Data-driven Marketing Research Articles

MARKETING PROCESSES MODELING USING INTEGRATED DYNAMIC MODELS

In the paper it solves the problem of modeling complex economic processes. There is presented an analytical review of economic models, their advantages and disadvantages. The use of integral models for simulation of nonlinear dynamic processes in marketing tasks is substantiated. The mathematical expressions for the writing of integral models in the form of multidimensional weighted functions are given. The computational method of identification of integral models in the form of multidimensional transient characteristics is developed with the help of measuring the reaction of the market to the input influence. The results of modeling of the advertising audience on the example of the advertising campaign of the higher educational institution are presented. Keywords: digital marketing, marketing model, nonlinear models, integral dynamic models DOI: 10.15276/mdt.2.1.2018.5 Korbicz, J. & Kościelny, J.M., (eds). (2010). Modeling, Diagnostics and Process Control: Implementation in the DiaSter System. Springer: Berlin. Balasubramanian, S., Gupta, S., Kamakura, W.A., & Wedel, M. (1998). Modeling large datasets in marketing. Statistica Neerlandica, 52 3, 303–324. Leeflang, P.S., & Wittink, D.R., (2000). Building models for marketing decisions: Past, present and future. International Journal for Research in Marketing 17, 105–126. 4. Doll, J., & Eisert, U. (2014). Business Model Development and Innovation, a Strategic Approach to Business Transformation. The Business Transformation Journal, 11, 7–15. Gassmann,O., Frankenberger, K., & Csik, M. (2015). The Business Model Navigator: 55 Models That Will Revolutionise Your Business. FT Press. Bishop, W. (1996). Strategic Marketing for the Digital Age. HarperBusiness. Celaya, J., Vazquez, J., & Rojas, M. (2014). How the new business models in the digital age have evolved, Kindle Edition. Oklander, M.A., Oklander, T.O., & Yashkina, O.I. (2017). Tsifroviy marketing – model marketingu XXI storichchya [Digital marketing – a model of marketing ХХІ century]. M.A. Oklander (Ed). Odesa: Astroprint [in Ukrainian]. Masri, M, & Pavlenko, V. (2016). Intelligent Technology of Nonlinear Dynamics Diagnostics using Volterra Kernels Moments. International journal of mathematical models and methods in applied sciences, 10, 158–165. Antoshchuk, S.H., & Fomin, O.O. (2017). Model marketynhu, yaka keruietsia danymy [Data-driven marketing model]. Marketynh i tsyfrovi tekhnolohii [Marketing and digital technology], 1 (2), 92–101 [in Ukrainian].

An impulse to exploit: the behavioral turn in data-driven marketing

ABSTRACTIndustry advocates argue that by tailoring services and commercial solicitations to match media users’ personal interests, data-driven marketing benefits both consumers and businesses. This article shows, however, that advertisers and marketers who are taking up ideas and techniques from behavioral economics tell their clients a very different story about the aims and use of digital marketing and consumer surveillance. Listening in on this discourse demonstrates that some digital marketers conceptualize their own practices as forms of social control, appropriating concepts from behavioral economics to identify consumers’ cognitive and affective biases and target their vulnerabilities. Behavioral economics recognizes that economic decisions are not simply dictated by rational self-interest; rather, such choices depend on cognitive heuristics and habits, and can be manipulated through the design of “choice architecture.” This article discusses implications of the behavioral turn in data-driven marketing for critical advertising scholars, public advocates, and regulators.

End-to-End Predictive Analytics and Optimization in Ingram Micro’s Two-Tier Distribution Business

Ingram Micro, the world’s largest distributor of technology products, operates in a high-volume low-margin environment. The company started its Business Intelligence and Analytics practice in North America in 2009. This group has since built and deployed a scalable, innovative price-optimization engine, a set of analytics applications to identify sales opportunities for Ingram Micro’s sales force and an integrated digital marketing platform to run data-driven marketing campaigns for its customers and end-user businesses. Since 2011, these products and analytics programs have generated $1.3 billion of incremental product revenue and $42 million of incremental gross profit. Our next steps are to continue to implement these best practices in regions outside of North America and continue our activities that enable our sales force to generate revenue.

A framework for increasing the value of predictive data-driven models by enriching problem domain characterization with novel features

The need to leverage knowledge through data mining has driven enterprises in a demand for more data. However, there is a gap between the availability of data and the application of extracted knowledge for improving decision support. In fact, more data do not necessarily imply better predictive data-driven marketing models, since it is often the case that the problem domain requires a deeper characterization. Aiming at such characterization, we propose a framework drawn on three feature selection strategies, where the goal is to unveil novel features that can effectively increase the value of data by providing a richer characterization of the problem domain. Such strategies involve encompassing context (e.g., social and economic variables), evaluating past history, and disaggregate the main problem into smaller but interesting subproblems. The framework is evaluated through an empirical analysis for a real bank telemarketing application, with the results proving the benefits of such approach, as the area under the receiver operating characteristic curve increased with each stage, improving previous model in terms of predictive performance.

O interdyscyplinarnym charakterze analitycznego CRM

The purpose of this article is to highlight the interdisciplinary nature of analytical CRM and its relationships with other disciplines, research approaches and procedures. The author attempts to locate this research approach relative to other related disciplines. He refers to the Anglo-American and Scandinavian schools of relationship marketing, database marketing, data-driven marketing, business intelligence and market research. The summary of this study is to define analytical CRM from the perspective of marketing research.

Data and creativity: Blessing or curse?

This article advocates the benefits to data-driven marketing of encouraging innovative personalities within the sector, and considers the practices and processes that need to be introduced within the sector for it to become a career where people with creative and disruptive personalities are enabled to thrive.

Global Review of Data-Driven Marketing and Advertising

This article provides the executive summary and high-level findings from ‘The Global Review of Data-Driven Marketing and Advertising’, published by GlobalDMA and Winterberry Group in November 2014. The research examines and benchmarks data-driven marketing and advertising priorities and investments across 17 global markets: Argentina, Australia, Belgium, Brazil, France, Germany, Hungary, India, Ireland, Italy, the Netherlands, New Zealand, Singapore, South Africa, Sweden, the United Kingdom and the United States.

Bootstrap Based Large Scale Data Processing Using Cluster

Cloud computing is model in which large groups of remote servers are networked to allow centralized data storage and online access to computer services or resources. Clouds can be classified as public, private. A corporate network is a group of computers, connected together in a building or in a particular area, which are all owned by the same. The corporate network is often used for sharing information among the participating companies and facilitating collaboration in a certain industry sector where companies share a common interest, there is so challenges and some security issues appeared .So in the proposed System it implement the Best Peer++, a system which delivers elastic data sharing services for corporate network applications in the cloud based on Best Peer—a peer-to-peer (P2P) based data management platform. A data management platform is the backbone of data-driven marketing, and serves as a unifying platform to collect, organize, and activate your first- and third-party audience data from any source, including online, offline, or mobile. A true Data Management Platform should have the ability to collect unstructured audience data from any source, including mobile web and app, web analytic tools, CRM, point of sale, social, online video, and other available offline data sources.

Getting to the bottom of Pandora's Box

This paper proposes that the consumer perspective has been overlooked in implementing Customer Relationship Marketing (CRM). Examples are given of how firms have ignored the consumer side of the CRM promise, misused customer data and failed to recognize and act upon the strategic implications of CRM. Correcting this is critical as firms move forward with data-driven marketing, in the light of the movement towards consumer empowerment. The paper explains how companies can use customer data to fulfil the neglected customer service promise and lighten the burden on consumers caused by excess marketing pressure while increasing profits.

How Can Marketing Academics Serve Marketing Practice? The New Marketing DNA as a Model for Marketing Education

This article seeks to address how marketing academics can best serve marketing practice through marketing education. It is contended that, where technology is driving marketing in practice, it is afforded significantly less attention in both theory and education. Thus, the marketing graduates being produced from universities are often lacking in the skills that 21st-century marketers require. Where the focus of the article is on marketing education, a broad analysis of the content of marketing textbooks and degree programs is presented and an “old Marketing DNA” presented. The study also adopted an inductive approach to data collection where the aim was to investigate the exact nature, constituency, and role of marketing in organizations. Qualitative in-depth interviews were undertaken with senior marketing managers and executives in U.K. organizations. Findings are organized into the areas of customer-led marketing, value-driven strategic marketing, channels, data-driven marketing, and online and off-line integrated marketing communications. The article concludes that there is a disconnect between marketing education and marketing practice and goes some way to recommending what the response of marketing academia should be through the “new Marketing DNA.” This article aims to inspire a holistic response from marketing educators to bring their practice more in line with what is actually being practiced by marketing practitioners in the 21st century.

Judge Says Prescribing Data Can't Be Marketing Fodder

Back to table of contents Previous article Next article Legal NewsFull AccessJudge Says Prescribing Data Can't Be Marketing FodderRich DalyRich DalySearch for more papers by this authorPublished Online:5 Jun 2009https://doi.org/10.1176/pn.44.11.0003A federal judge has upheld a Vermont law that bars the release of physicians' prescribing information to drug companies, which then use the information for marketing purposes.U.S. District Court Judge Garvan Murtha in April rejected a suit by“ data-mining” companies challenging the state law that bars access to prescribing records without consent of the prescribing physician.As part of the data-mining process, third-party companies purchase prescribing information from pharmacy chains and the companies that manage drug benefits for employers and then sell it to drug companies. Drug companies pair physicians' professional information obtained from the AMA's database of member and nonmember physicians with physician-specific prescribing data to tailor sales pitches to individual clinicians.In his decision in IMS v. Sorrel, Murtha also upheld the law's creation of an evidence-based education program for physician prescribers and creation of a consumer-fraud cause of action for advertisements printed, distributed, or sold in Vermont that violate federal law.The ruling was based in part on the input of the Vermont Medical Society, which said that the use of prescribing data to market to clinicians intrudes on the way physicians practice medicine and creates the “possibility that representatives could exert too much influence on prescription patterns.”Lawmakers crafting the measure cited evidence indicating that the use of prescriber profiles increased the cost of health care by fueling the marketing of only the most expensive brand-name medications.“As the court found, this evidence adequately demonstrates that prescription data privacy regulations promote substantial state interests in cutting prescription drug costs and promoting evidence-based prescribing,” said Sean Flynn of the Program on Information Justice and Intellectual Property, which filed an amicus brief in support of the state law on behalf of the Vermont Medical Society, AARP, and other patient-privacy advocates.The judge agreed with evidence that lawmakers cited in crafting the legislation indicating that data-driven marketing resulted in the prescription of newer medicines, which ran counter to evidence-based prescribing guidelines. He cited several specific examples of brand-name drugs that were widely prescribed over generic alternatives and were eventually pulled from the market after potentially lethal side effects were discovered.The impact on health care costs in Vermont resulting from marketing based on data mining was cited by state legislators who backed the measure. Bill supporters noted that drug makers had been spending an estimated $10 million annually on prescriber-focused marketing in Vermont.“This law certainly seems to return more control to physicians and gives them more awareness about what can or cannot happen to their patterns of prescribing,” said Jonathan Weker, M.D., secretary of the Vermont Psychiatric Association.Murtha's decision was based in part on his conclusion that a substantial state interest existed in restricting such commercial activity. Legislators had delayed the law's start date until July so that the courts could rule on its constitutionality.The case was consolidated with another lawsuit filed by the Pharmaceutical Research and Manufacturers of America (PhRMA), which sought to block part of the law requiring drug companies to pay a fee to support an“ evidence-based education” program for clinicians. The judge rejected PhRMA's argument that the provision unconstitutionally forced drug makers to fund a government-controlled message in which they had no input.Three of the data-mining companies that challenged the Vermont law said in a written statement that the ruling would cost patients in Vermont more money by restricting the companies' ability to access prescribing data, and the companies raised the possibility of appealing Murtha's ruling.The decision followed a federal appeals court ruling in November 2008 in the case IMS v. Ayotte, which upheld a New Hampshire law to restrict data mining (Psychiatric News, December 19, 2008). A similar Maine law, however, was overturned by a federal court in December 2007.The ruling inIMS v. Sorrellis posted at<www.prescriptionproject.org/tools/solutions_resources/files/0040.pdf>.▪ ISSUES NewArchived