Customer Relationship Management Research Articles

Boosting customer loyalty through marketing distribution, customer experience management and customer relationship management

This study aims to analyze the effect of marketing distribution on customer experience management (CEM), customer relationship management (CRM), and customer loyalty. This study also analyzes the effect of CEM and CRM on customer loyalty. This study uses quantitative methods with a population of all BPRS (Sharia People's Financing Bank) customers in the Cirebon area, West Java. The sample in this study was taken through the purposive sampling method regarding sampling criteria tailored to the research objectives. From the sampling process, we obtained 185 respondents who met the criteria and became the research sample. Data were collected through the distribution of questionnaires and analyzed using a structural equation model with Smart-PLS 3. The analysis shows that marketing distribution positively affects customer experience management, customer relationship management and customer loyalty. Furthermore, customer experience management and customer relationship management are also proven to positively affect customer loyalty. Conclusion: It is concluded that marketing distribution has an important role in improving CEM, CRM and customer loyalty. This research proves that the implementation of good marketing distribution can encourage consumer interest in the company's products and services and build customer loyalty.

Harnessing the Power of AI in Salesforce: An Empirical Study on Enhanced Data Insights and Organizational Efficiency

Abstract: This article examines the integration of Artificial Intelligence (AI) in Salesforce platforms to enhance business analytics and decision-making processes. We explore how AI-powered solutions are revolutionizing data analysis, providing organizations with actionable insights, and improving market responsiveness. The article investigates key AI techniques implemented in Salesforce, including machine learning algorithms for pattern recognition and natural language processing for unstructured data analysis. We analyze the impact of these technologies on identifying trends, forecasting, threat detection, and opportunity identification for sustainable growth. Through case studies and empirical analysis, we demonstrate the effectiveness of AI-driven Salesforce solutions in streamlining data processing, enabling real-time market adaptation, and enhancing organizational efficiency. The article also addresses the technological infrastructure supporting these AI solutions, discussing cloud-based computing resources, integration challenges, and data security considerations. Our findings suggest that AIpowered Salesforce solutions significantly improve business analytics capabilities, allowing companies to make more informed decisions and maintain a competitive edge in rapidly evolving markets. This article contributes to the growing body of knowledge on AI applications in customer relationship management and business intelligence systems

Developing and validating an instrument for assessing E-entrepreneurial idea feasibility

Despite the critical importance of e-entrepreneurship idea generation for e-venture success, there remains a significant lack of valid and reliable instruments to evaluate the feasibility of e-entrepreneurial ideas proposed by undergraduates during entrepreneurship learning. This study addresses this gap by creating and validating a scale based on the Business Model Canvas with a sample of 299 participants. Following established scale development procedures, a 13-item scale with four factors emerged: value creation and customer relationship management, cost structure, business viability, and customer segmentation and personalization. The scale demonstrates satisfactory internal consistency and criterion-related validity, providing a reliable tool for assessing e-entrepreneurial idea feasibility in higher education, benefiting both educators and researchers.

Forecasting financial stability in SMEs: A comprehensive analysis of strategic budgeting and revenue management

Small and medium-sized enterprises (SMEs) are vital contributors to global economies, but they often face unique financial challenges that threaten their long-term stability. This review presents a comprehensive analysis of forecasting financial stability in SMEs, focusing on strategic budgeting and revenue management as key pillars. Strategic budgeting plays a crucial role in aligning financial plans with business goals, managing risks, and adapting to market changes. Techniques such as zero-based budgeting, activity-based budgeting, and rolling budgets offer SMEs flexibility in allocating resources and ensuring optimal cash flow management. Meanwhile, effective revenue management involves the use of pricing strategies, sales channel diversification, and customer segmentation to optimize revenue streams and improve profitability. The interplay between strategic budgeting and revenue management is critical for creating dynamic forecasting models that help SMEs anticipate financial challenges and make informed decisions. By integrating both strategies, SMEs can better manage risks, enhance financial predictability, and achieve long-term sustainability. This review also explores the role of technological tools, such as financial software and predictive analytics, in supporting financial decision-making processes. Tools like customer relationship management (CRM) systems and AI-driven forecasting platforms enable SMEs to optimize revenue potential and refine budgetary practices. The review provides recommendations for SMEs to implement best practices in financial planning, suggesting regular budget reviews and proactive revenue management strategies to respond to market fluctuations. By leveraging strategic budgeting and revenue management, SMEs can enhance their financial resilience and improve their capacity to navigate economic uncertainties. The review concludes with insights into emerging trends in financial forecasting, emphasizing the importance of continuous adaptation to maintain financial stability.

Customer Segmentation by using Annual E-Invoice Data

As businesses navigate the digital landscape, the proliferation of electronic transactions has led to an abundance of valuable data that can be harnessed for strategic decision-making. This study explores the application of CRM and RFM analysis for customer profiling and segmentation, utilizing e-invoice data as a rich source of information. By leveraging these advanced statistical techniques, the research aims to uncover hidden patterns within electronic transaction records, allowing for the identification of distinct customer segments based on their purchasing behavior. The methodology involved collecting and pre-processing one year of e-invoice data from Fit IT Company, followed by applying statistical models to uncover underlying structures and relationships. Furthermore, the research examines the implications of customer segmentation on marketing strategies, customer relationship management, and personalized service offerings. CRM and RFM analyses were performed on the annual sales data obtained as a result of e-invoice usage service to customers. When the results of the analysis were analyzed, the number of transactions belonging to the sender, recipient, and parties in the top 10 every month were extracted. It has been demonstrated that customer segmentation can be conducted more comprehensively by using CRM and RFM analyses together. While CRM analysis focuses on transaction volume and customer relationships, RFM analysis provides a more detailed perspective on customer behavior by evaluating purchase frequency, recency, and monetary value. In the study, by analyzing e-invoice data through these two methods, the most valuable customer groups were identified, and how strategic marketing approaches can be developed for these groups was illustrated. The combined use of CRM and RFM analyses allows for more accurate customer segmentation based on both transaction volume and spending habits. This approach concludes that strategies can be developed to increase customer loyalty, optimize marketing strategies, and improve business performance.

Innovative technologies of rail transport used by the Armed Forces of the Republic of Poland

Innovation in rail transport has a wide range of applications, which includes customer contact, train moni-toring with modern internet-connected sensors and data analysis, as well as the use of artificial intelli-gence for route optimization, customer service management and vehicle maintenance. The presented is-sues constitute a research niche in the field of the use of innovations in military rail transport, which en-courages research in this area. The article describes innovative technologies of rail transport used by the Armed Forces of the Republic of Poland. The subject of the research included in the article are the latest innovations in the field of rail transport technology and the analysis of their benefits and potential use by the Polish Armed Forces. These include: intelligent control systems, infrastructure maintenance, innova-tive designs of trains and wagons. The aim of the article is to identify the advantages of innovative tech-nologies and their potential application in the Polish Armed Forces. In order to achieve the objectives of the article outlined in this way, it is necessary to answer the following research questions: What innovative technologies of rail transport are used by the Polish Armed Forces? What are the prospects for the devel-opment of innovative rail transport technologies for defence purposes in Poland? What innovative solu-tions concerning the railway infrastructure in Poland could improve the safety of movements of troops by rail? The research hypothesis was adopted in the article: Innovative solutions in rail transport used by the Polish Armed Forces will effectively support the implementation of transports in the movement and transport subsystem (M&T). In order to verify the hypothesis, the following research methods were used: theoretical methods (analysis, synthesis, abstraction, inference, generalization) and the method of expert interview with representatives of the movement and transport subsystem. The presented approach allowed to analyse the problem from different perspectives, which makes it possible to conduct detailed research on this important and current issue.

The Role of AI in Improving Customer Service, Fraud Detection, and Risk Management in Banking

The Role of AI in Improving Customer Service, Fraud Detection, and Risk Management in Banking

The Impact of Sports Background on Sales Performance of Sporting Goods: Evidence from Companies in Pingdingshan

Sales performance is an important indicator of business operations, especially in the field of sporting goods sales, but less attention has been paid to the role of sales staff’s professional background on performance. This article focuses on the impact of sports professional background on sales performance. The results show that sports professional background significantly improves the subjective and objective performance of salespeople. Further analysis found that this influence mechanism is mainly reflected in three aspects: first, sports expertise provides unique advantages for sales; second, good interpersonal skills enhance customer relationship management; third, strong sports enthusiasm stimulates sales enthusiasm. Finally, this article puts forward corresponding management suggestions, such as giving priority to sales staff with a sports professional background, strengthening targeted training and incentives, etc., in order to provide reference for the construction of sales teams of sports brand enterprises.

D’ROOM Designer Professional Solution: Utilizing Digital Applications to Navigate the Gig Economy for Financial Well-being

In an era marked by the rapid evolution of the gig economy, financial well-being has become an ever- elusive goal for many independent professionals. The D’ROOM Designer Professional Solution emerges as a pioneering innovation designed to address this pressing concern. This digital application offers a transformative approach to navigating the gig economy while prioritizing financial well-being. D’ROOM Designer Professional Solution recognizes these challenges and presents a comprehensive solution. By leveraging the power of digital technology, it empowers designers and other gig workers to secure their financial future. This innovative application combines user-friendly features with a robust support system, creating a unique platform tailored to the needs of gig professionals. Key features of the D’ROOM Designer Professional Solution include: Financial Planning Tools: The application offers a suite of financial planning tools, enabling users to set financial goals, create budgets, and track income and expenses. It provides insights and recommendations to optimize earnings. Client Management: Simplifies client relationship management by offering a centralized platform for communication, project tracking, and invoicing. This streamlines business operations, enhancing efficiency and client satisfaction. Resource Hub: The application provides access to a curated resource hub, offering educational content, industry insights, and skill development opportunities. This empowers gig workers to continuously enhance their skills and stay competitive. well-being and Privacy: Prioritizes data well-being and privacy, ensuring that sensitive financial and client information remains confidential and protected. Community Support: Users can connect with a vibrant community of fellow gig professionals, sharing experiences, advice, and best practices. The D’ROOM Designer Professional Solution aims to revolutionize the gig economy by fostering financial well-being and professional growth. By providing gig workers with the tools and resources they need to thrive, it empowers them to navigate the gig economy with confidence. This innovation not only improves the financial well-being of independent professionals but also strengthens the overall resilience of the gig economy itself. As we move forward in this ever-changing work landscape, D’ROOM Designer Professional Solution stands as a beacon of innovation, offering a brighter and more secure future for gig workers in the digital age.

Proposed Dashboard Concept for TUS MART: Enhancing Aquaponic and Hydroponic Sales Management Using the Innovation Canvas Method

The rapid evolution of e-commerce has transformed agricultural operations, prompting Telkom University Surabaya to develop TUS MART, an e-commerce platform designed for managing and selling aquaponic and hydroponic products cultivated by the university. However, TUS MART faces challenges such as inadequate data management, limited user interface intuitiveness, and inefficiencies in sales tracking and customer relationship management. This research proposes a comprehensive dashboard for TUS MART, developed using the Innovation Canvas Method, which aligns with both user needs and business objectives. The methodology involved phases like "Explore," "Ideate," "Market," "Design," and "Value Proposition," ensuring that the dashboard meets essential performance standards while addressing critical risks. The resulting dashboard enhances real-time inventory tracking, sales analytics, and customer management, contributing to TUS MART’s operational efficiency, sustainability, and educational objectives. This study highlights the successful application of innovative design frameworks in developing user-centered e-commerce solutions that integrate technological and agricultural advancements.

Risk Analysis in Customer Relationship Management via QRCNN-LSTM and Cross-Attention Mechanism

Risk analysis is an important business decision support task in Customer Relationship Management (CRM), involving the identification of potential risks or challenges that may affect customer satisfaction, retention rates, and overall business performance. To enhance risk analysis in CRM, this paper combines the advantages of QRCNN-LSTM and cross-attention mechanisms for modeling. The QRCNN-LSTM model combines sequence modeling with deep learning architectures commonly used in natural language processing tasks, enabling the capture of both local and global dependencies in sequence data. The cross-attention mechanism enhances interactions between different input data parts, allowing the model to focus on specific areas or features relevant to CRM risk analysis. By applying QRCNN-LSTM and cross-attention mechanisms to CRM risk analysis, empirical evidence demonstrates that this approach can effectively identify potential risks and provide data-driven support for business decisions.

The Effect of Internet Banking, Product Advantages, and Customer Relationship Management on Customer Loyalty at Bank Syariah Indonesia Semarang City

Introduction: The growing significance of customer loyalty in the competitive landscape of Islamic banking underscores the need for Bank Syariah Indonesia to understand the key factors that influence it, particularly in Semarang City. Objective: This research aims to analyze the effect of Internet banking, product advantages, and customer relationship management on customer loyalty at Bank Syariah Indonesia in Semarang City. Method: A non-probability sampling technique was applied, explicitly utilizing the snowball sampling method, which started with a small initial group of respondents and expanded through referrals. The sample obtained in this research was 100 Bank Syariah Indonesia customers in Semarang City. The data were analyzed using various statistical tests, including validity and reliability checks, classical assumption tests (normality, multicollinearity, heteroscedasticity), and multiple linear regression with Statistical Package for the Social Sciences (SPSS) v.26. Result: The findings show that Internet banking, product advantages, and customer relationship management positively and significantly affect customer loyalty. This study shows that Internet banking, product excellence, and customer relationship management significantly affect customer loyalty at Bank Syariah Indonesia Semarang City. These variables can explain 66.1% of the variance in customer loyalty, while other factors influence the remaining 33.9%. Implication: The impact of this research provides strategic insights for Bank Syariah Indonesia or other banks to understand better and fulfill customer needs, which ultimately can increase customer loyalty and satisfaction in the long term.

The Role Of Customer Relationship Management (Crm) Systems In Small Business Marketing

The Role Of Customer Relationship Management (Crm) Systems In Small Business Marketing

The Mediating Role of Self-Efficacy in the Relationship Between Salespersons’ Personal Factors and Sales Performance

A skilled salesperson can build strong relationships with clients, which fosters loyalty and repeat business. They provide valuable insights into customer preferences and competitive landscapes as well as creating value for their customers, manage customer relationships, and gather information for their firms. Hence, this paper explores how self-efficacy functions as a mediator in the correlation between improvisational behaviour, adaptive selling, and sales performance of salespersons. This study investigates the direct and indirect relationship of self-efficacy with sales performance. This study used a survey research approach using clustered random sampling. Data are collected from 315 salespersons employed by Malaysian commercial banks in Klang Valley via survey questionnaires. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyse the data. The findings indicate that self-efficacy serves as a partial mediator in the relationship between improvisational behaviour and adaptive selling with sales performance. Additionally, the results also showed that improvisational behaviour and adaptive selling are positively related to sales performance. The study concluded that personal factors of salespersons are important in determining their sales performance. Hence, for managers to have a competitive advantage in the banking sector, they need to adopt a more comprehensive understanding of what makes a good customer service provider.

Optimization Strategy of Customer Relationship Management based on Big Data Analysis

Optimization Strategy of Customer Relationship Management based on Big Data Analysis

An Impact of CRM at Max Fashion Retail Limited

Effective customer relationship management (CRM) is essential for maintaining competitive advantage in the retail fashion industry. At Max Fashion, CRM strategies have been designed to enhance customer loyalty, streamline communication, and improve overall customer satisfaction. This study examines the various CRM practices employed by Max Fashion, including the use of customer data analytics, personalized marketing campaigns, and loyalty programs. By integrating technology such as CRM software and social media platforms, the company aims to better understand customer preferences and purchasing behaviour. The research highlights how these strategies contribute to increased customer retention and long-term business success. Through a combination of qualitative interviews with Max Fashion's management team and quantitative data analysis from customer feedback, the study identifies the key factors driving CRM effectiveness. This research provides valuable insights for fashion retailers seeking to implement or refine their own CRM strategies in an increasingly digital marketplace

Strategic Relationship of CRM with Effectiveness of Branch-Banking and E-Banking: An Input for Innovative Marketing of Banking Products

A profitable relationship between today’s tech-savvy customers and banks is the primary component for most of the strategies of the banking organizations. So, the main purpose of this research-work is to test the structural paradigm of CRM (Customer Relationship Management) with the effectiveness of e-banking and branch-banking. With a sample size of 518 bank customers through a stratified sampling method, SEM (Structural Equation Modeling) is applied to test the above-mentioned structural relationship after testing two measurement models through CFA. So, this study proceeds with an experimental research design. Major outcomes of the study indicate that the CRM practices of banks have a significant direct effect on the effectiveness of e-banking; along with significant indirect effect through the mediation of the effectiveness of branch banking. Further, customer biases are seen to significantly moderate the above effects, and the model invariance is also successfully tested. Novelty refers to structural relationships among components of both traditional business practices (branch banking) and modern business practices (e-banking) have never been studied prior to this research work having CRM as its context. Practical implications say that the structural relationship along with testing results of moderation effect of customers’ biases and model invariance is providing innovative input for marketing strategies of banking products/services. Further, results of this study can create social awareness regarding concerns of banks regarding economic development of society. Rather than taking bank-customers’ opinion only, the bank-employees’ inputs alongside would be strengthening the research outputs.

Customer Relationship Management in the Hospitality Industry: An Empirical Study of Hotels in Agra

industry, significantly impacting customer satisfaction, loyalty, and business performance. This study aims to explore the implementation and effectiveness of CRM practices in the hotel sector of Agra, a prime tourist destination. Through empirical research, it investigates how hotels manage customer relationships to enhance repeat patronage and foster long-term relationships. The research utilizes quantitative and qualitative methodologies to assess the role of CRM systems in improving guest satisfaction and retention. The findings suggest that well-executed CRM strategies contribute to the growth of customer loyalty, brand reputation, and overall operational success in the hospitality industry

Nexus between customer relationship management dimensions, customer involvement and customer retention: a mediation analysis in Ghana’s hotel industry

PurposeThis research investigates the role of customer involvement (CINV) in customer relationship management (CRM) dimensions and customer retention (CR) in Ghana’s hotel industry.Design/methodology/approachThis quantitative-based explanatory research obtained primary data via structured questionnaires from 277 hotel customers in Ghana, processed it with SmartPLS4.0 software, and analysed it with structural equation modelling.FindingsCRM dimensions (CRM-based technology, managing knowledge and personalisation of services) and CINV positively affect CR. Also, CINV partially mediates the interactions between the CRM dimensions and CR in Ghana’s hotel industry.Research limitations/implicationsThe study is geographically limited to hotels in Ghana and conceptually limited to three CRM dimensions, CINV and CR. Methodologically, the study was limited to the quantitative approach. However, our outcomes imply that hotels in Ghana that invest in relevant CRM dimensions would improve CR. CRM-CR association can also be improved through CINV.Practical implicationsThe study outcomes imply that when Ghanaian hotels implement the CRM dimensions and foster active CINV, their customers’ retention will improve significantly. Hence, CRM and CINV are prerequisites for enhancing CR in Ghana’s hotel industry.Originality/valueThe study offers valuable contributions to the current literature on CRM, consumer behaviour and hospitality management, especially in a developing economy context. Its novel contribution, the mediating role of CINV, would advance CRM studies in the hospitality sector.

Airline business models as complex systems: assessing component interdependencies through interpretive structural modelling

PurposeThis paper explores the intricate interdependencies among core components of airline business models (BMs). In the airline industry, where BMs are complex systems, a successful BM requires an orchestrated configuration of various components. However, there is a paucity of research in BM literature pertaining to the interrelationships among key components of airline BMs.Design/methodology/approachEmploying interpretive structural modelling, we gathered input from experts in Iran to assess the driving power and dependency of elements within airline BMs.FindingsOur findings highlight the significance of operating environment conditions and competitive market dynamics as pivotal external components shaping the foundational structure. Value proposition, customer relationship management, and process monitoring are crucial linkage components that drive power and dependency. Notably, capturing value is positioned with the highest dependency.Practical implicationsWe utilised the ISM technique to visualize interdependencies within airline business models, aiding strategic decision-making. Our findings suggest aligning business and operational strategies with market needs ensures effective value creation and capture, maintaining competitive advantage in the airline industry. In addition, our research reveals critical factors affecting value creation and capture, emphasising monitoring the operating environment and competitive market, and strategically managing value propositions and customer relationship initiatives in the airline industry. We advise adapting business models to external changes for sustained growth and recommend regular monitoring of industry trends and customer expectations.Originality/valueFramed within complexity theory, these insights offer valuable perspectives on identifying and situating critical BM components in the airline industry. The practical implications derived from this study serve as strategic tools for airline managers and potential investors to optimise the design of their airline BMs.