant improvements achieved in sales performance and customer interaction through cloud adoption. The study also addresses the challenges and risks associated with cloud implementation, such as technical barriers, financial constraints, and resistance to change. Future trends, including AI-driven sales insights, multi-cloud strategies, and the integration of blockchain technology, are discussed to provide a forward-looking perspective on how cloud computing will continue to evolve in the sales domain. This research underscores the crucial role of cloud computing in modernizing sales force management and achieving competitive advantage in a rapidly digitalizing business environment.

Pengaruh Strategi Bauran Pemasaran Digital Terhadap Kinerja Pemasaran melalui Manajemen Hubungan Pelanggan di Objek Wisata Pantai Randusanga Indah Brebes

This study aims to determine the effect of digital marketing mix strategy on marketing performance through customer relationship management at Randusanga Indah Brebes Beach tourist attraction. Using quantitative and qualitative approaches, this research sample involved 203 respondents who were beach visitors who were taken using purposive sampling techniques. Data analysis was conducted using the Structural Equation Modeling (SEM) model with the AMOS program. The results showed that the digital marketing mix strategy had a significant effect on customer relationship management with a CR value of 11.252 (CR ≥1.96) and a probability value ≤ 0.05. However, the digital marketing mix strategy has no significant effect on marketing performance with a CR value of -,434 (CR ≥1.96) and a probability value of 0.664 (p ≤ 0.05). Similarly, customer relationship management also has no significant effect on marketing performance with a value of CR 1,261 (CR ≥1.96) and a probability value of 0.207 (p ≤ 0.05).

Analysis of Customer Relationship Management at Animation Studio - PT Jiwa Muda Cipta Indonesia in Yogyakarta

The role and function of Public Relations (PR) in carrying out tasks in the marketing sector of a digital service company, namely Animation Studio. Nowadays, managing relationships with customers is more familiarly known as Customer Relationship Management (CRM). In CRM management, a series of flows have been arranged as mentioned by Buttle, namely analysis, resource development and implementation. The data obtained in this research is the result of observation, documentation and interviews with Marketing and CEO while carrying out research at the Animation Studio. It was found that analyzes covering portfolio and customer intimacy had been run on a strong basis and implemented quite well. Likewise, the development of resources that have been designed by the CEO to develop the network and add value propositions has been carried out systematically according to procedures. As for the implementation of CRM in Animation Studio, although it is quite good, it still needs to be developed further in terms of the process to further perfect CRM within the company.

Addressing challenges in customer relations management for creative industries: Innovative solutions and strategies

Addressing challenges in customer relations management for creative industries: Innovative solutions and strategies

Identifying obstacles to evaluating business intelligence in Micro-Small Apparel Enterprises: a case study in Durban, South Africa

The escalating financial burdens faced by the Small Medium and Micro Enterprise (SMME) sector necessitate a perpetual pursuit of enhanced managerial efficacy. For enhanced financial management, client relationship management and inventory control, it is necessary for businesses to utilise various technologies and methodologies. One approach involves the utilisation of business analytical technologies, such as Business Intelligence (BI). Business Intelligence (BI) serves as a valuable tool for enterprises, aiding in the examination and interpretation of data to facilitate informed decision-making processes aimed at enhancing overall business efficacy. The eThekwini region encompasses a significant presence of micro-small enterprises within the apparel manufacturing and retail sector. The primary aim of this research was to identify and analyse the many issues that hinder the evaluation of business intelligence (BI) in micro-small apparel enterprises located in Durban, a city in Kwa-Zulu Natal, South Africa. A cross-sectional quantitative study was undertaken to examine a cohort of 161 small apparel business owners. The participants were chosen through the utilisation of a judgemental sampling technique. The data was gathered through the utilisation of anonymous questionnaires. The data was analysed by utilising multiple linear regression analysis to determine the characteristics that hinder the evaluation of business intelligence (BI) in the small apparel industry. The study employs the Technology-Organisation-Environment (TOE) framework as its conceptual framework. The researcher identified several obstacles that hinder the evaluation of business intelligence in micro-small textile enterprises in South Africa. These factors include perceived relative advantage, cost, organisational data environment, organizational decision-making culture, and external support. However, there are numerous governmental institutions that are intended to provide support for micro-small companies. Therefore, it is recommended that these institutions establish training initiatives aimed at educating apparel SMMEs on BI. The implementation of target-driven training has the potential to significantly contribute to the achievement of vision 2030 for fostering the growth of small, medium, and micro enterprises (SMMEs) to enhance the South African economy.

The Emerging Challenges of Customer Relationship Management with Customer Data Platforms (CDP): Constraints and Perspectives

Customers today are increasingly demanding a personalized shopping experience, coupled with stringent data security measures and prompt responses. As the landscape of online privacy evolves, particularly with the anticipated sunset of third-party cookies by 2024, businesses face a critical imperative to revamp their customer data management strategies. The emergence of Customer Data Platforms (CDPs) stands out as a pivotal solution in this evolving ecosystem. This article undertakes a detailed critique of CDPs, starting with insights gathered from both users and industry experts, and subsequently examining consumer perceptions and behaviors in the digital realm. At the heart of contemporary consumer expectations lies the desire for tailor-made interactions that reflect their preferences and behaviors. This demand necessitates robust data management tools capable of aggregating, analyzing, and activating customer data across multiple touchpoints. CDPs have emerged as a central tool in this endeavor, offering businesses a unified platform to integrate disparate data sources and derive actionable insights in real-time. By leveraging comprehensive customer profiles built from first-party data, CDPs enable businesses to deliver personalized experiences that foster customer loyalty and drive revenue growth. Moreover, the impending demise of third-party cookies, compounded by stringent data protection regulations like GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act), underscores the urgency for businesses to adopt privacy-centric data practices. CDPs play a crucial role in this paradigm shift by empowering businesses to ethically collect and utilize customer data, thereby enhancing transparency and trust. However, challenges persist, including the complexity of integrating CDPs into existing infrastructures and ensuring compliance with evolving regulatory frameworks. From a consumer standpoint, attitudes towards data privacy are evolving, with an increasing emphasis on transparency and control over personal information. Consumers are more inclined to engage with brands that demonstrate a commitment to data security and ethical data usage practices. This shift necessitates a nuanced approach from businesses using CDPs, emphasizing not only personalization but also data protection and consent management. While CDPs offer substantial benefits in navigating the complexities of modern data management and meeting consumer expectations for personalized experiences, their successful implementation hinges on addressing technical, regulatory, and ethical considerations. By doing so, businesses can not only adapt to the evolving landscape of digital privacy but also foster enduring customer relationships grounded in trust and mutual value.