Data-driven Marketing Research Articles

Marketing Analytics: Driving Roi through Data-Driven Marketing Strategies

An organization’s ability to develop and execute strategy relies on its grasp of customer behavior, especially in today’s volatile business climate. Achieving market dominance relies on it. Consequently, customer centricity should permeate all aspect of a company’s operations. In order to assist businesses locate the “right” customers, retain and expand their customer base, and maintain growth and profitability, marketers must utilize big data through data driven marketing (DDM). Aiming to increase shareholder value through establishing “customer centricity” is the focus of this research, which also delves into DDM adoption techniques. The decision-making process has grown in significance with the advent of analytics and the raging digital era. Also essential to the process are intuition and judgment. Choosing the right thing to do isn’t something that can be done purely rationally. This study provides the answers to the research questions about how data analytics in one department affects that department and the company as a whole. To be more specific, it uses an information value chain technique to hypothesize the link between the marketing unit’s and the firm’s performance in terms of quality data and the sensing capabilities of IT- based analytics. Supporting the predictions, a survey of 346 companies found evidence of both direct and partially mediated effects on sensing capabilities, as well as partially mediated effects on quality data.

Agencing the digitalised marketer: Exploring the boundary workers at the cross-road of (e)merging markets

In this paper, we study the formation of a new market actor, the digitalised marketer, which emerges at the boundary between strategy- and data-driven marketing. Building on constructivist market studies, we draw attention to the notion of agencing as boundary work and the range of boundary workers in the agencement of which the marketer is part. Drawing on 63 interviews with marketing professionals from multiple contexts, we reveal the difficulties to keep a pace with the plethora of digital marketing tools and highlight the emerging ‘market for digital marketing’ as a key device in the agencing of the digitalised marketer. We present two modes of agencing work, prosthetic and habilitative, to conceptualise how digitalised markets and platforms concurrently enable and captivate marketers’ agency, but also how marketers and their peer networks contest these limits and expand the space for action. This contribution serves to extend the recognised need to reconnect marketing with markets, to also acknowledge how markets are connected to the shaping of marketing and its actors. Implications for theory, practice and marketing education are discussed as we seek to capacitate marketers to operate in an increasingly digitalised environment.

Green Agricultural Products Supply Chain Subsidy Scheme with Green Traceability and Data-Driven Marketing of the Platform

Government subsidies have played an important role in the development of green agriculture. In addition, the Internet platform is becoming a new channel to realize green traceability and promote the sale of agricultural products. In this context, we consider a two-level green agricultural products supply chain (GAPSC) consisting of one supplier and one Internet platform. The supplier makes green R&D investments to produce green agricultural products along with conventional agricultural products, and the platform implements green traceability and data-driven marketing. The differential game models are established under four government subsidy scenarios: no subsidy (NS), consumer subsidy (CS), supplier subsidy (SS), and supplier subsidy with green traceability cost-sharing (TSS). Then, the optimal feedback strategies under each subsidy scenario are derived using Bellman's continuous dynamic programming theory. The comparative static analyses of key parameters are given, and the comparisons among different subsidy scenarios are conducted. Numerical examples are employed to obtain more management insights. The results show that the CS strategy is effective only if the competition intensity between two types of products is below a certain threshold. Compared to the NS scenario, the SS strategy can always improve the supplier's green R&D level, the greenness level, market demand for green agricultural products, and the system's utility. The TSS strategy can build on the SS strategy to further enhance the green traceability level of the platform and the greenness level and demand for green agricultural products due to the advantage of the cost-sharing mechanism. Accordingly, a win-win situation for both parties can be realized under the TSS strategy. However, the positive effect of the cost-sharing mechanism will be weakened as the supplier subsidy increases. Moreover, compared to three other scenarios, the increase in the environmental concern of the platform has a more significant negative impact on the TSS strategy.

Marketing Education Renaissance Through Big Data Curriculum: Developing Marketing Expertise Using AI Large Language Models

Utilising big data sources and artificial intelligence (AI) tools with marketing activities and analysis contrast with questionnaires and small n observations, essentially creating a renaissance in marketing education. As a result, marketing education keeps pace with AI developments and ensures learners (or students) prepare for the demands of the modern marketing landscape 2025-30. The authors advocate a central focus on a big data-driven marketing curriculum for marketing education. Such a curriculum places AI and machine learning center stage to help understand, analyze and utilize large and complex marketing datasets for predictive marketing. In doing so, the potential exists for practitioners to link marketing strategy directly with marketing execution, allowing learners to use big data and AI for upstream strategy design and marketing plan development while downstream predicting the results of marketing campaigns, programs, and initiatives But necessary changes in pedagogy are creating adaptive learning experiences breaking free from traditional assessments In our model of learning educators enable the development of practical marketing expertise using the techniques and tools of micro-testing to nudge learners using Python data science notebooks. Overall, a renaissance in marketing education is made possible with a focus on a big data AI tools-driven curriculum. Such attention ensures learners prepare for the demands of the modern marketing landscape, moving well beyond marketing analytics using the AI technologies of Large Language Models, further expanding the use of big data Learners use role play, witnessing firsthand experiences fulfilling new hitherto emerging marketing roles By 2025, Educators fostering a big data AI-focused marketing education curriculum ensure the next generation of AI marketers will eagerly shape the future of marketing practice and behavior with new roles combining human work with AI.

Decisions of pricing and delivery-lead-time in dual-channel supply chains with data-driven marketing using internal financing and contract coordination

PurposeThe purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven marketing (DDM) quality, cross-channel-return (CCR) rate and financing interest rate on the members' pricing and delivery-lead-time decisions and optimal performances, and analyzes `how to achieve the coordination within a dual-channel supply chain (DSC) by contract coordination.Design/methodology/approachThis work establishes a DSC model with DDM, and the offline retailer can provide internal financing to the capital-constrained online manufacturer. The demand under the price is determined based on DDM quality, customer channel preference and delivery lead time. Then, combined with the Stackelberg game, the optimal pricing and delivery-lead-time decisions are discussed under the inconsistent and consistent pricing strategies with decentralized and centralized systems. Furthermore, it designs a manufacturer-revenue sharing contract to coordinate the members under the two pricing strategies.Findings(1) The increase of DDM quality will reduce the delivery-lead-time under the inconsistent or consistent pricing strategy and will push the selling prices; (2) The growth of the CCR rate will raise selling prices and extend the delivery-lead-time under the decentralized decision; (3) Under price competition, the offline selling price is higher than the online selling price when customers prefer the offline channel and vice versa; (4) The retailer and the manufacturer can achieve a win-win situation through a manufacturer-revenue sharing contract.Originality/valueThis paper contributes to the studies related to DSC by investigating pricing and delivery-lead-time decisions based on DDM, CCR, internal financing and supply chain contract and proposes some managerial implications.

Harnessing Big Data Processing in Computer Networks for Digital Marketing Entrepreneurship

This research investigates the integration of big data processing in computer networks for digital marketing entrepreneurship to optimize marketing strategies and drive business growth. By analyzing current digital marketing practices, we identify key challenges faced by entrepreneurs. Through examining successful case studies, we showcase the effectiveness of big data processing in marketing campaigns. A practical framework is developed to guide startups and small businesses in integrating big data processing into their marketing strategies, considering factors like customer behavior analysis, segmentation, and personalized marketing. Additionally, we explore scalability and cost-effectiveness concerns, particularly relevant for entrepreneurs with limited resources. Ethical implications of data collection, processing, and utilization are thoroughly examined, and strategies to address challenges and limitations are proposed. Through comparative analysis, we assess the performance of big data-driven marketing campaigns in comparison to traditional approaches, revealing improved outcomes and return on investment. This research provides entrepreneurs with valuable insights and recommendations, empowering them to make data-driven decisions and succeed in the dynamic world of digital marketing. Moreover, it contributes to the discourse on big data in entrepreneurship, promoting responsible and innovative practices in the digital marketing landscape.

Artificial Intelligence in Communication with Music Fans: An Example from South Korea

According to Kotler, Kartajaya, and Setiawan, there are five components of marketing 5.0: it is data-driven, predictive, contextual, augmented, and agile. This paper uses the case study method to investigate the presence of the 5.0 marketing components in promotional strategies employed by the South Korean popular music industry. The paper explores promotional strategies used by the BTS music group in particular. The group uses the 5.0 marketing method in its promotional strategies, especially in communication with the fans, and such communication thus enters the field of public relations. The case study analysis also indicates the use of data-driven marketing and predictive analytics, which are achieved using artificial intelligence. Additionally, elements of contextual marketing were used to improve the consumer experience, and augmented marketing was utilized to facilitate business, especially for front office staff. Finally, the analysis of BTS's promotional strategies shows a focus on innovation and flexibility, which are elements of agile marketing.

The ‘dark side’ of data–driven marketing: a system’s thinking analysis

ABSTRACT Data-driven marketing has become a prominent strategic marketing approach, but it is prone to complex challenges, often referred as its dark side. The literature on data-driven marketing is dominated by its positive aspects, but there is an emerging literature stream focussing on its challenges. This study aims at contributing to this literature stream by providing an empirical study involving a holistic analysis of the undesirable effects of data-driven marketing using a systems thinking approach. The challenges faced by a New Zealand university in its international marketing using data-driven marketing is used as a case. Using 23 interviews, a systems model was developed, capturing the underlying structure behind these challenges. Eight interacting feedback loops were identified in the model, responsible for these complex challenges. A focus group was used to formulate three strategic interventions to address the complex challenges facing this organisation involved in data-driven marketing.

Government Subsidy Policy and Online Selling Strategy in a Platform Supply Chain with Green R&D and DDM Activities

Many governments actively subsidize the green activities of manufacturers and consumers to effectively realize the achievement of carbon emissions peak and carbon-neutral goals, while the development of a platform economy can effectively contribute to sustainable development. Therefore, we have modeled a platform supply chain using game theory, in which the manufacturer conducts green research and development (R&D) activities, the third-party platform conducts data-driven marketing (DDM) activities to promote green products, and all consumers have green preferences. The numerical example and empirical analysis methods are used to mine management insights. The government subsidizes the manufacturer’s green R&D, the third-party platform’s DDM, and the consumers’ green consumption. The third-party platform provides an agency selling or reselling strategy to sell products. Our results show that: (1) the sensitivity coefficient of consumers to green R&D and DDM activities has positive impacts on all members’ profits and on the green R&D level of products in the platform supply chain, with three kinds of government subsidy policies. (2) The levels of the three kinds of government subsidies mainly have an impact on all members’ profits and on the green R&D level of products in the platform supply chain with an agency selling or reselling strategy; government subsidies to the manufacturer are more conducive to improving the green R&D level of products. (3) The levels of the three government subsidies and the unit service commissioning fee for selling products are the main factors affecting the preferred selling strategy of each member and the equilibrium of the selling strategy.

Privacy controls as an information source to reduce data poisoning in artificial intelligence-powered personalization

The latest advances in data-driven marketing, such as real-time personalization, have increasingly made consumers more vulnerable. In response, some consumers deliberately falsify information in order to redress the balance of power, a practice that constitutes a serious threat to the digital economy. The topic of falsification is still largely under-researched in information systems and marketing. Based on protection motivation theory, the author conceptualizes privacy controls as a source of information and the falsification of information as a coping response, with vulnerability representing the threat appraisal mechanism and self-efficacy the coping appraisal mechanism. Through a within-subject experiment (n = 207), the results of the mediation analysis for repeated measures show that the effect of privacy controls as a source of information on the falsification of information is fully mediated by vulnerability and self-efficacy. The author provides insights for managers regarding the significant trade-off between reducing consumer vulnerability and maintaining the usefulness of the data.

Green R&D Financing Strategy in Platform Supply Chain with Data-Driven Marketing

Platform enterprises can improve green R&D efficiency by data-driven marketing (DDM) activities and can also provide financing assistance to manufacturers. In this context, for a platform supply chain consisting of one manufacturer facing a shortage of green R&D funds and a one third-party platform, this paper develops four game models under two financing channels (bank financing channel and platform financing channel) and two selling modes (agency selling mode and reselling mode). The equilibrium results of different models are derived and compared, and then the choices of selling mode and financing channel from the perspectives of both the manufacturer and the platform are analyzed. The conclusions show that the consumers’ sensitivities to green R&D and DDM activities, as well as service commission fee, are major factors influencing green R&D level and both parties’ choice of selling mode and financing channel. In most cases, a platform financing channel can promote the green R&D level better and is more beneficial to the manufacturer and the platform. Only in a few cases, the two parties prefer the reselling mode and bank financing channel. However, agent selling with bank financing will never be their optimal strategy. There exists four situations in which the manufacturer and the platform can agree on a same strategy on selling mode and financing channel.

Researching on Data Culture and Its Application in Solving Organizational Problems

The volume of data that individuals & businesses create tends to increase rapidly, leading to the challenge of how to leverage them to create real value? That's why more and more businesses are engaged in pursuing Data Culture & orienting it to become the number one priority (according to Gartner's survey). However, the transition from instinct-driven decision-making to data-driven decision making is not an easy process. From culture to logistics, there are countless barriers that organizations must navigate in order to make optimal use of cultural data to their benefit. This Paper is based in the following Research Design. It first seeked the theoretical framework on Data-Driven Culture, Data-Driven Marketing and its importance in an Organization. Then, via the application of Data Analytics – An application that analyzes data to identify problems and solutions, the Paper then proposes this data as the backbone for all activities and decisions in the process of planning, implementing, and optimizing operations. Thirdly, it researches a sample case study of Common types of data in Performance Marketing and Marketing data analysis process. The study has shown very significant results. One of the primary outcomes of this research is to find out the definition of Data Driven Culture, Data-Driven Marketing and related theorectical framworks. In addition, the findings showed a Case Study of Performance Marketing which reveals the Data Driven Culture, Data-Driven Marketing and its applications for business decison making and for Enterprises problems solving. Keywords: Data-driven culture, data-driven marketing, performance marketing, data-driven decision making

Marketing competency, marketing innovation and sustainable competitive advantage of small and medium enterprises (SMEs): a mixed-method analysis

PurposeThe purpose of the current research is to investigate the relationship between marketing capabilities and marketing innovation toward the sustainable competitive advantage of small and medium enterprises in the Philippines. The research study aims to improve the prior conducted literature by concentrating on the precursors of innovation in marketing and its impact on building a sustainable competitive market. The paper intends to address this by examining the following variables using a mixed-method approach.Design/methodology/approachThe researcher employed the mixed methods particularly the sequential explanatory design to explain and interpret the quantitative data collected from 89 business owners/managers using Jamovi Software while the qualitative data were collected through an in-depth interview conducted with 10 SME owner-managers of new and established businesses in Angeles City, Pampanga using Taxonomic Coding Scheme. The sequential explanatory design was used to explain and interpret quantitative results by collecting and analyzing follow-up qualitative data.FindingsThis study investigates the relationship between marketing capabilities and marketing innovation towards sustainable competitive advantage of micro-small and medium enterprises in the Philippines through mixed method approach. For quantitative result, the study found that marketing competency significantly influenced marketing innovation. The result shows that all SMEs have enough people in place who are capable of implementing marketing innovation activities and use new technology like the use of information technology. The paper also found that marketing innovation, significantly predicted sustainable competitive advantage. MSMEs exhibit this innovation such as product, price, place, and promotion can create a distinctive position in the market towards sustainable competitive advantage. The paper also tested the mediation effect of marketing innovation that influences the relationship between marketing competence and sustainable competitive advantage. Most of the hypotheses posited were supported. For qualitative data, it was revealed that these SMEs through their key informants and key leaders are open to innovations thus, willing to learn by establishing networks with customers and other managers/business owners to expand and improve their business. The food business in Pampanga is highly competitive, and most of the SMEs are engaged with it. In order to survive the saturated market, continuous improvement is important in the identified areas for growth and innovation. Mixed method analysis supported quantitative and qualitative findings. Hence, it indicated that marketing competency significantly influences sustainable competitive advantage, which can be achieved through marketing innovation. In this study, the researcher analyzed the influence between marketing competence and marketing innovation to achieve a sustainable and competitive market.Research limitations/implicationsThere were certain limitations of this research study. First, the lack of panel data limits the investigation of causality that is instrumental in substantiating the findings. Second, the proposed conceptual framework offers a deeper understanding of innovation performance, examining how integrating activities of the R&D department, human resource department, and marketing department affect innovation commercialization will likely provide more meaningful insights. Moreover, finally, future studies may go beyond the scope of our study to examine (1) food and meat processing, (2) agriculture, hunting, and forestry, (3) hotels and restaurants, (4) mining and quarrying, (5) wholesale and retail trade, (6) transport, storage communication.Practical implicationsTo remain relevant in this extraordinary time, this paper suggests a support instrument to offer vital data on different categories of innovation to the foodservice sector SMEs in Angeles City to embrace and implement new innovative methods in their practices. The key practical implication of this research, therefore, is the requirement for small and medium business owner-managers to improve their technical capability to realize the full benefits, particularly in terms of more responsive and user-centered, data-driven marketing personnel.Social implicationsThese findings may influence positive social change by contributing to more effective and efficient marketing practices in small and medium firms that can lead to better financial performance, higher survival rates, and a healthier economic system. This study demonstrates that SME owner-managers require new skillsets to overcome the barriers to adopting technology for marketing. This primary capability is a prerequisite to the competitive advantage of the business, yielding to brand equity, business growth, and marketing dominance.Originality/valueThis study used a sequential explanatory mixed-methods strategy to determine the significant variables. This paper addresses an interesting and practical issue related to the impact of marketing capabilities and marketing innovation towards sustainable competitive advantage of micro-small and medium enterprises in the Philippines using mixed method approach.

Green Technology Investment with Data-Driven Marketing and Government Subsidy in a Platform Supply Chain

Expanding green consumption market and precise data promotion advantages make the platform economy have a significant effect on influencing manufacturers to carry out green R&D and production activities, and government subsidies have a positive incentive effect. In this context, for the studies about platform supply chain management with manufacturer’s green production and the platform’s marketing activities simultaneously are rare, we consider that a manufacturer invests in green technologies to produce products and sell them through a smart platform supply chain by an agency selling or reselling strategy, in which the platform provides data-driven marketing technology to promote green products. Four game models are constructed to study the operational efficiency of the platform supply chain considering selling strategy difference and government subsidy. The results show that: (1) The manufacturer’s green technology and the platform’s data-driven marketing levels, as well as all member’s profits are all influenced by the potential market demand of green products, the sensitivities of consumers to green product attributes, and data analysis technology. (2) The service commission rate charged by the platform plays a main role on the manufacturer’s selling strategy choice, when the service commission rate is low, the manufacturer chooses an agency selling strategy and can obtain more profit, but now the green technology level is not necessarily better than that in the reselling system. With the service commission rate increases, a manufacturer that chooses the reselling strategy can obtain more profit, and the green technology level is better than in the agency selling system. (3) Government subsidy can effectively encourage the manufacturer to improve the green technology level, and now the platform will improve the data-driven marketing level. There is a threshold range of the service commission rate charged by the platform in which the government can guide the manufacturer and the platform to reach an equilibrium selling strategy by regulating the subsidy level.

A New Approach in Marketing Research: Identifying the Customer Expected Value through Machine Learning and Big Data Analysis in the Tourism Industry

With the advent of the digital age and its entry into the business environment, marketing trends have undergone several changes, such as the expansion of data-driven marketing and the digitalization of the business environment that requires further investigation. As a result, the aim of this study is to present a novel approach in marketing research and identify value components among the large volume of customer feedback in virtual networks using machine learning, big data analysis, and a predictive marketing strategy. This research is applied in terms of purpose, qualitative-quantitative (mixed) in terms of method and descriptive-survey in terms of data collection that has used an inductive approach. For this purpose, the Iranian tourism industry and tourist areas of Tehran province was selected as a case study and 9325 comments from customers about hotels used in their travels to Tehran were collected from the Internet between the summer of 2020 to winter 2021 and using "data clustering" and "Association Rules Extraction" methods, the value components were extracted and RapidMiner software and Python programming language were used to perform data mining, text mining and big data analysis processes. In summary, the findings demonstrate that by employing big data analysis and machine learning, the process of "marketing research" can be performed with greater speed, accuracy, and extensiveness, as well as at a lower relative cost. The findings and suggestions of this study are used to inform marketing researchers, as well as to raise the awareness of managers, especially in hotel industry.

An Expert Systems Journey—Red Pepper and Blue Martini

This article traces my journey building expert systems and bringing them into the business world. I started out learning about rule-based systems at Carnegie Mellon in the 1970s and implementing constraint-based systems at NASA and MITRE in the 1980s. I built upon this early experience to co-found Red Pepper Software, a company that specialized in planning and scheduling manufacturing tasks. Following Red Peppers success, I founded my second startup, Blue Martini, which used machine learning to enhance e-commerce businesses. Since the arrival of Big Data in the 21st century, Ive watched the industry transform, and was a part of the data-driven marketing revolution at Rocket Fuel. Throughout my career, my work has centered on expert systems and how they can be used to help people. This is the story of my journey, and the evolution of AI in business

A Systematic Mapping Study of Digital Marketing and Large Manufacturing Firms: Perspective from Japan

The very rapid development of ICT in the digital era has an impact on various lines of life, including changes in consumer behavior in shopping. Business people need to know the proper use of digital marketing in order to effectively target appropriate consumers. Digital marketing describes the use of technology in marketing efforts and business practices by marketing goods, services, information, and ideas via the internet, cell phones, display advertisements, and other electronic media. Data-driven marketing uncovers a variety of tactics to approach, attract, resuscitate, delight, and drive customers to online marketing. Digital marketing facilitates many-to-many communications because of the high level of connectivity and is usually used to promote products or services in a timely, relevant, more personal, and cost-effective manner. Marketing activities are carried out intensively using digital media, from promotions or product offers to product sales. Today, a website is arguably the most crucial element of your entire marketing strategy. Even a simple site without a lead capturing process or sales page will be consulted as a digital business card before a deal is struck or a purchase is made. For this reason, overhauling outdated designs to keep up with industry standards is a no-brainer. Traditional advertising is not completely dead yet. Manufacturers still use formal events like trade shows to good effect, and often spend on TV spots, magazines, and other traditional media forms. Based on the available literature, the old method of print advertising and radio ads still work but they are becoming less effective as people look to online sources for their shopping. Manufacturing companies still use these old school methods like networking events and trade shows and they still produce results. Keywords: Systematic mapping, Digital Marketing, Manufacturing, Industrial Revolution.

Analytics Capability in Marketing Education: A Practice-Informed Model

As marketing continues to be transformed by technology and the explosion of big data, academic research has identified a significant need for analytics skills in marketing education. However, it is unclear whether current curriculum approaches to marketing analytics equip students with the skills employers need and prepare them effectively for data-driven marketing roles. This study identifies the knowledge and skills marketing graduates require for analytics practice to bridge the theory-practice gap and increase students’ employability. Our research reveals that a blend of knowledge, soft and technical skills is needed, and that the ability to communicate insights from data to stakeholders is critical. We offer a practice-informed model which demonstrates that conceptual knowledge, technical skills, tools skills and soft skills are required to develop holistic analytics capability for marketing practice. Actionable takeaways for how educators can embed holistic analytics teaching in marketing education are also provided.

BlockChain (BC), Technology Notary in Data Driven Marketing (DDM) Contracts

BlockChain (BC), Technology Notary in Data Driven Marketing (DDM) Contracts

Determinants of online shopping addiction among Vietnamese university students

ABSTRACT Online shopping addiction, which refers to the inability to take an individual’s online shopping urges under control has attracted a great deal of research interest over the last decade, given the prevalence of internet technologies and the advent of data-driven marketing strategies in e-commerce. The current study sought to examine the determining factors that can potentially result in online shopping addiction among Vietnamese university students. We found a strong correlation presented between daily online shopping frequency and daily internet shopping usage. Results from the hierarchical analysis indicate that internet experience has a significant negative effect on online shopping addiction. Besides, time spent on internet shopping per day and daily internet shopping frequency has the significant effect on the score of online shopping addiction. Students are recommended to manage their online routine wisely and efficiently to avoid detrimental consequences resulted from online shopping addiction.