Customer Interaction Research Articles

Enhancing Customer Engagement through Marketing 5.0: An Empirical Analysis

This study explores the impact of Marketing 5.0 techniques—Artificial Intelligence and Machine Learning (AIML), Big Data Analytics (BDA), Internet of Things (IoT), Augmented Reality and Virtual Reality (ARVR), Blockchain Technology (BT), and Voice Search Optimization (VSO)—on customer engagement (CE). The research employs a regression model with a sample of 250 respondents to examine the correlations and significance between these technologies and CE.The analysis reveals that AIML, BT, and ARVR significantly enhance CE, with AIML and BT showing the strongest positive correlations. Conversely, VSO is associated with a negative impact on CE. The regression model demonstrates an adjusted R-squared value of 0.489, indicating that these predictors explain a substantial portion of the variability in CE. ANOVA results confirm the model's statistical significance, emphasizing the importance of AIML, BT, and ARVR in improving customer interaction and brand involvement. The findings highlight the transformative potential of Marketing 5.0 technologies in delivering personalized and immersive experiences that drive customer loyalty and business growth in a competitive digital landscape. Organizations should strategically integrate AIML, BT, and ARVR into their marketing efforts to enhance customer engagement and gain a competitive edge.

Towards enhanced creativity in fashion: integrating generative models with hybrid intelligence.

This study explores the role and potential of large language models (LLMs) and generative intelligence in the fashion industry. These technologies are reshaping traditional methods of design, production, and retail, leading to innovation, product personalization, and enhanced customer interaction. Our research analyzes the current applications and limitations of LLMs in fashion, identifying challenges such as the need for better spatial understanding and design detail processing. We propose a hybrid intelligence approach to address these issues. We find that while LLMs offer significant potential, their integration into fashion workflows requires improvements in understanding spatial parameters and creating tools for iterative design. Future research should focus on overcoming these limitations and developing hybrid intelligence solutions to maximize the potential of LLMs in the fashion industry.

Legal regulation of intellectual property issues within technology transfer in Ukraine

Problem setting. Technologies affect many intellectual property issues, from inventions and technology brands to the content of transfer agreements, so the harmonious coverage of such aspects and consideration of the needs of interested parties in the current legislation is an urgent problem. Analysis of recent researches and publications. The new requirements of the technology transfer ecosystem affect the widening variety of intellectual property rights that arise with the creation of today’s technologies. Legislation should be flexible to such changes. Purpose of research is a critical review of the Law of Ukraine “On State Regulation of Activities in the Field of Technology Transfer” and the development of proposals for its improvement. Article’s main body. It is established that the said Law is more focused on inventions, while copyright, industrial designs, and trademarks are considered very limited, and separate provisions generally exclude the importance of such types of intellectual property for technology transfer; the said Law contains conceptual legal inaccuracies in the distinction between assignments and license agreements. It is proposed to replace the terms “patenting” and “patent immunity”, which appear many times in the document, with the broader and more flexible terms “acquisition of intellectual property rights” and “immunity from the intellectual property rights of third parties”, respectively. Such a proposal is justified as follows. In Ukraine, patents are granted only for inventions and utility models. Industrial designs receive a certificate of registration (as in the EU), the same applies to copyright (at the owner’s request) and trademarks. In the Digital Age, copyright now serves more than just the creative industries. Industrial designs are found everywhere and not taking into account this type of intellectual property from the economic evaluation of the technology or the research of promising areas is unjustified. A technology brand can move alongside it. Patent analysis provides insight into technologies and technological capabilities, as well as new business opportunities. Obtaining trademarks for patented solutions increases the value of these technical solutions, and trademark analysis provides information on the areas in which competitors operate, promising niches and regions, promising products and services, as well as customer interaction approaches and branding strategies. It is also proposed to set out in the document the definition of the term “technology transfer agreement” in accordance with Regulation 316/2014/EU, namely to add to the already existing definition that it can also be a license agreement entered into between two undertakings for the purpose of the production of contract products by the licensee and/or its sub-contractor(s). Conclusions and prospects for development. On the basis of the justifications given in the presented article, it is proposed to make appropriate amendments to the Law of Ukraine “On State Regulation of Activities in the Field of Technology Transfer” in Articles 7, 8, 13, 14, and 23 in the direction of expanding the types of intellectual property and in Article 1 in the direction of expanding definition of the term “technology transfer agreement”.

The Impact of Sales Promotion Programs on the Loyalty of Saudi Telecom Company Customers STC

This study investigates the impact of sales promotion programs on customer loyalty in the context of the Saudi Telecom Company STC. Utilizing data from 457 respondents, the research examines the role of different types of sales promotions, the frequency of promotions, promotional communication channels, and seasonal promotions on customer retention and satisfaction. The findings reveal a significant positive relationship between frequent and well-structured sales promotions and customer loyalty, with a β value of 0.914 for the frequency of promotions. While promotional communication channels showed a moderate influence (β = 0.592), seasonal promotions played a strong role in driving repeat purchasing behavior (β = 0.768). Customer retention and interaction with loyalty programs were also shown to be critical intermediary factors that mediate the effect of sales promotions on loyalty. The study confirms that well-designed promotional programs and consistent communication efforts can significantly enhance customer retention and satisfaction. Limitations and recommendations for future research are discussed, including the need for cross-industry studies and the exploration of digital and personalized promotional strategies.

The Interplay Between Digital Artifacts and Value Creation in the Ecosystem Design

Since Satoshi Nakamoto's first publication of the Bitcoin whitepaper in 2008, blockchain based technologies has gradually permeated various aspects of our lives. From the emergence of cryptocurrencies like Bitcoin to the development of platforms such as Ethereum, and the rise of phenomena like NFTs and Fan Tokens, the impacts of this technology has been diverse. While speculation surrounding these innovations persists, there exist successful use cases that have breathed new life into industries and enhanced customer interaction with established brands. One such domain where this is evident is the sports industry. Historically, sports teams, particularly football clubs, have sought avenues to capitalize on their fan base, aiming to diversify revenue streams. The advent of Fan Tokens has facilitated this endeavour, allowing teams to monetize fan engagement effectively. Consequently, an exploratory study comprising multiple case analyses was undertaken to examine how digital artifacts, exemplified by Fan Tokens, contribute to value creation within an ecosystem, fostering innovation and monetization for sports enterprises. The findings of this study elucidate the correlation between the characteristics of digital artifacts and the sources of value creation within an ecosystem. Furthermore, they underscore how these characteristics catalyse the formation of such ecosystems, thus propelling innovation and revenue generation within the sports industry.

Exploring online advocacy mechanisms through self-presentation: a comparative analysis between e-commerce website customers

PurposeUnderpinning social identity theory (SIT) and service-dominant logic (SDL), the current paper seeks to explore the effect of self-presentation on online brand advocacy (OBA). Furthermore, this paper investigates the mediating role of hedonic value and the moderating role of customer interaction with e-commerce websites (i.e. Amazon, Walmart and eBay).Design/methodology/approachData were collected from customers of three e-commerce platforms (i.e. Walmart, Amazon and eBay) using a structured questionnaire – multi-group analysis applied on SmartPLS 4.4.FindingsSelf-presentation has a positive role in increasing hedonic value and its impact on OBA. The moderating effect of customer interaction on these relationships is also investigated and found to be significant.Social implicationsOur findings underscore the significance of fostering inclusive online communities and favorable online settings. Existing findings are consistent with overarching objectives of digital empowerment and enhanced online interaction quality. This paper contributes to harmonious and collaborative digital societies by encouraging personalized experiences that foster a sense of belonging among diverse customers.Originality/valueThis paper adds to the existing body of knowledge by comparing customer behavior on three major e-commerce platforms, going beyond the traditional focus on a single platform. Drawing on SIT and SDL, this paper provides a distinct nomological framework for OBA that unifies disparate constructs, filling theoretical gaps in our understanding of online customer behavior.

Harnessing Artificial Intelligence for Hyper-Personalization in Digital Marketing: A Comparative Analysis of Predictive Models and Consumer Behavior

In this research, the impact of AI in improving the extent of hyper-personalization in digital marketing is explored by comparing and contrasting the outcomes of the various predictive models with consumers' behavior. With the change in customer demands, companies are now incorporating AI technologies in the production of services and products that cater to the customer's needs. Thus, the study uses quantitative and qualitative interviews to examine the extent to which the different types of predictive models can contribute to hyper-personalization initiatives. Studies show that organizations that have adopted hyper-personalization through AI reap significant benefits in terms of customer interaction, satisfaction, retention, and higher conversion rates arising from segmented marketing. However, data privacy issues and issues related to the ethical use of the data are also pointed out, which have to do with data responsibility. As such, the study establishes that applying best practices and developing superior and sophisticated forms of AI enables organizations to build valuable and relevant customer experiences that lead to organizational success in the current environment.

Pemanfaatan Digital Marketing dalam Proses Pemasaran Produk Secret Garden Village

The use of digital marketing has become an important strategy in product marketing to increase company profits and competitiveness. This article discusses the use of digital marketing in marketing Secret Garden Village products. The background to this research is the importance of digital marketing in the modern era which is supported by the rapid development of information and communication technology. This research aims to explore how the use of digital marketing can improve the marketing of Secret Garden Village products and expand market reach. The methodology used in this research is a case study with data collection through direct observation, interviews, and analysis of related documents. The research results show that the use of digital marketing in marketing Secret Garden Village products has succeeded in increasing brand awareness, increasing customer interaction, and increasing sales. In conclusion, the use of digital marketing can be an effective means for companies to reach a wider target market and get better profits. Therefore, companies should consider adopting digital marketing strategies in their product marketing efforts.

Understanding how customer interaction drives e-loyalty during returns handling in online retailing

Understanding how customer interaction drives e-loyalty during returns handling in online retailing

Impact of Digital Evolution on Customer Relationship Strategies in the Banking Sector

Digital evolution in the banking sector refers to the integration and development of digital innovations, such as internet banking, mobile applications, AI, and data analytics in banking operations and customer service measures. The research examines the influence of digital development on customer interaction strategies in the banking sector. As banks increasingly adopt digital tools to meet customer expectations for convenience and personalized services, the dynamics of customer relationships are changing. The study purpose is to understand how digital transformation influences customer engagement, satisfaction, loyalty and challenges banks face in maintaining personalized interactions in a digital environment. The study looks into a number of factors, including digital engagement, customer satisfaction, service personalization, customer loyalty, service accessibility, trust and security. The study involves 600 banking customers filling out a questionnaire after being informed about the purpose of the survey. SPSS was employed to conduct various statistics tests such as, pearson correlation, chi square, and t-test the obtain data and variables. The result indicates a positive correlation between the adoption of digital banking solutions and increased customer engagement. Research results underscore the importance of continued investment in a digital technologies to maintain a competitive edge in the banking industry. Banks that effectively integrate digital tools into their customer relationship management practices are better positioned to evolving requirement of customers, leading to improved satisfaction and loyalty.

Analysing the Correlation between Social Media Marketing and Consumer Purchase Behaviour

This study analysis of social media marketing includes use of platforms to communicate with consumers, promote items, and influence their decisions. The process by which customers choose which products or services to purchase is known as consumer purchase behaviour. Data was provided for this study, which observed exactly how social media marketing distresses customer buying behaviour, by consuming 350 participants, 150 marketers, and 200 customers. It is understood that many social media marketing features distress and unfair customer decisions. Hypotheses remained established to observe the relationships between commitment to social media marketing content, frequency of commercials, influencer content, and various social media platforms with consumer purchase behavior. Using SPSS logistic and linear regression analyses remained engaged to evaluate these relationships. Results expose that arrangement with social media marketing comfortable and influencer content positively moves buying behaviour. Linear regression analysis verifies these outcomes, proving the power of these relationships and the importance the effect of standard buying behavior. As that, the study delivers proposals concerning the way to use social media marketing approaches to increase consumer appointment and sales. Based on these insights, the study recommends optimizing social media marketing techniques to maximize customer interaction and improve financial outcomes.

The Influence of Artificial Intelligence on the Automation of Processes in Electronic Commerce

This study explores the transformative impact of Artificial Intelligence (AI) on automating business processes in electronic commerce (e-commerce), with a focus on enhancing efficiency and customer experience. The research employs Deep Learning (DL) and Machine Learning (ML) as primary analytical tools to process and analyze data from e-commerce transaction records and customers’ browsing histories. Techniques such as data preprocessing, normalization, sentiment analysis, and advanced predictive models using Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Support Vector Machines (SVMs) are utilized. Data collection was conducted using web scraping tools like Beautiful Soup and Scrapy, along with APIs from Amazon and Google. The application of AI in e-commerce has led to significant improvements in inventory control, fraud prevention, and customer relations. ML algorithms have enhanced the estimation of product demand and personalized customer interactions, while DL has strengthened product recommendation systems and fraud detection mechanisms. The findings indicate that AI contributes to a more secure, faster, and smarter operational environment in e-commerce. This research highlights the substantial benefits and broad potential of AI in optimizing e-commerce operations, demonstrating that the integration of advanced AI technologies not only streamlines transactions but also reinforces platforms against fraudulent activities.

THE STATE, PROBLEMS AND PROSPECTS OF PRICING DEVELOPMENT IN THE FIELD OF CONSTRUCTION OF ANTENNA-MAST STRUCTURES OF CELLULAR COMMUNICATIONS

The article examines issues related to the current state and problems of pricing in the field of construction of antenna-mast structures of cellular communications. The authors point out the peculiarity of the considered sphere of construction in terms of the mechanism for determining the estimated cost using tariffers, which differs from the generally accepted method, which implies the use of approved estimated standards, and is due to the lack of prices in the current regulatory framework that allow full marking of special types of work performed during the construction of antenna-mast structures. The disadvantages of this approach are given due to the establishment of prices in the tariff for enlarged work complexes and elements of the structure as a whole, which does not allow taking into account factors that have a significant impact on the design features of the support and, as a result, the cost of its construction and depend on the construction conditions and customer requirements. At the same time, the authors note and clearly confirm the absence of linking the rates of the tariff to the amount of work actually performed and the consumption of resources during the construction of a specific antenna-mast structure, which entails an unreliable estimate of the cost of construction. Separately, a comparison of the cost of materials for the construction of supports of the same height, depending on the projected payload, is provided, which also confirms the need to revise the existing pricing system. The authors provide recommendations aimed at improving the pricing mechanism used: options are proposed for the development and implementation of estimated standards for the construction area under consideration, as well as for improving the tariff rates in the interaction of construction organizations and customers.

Identifying the job competencies of Generation Z hotel employee in an intelligent environment in China

This study aims to identify and enhance the job competencies of Generation Z hotel employees in China, focusing specifically on how intelligent environments influence their job roles. Employing a mixed-methods approach, the research integrates focus group interviews with five groups to explore how job roles evolve in response to intelligent environments and uses questionnaires with 167 participants to develop a competency framework. The investigation addresses various dimensions of the intelligent hotel environment, including work support, internal communications, customer experience, and staff-customer interactions. Results show that the sense of responsibility towards customer interactions escalates to another level after hotels adopt an intelligent environment. Furthermore, this study establishes a job competency framework with 3 dimensions and 33 evaluation factors for Generation Z hotel employees, validated through Exploratory Factor Analysis and Confirmatory Factor Analysis. The framework of job competencies assists hotels in refining job competency assessment standards, developing robust performance appraisal systems, planning effective career development pathways, and designing targeted training programs. We expect these enhancements to significantly enhance the operational excellence and competitive advantage of hotels in China.

Improving Digital Marketing Skills of MSMEs in Legok Village through a Community Service Program

There are several problems in marketing the products of Micro, Small and Medium Enterprises (MSMEs) in this digital era. Problems such as limited access to technology and lack of knowledge and expertise in managing digital platforms or tools. To overcome these problems, Community Service (PKM) activities are carried out. This PKM is focused on improving marketing skills for MSME players in Legok Village, Tangerang, Banten by Universitas Multimedia Nusantara (UMN). Specifically, this solution is in the form of training with the theme of digital marketing management, market trend analysis, customer preferences, and strategies to increase customer interaction on e-commerce platforms and social media. The materials in this PKM activity are market trend analysis and the use of digital marketing tools where there are 19 participants from different MSME players. The results of this training showed that 100% of participants stated that the training delivered provided new insights or ideas to improve their business, especially in terms of marketing management. Thus, MSMEs in Legok Village are expected to be able to compete better in the digital market, which in turn can encourage local and national economic growth.

Crafting Language for Culinary Excellence: Customizing ESP Content to Align with Student and Industry Needs

The alignment of English for Specific Purposes (ESP) materials with the needs of students and the culinary industry is crucial for preparing graduates to excel in the competitive fields of tourism and hospitality. In particular, essential English language skills such as culinary terminology, effective communication in professional kitchen environments, and writing recipes or menus in English should be addressed more in existing curricula. This study aimed to assess the relevance and practicality of current ESP materials within the context of culinary education at an Indonesian university. Using a qualitative descriptive approach, the research involved 40 second-semester students who had completed a course in Professional English, along with 11 waitstaff from hotels and restaurants in West and North Sumatra. The findings revealed significant gaps in the current materials, particularly in areas critical for international customer service and multicultural teamwork, such as food presentation, customer interaction, and sanitation practices. The study concludes that English learning materials must be tailored to meet the general needs of English learners and the specialized demands of the culinary industry. Incorporating relevant terminology, practical communication skills and industry-specific content is essential for better preparing students for professional roles in catering and hospitality. The research suggests that focused classroom techniques on communication and specialized vocabulary can guide educators in developing more effective ESP materials for the culinary field.

Research of Artificial Intelligence’s Impact on Innovation and Entrepreneur

In a time of innovation, Artificial Intelligence (AI) is leading the way exploring frontiers, w in innovation and business. This engaging story delves into the impact of AI portraying it as a driver of opportunities while also recognizing the significant challenges that it brings. By examining how AI transforms customer interactions streamlines processes, enhances decision making this exploration delves deep into AIs capabilities and the ethical and technical dilemmas it raises. Through analysis this research paper aims to shed light on how to navigate AIs potential in the business world showcasing its transformative role across various industries existing. This article not only highlights AIs influence but also encourages readers to think about its future path paving the way for new discoveries, new opportunities. In doing it promotes a discussion, on using AIs power responsibly and in a secure way to ensure its benefits are maximized while addressing its challenges thoughtfully.

Application of GWO-attention-ConvLSTM model in customer churn prediction and satisfaction analysis in customer relationship management

Customer Relationship Management (CRM) is vital in modern business, aiding in the management and analysis of customer interactions. However, existing methods struggle to capture the dynamic and complex nature of customer relationships, as traditional approaches fail to leverage time series data effectively. To address this, we propose a novel GWO-attention-ConvLSTM model, which offers more effective prediction of customer churn and analysis of customer satisfaction. This model utilizes an attention mechanism to focus on key information and integrates a ConvLSTM layer to capture spatiotemporal features, effectively modeling complex temporal patterns in customer data. We validate our proposed model on multiple real-world datasets, including the BigML Telco Churn dataset, IBM Telco dataset, Cell2Cell dataset, and Orange Telecom dataset. Experimental results demonstrate significant performance improvements of our model compared to existing baseline models across these datasets. For instance, on the BigML Telco Churn dataset, our model achieves an accuracy of 95.17%, a recall of 93.66%, an F1 score of 92.89%, and an AUC of 95.00%. Similar results are validated on other datasets. In conclusion, our proposed GWO-attention-ConvLSTM model makes significant advancements in the CRM domain, providing powerful tools for predicting customer churn and analyzing customer satisfaction. By addressing the limitations of existing methods and leveraging the capabilities of deep learning, attention mechanisms, and optimization algorithms, our model paves the way for improving customer relationship management practices and driving business success.

PaaS Solutions for Scalable Social Media Engagement and Brand Loyalty Programs

Abstract: This research paper is a systematic analysis of how PaaS solutions can revolutionize the approach to increasing social network presence and improving brand reward programs. Based on the literature survey, comparison with current practices, and case study investigations, we study how, benefiting from PaaS, organizations deliver enhanced, efficient, and customer-centric experiences. This paper explores the attributes of PaaS that Microsoft especially targets for such applications the ability to perform real time analysis, omnichannel support and superior personalization. Based on the analysis of successful stories in different industries, we illustrate how, with the help of PaaS, Starbucks, Nike and Sephora were able to significantly enhance the specifics of customer interactions. It also focuses on the implementation issues that can be tackled. Some of the problems that may conflict with the research are data privacy, the complexity of integration, and sometimes, the use of the system by the targeted users. In addition, we analyze such innovative tendencies and tools as artificial intelligence, blockchain, augmented reality, and other future aspects concerning the development of PaaS-based loyalty and engagement solutions. The results reveal that PaaS provides definite top-line and bottom-line benefits for scalability, cost, and flexibility; it provides enterprises of all sizes with complex engagement solutions that were earlier only available to large enterprises. The study benefits both the academic and business worlds by offering theoretical and practical insights into the adoption of PaaS within businesses that desire to improve their app-based presence and connections with clients. The article ends with implementation suggestions and propositions for further research, focusing on the developments and trends related to cloud solutions concerning the future of customer engagement and their loyalty schemes..

Advancements in artificial intelligence for omnichannel marketing and customer service: Enhancing predictive analytics, automation, and operational efficiency

Gone are the days of impersonal customer service and generic marketing. Artificial intelligence (AI) is changing how businesses interact with customers, making interactions personalized and smooth across every platform. This transformation is powered by AI's capability to predict what customers want, automate routine tasks, and analyze large volumes of data. The Predictive Power of AI examines customer data to predict their preferences. Imagine receiving targeted ads and product recommendations that seem tailored exactly to your preferences! This personalized marketing approach enhances engagement and boosts sales significantly. AI-powered 24/7 chatbots provide instant customer support, eliminating the need for waiting on hold. They handle common inquiries and offer real-time assistance, continuously improving their ability to understand natural language and provide increasingly accurate help with each interaction. AI provides efficiency boost by automating repetitive tasks, allowing human teams to dedicate more time to cultivating relationships with customers, this includes qualifying leads, building targeted email campaigns, and analyzing data to inform business decisions, the outcome? More efficient operations and a happier team. It is imperative for businesses to understand customer sentiments and integration of AI analyzes customer interactions across various channels to assess their emotions and attitudes. This process, known as "sentiment analysis," enables businesses to detect dissatisfaction early, manage online brand perception, and gather valuable insights to enhance products and refine marketing strategies. There are also concerns about Ethical considerations, as AI becomes more integrated, businesses must prioritize customer privacy, eliminate bias in algorithms, and maintain a human touch to build genuine relationships. The future of AI and its possibilities are limitless! Natural Language Processing (NLP) advancements will lead to chatbots that sound and act human, while the integration of AI with virtual reality (VR) and augmented reality (AR) could create immersive and personalized experiences. In summary, AI is not here to replace humans; it is here to collaborate as your customer experience partner.