MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

Marketing for management.

https://cronfa.swan.ac.uk/Record/cronfa54400/Download/54400__17763__d6602f13cc44449b8145bc15173fc903.pdf

Setting the future of digital and social media marketing research: Perspectives and research propositions

https://repositorio.fei.edu.br/bitstream/FEI/3436/1/Mattos_pdf

The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions

Using Data Sciences in Digital Marketing: Framework, methods, and performance metrics

Exponential technological expansion creates opportunities for competitive advantage by applying new data-oriented approaches to digital marketing practices. Machine learning (ML) can predict future developments and support decision-making by extracting insights from large amounts of generated data. This functionality greatly impacts and streamlines the strategic decision-making process of organizations. The research gap analysis revealed that a little is known about marketers’ attitude toward, and knowledge about, ML tools and their adoption and utilization to support strategic and operational management. The research presented here focuses on the selection and adoption of the ML-driven analytical tools by three distinct groups: marketing agencies, media companies, and advertisers. Qualitative and quantitative research was conducted on a sample of these organizations operating in Slovakia. The findings highlight: 1) the important role of intelligent analytical tools in the creation and deployment of marketing strategies; 2) the lack of knowledge about emerging technologies, such as ML and artificial intelligence (AI); 3) the potential application of the ML tools in marketing, and; 4) the low level of adoption and utilization of the ML-driven analytical tools in marketing management. A framework consisting of enablers and a process map was developed to help organizations identify the opportunities and successfully execute projects that are oriented toward the deployment and adoption of the analytical ML tools in digital marketing.

/pdf/towards-the-adoption-of-machine-learning-based-analytical-aum7ozewyd.pdf

Towards the Adoption of Machine Learning-Based Analytical Tools in Digital Marketing

Users as consumers of the content generated by publishers expect to receive a certain level of content quality and availability. However, consumers often do not accept the monetization schemes employed by publishers to ensure sufficient revenue streams to support their editorial work and infrastructure. To protect their privacy, a growing number of users utilize ad blockers that protect them from displaying third-party advertisements while browsing the internet and consuming the content. Content publishers are looking for ways of increasing their income through new subscription models and online advertising. In this paper, the authors introduce a framework that enables the publishers of digital content to utilize the potential of the online advertising revenue stream with respect to the preferences of their audience and the privacy protection practices applied by website users. An empirical research in the form of a case study analyzing 105 websites located in seven countries was conducted using the method of content analysis. The suggested framework consists of three main approaches that can be adopted by content publishers to optimize the effectiveness of their online advertising system and thus maximize the contribution of advertising sales revenues to the media budget.

/pdf/privacy-protection-versus-advertising-revenues-the-case-of-3sypd5lubx.pdf

Privacy Protection Versus Advertising Revenues: The Case of Content Publishers

The viewers' response to television advertising has changed dramatically over the past years. Search visibility of advertisers has become of paramount importance to ensure that communication messages are followed up appropriately, and that the specific brand is considered in the customer decision-making process. This paper examines the effectiveness of communication campaigns that include TV advertisements. Specifically, it determines if, and to what extent, the advertisers of selected Australian TV advertising campaigns are visible in full-text searches on Google for a variety of relevant keywords. The visibility of advertisers is measured as the number of keyword searches that result in a high ranking on the search engine results page, average ranking, and site visibility. The results revealed notable differences in the visibility of advertisers in searches. Enhancing their visibility represents a challenge for companies striving to optimise the delivery of their communication message(s) across the entire spectrum of traditional and online media.

/pdf/are-australian-tv-advertisers-aware-of-evolving-online-b55159v5eg.pdf

Are Australian TV Advertisers Aware of Evolving Online Information Search Patterns

Facebook is the most used social network in the world. It dedicates a lot of energy and resources to developing and fine-tuning its algorithms, thus enabling it to serve accurate content to eligible users and to fulfill the expectations of every entity that utilizes the platform. These algorithms need to evolve in time to adapt to the changing preferences of Facebook and its users. The evolution of the adjustments in the algorithms is a demanding process, mainly (but not only) because of the enormous number of its users. Changes need to be tested first, and this approach has been applied to the Explore Feed, which divides the Facebook News Feed into two sections. One section is for friends’ content only and the second is dedicated solely to the content of media and organizations. Slovakia represents one of the six countries where the test was executed. The aim of this article is to identify and summarize perceptions and feedback on the Explore Feed and to determine the consequences of similar tests for global firms. This paper presents the results of a survey devoted to an examination of the perceptions of the Facebook Explore Feed. Survey questions, collected answers, and an evaluation of the answers were conducted in cooperation (and consultation) with an independent local media publishing company and its website. This website was selected because of the demographic profile of its users who represent the target group who most frequently use the Facebook platform.

Martin Kuchta

Papers

Towards the Adoption of Machine Learning-Based Analytical Tools in Digital Marketing

Privacy Protection Versus Advertising Revenues: The Case of Content Publishers

Are Australian TV Advertisers Aware of Evolving Online Information Search Patterns

Facebook Explore Feed: Perception and Consequences of the Experiment

Influencer marketing taxonomy from a brand point of view