Personal Customer Research Articles

Deep Learning Application in Sales Automation and Customer Experience Personalization in Small and Medium-Sized Business: A Hybrid Approach Using Transformer-Based Large Language Models and Reinforcement Learning

Due to limited resources and fragmented technological infrastructures, omnichannel small and mediumsized businesses (SMBs) often face challenges in automating sales processes and delivering personalized customer experiences. This paper proposes a hybrid AI framework that integrates transformer-based large language models (LLMs) and reinforcement learning (RL) to address these challenges effectively. By combining LLMs' natural language understanding capabilities with RL’s dynamic decision-making, the framework aims to optimize customer engagement and sales automation in SMB contexts. The research employs LLMs to analyze customer behavior and deliver real-time conversational assistance through an AI concierge. This system provides personalized product recommendations, navigates shoppers to checkout, and collects data for customer insights. RL enhances this functionality by optimizing decision-making policies, such as dynamic pricing and resource allocation, based on long-term reward structures [4]. Key methodologies include multi-task learning to handle diverse customer interactions and offline simulators like Pseudo Dyna-Q to reduce deployment risks. Simulations based on retail scenarios demonstrated significant improvements: customer satisfaction scores increased by 20%, sales efficiency rose by 15%, and average order values grew by 40%. These findings highlight the potential of hybrid AI frameworks to empower SMBs by delivering scalable, resourceefficient solutions tailored to their unique operational constraints. The study also addresses ethical considerations, including fairness and transparency, by incorporating fairness-aware RL and explainable AI techniques to mitigate biases and build trust [15]. These measures ensure that the system promotes equitable outcomes, maintains user autonomy, and adheres to data protection standards. This research bridges the technological gap for SMBs and contributes to the democratization of advanced AI tools, enabling smaller enterprises to compete in increasingly customer-centric markets. The findings provide a robust foundation for further exploration of scalable and ethical AI-driven solutions in sales automation and personalization.

Consumer Financial Self-Disclosure Online Positive Affect Trumps Perceived Privacy Risks in Personal Customer Portals

Consumer Financial Self-Disclosure Online Positive Affect Trumps Perceived Privacy Risks in Personal Customer Portals

ARTIFICIAL INTELLIGENCE IN SOCIAL MEDIA MARKETING AND THE EFFECTS ON YOUTH- THE CASE OF INSTAGRAM

In today’s society, online marketing has become essential for almost every business. As digitalization accelerates, companies are increasingly compelled to strengthen their online presence and strategically position themselves within the digital space. Younger consumers, in particular, actively use social media platforms to inform their purchasing decisions. As a result, it is critical for brands to boost their visibility on these platforms and develop effective marketing strategies. With consumers becoming more mobile, they expect personalized experiences and seamless interactions across all touchpoints when engaging with a company. To address these challenges, the integration of artificial intelligence (AI) in marketing, alongside collaborations with influencers, has gained significant traction in recent years. AI plays a pivotal role in crafting personalized customer experiences, while influencers have considerable sway over young consumers. Social media campaigns are especially effective in shaping the consumption habits of adolescents, who tend to trust the recommendations and experiences shared by influencers. This trust significantly influences their purchasing behavior. In particular, influencer marketing strategies on platforms like Instagram enable brands to effectively connect with younger audiences. This study aims to explore how businesses utilize AI to enhance their online marketing efforts within the realm of social media, and to analyze the influence of influencers on the consumption patterns of young people. In this context, the growing impact of influencer marketing is increasingly shaping brand loyalty among young consumers, leaving a lasting effect in today’s digital age.

Artificial Intelligence in the Service Industry: Transforming Operations and Enhancing Customer Experience

Artificial Intelligence (AI) has become a driving force in reshaping the service industry, fundamentally altering how businesses operate and deliver value. Through the automation of tasks, AI enhances decision-making, streamlines operations, and provides personalized customer experiences. AI’s ability to analyze vast datasets, recognize patterns, and automate tasks previously handled by humans leads to significant improvements across industries like hospitality, retail, healthcare, and customer service. For example, in hospitality, AI-driven dynamic pricing and virtual concierges improve guest satisfaction and optimize revenue. In retail, AI powers recommendation engines, driving significant revenue growth. In healthcare, AI reduces diagnostic errors and accelerates decision-making. Similarly, AI-driven chatbots in customer service improve operational efficiency while ensuring high customer satisfaction. This paper explores these applications in depth, discussing benefits, challenges, and ethical considerations associated with AI integration in the service sector.

Real-Time Data Analytics in Customer Experience Management: A Framework for Digital Transformation and Business Intelligence

Real-time data analytics has emerged as a transformative force in customer experience management, enabling organizations to process and respond to customer interactions instantaneously. This article presents a comprehensive framework for implementing real-time analytics in customer-centric business operations, examining both theoretical foundations and practical applications across multiple industries. Through systematic analysis of implementation strategies, technical architectures, and organizational challenges, this article illuminates the critical role of real-time analytics in enabling personalized customer experiences, dynamic pricing optimization, and predictive service delivery. The article synthesizes current industry practices while identifying key success factors and potential barriers in real-time analytics adoption. Findings indicate that organizations leveraging real-time analytics capabilities demonstrate enhanced customer satisfaction, improved operational efficiency, and strengthened competitive positioning. This article contributes to both theoretical understanding and practical implementation of real-time analytics in customer experience management, providing actionable insights for practitioners while identifying promising directions for future research. The article concludes with a structured framework for organizations seeking to implement or enhance their real-time analytics capabilities in pursuit of superior customer experience.

Assessing the role of artificial intelligence in enhancing customer personalization: A study of ethical and privacy implications in digital marketing

Technological evolution, especially in artificial intelligence (AI), has significantly changed digital marketing, specifically customer-targeted experience. Machine learning, recommendation systems, and predictive analytics have made it possible for enterprises to personalize content, products, and services, among other things, on a very large scale. Nevertheless, all these advances have come with large ethical and privacy concerns that are yet to be met. This paper discusses how AI can enhance customers' personalization to analyze the moral and privacy considerations involved. The research examines how machine learning marketing strategies work in the digital environment and real-life examples of organizations that successfully implement these approaches and potential issues. It highlights how individuals might buy more products and make businesses more profitable with customized advertising techniques. However, the paper also describes the moral problems of AI that use personal data without permission, artificially intelligent algorithms that affect decision-making, and artificial intelligence decision-making. At the same time, its work has yet to be well known. The paper looks into privacy risks like data breach incidents, privacy violations, GDPR, and CCPA. This paper adopts an exploratory case study research design as it gathers academic papers, industry examples, and expert opinions to present a balanced view of the effects of AI. Based on the research, conclusions can be drawn that great opportunities AI opens for personalization should be met with safety considerations and working ethical guidelines. In the end, the paper presents guidelines that should help businesses integrate trust and compliance into creating and using AI technologies.

Research on Decoration of Tourist Homestays and Hotels Based on Digital Image Network Computing

In today’s digital age, the tourism and homestay industry is facing unprecedented opportunities and challenges. With the continuous expansion of the tourism market, tourists’ demands for accommodation experience are becoming increasingly diverse and personalized. Traditional design methods often struggle to quickly respond to these changes, fully showcase regional characteristics, and achieve efficient personalized customization. At the same time, how to integrate modern technology while retaining traditional charm to enhance the attractiveness and comfort of homestays has become an urgent problem to be solved. This paper aims to explore in depth how to use this technological framework to optimize the decoration design of tourist homestays, in order to create living spaces that retain traditional charm and are rich in modern technology. By utilizing digital image network computing technology, it is possible to conduct 3D modeling and virtual simulation of the indoor space of homestays. By simulating different furniture placement and spatial separation schemes, combined with tourist behavior analysis data, the optimal spatial layout scheme is automatically recommended to achieve maximum space utilization and a comfortable living experience. This technology can analyze a large number of color matching cases, combined with the cultural characteristics of the area where the homestay is located, and apply the principles of color psychology to provide personalized color schemes for homestay design. Meanwhile, through style recognition and recommendation algorithms, designers can quickly locate and integrate traditional and modern elements to create unique decorative styles.

Unlocking financial innovation through strategic investments in information management: a systematic review

PurposeThe purpose of this study is to explore strategic investment in information management and its crucial role in driving financial innovation. By examining the integration of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Blockchain, Big Data Analytics, Cloud Computing, Large Language Models (LLMs), Robotic Process Automation (RPA), Internet of Things (IoT), Cybersecurity Technologies, and Quantum Computing, this research aims to highlight how these technologies enhance decision-making, operational effectiveness, risk management, and compliance within the financial sector.MethodologyThe study employs a comprehensive literature review of existing research to analyze the impact of strategic investment in information management on financial innovation. Key technologies are identified and their applications in finance are discussed. The methodology includes synthesizing findings from various sources to present a cohesive understanding of the relationship between information management, technology, and financial innovation.ResultsThe results indicate that strategic investment in information management significantly enhances financial innovation by leveraging advanced technologies. AI and ML improve predictive analytics and customer personalization, Blockchain ensures secure transactions and transparency, Big Data Analytics enables data-driven decision-making, and Cloud Computing provides scalable solutions. LLMs enhance natural language processing capabilities, RPA automates repetitive tasks, IoT facilitates real-time monitoring, Cybersecurity Technologies protect financial data, and Quantum Computing offers potential breakthroughs in financial modeling and encryption.ImplicationThe implications of this study suggest that financial institutions should prioritize strategic investments in information management and the adoption of advanced technologies to stay competitive and resilient in the evolving financial landscape. Effective information management practices enable better decision-making, improved operational efficiencies, enhanced risk management, and regulatory compliance, ultimately fostering financial innovation.ContributionThis study contributes to the existing body of knowledge by providing a detailed analysis of the role of strategic investment in information management and its impact on financial innovation. It highlights the importance of integrating advanced technologies in financial practices and offers insights into how these technologies can be leveraged to achieve innovative solutions and improvements in the financial sector. The findings serve as a valuable resource for financial institutions, policymakers, and researchers interested in the intersection of technology and finance.

Enhancing Customer Engagement in Insurance Companies Using Salesforce Journey Builder: Tracking Customer Journeys Through Email Open and Ad Clicks

In the competitive insurance industry, understanding and engaging customers throughout their journey is crucial for retaining existing clients and acquiring new ones. Salesforce Marketing Cloud's Journey Builder provides a powerful platform for designing and automating personalized customer experiences. This paper explores how insurance companies can leverage Journey Builder to track and analyze customer interactions such as email opens, and ad clicks. Detailed explanations of journey flows, including the use of Apex code for integrations, are provided. Key Performance Indicators (KPIs) essential for measuring the success of these customer journeys are highlighted. An illustrative example is included to demonstrate the practical application of Journey Builder in enhancing customer engagement within the insurance sector. Keywords: Salesforce Journey Builder, Insurance Industry, Customer Engagement, Marketing Cloud, Apex Code, Customer Journey Tracking, Email Opens, Ad Clicks, KPIs

The Influence of Fake News, Personality of Muslim Customers and Anger Against Hateful Behavior of Muslim Consumers at Brands Halal Products With Religiosity As Moderation Variable

This study aims to determine the role of religiosity in moderating the influence of fake news variables, the personality of Muslim customers, and anger towards the hateful behavior of Muslim consumers towards halal product brands. Primary data collection was carried out by purposive sampling with a total sample of 340 response questionnaires collected from consumers of fast food restaurant outlets (Kentucky Fried Chicken, McDonald's, and Pizza Hut) domiciled in Purwokerto, Tegal, Yogyakarta, Surakarta, and Semarang. The relationship between fake news variables, Muslim customer personality, and anger towards hateful behavior towards brands were analyzed using Structural Equation Modeling from the Warp Partial Least Squares regression program package. Empirical research shows the influence of fake news, Muslim personality, and anger on brand hatred. The test results show that religiosity can be a moderating variable between fake news, Muslim personalities, and anger towards brand hate for halal products. Hatred about the brand can be suppressed if the company provides information quickly regarding the products offered, and this news can be quickly verified through social media; the information provided is straightforward to understand, and consumers are always optimistic and able to provide good perceptions so consumers do not feel they hate food and beverages and can ensure a halal product.

Digital Banking Transformation AI Enhances Efficiency And Customer Experience Seminar Perspective Industry

This study examines the transformative impact of artificial intelligence (AI) on operational efficiency in the Indonesian banking sector. It investigates how AI technologies enhance responsiveness to customer inquiries, streamline service processes, and improve overall customer satisfaction. Using a qualitative approach, the research integrates literature reviews, in-depth interviews, and case studies to comprehensively analyze AI adoption and its implications. The findings demonstrate that AI implementation not only boosts operational efficiency but also facilitates personalized customer service through advanced data analytics and AI-driven automation. The study emphasizes the importance of transparent AI algorithms and robust data protection measures to address ethical considerations and ensure adherence to Sharia principles. Insights from leading banks such as Bank Mandiri and Bank BRI highlight substantial reductions in operational costs and enhanced service capabilities following AI integration. This research contributes to a deeper understanding of AI's role in shaping contemporary banking services and provides strategic recommendations for optimizing AI applications in Indonesian banks.

Customer personality analysis and clustering for targeted marketing

A customer’s personality has been stated to be a key determinant in his or her purchasing behavior. Therefore, in today's highly competitive market, understanding customer behavior and preferences is very important for businesses aiming to stay ahead. This research presents a customer personality analysis and clustering of consumers using machine learning into different consumer groups, this kind of clustering is key for targeted marketing strategies. The machine learning technique used in this work is the k-means machine learning clustering algorithm which divides a set of n observations into k clusters with the aim of designating each observation as a representative of a cluster. The model revealed insightful patterns and correlations between customer characteristics and their purchasing behavior. Through comprehensive data analysis and feature engineering, the model identifies key personality traits such as extroversion, openness, conscientiousness, agreeableness, and neuroticism, based on customer interactions, demographics, and psychographic data. The dataset that was used for this work was obtained from kaggle, it originated from different sources such as customer relationship management (CRM) systems, e-commerce platforms, social media platforms, surveys. The dataset comprises information on "people," "products," and "promotion," aiming to understand customer behavior, preferences, and responses to various marketing efforts. The output of this work provides businesses with actionable insights to tailor marketing campaigns and product offerings to individual customer preferences, thereby enhancing customer satisfaction and maximizing profitability.

Konten Youtube Sebagai Jaminan Bagi Pelaku Ekonomi Kreatif Dalam Perspektif Hukum Jaminan

YouTube content copyright is an object that moves and has no form, so it can be the object of fiduciary guarantees from financial institutions. However, this provision has given rise to many interpretations because it does not specifically regulate the criteria for YouTube content copyright which will be the object of fiduciary guarantees. Therefore, the author examines the legal certainty and facilitation of schemes for creditors holding fiduciary guarantees over YouTube content copyright objects. The research is normative legal research using a statutory approach and a conceptual approach, which is carried out by analyzing primary legal materials and secondary legal materials. The results of this research are Law Number 10 of 1998 concerning Amendments to Law Number 7 of 1992 concerning Banking, ordering banks to implement the principle of prudence in assessing customer personality, customer business and collateral objects in the form of YouTube content copyrights. carry out credit distribution. If there is a default in the credit agreement, based on Law Number 42 of 1999 concerning Fiduciary Guarantees, the creditor can execute the YouTube content copyright which is the object of the collateral.

A STUDY ON ADVERTISEMENT EFFECTIVENESS ON BRAND IMAGE: A CASE STUDY ON HONDA MOTORS

In this study, we shall be investigating the types of advertising that Honda resorts to and the role that advertisements play in the establishment of customer opinions regarding the brand. The primary objectives of the study are threefold: However, I Start With the Important Elements of Honda such as H.O.N.D.A. and Ultimate Benefit. It can be viewed as a sign of how the ad campaigns of Honda help to create and keep a positive brand image. This means adopting advertising methods of different forms, but which are not so conspicuous, therefore, making customers notice them and finally, their reactions to them. First, the author investigates the efficiency of advertisements in the formation of a brand image with account taken of such factors as brand association, brand familiarisation, and personal customer relationship with the Honda car. The research outcome will likely be in line with the advertisement which could be employed with consumer perception as well as brand awareness. On the contrary, however, the outcome is associated highly with a brand that has been acknowledged positively. With this study, the final (decisive) instrument that is most responsible for the advertising effectiveness of Honda will be identified as well. Hence evaluating the performance of each part it will be possible to reach the best one and identify the determining feature that is the main reason for the positive image of Honda in the highly competitive automotive industry. The outcomes of this investigation would constitute a critical source of information that would be extremely beneficial to the marketing and brand managers of Honda, as they can now apply the aforementioned principles in their ads to improve their brand positioning and buyers' engagement level. Keywords: advertisement effectiveness, brand image

Effect of Cu content on the properties of laser powder bed fused biomedical titanium alloys

Laser powder bed fusion (LPBF) technology enables personalized customization of medical implants. However, the clinical titanium alloy is biologically inert and can't address bacterial infections. It has been proved that Copper (Cu) -bearing titanium alloys exhibit excellent antibacterial ability and potentials for clinical application. However, it still unclear that the effect of Cu content on the comprehensive properties of LPBF-produced titanium alloy which usually has high strength but poor ductility and corrosion resistance caused by its α′ martensite. This study systematically investigates the effects of Cu content (x = 2, 5, 8 wt%) on the microstructure, mechanical properties, corrosion resistance, antibacterial properties, and cytrocompatibility of the LPBF-produced Ti-xCu alloys. These results prove that the LPBF produced Ti–5Cu alloy possesses the optimal comprehensive performance and has promising clinical application prospects as implant materials.

Sustainable business models in SMEs: The customer’s perspective


 
 
 The main purpose of the study is to identify the relationship between sustainability goals and measures of the degree of sustainable policy implementation, as well as the customer perspective as determined by the business model (BM) template of A. Osterwalder and Y. Pigneur. In the conducted research, the customer perspective takes into account five elements of the BM and each element was examined by several characteristics. The elements of the BM from the customer perspective are: customer segment, value proposition, distribution channels, customer relationships, and revenue. The study used the authors’ survey questionnaire, in which respondents, who were enterprises in the SME sector, answered questions about their own BM divided into three layers – business, social, and environmental. The results were statistically analysed using SPSS STATISTIC 28 software and a logit model was developed to verify the significance of the relationship between the binary variables studied. 303 enterprises participated in the survey, 59% of which were enterprises guided by sustainability goals (SGs) in their BMs. However, only 27% of those surveyed had measures of the degree of sustainable policy implementation.
 
 
 
 The conducted research confirmed that acting in accordance with SGs is strongly related to customer-oriented elements of the business model, such as (1) customer segregation by sex or by level of environmental awareness, (2) value proposition – an environmental orientation, (3) distri- bution channels – direct sales online, (4) customer relationships through dedicated personal assistance or automated service based on personal customer profiles, (5) revenue – sales of products and services. Slightly different results were obtained for using measures of the degree of the SD policy implementation, where the highest correlation occurred for: (1) main customers – manufacturing entrepreneurs, (2) customer segregation by end-user experience or by level of involvement in socially important issues, (3) value proposition – strengthening democracy, (4) distribution channels – wholesale stores are run by partners, (5) customer relationships through self-service or automated service based on personal customer profiles or involving customers in the product development process, (6) revenue – rental/lease/leasing or licenses.
 
 
 
 
 

Toward Competitive Advantage: Harnessing Artificial Intelligence for Business Innovation and Entrepreneurial Success

The digital revolution of the past few decades has significantly transformed the business paradigm. One of the technologies dominating this change is artificial intelligence (AI). AI has opened new opportunities in the business field with its ability to process data rapidly and detect previously unseen patterns. The aim of this research is to identify the potential utilization of AI in enhancing operational efficiency and business innovation. The research method employed is a literature review with a qualitative approach. Data used are sourced from Google Scholar for the period from 2017 to 2024. The findings of this research indicate that in an increasingly competitive and dynamic digital era, artificial intelligence (AI) has become a key driver for companies aiming to remain relevant and successful in a constantly changing environment. The use of AI opens new opportunities and stimulates business innovation by enabling companies to optimize strategies, enhance operational efficiency, and create more personalized customer experiences. However, the utilization of AI also brings challenges and risks, including data privacy and security concerns, as well as biases in AI decision-making. To address these challenges, companies must focus on talent development, collaboration among stakeholders, and cultural and organizational paradigm shifts.

Challenges and Opportunities of Fintech Innovation for Traditional Financial Institutions

The rapid rise of fintech innovation has ushered in an era of change in the global financial services industry, presenting traditional financial institutions with a complex mix of challenges and opportunities. The dynamic interaction between fintech advances and the traditional banking system marks a pivotal moment in the financial industry, where the convergence of digital technologies with the financial services structure is reshaping the traditional banking business model. FinTech innovations, characterised by their flexibility, innovation and customer-centric solutions, are challenging the established models of traditional banks, forcing them to rethink their strategies, operations and services. These challenges are multifaceted, including the need for digital transformation, increasing competitive pressures from fintech startups, evolving consumer expectations for instant and seamless financial services, and the need to find a balance between innovation and financial stability and consumer protection in a changing regulatory environment. At the same time, fintech innovations offer unprecedented opportunities for traditional financial institutions to redefine their roles in the financial ecosystem, improve operational efficiency, and expand the scope of their services. By adopting blockchain technology to enable secure transactions, artificial intelligence technology to provide personalised customer service, and data analytics to improve risk management, traditional banks can open up new avenues for growth and innovation. In addition, fintech can enable traditional banks to offer convenient and affordable financial products to underserved or unbanked populations, thereby promoting financial inclusion. The intricate relationship between fintech innovation and traditional financial institutions embodies a dual narrative of disruption and convergence, highlighting the need for traditional banks to take a strategic and adaptive approach to navigating the fintech revolution. As traditional financial institutions endeavour to address the challenges posed by fintech and embrace the opportunities it presents, they will play a crucial role in shaping a more inclusive, efficient and resilient financial system of the future. The need for a nuanced understanding of technological, regulatory and market dynamics in the evolution of fintech underscores the importance of innovation, collaboration and customer-centricity in the development of the financial services industry.

AI-Powered Marketing: Transforming Consumer Engagement and Brand Growth

This paper explores the profound impact of artificial intelligence (AI) on marketing strategies across various sectors. AI has revolutionized marketing practices by enabling personalized customer experiences, enhancing data analytics, and optimizing advertising campaigns. The paper examines case studies from companies like Alibaba, Sephora, and Toyota, highlighting how they leverage AI to improve customer engagement and drive sales. Additionally, it discusses the components of AI marketing, including machine learning and big data analytics, and their role in bridging the gap between data collection and actionable insights. Furthermore, the paper delves into the implications of AI for different aspects of marketing, such as email marketing, advertising, chatbots, predictive analysis, and dynamic pricing. By synthesizing insights from a diverse range of sources, this paper provides a comprehensive overview of the transformative impact of AI on modern marketing practices.

The Future of Marketing: The Transformative Power of Artificial Intelligence

This research offers a rich narrative explaining this multifaceted relationship by exploring the transformative impact of Artificial Intelligence (AI) on marketing by adopting a qualitative descriptive approach for in-depth exploration. The findings reveal profound implications for customer engagement, market strategy, and ethical considerations. The multifaceted integration of AI into marketing enables customer personalization and increases brand loyalty. Predictive analytics enable businesses to develop proactive strategies aligned with future market dynamics. Despite its advantages, ethical considerations surrounding data privacy and consumer consent require AI to be used responsibly and transparently. Integrated augmented reality, virtual reality, predictive customer journeys, and the Internet of Things that transform marketing dynamics must be harnessed to balance ethical concerns. A comprehensive resource for academic researchers and industry professionals, this work provides a clear roadmap for organizations to effectively leverage AI in their marketing operations in an environment of increasing reliance on digital platforms and expanding data availability.