Enhance Customer Satisfaction Research Articles

AI-enabled intelligent inventory and supply chain optimization platform for SMEs

An AI-enabled intelligent inventory and supply chain optimization platform offers SMEs a transformative solution to streamline operations, improve forecasting accuracy, and reduce costs. SMEs often face challenges in managing inventory efficiently, forecasting demand, and maintaining strong supplier relationships, largely due to limited resources and fragmented data. This platform integrates data from multiple sources such as sales, ERP, and supplier systems into a centralized system, enabling comprehensive visibility across inventory and supply chain functions. The platform employs machine learning algorithms to analyze historical data, identify trends, and predict demand patterns, resulting in more accurate forecasting and optimized stock levels. With predictive analytics, SMEs can set dynamic reorder points, minimizing overstock and stockouts while maintaining optimal safety stock. Additionally, the platform provides real-time tracking of shipments and supplier performance, allowing SMEs to monitor logistics in real-time and make informed, proactive decisions. Intelligent automation tools further enhance productivity by automating reorder processes, handling order generation, and reducing manual intervention in restocking. Benefits of this AI-driven platform include increased operational efficiency, reduced inventory holding and ordering costs, and enhanced customer satisfaction through timely order fulfillment. By optimizing stock levels and supply chain flows, SMEs can adapt quickly to market fluctuations and demand shifts, gaining a competitive edge. While challenges remain, such as data integration and employee training, the platform’s scalable design allows SMEs to start small and expand as needed. As AI technology advances, SMEs adopting these intelligent systems will position themselves for sustainable growth, improved resilience, and higher customer satisfaction in a rapidly evolving market landscape.

Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing

This article presents a discussion of the application of machine learning methods to enhance the quality of drive shaft production, with a particular focus on the identification of critical quality issues, including cracks, scratches, and dimensional deviations, which have been observed in the final stages of machining. A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. The results show that neural networks achieved the highest accuracy (94.7%) and the fastest prediction time, thereby underscoring their efficiency in processing complex production data. The BT model demonstrated stability in its predictions with a slower prediction time, while the SVM model exhibited superior training speed, though with slightly lower accuracy. This article proposes that optimising key process parameters, such as temperature, machining speed, and the type of coolant used, can markedly reduce the prevalence of production defects. It also recommends integrating machine learning with traditional quality management techniques to create a more flexible and adaptive control system, which could help reduce production losses and enhance customer satisfaction.

Integrating servitisation into the halal supply chain: a roadmap for sustainable business growth

Purpose The limited existing literature on the future research direction regarding how servitisation and the halal supply chain interact motivates this study. The paper aims to integrate servitisation into the halal supply chain by proposing an integration roadmap for successful adoption in the halal industry. Design/methodology/approach The study used the preferred reporting items for systematic reviews and meta-analyses method. Initially, 1,830 documents from Scopus and Web of Science were reviewed. After screening and refining, 1,241 documents remained. The authors then assessed these in full text, narrowing it down to 61 papers for the study. Findings The study discovered that the literature concerning servitisation and halal supply chains lacks essential conceptualisation, presenting an opportunity for exploration within the halal industry. Furthermore, it revealed that integrating servitisation into the halal supply chain can foster sustainable business growth and enhance customer satisfaction. Additionally, the study indicated that the interaction between servitisation and the halal supply chain may impact customers’ purchasing decisions and improve profit generation performance. Practical implications The study confirmed that integrating servitisation into the halal supply chain is crucial. The proposed roadmap aims to enhance the firm’s service delivery performance and impact customer purchasing behaviour through increased brand loyalty. In terms of industrial implications, the study offers guidance for industries transitioning to servitisation. The integration of servitisation in the halal supply chain can enhance efficiency and the ability to provide halal products that align with customer preferences and requirements. Originality/value This study suggests integrating servitisation into halal supply chains and provides a roadmap for exploring future research directions towards sustainable business growth. It not only offers thematic research direction but also practical insights. The roadmap can guide future research and development, enhancing business efficiency and customer experiences. This study reveals the potential of servitisation in halal supply chains and encourages further research on their interaction.

FACTORS INFLUENCING ONLINE PURCHASE IN OMNICHANNEL STRATEGY OF X STORE

This research explores the factors influencing online purchasing decisions within the omnichannel strategy of X Clothing Store, focusing on a sample of 100 respondents. Utilizing a combination of univariate until multivariate analyses, the study examines the relationships between various independent variables such as gender, age, promotions/discounts, online stock availability, customer service satisfaction, shipping speed, and product information and the likelihood of making online purchases. Findings reveal that a significant majority of respondents (72%) engage in online purchasing, with key factors such as promotional availability (78%), customer service satisfaction (72%), and clear product information (69%) being crucial determinants of purchasing behavior. The analysis indicates that younger consumers (ages 18-42) are more inclined to shop online, while women exhibit a higher likelihood of making purchases compared to men. Additionally, the results demonstrate that factors such as shipping speed and online stock availability significantly influence purchase decisions. The study underscores the importance of optimizing these factors to enhance customer satisfaction and increase online sales for X Clothing Store. Overall, the findings provide actionable insights that can inform marketing strategies aimed at improving the online shopping experience.

Impact of Service Quality, Pricing Strategies, User Trust, and Technological Innovation in Indonesia's Online Transportation Services Industry

This study investigates the impact of service quality, pricing strategies, user trust, and technological innovation on customer satisfaction in Indonesia's online transportation services industry. Using a sample of 400 respondents, the research employs regression analysis to identify the relationships between these variables. The findings reveal that service quality is the most significant predictor of customer satisfaction, followed by user trust, pricing strategies, and technological innovation. The results highlight the interrelated nature of these factors, suggesting that improvements in one area can positively influence the others. The study underscores the importance of maintaining high service standards, establishing user trust, implementing effective pricing strategies, and leveraging technological advancements to enhance customer satisfaction. These insights provide valuable implications for practitioners aiming to optimize user experiences and foster loyalty in a competitive market.

Impact of Total Quality Management Practices on Sustainability And Company Performance: A Case Study of Miro Forestry Company Ltd in Mile 91, Sierra Leone

Organizations globally are increasingly adapting to dynamic business environments, where management must consistently identify strategies to maintain or enhance competitive advantage. Total Quality Management (TQM) has emerged as a critical approach for manufacturing firms seeking to improve operational efficiency and effectiveness. Although previous research has explored the relationship between TQM practices and organizational performance, the findings have been inconclusive, signaling the need for further investigation. Notably, in Sierra Leone, limited research exists on the effect of TQM on the performance of manufacturing firms, revealing a knowledge gap. This study addresses this gap by examining the impact of TQM practices on the performance of manufacturing firms in Sierra Leone, with a specific focus on Miro Forestry Company Ltd. The main objectives of the study are to: (1) assess the impact of customer focus on organizational performance, (2) evaluate the role of top management commitment in enhancing performance, (3) examine the effect of continuous improvement on performance outcomes, and (4) determine the influence of employee involvement on organizational performance. The study employed a descriptive quantitative research design. A sample of 121 employees was selected from a target population of 400 using stratified random sampling. Data were collected through self-administered questionnaires and analyzed using SPSS alongside correlation analyses to assess relationships between variables. The findings were presented using figures and tables. Results show that TQM practices, which mainly involve customer focus, top management commitment, continuous improvement, and employee involvement were found to positively impact organizational performance. Customer focus significantly enhances customer satisfaction, while top management commitment and continuous improvement contribute to overall performance. Employee involvement also positively influences performance outcomes. The study recommends that companies should foster a robust organizational culture characterized by trust, respect, and a shared sense of purpose. Additionally, continuous improvement should remain a central focus to sustain performance. Management is also advised to prioritize quality management by motivating employees and offering incentives to support TQM initiatives.

Influence of Informational Internet Banking on Performance of Copedu PLC Microfinance

Purpose: This study investigates the influence of informational internet banking on the performance of COPEDU PLC Microfinance in Rwanda. It explores how access to online banking information affects customer satisfaction, retention, and overall financial performance. By focusing on non-transactional digital services, the study evaluates the extent to which informational internet banking impacts transparency, customer engagement, and financial literacy among clients. Methodology: The researcher employed a descriptive case study research design that integrated both qualitative and quantitative approaches. The study population comprised 74 individuals, and therefore, a census sampling technique was employed to select all 74 respondents. The researcher employed the SPSS software application to analyze the data. Mean, standard deviation, and percentages are utilized for data analysis. Pearson correlations were employed to establish the relationships among the variables. Findings: The regression analysis results demonstrated a significant correlation between the predictors (Informational internet banking, Transactional internet banking, and Communicative internet banking) and the dependent variable, Financial Performance, with a R value of 0.720, indicating a high degree of correlation. The R Square value of 0.519 signifies that around 51.9% of the variance in financial performance is elucidated by these predictors. The adjusted R Square of 0.497 provides a more precise estimate by considering the number of predictors in the model. A substantial majority of respondents (57.1%) agree that internet banking provides easy access to account information, reflected in a high mean score of 4.57. Additionally, 68.6% believe that the availability of internet banking services has improved customer satisfaction, with a mean of 4.64. The data suggests that informational internet banking has effectively reduced the need for in-person visits (61.4% agreement, mean 4.50) and has enhanced transparency in financial transactions (55.7% agreement, mean 4.56). Furthermore, respondents acknowledge that internet banking has positively impacted COPEDU's operational efficiency (57.1% agreement, mean 4.53) and improved the speed and convenience of accessing financial information (57.1% agreement, mean 4.49). Lastly, the provision of timely financial updates through internet banking was seen to contribute to better decision-making, with 50% of respondents agreeing (mean 4.44). Overall, the findings underscore the critical role of informational internet banking in enhancing customer satisfaction, operational efficiency, and informed decision-making at COPEDU PLC. In conclusion, the study demonstrates that informational internet banking significantly enhances customer satisfaction and operational efficiency at COPEDU PLC Microfinance, indicating its essential role in modern financial services. Unique Contribution to Theory, Practice and Policy: The research was underpinned by agency theory, contingency theory, behavioral theory, and information theory. It is recommended that COPEDU continues to invest in and promote its digital banking services, ensuring that clients are aware of the benefits and features available to them. For future research, it would be valuable to explore the long-term effects of digital banking on client retention and financial performance, as well as to examine the challenges and barriers faced by customers in utilizing these services effectively.

The Contribution of Quality of Work Life to Employee Job Satisfaction in Travel and Tourism Industry: A Theoretical Construct

Tourism industry is one of the most intensive labor sector in the world which generates employment opportunities and income for the global economy, but the work in tourism industry is characterized by difficulty due to irregular and long working hours and pressure that employees have to work under to satisfy the expectations of various customers. For the purpose of sustainable tourism development, the management of tourism industry has to take care of quality of work life in order to enable employees to meet their important personal needs and to effectively balance their personal and work life. The objective of the current study is to find out whether there is contribution of QWL to employees job satisfaction in tourism industry, to add to literatures of tourism and human resources and to provide some valuable recommendations that can be applicable by tourism service providers to enhance QWL of employees and hence their level of job satisfaction.. After reviewing several literatures the study found that there is a significant relationship between QWL and employee job satisfaction or in other words, QWL contributes significantly to employee job satisfaction in tourism industry. The study highly recommended that the management of tourism industry should promote QWL practices to enhance the level of employee job satisfaction and hence employee productivity in tourism industry from one hand and to enhance customer satisfaction from the other hand and this last plays a crucial role in success of tourist establishments and tourism industry in general.

Role of Technological Advancements on Customer Satisfaction in Japan’s Hospitality

Purpose: The aim of the study was to analyze the role of technological advancements on customer satisfaction in Japan’s hospitality. Methodology: 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: Technological advancements have significantly enhanced customer satisfaction in Japan’s hospitality industry by improving service efficiency, personalization, and overall guest experience. Innovations such as AI-driven customer service robots, automated check-in systems, and smart hotel rooms equipped with IoT devices offer convenience and seamless interactions for guests. These technologies reduce waiting times, streamline operations, and allow for personalized services, such as customized room settings and tailored recommendations, increasing guest satisfaction. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM), service quality model (SERVQUAL) & expectancy-confirmation theory (ECT) may be used to anchor future studies on the role of technological advancements on customer satisfaction in Japan’s hospitality. Hospitality businesses should adopt integrated management systems that combine customer relationship management (CRM), property management systems (PMS), and online booking platforms. Industry regulators should promote standards for technology integration in the hospitality sector.

Analyzing Factors Influencing Customer Satisfaction with Organic Coffee in E-Commerce

In recent years, there has been a notable increase in interest in sustainable products, particularly organic goods, driven by the push for sustainable societies. However, Japan’s organic market lags behind the global trend, representing just 0.3% of total farmland in 2021. To tackle this issue, the Ministry of Agriculture, Forestry and Fisheries introduced the “Green Strategy,” with the goal of raising the organic share to 25% by 2050. The COVID-19 pandemic has brought about significant lifestyle changes, such as increased remote work and reduced outdoor activities, leading to a surge in the E-commerce market and an increased need for analyzing consumer satisfaction. To enhance Japan’s organic market, it is crucial to familiarize consumers with organic products like coffee, tea, and snacks. This study proposes a model using E-commerce customer reviews to predict consumer satisfaction. The aim is to improve services and develop new strategies based on customer preferences, promoting sustainable growth and enhancing customer satisfaction. This study delves into the impact of factors derived from latent Dirichlet allocation (LDA) on consumer satisfaction with organic coffee, utilizing three years of data from Rakuten Marketplace customer reviews (2017–2019). A total of 1444 review texts were analyzed, including 154 low-rated reviews (ratings 1–3) and 1290 high-rated reviews (ratings 4–5). To build a satisfaction prediction model using regression analysis, a survey was conducted using question items explored through factor analysis to assess the reliability of items in conveying the consistent meanings of high frequency words extracted by LDA: “taste,” “aroma,” “gift,” “sales/discounts,” “freshness,” and “decaffeinated.” The results of the regression analysis revealed that “gift,” “sales/discounts,” and “decaffeinated” significantly impact consumer satisfaction. Insights derived from these factors illuminate marketing strategies that focus on delivering happiness through products, adding value through pricing strategies, and introducing benefits and consumption methods that effectively meet customer needs. These findings underscore the potential of customer reviews to enhance consumer satisfaction and inform strategic marketing decisions, thereby contributing to the growth and success of the organic coffee market.

The Impact of Service Quality and Product Attributes on Customer Satisfaction in Islamic Finance

This study investigates the impact of service quality and product attributes on customer satisfaction within the context of Islamic finance. Utilizing a quantitative approach, data were collected from 500 customers across various Islamic banking institutions. The findings reveal that both service quality and product attributes significantly influence customer satisfaction, with service quality demonstrating a stronger correlation. Notably, aspects such as employee friendliness, responsiveness, and product diversity emerged as critical factors. This research contributes to the existing literature by providing empirical evidence on the importance of service quality in enhancing customer satisfaction specifically in the Islamic banking sector, an area that has received limited attention. The implications of this study are twofold: first, it offers valuable insights for Islamic banking institutions to refine their service delivery and product offerings, thereby fostering greater customer loyalty. Second, it highlights the need for continuous assessment of customer expectations and satisfaction metrics to ensure sustainable growth in the competitive financial landscape. This study lays the groundwork for future research on the interplay between service quality, product attributes, and customer satisfaction in Islamic finance.

Exploring Inventory Management System with Priority Sequencing

Effective inventory management is crucial for businesses to optimise their resources and meet customer demand. This abstract introduces an Inventory Management System (IMS) that utilises priority sequencing to enhance the control and organisation of inventory items. The system employs various prioritisation criteria, such as item demand, shelf life, or profitability, to determine the sequence in which items are received, stored, and dispatched. Prioritisation Criteria: The IMS allows businesses to set specific rules and criteria for prioritising inventory items. This includes factors like customer demand, product shelf life, or item profitability. Real-time Monitoring: The system provides real-time visibility into inventory levels, allowing businesses to make informed decisions on restocking, order processing, and inventory allocation. Automated Reordering: IMS can automatically generate reordering recommendations based on preset priorities, ensuring that essential items are always in stock. Cost Reduction: By efficiently managing inventory based on priority sequencing, businesses can minimise holding costs, reduce wastage, and optimise working capital. Enhanced Customer Satisfaction: Prioritising items based on customer demand ensures that popular products are readily available, leading to improved customer satisfaction and retention. Forecasting Capabilities: The system can use historical data to predict future demand trends and adjust prioritisation accordingly. Reporting and Analytics: IMS provides detailed reports and analytics to help businesses fine-tune their inventory management strategies.

A Study on Consumer Satisfaction Regarding Online Vs Offline Shopping of Clothes Among Genzs in Ahemdabad City

This study investigates consumer satisfaction regarding online versus offline shopping for clothes among Generation Z in Ahmedabad, aiming to understand their preferences, behaviors, and concerns. Using a survey-based approach, the research analyzes key factors influencing their shopping experiences, such as trust, convenience, security, product quality, variety, fit, and customer service. The findings reveal that while Generation Z appreciates the convenience, discounts, and variety offered by online shopping, they still express concerns about security and confidence in product quality and fit. Offline shopping, on the other hand, is preferred for its reliability in assessing product quality, fit, and personalized customer service. The study also highlights the hybrid nature of Generation Z's shopping behavior, with many consumers using both online and offline channels based on the advantages each provides. These insights suggest that retailers should adopt an omnichannel approach, integrating online and offline experiences to enhance customer satisfaction. The practical implications for retailers include improving online security, navigation, and return processes, while maintaining high-quality in-store experiences. Recommendations for future research include expanding the study to other regions, investigating the role of emerging technologies, and exploring the impact of sustainability and ethics on shopping preferences

The Impact of Components in Marketing - Mix Strategy on Customer Satisfaction and Loyalty: Case Study at Codegym Vietnam Joint Stock Company, Hue Branch

This study aims to analyze the impact of 7 components on the marketing - mix strategy on the satisfaction and loyalty of programming course students at the branch of CodeGym Vietnam Joint Stock Company in Hue. The study combined exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) to measure the impacts of each component into the success of marketing - mix strategy then applied linear structural modeling (SEM) to test the related hypothesis of driving parameters to the customers’ satisfaction and loyalty. The finding indicated that there are 3 major factors having positively impact on customer satisfaction and loyalty, including: product, distribution and process. On the contrary, price, promotion, people and facilities factors have a negative impact on student satisfaction. The study also suggests several important implications to enhancing the efficiency of marketing mix strategy - with a need to focusing on developing marketing mix programs for centers to enhance customer satisfaction and loyalty.

A strategic IT policy implementation model for enhancing customer satisfaction in digital markets

In the increasingly competitive landscape of digital markets, customer satisfaction is paramount for sustained business success. This paper proposes a Strategic IT Policy Implementation Model aimed at enhancing customer satisfaction by aligning IT policy development with customer-centric strategies. The model serves as a framework that integrates technological advancements with customer expectations, ensuring that IT policies effectively support business objectives and improve operational reliability. The proposed model emphasizes a holistic approach to IT policy formulation, incorporating stakeholder input, market analysis, and performance metrics. It identifies key areas where IT policies can directly influence customer experiences, including data management, service delivery, and communication channels. By focusing on these elements, organizations can develop IT policies that not only comply with regulatory standards but also enhance user engagement and satisfaction. Central to the model is the concept of continuous feedback loops, which facilitate the ongoing evaluation and refinement of IT policies based on customer insights. This adaptive mechanism enables businesses to remain responsive to changing customer needs and technological advancements, fostering a culture of innovation and customer-centricity. Moreover, the model advocates for cross-departmental collaboration, ensuring that IT policies are harmonized with marketing, sales, and customer service strategies. Implementation of the model is illustrated through case studies of leading technology firms that have successfully aligned their IT policies with customer-centric approaches. These examples highlight the tangible benefits of improved customer satisfaction, increased loyalty, and enhanced operational reliability. Furthermore, the model addresses common challenges faced during implementation, such as resistance to change and resource constraints, offering practical solutions to overcome these obstacles. In conclusion, the Strategic IT Policy Implementation Model provides a structured approach for organizations aiming to enhance customer satisfaction in digital markets. By aligning IT policies with customer-centric strategies, businesses can achieve greater operational efficiency and foster long-term relationships with their customers.

Customer journey mapping framework for SMES: Enhancing customer satisfaction and business growth

Customer journey mapping (CJM) is an essential tool for small and medium-sized enterprises (SMEs) to understand and optimize their interactions with customers, thereby driving satisfaction and business growth. This review outlines a customer journey mapping framework designed specifically for SMEs, aiming to enhance customer experiences through a structured approach to identifying key touchpoints, pain points, and opportunities for improvement across the customer lifecycle. The proposed framework involves systematically mapping out every stage of the customer journey, from initial awareness to post-purchase interactions, highlighting moments that significantly impact customer satisfaction. By leveraging customer data, feedback, and analytics, SMEs can gain valuable insights into customer behavior, motivations, and preferences. This framework emphasizes the importance of personalization, using data to tailor the customer experience and foster deeper connections. Additionally, the framework integrates feedback loops, allowing SMEs to continuously gather and analyze real-time customer data. This iterative process helps businesses to proactively identify emerging trends, address customer concerns, and adapt to evolving market demands. By aligning customer needs with business objectives, SMEs can create more targeted marketing campaigns, improve product or service offerings, and enhance customer retention strategies. The implementation of this customer journey mapping framework can lead to several key benefits for SMEs, including improved customer satisfaction, increased brand loyalty, and greater operational efficiency. It also enables SMEs to compete more effectively in their markets by delivering personalized and seamless customer experiences. The framework supports scalability, allowing SMEs to refine their customer engagement strategies as their businesses grow. In conclusion, the customer journey mapping framework serves as a critical tool for SMEs looking to enhance customer satisfaction and drive sustainable business growth. By focusing on data-driven insights and continuous improvement, SMEs can deliver more value to customers, strengthen brand loyalty, and achieve long-term success.

Personalized customer journeys for underserved communities: Tailoring solutions to address unique needs

In today's diverse marketplace, creating personalized customer journeys for underserved communities is essential for fostering inclusion and promoting equitable access to services. This review explores the significance of tailoring solutions to address the unique needs of these communities, emphasizing the role of personalized experiences in enhancing customer satisfaction and loyalty. Underserved communities often face systemic barriers, including limited access to resources, information, and services. Traditional customer journey models may overlook these specific challenges, leading to ineffective engagement and unmet needs. By adopting a personalized approach, businesses can better understand the distinctive characteristics, preferences, and pain points of these communities. This understanding allows for the development of targeted strategies that resonate with individuals' cultural, social, and economic contexts. The framework for personalized customer journeys involves several key components. First, comprehensive data collection is crucial for identifying the unique demographics and psychographics of underserved communities. Utilizing qualitative and quantitative research methods, businesses can gather insights on customer behaviors, preferences, and challenges. Next, leveraging advanced analytics and artificial intelligence can enhance the personalization of interactions, ensuring that offerings align with the specific needs and aspirations of these communities. Additionally, fostering collaboration with community organizations and leaders is vital. Engaging with local stakeholders helps businesses build trust and credibility, facilitating the co-creation of solutions that genuinely address the community's needs. This collaborative approach can lead to the development of tailored products and services, targeted marketing strategies, and supportive customer service frameworks. Ultimately, personalized customer journeys for underserved communities not only improve customer satisfaction but also drive business growth and social impact. By prioritizing equity and inclusion, businesses can enhance their brand reputation, foster customer loyalty, and contribute to the economic empowerment of these communities. In conclusion, a commitment to understanding and addressing the unique needs of underserved communities through personalized customer journeys is essential for fostering inclusive growth and creating lasting positive change.

Unveiling the Power of AI-Driven Personalization: Transforming Consumer Behavior in the Age of Digital Marketing

Artificial intelligence (AI) is revolutionizing digital marketing, with AI-driven personalization emerging as a powerful tool for shaping consumer experiences and driving engagement. This study explores how AI-powered technologies, such as recommendation engines, dynamic content delivery, and targeted advertisements, are transforming consumer behavior in the digital landscape. By leveraging big data, machine learning, and predictive analytics, marketers are now able to deliver hyper-personalized experiences that cater to individual preferences, leading to enhanced customer satisfaction and increased conversion rates. This research examines the impact of AI-driven personalization on key aspects of consumer behavior, including decision-making processes, brand loyalty, and purchase intentions. Additionally, it addresses the ethical challenges that arise from the use of AI in marketing, particularly around data privacy, algorithmic bias, and consumer trust. Through case studies from various industries, this study provides a comprehensive analysis of how personalization influences consumer psychology and purchasing patterns. Ultimately, the research offers valuable insights into the benefits and risks of integrating AI into marketing strategies, helping businesses understand how to harness the power of AI while maintaining ethical standards and safeguarding customer relationships in an increasingly digital world. Moreover, the study delves into the nuances of AI-driven personalization by exploring how consumers respond differently based on demographic factors such as age, gender, and cultural background. By analyzing customer data in real-time, AI allows for more accurate segmentation, ensuring that marketing messages are highly relevant and resonate with individual consumers. This level of precision not only increases customer engagement but also fosters a sense of exclusivity, making consumers feel more valued and understood by the brand. The research also investigates the role of AI in predicting future consumer behavior, using historical data to forecast trends and preferences, thereby enabling brands to stay ahead of the competition. As AI algorithms continuously learn and adapt, they can refine their recommendations, becoming more effective over time. However, there are concerns about over-reliance on AI, as excessive personalization may lead to "filter bubbles," where consumers are only exposed to a limited range of products or content, potentially stifling creativity and innovation.

Interconnectivity and customer satisfaction

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Firms operating in a business-to-business-to-customer (B2B2C) context can utilize relevant Internet-of-Things (IoT) capabilities to facilitate connectivity between different stakeholders and to build a portfolio of complementary unique resources. Through emphasis on capabilities with most capacity to enhance customer satisfaction, such companies can hope for a positive impact on this performance metric. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The Role of Business Analysts in Enhancing Customer Satisfaction through Advanced Business Systems

Business Systems Analysts (BSAs) play a pivotal role in today's digital-first business environment, particularly in sectors such as insurance, fraud detection, and e-commerce. This article examines the critical function of BSAs in leveraging advanced business systems to drive operational efficiency, risk mitigation, and customer satisfaction. With the global business intelligence market projected to reach $33.3 billion by 2025, the demand for skilled BSAs continues to grow. Their unique ability to bridge technical capabilities with business needs positions them as key enablers of digital transformation. Through case studies and industry data, this research illuminates how BSAs contribute to project success, cost reduction, and enhanced customer experiences. The article also explores emerging trends and technologies that are shaping the future of business systems analysis, highlighting the evolving nature of the BSA role in an increasingly data-driven business landscape. This revised abstract provides a more condensed overview of the article's content, touching on the key points without duplicating the detailed information presented in the introduction. It also emphasizes the forward-looking aspects of the study and its relevance to current business trends.