STRIVING FOR DIVERSITY IN POPULATION-BASED RESEARCH: STRATEGIES AND OUTCOMES IN THE RISE FOR HEALTH STUDY.

Increasing low-cost funds, or Current Account and Savings Accounts (CASA), has become a key focus for banks to optimize funding costs and increase profitability. In an increasingly digital era, banks can leverage big data analytics–based technology to develop more effective and efficient marketing strategies. This technology enables the processing of transaction data, digital interactions, and customer behavior to increase engagement and retention. This research aims to (1) analyze the implementation of hyperpersonalized marketing strategies in the banking sector; (2) examine the influence of data-based marketing strategies on marketer performance; and (3) analyze the potential for increasing CASA through data-based marketing strategies. This research uses a qualitative approach with a systematic literature review method to examine various studies related to digital marketing strategies in the banking sector. The results show that utilizing customer transaction data and digital interactions enables banks to conduct more accurate customer segmentation. This study examines hyperpersonalized marketing strategies based on data-driven technology that can improve marketer performance, as well as the potential for increasing CASA, by focusing on identifying marketer success factors in increasing engagement, the potential for increasing CASA, and the challenges in implementing this strategy, using literature analysis and case study methods.

This study aims to analyze the implementation of Integrated Marketing Communication (IMC) on the Instagram account @melvantbali in building brand image and strengthening product branding as a local streetwear-based fashion brand. This research employs a descriptive qualitative method and is grounded in the IMC framework proposed by Kotler and Keller, which consists of eight key elements of marketing communication: advertising, sales promotion, events and experiences, public relations and publicity, online and social media marketing, mobile marketing, direct and database marketing, and personal selling. The findings show that these communication elements operate in an integrated and consistent manner, creating message unity, visual identity continuity, and a strong brand experience in the minds of the audience. Advertising through visual content shapes brand identity, sales promotion is applied selectively without reducing brand exclusivity, events and experiences strengthen consumer trust through direct interaction, while public relations reinforces brand legitimacy and value through storytelling. Furthermore, online and social media marketing enable participatory two-way communication, mobile marketing fosters psychological closeness through real-time responses, direct and database marketing build personalized relationships with consumers, and digital personal selling functions as a supportive process in purchase decision-making. These findings indicate that IMC is not merely a promotional instrument, but a relational strategy that shapes emotional engagement, brand awareness, and consumer trust toward the brand.

In this paper, the field of algorithmic engineering and data-based marketing of competitors and technological advancements in contemporary organizations are taken into account. The aim is to analyze the possibility of using analytical systems based on algorithms to enhance marketing acumen, innovation, and rivalry in data-driven enterprises. The study assumes a quantitative approach to analysis based on the secondary data gathered on the basis of peer-reviewed research materials and digital marketing analytics reports. The essential variables are algorithms engineering capability (AEC), the data-driven marketing strategy (DDMS), technological innovation (TI), and market competitiveness (MC). The study uses predictive analytics evaluation, statistical analysis, and algorithms in the workflow, structural equation modeling (SEM), and regression analysis are implemented to analyze the correlations between the variables. The measures that are employed in the evaluation of the algorithmic performance are the predictive accuracy, processing speed, and computational efficiency measures. The descriptive analysis indicates the key variables have a high mean value, such as AEC (4.12), DDMS (4.05), TI (3.96), and MC (4.08). The accuracy of the predictive algorithmic performance is shown to be 91.4% better, processing speed 35.7% better, and computational cost 28.5% cheaper, which gives an index of algorithmic efficacy of 0.82. Innovation records include 18 new products, 12 technology implementations, and an index of 1.20 of innovation. The 12.8% market share growth, 84.6% customer retention, and 15.2% revenue growth indicate the market competitiveness and yielded a competitiveness index of 0.87. The results of regression confirm the significant relationships, including AEC → DDMS (0.62), DDMS → TI (0.58), and TI → MC (0.55). The findings confirm that the data-driven marketing process, with the help of algorithmic engineering, can significantly contribute to the enhancement of the performance of innovation and competitiveness in the market. With the adoption of advanced analytics and predictive algorithms, organizations are bound to become more efficient in their decision-making, invent, and present new products, and make the most impact in the digital market, which facilitates the formation of strategies.

Palm sugar production in Semarang Regency has excellent potential to the abundance of palm trees that thrive. One of the production centers is Kalisidi Village, which is located on a plateau with hilly topography and green vegetation. The local community has maintained traditional production methods for generations, from manual sap harvesting to natural firewood processing. Although these products have authentic appeal and high quality, manufacturers face the challenge of increasingly fierce competition with other businesses that have adopted modern technology. Strategic solutions can be implemented to help palm sugar MSMEs in Kalisidi Village maintain a sustainable competitive advantage through innovation in packaging design. Packaging design training using applications such as Canva are expected to produce attractive, informative, and functional packaging that can increase product appeal while strengthening the brand image. Digital marketing through e-commerce platforms is an advanced strategic solution to expand market reach. Assistance in digital business processes can increase understanding of data-based marketing and direct interaction with consumers. With the implementation of this community service program, participants have gained an understanding of how to create innovative packaging designs and develop appropriate digital marketing strategies. The follow-up to this community service activity is the continued guidance and monitoring of participants to ensure the sustained implementation of innovative packaging design and effective digital marketing strategies.

This research examines how Business Intelligence (BI) and Technological Capabilities (TC) cumulatively impact Digital Marketing (DM) performance in industrial companies, based on empirical data from Jordan. Drawing on Resource-Based View and Dynamic Capabilities Theory, the research formulates and examines a conceptual framework where BI constitutes a strategic resource and TC represents a key marketing effectiveness enabler. Data were obtained from 252 managerial respondents from different manufacturing industries by using a structured questionnaire. Covariance-Based Structural Equation Modeling (CB-SEM) was used to test associations. The findings indicate that BI has direct and indirect impacts on DM performance, where TC represents an essential mediating variable. These results underscore that although BI facilitates data-based marketing decisions, its strategic advantage depends on internal technological readiness of the firm. The research contributes to knowledge by validating an integrated BI–TC–DM framework in an emerging market industrial setting and enhances practical knowledge by illustrating how digital infrastructure can be aligned with analytics to enhance marketing outcomes. The findings have particular relevance to industrial companies facing digital transformation as well as policymakers seeking to support Industry 4.0 implementation within resource-scarce environments.

The study aims to discover a new homecare cleaner product and its marketing strategy using New Product Development (NPD) and Integrated Marketing Communication (IMC) theory. PT. Siklus Refil Indonesia, the eco-friendly retail homecare cleaning company, faces a fall in revenue due to limited product development and inefficient marketing strategy. This study uses mixed methods involving home care cleaner users. The quantitative data is from the questionnaire, and the qualitative data is from nethnography, interviews, and the VRIO and PESTLE framework. The new product is developed based on the findings on netnography, and interviews strengthened with VRIO and PESTLE framework. The marketing strategy is defined based on IMC principles and insights from interviews and questionnaires. The findings are the new product to be developed is a multipurpose cleaner. The marketing strategy involves an integrated communication approach consisting of the eight channels tailor-made for the multipurpose cleaner, which are advertising, sales promotion, online and social media marketing, event and experience, mobile marketing, public relations and publicity, direct and database marketing, and personal selling.

In today’s digital age, enormous volumes of data are generated every moment. Data mining leverages mathematical and statistical methods—alongside machine learning, database management, and data visualization—to extract valuable knowledge from these large data sets. Its techniques are applied successfully in diverse areas, including business, government, healthcare, science, and sports, with use cases such as database marketing, fraud detection, retail analytics, credit scoring, astronomy, and molecular biology. Mathematics provides the backbone of these processes through statistics, optimization, linear algebra, probability theory, and other fields. Together, mathematical and statistical methods enable efficient preprocessing, accurate modeling, reliable forecasting, and optimization. Their integration makes large‑scale data easier to process and analyze, ultimately supporting informed decision‑making across multiple domains.

Purpose: Research exists exploring prevalence of lower urinary tract symptoms (LUTS) in cisgender heterosexual women yet validated instruments have not been used to survey sexual and gender minority (SGM) people. Alongside LUTS measures, recently validated bladder health instruments were used in the RISE FOR HEALTH Study that included expanded demographic information of sexual orientation, gender identity, and sex assigned at birth questions. Materials and Methods: The RISE FOR HEALTH study is a population-based prospective cohort survey study of adults born female, recruited from a commercial marketing database. Participants who responded to questions identifying them as SGM people were compared with age-matched non-SGM participants. Chi-square and t tests were used for comparison between groups in general, and in the age-matched sample paired t tests, McNemar, and McNemar-Bowker tests were used. Results: Among 98% of participants who answered sexual and gender identity questions (3364 of 3424), 260 (8%) met sexual and gender subset criteria with a selected group of 260 non-SGM people participants for the age-matched comparison. The SGM participants had significantly lower bladder health scores and bladder function indices yet there were no significant differences in lower urinary symptoms between the SGM participants and the age matched non-SGM participants. Conclusions: In this study, SGM populations had bladder health and bladder function outcomes suggesting poorer bladder health and higher risk for LUTS compared with cisgender populations.

Retail businesses are increasingly using e-commerce platforms in the quickly changing digital age in order to reach a wider audience, increase operational effectiveness, and satisfy changing customer demands. For The Familiy Collection Store, a fashion and family accessory firm, to be competitive in a changing and difficult market, it must integrate e-commerce in a suitable and well-thought-out manner. The purpose of this study is to evaluate and create an e-commerce platform that is specifically suited to the requirements of The Familiy Collection Store's operations. A user-friendly and responsive interface design, quick and secure integration of a digital payment system, effective and real-time inventory management, and the application of data-based marketing strategies and consumer behavior to boost customer engagement are the primary goals in the development of this platform. In order to gather thorough and precise insights, this study's methodologies include a review of the literature on e-commerce, an analysis of current developments in the digital business, and in-depth interviews with important stakeholders. It is envisaged that by using this strategy, the created e-commerce platform will be able to improve customer happiness, attract a wider audience, fortify the brand, and significantly and sustainably contribute to the long-term success of the business.

Digitalization has emerged as a significant driver of change in business operations, improving efficiency, financial performance, and customer engagement. This study investigates the effects of digital adoption on business strategies, with a focus on cashless transactions, digital marketing, automated inventory management, and online ordering systems. A descriptive research design was used, combining quantitative and qualitative methods to evaluate digital integration in selected businesses in Cabanatuan City, Gapan City, and San Jose City, Nueva Ecija, Philippines. The findings show that businesses with higher levels of digitalization achieved 20% faster service times, a 15% increase in customer numbers, and a 10% reduction in operational costs compared to those using traditional practices. Despite these benefits, challenges such as high initial investment, employee resistance, and the need for operational adjustments hinder full digital adoption. The study emphasizes the importance of technology-driven management and suggests that businesses prioritize cost-effective digital tools, workforce training, and data-based marketing strategies. It also calls for further research on the long-term effects of digital transformation across different industries.

The bodywork industry in Indonesia is under high competitive pressure, requiring companies to be more adaptive in understanding customer behavior in order to maintain business continuity. PT. Bengawan Karya Sakti as one of the national bodywork companies, has not optimally utilized historical transaction data to assess customer loyalty. This study aims to identify customer loyalty segmentation through the application of the RFM (Recency, Frequency, Monetary) method, which is used to analyze sales transaction data in 2022 and 2023. The study uses the CRISP-DM approach which includes the stages of business understanding, data exploration, data cleaning and processing, modeling, evaluation, and implementation of results. The transaction data analyzed includes attributes of transaction date, customer, number of transactions, and transaction value, which are then processed into RFM scores based on the transaction year and classified into categories such as Very Loyal, Loyal, At Risk, and others. The segmentation results show an increase in the number of very loyal customers from 2022 to 2023, as well as a significant decrease in inactive and at-risk customers. The chi-square statistical test shows that the difference in customer distribution between years is statistically significant (p-value <0.05), indicating a real influence from the company's strategy or external factors. The main conclusion of this study is that the RFM method is effective in the bodywork industry to support data-based marketing decision making and more targeted customer retention strategies.

This study aims to group sales products in a coffee shop based on transaction data using the K-Means Clustering algorithm. The dataset from Kaggle.com includes the attributes product_id, transaction_qty, and unit_price. This method was chosen because of its ability to identify sales patterns in grouping products into three main clusters including high, medium, and low sales. The research process includes data collection, pre-processing, normalization, determining the optimal number of clusters, to evaluating the results using a Silhouette Score of 0.65. These results indicate that the K-Means method is effective in providing product segmentation that can be used as a basis for making business decisions, in optimizing stock and data-based marketing strategies.

Purpose: This insightful research developed into a forensic marketing and organisational effectiveness nexus. Specifically, forensic marketing was disaggregated into data-based marketing and marketing intelligence, while organisational effectiveness was measured by.Method: Eighty-four (84) bank executives of listed commercial banks were sampled using a well-structured questionnaire, while the Pearson Product Moment correlation (PPM) coefficient was used to analyse the data sourced.Result: Data-based marketing is positively and significantly related to organisational effectiveness (r=0.507, p<0.05). Also, marketing intelligence improves organisational effectiveness significantly (r=0.788, p<0.05).Conclusion: Forensic marketing (data-based marketing and marketing intelligence) are strategic tools for achieving organisational effectiveness.Recommendations: Bank executives are advised to place more attention on forensic marketing as it helps to reduce financial irregularities. Also, there is a need for Nigerian banks to invest more funds in data infrastructure and continuous training of bank utility staff in data analytics and, at the same time, integrate market intelligence into their strategic decision-making process.Originality/Contribution: The research is unique in positioning forensic marketing as both a fraud-mitigating and performance-inducing strategy. Also, the research offers an in-depth understanding of how data-driven marketing and marketing intelligence can serve not only as a tool for improving organisational performance but also as an efficient tool for reducing financial misconduct and organisational inefficiency. Lastly, the research originality centres on expanding the strategic scope of marketing beyond traditional promotional functions to cover a wider performance and risk management model.

Universities in Indonesia, especially in the East Nusa Tenggara region, face great challenges in attracting new prospective students amid increasingly fierce competition. For this reason, effective and innovative marketing strategies are needed to increase attractiveness and strengthen the competitive position of universities. One approach that can be implemented is the utilization of information technology in a digital-based new student admission system. A data-driven approach that relies on historical data analysis has also proven to be very effective in identifying targeted marketing potential. In this context, STIKOM Uyelindo Kupang can utilize data-driven forecasting methods, such as Simple Moving Average and Weighted Moving Average, to project areas with a focus on high schools and vocational schools that have the potential to generate new students at STIKOM Uyelindo Kupang. This method allows the college to focus resources on more potential areas and optimize its promotional activities. This research aims to develop a forecasting system for potential new student areas using the Simple Moving Average and Weighted Moving Average methods, which can provide more accurate information in designing data-based marketing strategies. Thus, it is that STIKOM Uyelindo Kupang can increase the number of new students, strengthen its position in the higher education market, and adapt to technological developments in supporting a more effective and efficient recruitment strategy.

The utilization of information and communication technology opens up great opportunities for MSMEs to expand their markets through digital platforms. BUMDESa Sido Makmur as a village-owned business entity has a strategic role in supporting the economic potential of MSMEs through empowerment programs. The products of MSMEs fostered by BUMDESa Sido Makmur have good quality and wide market potential but are still hampered by limited marketing access and inadequate promotional strategies. This community service activity aims to implement Smart Management through the use of the Shopee and Linktree platforms in optimizing digital marketing for MSMEs fostered by BUMDESa Sido Makmur. This training method involves two main stages, namely the smart management approach through Shopee to improve the quality of data-based marketing and the creation of Linktree to improve the connectivity and accessibility of product information. The results of this training show that the integration of Smart Management with the Shopee and Linktree platforms can have a major positive impact on the digital marketing of MSMEs fostered by BUMDESa Sido Makmur.

Introduction: Digital marketing has emerged as a crucial topic in research Promotion and marketing Contemporary, addressing different factors across multiple fields. This study aims to investigate the relationship between digital marketing and institutional excellence, as well as the moderating role of digital marketing strategies in this relationship. Using a quantitative research approach, data was collected from business organizations in Jordan, with the participation of 189 Participant, from friends and my manager These companies, contributed to the sample. Methodology followed: method was used Partial least squares structural equation modeling (PLS-SEM) In analytical procedures Main. Results: When studying The impact of digital marketing on achieving institutional excellence in Jordan, It was found that there was a statistically significant effect Between relying on digital marketing and achieving institutional excellence, Average​​Arithmetic (2.13) And deviation normative (0.86) On a big level (0.05). The value is high On a Likert scale. in the first place (Free and natural help to appear in search to improve web searches and thus the continuous development of the products/services offered) And he reached Average Year (2.29) and standard deviation (0.889). In the last order (Online marketing database allows - digital content anytime, anywhere.) On average​​ mathematics (2.01) and standard deviation (0.825). conclusion: This Results confirms that There is a statistical significance for digital marketing in achieving institutional excellence. And There is a moderate positive correlation between digital marketing and achieving institutional excellence (r=0.640) The impact of digital marketing in achieving institutional excellence was equal41%.

O marketing moderno visa entender as necessidades e desejos dos consumidores através da adoção das novas tecnologias disruptivas, como: Inteligência Artificial, algoritmos, chatbots, Internet das Coisas, Big Data dentre outros. Nesse cenário, as organizações buscam melhorar a experiência de compra dos clientes, com anúncios personalizados, recomendações e personalizações na entrega de produtos e/ou serviços no intuito de entender o perfil de consumo através do cruzamento de dados e informações disponíveis na web. Desse modo, o objetivo geral deste artigo é analisar o impacto da Inteligência Artificial nas estratégias e práticas das empresas no contexto do marketing moderno. Em relação à metodologia, o artigo divide-se em: revisão de literatura, exploratório e qualitativo. Na coleta dos dados foram analisadas 28 pesquisas entre livros, artigos, teses e dissertações referentes ao tema em questão. Conclui-se, portanto, que as principais tecnologias disruptivas oferecem, a curto prazo, um cenário exitoso para as organizações colocarem em prática a melhor experiência de consumo para os clientes. Por meio da Inteligência Artificial, é possível identificar o comportamento mais assertivo do consumidor tornando-se uma estratégia essencial para as empresas a fim de fortalecer a experiência de consumo e a hiperpersonalização no futuro. Palavras-Chave: Inteligência Artificial. Marketing Moderno. Marketing baseado em Dados. Marketing 6.0. Comportamento do Consumidor. Abstract: Modern marketing aims to understand consumers' needs and desires through the adoption of new disruptive technologies, such as: Artificial Intelligence, algorithms, chatbots, Internet of Things, Big Data, among others. In this scenario, organizations seek to improve customers' shopping experience, with personalized advertisements, recommendations and customizations in the delivery of products and/or services in order to understand the consumption profile through the crossing of data and information available on the web. Therefore, the general objective of this article is to analyze the impact of Artificial Intelligence on companies' strategies and practices in the context of modern marketing. Regarding methodology, the article is divided into: literature review, exploratory and qualitative. When collecting data, 28 research studies were analyzed, including books, articles, theses and dissertations relating to the topic in question. It is concluded, therefore, that the main disruptive technologies offer, in the short term, a successful scenario for organizations to put into practice the best consumer experience for customers. Through Artificial Intelligence, it is possible to identify the most assertive consumer behavior, becoming an essential strategy for companies to strengthen the consumer experience and hyperpersonalization in the future. Keywords: Artificial Intelligence. Modern Marketing. Data-based marketing. Marketing 6.0. Consumer Behavior.

This study aims to analyze the application of Business Intelligence (BI) using Tableau in the new student admission process at ABC University. Tableau is used to visualize admission data for the period 2021 to 2023, including the number of applicants, geographic distribution, and course preferences. The research methodology involves data collection, cleaning, and integration which is then visualized in an interactive dashboard. The results showed a decrease in the number of applicants during the study period, with the lowest applicants in 2024. Geographic distribution analysis shows that DKI Jakarta and West Java provinces still dominate, indicating the need for expansion in conducting promotions and also data-based marketing strategies. In addition, the shift in the interest of applicants from Communication Science study programs to Pharmacist and Management Professions is an important finding, indicating a changing trend in prospective students' preferences for the fields of Communication Science and Business. This study concludes that the implementation of BI using Tableau provides significant benefits in improving the efficiency of decision-making, expanding the range of admissions, and strengthening the competitiveness of ABC University amid changing educational trends. The findings contribute to the literature related to BI implementation in the education sector and recommend further development to optimize university management in the future

Universities face increasingly fierce competition in attracting new students amidst changes in technology and societal preferences. An effective service marketing strategy is the key to increasing competitiveness and maintaining the existence of higher education institutions. This research aims to identify relevant marketing strategies, analyze their success factors, and provide recommendations based on a literature review. Data was collected from various literature sources that discuss the main elements of service marketing, such as branding, digital marketing, and service quality, using content analysis methods. The research results show that appropriate market segmentation, customer relationship management (CRM), and the use of digital technology, such as social media and data-based marketing, are the main factors in increasing the attractiveness of higher education. Additionally, a strong branding strategy and improving service quality play an important role in building reputation and creating a positive experience for students. These findings underline the importance of marketing innovation integrated with technology and improving academic and non-academic services to strengthen institutional competitiveness in an increasingly dynamic higher education market.