Relevant bibliographies by topics / Big data in marketing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Big data in marketing'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Big data in marketing"

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Simakina, M. "Features of using Big Data technologies in marketing." Bulletin of Science and Practice 4, no. 6 (2018): 255–60. https://doi.org/10.5281/zenodo.1289864.

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The article discusses the applicability of Big Data technologies in modern marketing. The author analyzes the problems, limitations and risks of their application in practice. As a director of development of Big Data in marketing, the author focuses on Smart Data technologies.
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Graczyk-Kucharska, Magdalena. "Big Data as a Necessity of Modern Marketing." Zeszyty Naukowe Uniwersytetu Szczecińskiego. Problemy Zarządzania, Finansów i Marketingu 41 (2015): 265–78. http://dx.doi.org/10.18276/pzfm.2015.41/2-22.

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Pinarbasi, Fatih, and Zehra Nur Canbolat. "Big data in marketing literature." International Journal of Business Ecosystem & Strategy (2687-2293) 1, no. 2 (2019): 15–24. http://dx.doi.org/10.36096/ijbes.v1i2.107.

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The concept of big data is one of the important issues in business decision making in recent years. The expansion of social media platforms, the increase in data production devices and the evaluation and interpretation of the data produced by developing technology become crucial. Previous studies in the big data area have addressed the issue in limited contexts, and there are few studies in the field of marketing with a bibliometric approach. This study, which aims to examine how big data concept is evaluated in marketing literature, examines the publications on big data in indexed marketing j
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Matthew, N. O. Sadiku, C. Chukwu Uwakwe, Ajayi-Majebi Abayomi, and M. Musa Sarhan. "Big Data in Industry: An Overview." Journal of Scientific and Engineering Research 8, no. 8 (2021): 144–52. https://doi.org/10.5281/zenodo.10612339.

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<strong>Abstract</strong> With the rise of digital technology, big data has remarkably revolutionized the industry standards. Big data refers to large, hard-to-manage volumes of data, both structured and unstructured.&nbsp; The marketing and sales of any industry largely depend on how data is used.&nbsp; Industries that are improving their services through big data include healthcare, manufacturing, agriculture, telecommunications, retail, fitness, travel, finance, e-commerce, entertainment, banking, oil and gas, sports, and social media. This paper is an overview on the application of big dat
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Chasovskikh, V. P., and Е. V. Koch. "THE USE OF BIG DATA IN MARKETING RESEARCH." International Journal of Applied and Fundamental Research (Международный журнал прикладных и фундаментальных исследований), no. 3 2023 (2023): 47–50. http://dx.doi.org/10.17513/mjpfi.13521.

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Zheng, Shi, Xia Jin, and Wen Zheng. "Big Data Usage in Marketing Research." Frontiers in Business, Economics and Management 5, no. 3 (2022): 242–48. http://dx.doi.org/10.54097/fbem.v5i3.2029.

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In the marketing field, the use of big data in research can make us understand consumer deeply. In some areas of market research, big data is already established today. The social media analytics and the use of cookie data to measure internet coverage are two prominent examples. This essay combs through relevant literatures, discusses the big data uses in the marketing research and its contribution for decision-making. It presents a revision of main concepts about marketing research, the new possibilities of use and a reflection about limitations of big data in the marketing research.
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Diesperova, Natal'ya. "CAPABILITIES AND LIMITATIONS OF BIG DATA IN MARKETING." Russian Journal of Management 8, no. 4 (2021): 16–20. http://dx.doi.org/10.29039/2409-6024-2020-8-4-16-20.

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Using of Big Data increases the efficiency of solving of marketing tasks, including drawing up a portrait of a consumer and building communication with him, based on the analysis of information from social networks (Facebook) and search engines (Google). An assessment of the capabilities and limitations of these technologies showed that the use of Big Data doesn’t always provide the absolute best marketing solutions. Therefore, the use of Big Data seems to be justified in marketing only in a number of areas, directed by a professional marketer, for whom Big Data technologies are an effective t
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Mamlouk, Lamia, and Olivier Segard. "Big Data and Intrusiveness: Marketing Issues." Indian Journal of Science and Technology 8, S4 (2015): 189. http://dx.doi.org/10.17485/ijst/2015/v8is4/71219.

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Zanella-Martínez, Leonardo Mauricio, Fidel Ricardo Chiriboga-Mendoza, and Enrique Cristóbal Zambrano-Pilay. "Big data y marketing de experiencias." Revista Científica Arbitrada de Investigación en Comunicación, Marketing y Empresa REICOMUNICAR 2, no. 3 (2019): 15–22. http://dx.doi.org/10.46296/rc.v2i3.0034.

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Hoy por hoy, con el auge del internet y de la era digital, las empresas tienen el deber de adaptar sus estrategias y sistemas metodológicos de comercio para lograr crear y mantener la competitividad en los mercados existentes. En este marco contextual, el marketing de experiencias es una de las formas del marketing contemporáneo que busca crear dependencia a través de determinado producto o servicio en los consumidores, ofreciendo recursos empíricos para crear preferencias en los consumidores de una marca con respecto a otra marca. El marketing de experiencias, siendo una de las tantas formas
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Wu, Yiheng. "BIG DATA PROJECT - BANK MARKETING CAMPAIGN." European Journal of Economics and Management Sciences, no. 2 (2021): 3–15. http://dx.doi.org/10.29013/ejems-21-2-3-15.

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Dissertations / Theses on the topic "Big data in marketing"

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Liu, Xiao. "Marketing Solutions Enabled by Big Data Using Structural Models." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/512.

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Digital marketing has brought in enormous capture of consumer data. In quantitative marketing, researchers have adopted structural models to explain the (dynamic) decision process and incentives of consumers. However, due to computational burdens, structural models have rarely been applied to big data. Machine learning algorithms that perform well on big data, however, hardly have any theoretical support. Equipped with both economics perspective and machine leaning techniques, in this dissertation, I aim to combine rigorous economic theory with machine learning methods and apply them to data o
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Nybacka, A. (Aino). "Privacy concerns of consumers in big data management for marketing purposes:an integrative literature review." Bachelor's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201605261989.

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This bachelor’s thesis is a literature review about big data, privacy concerns for individual consumers and how these two overlap together in a way to possibly explain what are the privacy concerns that customers have, and the companies maybe should think about, when they utilize data as a marketing tool. The thesis introduces an integrative framework for the privacy concerns emerging from the process of big data management for marketing purposes and gives insights for phases in this process first separately from companies point of view, then from the consumers point of view regarding the pri
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Brauer, Jimmy, and Eriksson Björn Linnala. "Blockchain's influence on digital marketing : An exploratory study examining blockchain in relation to big data and digital marketing." Thesis, Umeå universitet, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172806.

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Today's society has grown to be highly digitalized where technologies are playing a large role in everyone's lives. Moreover, society is still developing at a rapid pace, with a new innovation around every corner and with more and more business conducted online. By using this as a starting point, the authors of this thesis choose to examine how blockchain can influence the use of big data in digital marketing. Moreover, as previous articles have perceived GDPR as an obstacle for implementing blockchain within this context, the authors perceived it as necessary to examine blockchains’ relation
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Nybacka, A. (Aino). "The role of consumers’ knowledge and attitudes in determining the importance of privacy in big data marketing." Master's thesis, University of Oulu, 2018. http://urn.fi/URN:NBN:fi:oulu-201806062496.

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The world has changed due to the digital revolution and this means that the marketing environment has changed and that it has to keep changing. Even though the data has always existed and been a part of marketing, due to this digital revolution the marketing done based on customer data has evolved immensely as well. Big data offers marketers opportunities that seem endless, due to the exponentially growing amount of data and the new innovations that are made to harness it, but what has to be remembered is that big data marketing is not a solution without its problems. In this research we fo
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Dervan, Philip. "Social networking theory and the rise of digital marketing in the light of big data." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/378356/.

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The topic of this thesis is the use of ‘Big Data’ as a catalyst for true precision target marketing, where online advertisements across all communication channels are so timely and relevant that they are welcomed by the consumer because they improve the customer experience. In particular, the research has been directed to demonstrate the link between investment in digital branding and sales revenue at the company level. This thesis includes a review of the accumulation of ‘Big Data’ from a plethora of social networks, and an assessment of its current use and application by marketing and sales
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Gibson, Scott D. "Advertising planning in the age of big data. An exploratory study." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/122469/1/Scott_Gibson_Thesis.pdf.

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The impact that big data has on relationships between advertising agencies and clients is explored from the planning perspective. Using diffusion of innovations theory, findings indicate that the complexities and expectations associated with using data in advertising decision-making both inhibits and accelerates its use. Clients are attracted to the promise of competitive advantage, driving agencies to respond, often with short-term gains at the expense of long-term brand building. Planners develop advertising strategies primarily using traditional research. However those who can meaningfully
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De, Koker Louise. "Fostering collaboration amongst business intelligence, business decision makers and statisticians for the optimal use of big data in marketing strategies." University of the Western Cape, 2019. http://hdl.handle.net/11394/6780.

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Philosophiae Doctor - PhD<br>The aim of this study was to propose a model of collaboration adaptable for the optimal use of big data in an organisational environment. There is a paucity of knowledge on such collaboration and the research addressed this gap. More specifically, the research attempted to establish whether leadership, trust and knowledge sharing influence collaboration among the stakeholders identified at large organisations. The conceptual framework underlying this research was informed by collaboration theory and organisational theory. It was assumed that effective collaborat
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Lager, Joel, and Pontus Hermansson. "Marknadsföringsmixens fortsatta betydelse, med hänsyn till digitaliseringen. : En systematisk litteraturstudie." Thesis, Högskolan Dalarna, Företagsekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:du-27860.

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Syfte: Syftet med denna studie är att diskutera hur marknadsföringsmixen kunnat bevarat sin betydelse över tid inom området marknadsföring, med hänsyn till de förändringar som digitaliseringen inneburit. Metod: Studien genomfördes som en systematisk litteraturstudie. Studien baserades på över 50 vetenskapliga artiklar som är relevanta för syftet. Artiklarna samlades in via akademiska databaser. Resultat: Studien visar på att marknadsföringsmixen fortsatt är en aktuell modell inom marknadsföring tack vare sin pedagogiska enkelhet och förmåga att anpassa sig till rådande förutsättningar. De f
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Shi, Fanjuan. "A Smart Marketing Personalization Methodology Based On Real-Time Contextualisation In The Era of Big Data." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE3019/document.

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La personnalisation peut améliorer la pertinence et l'utilité des communications marketing B2C. Cependant, ce n'est pas la panacée pour tous les défis marketing B2C. Dans le but de renforcer la pertinence et l'utilité des contenus de marketing personnalisés, nous proposons une approche de personnalisation marketing contextuelle qui permet d'analyser les comportements d’achat cross-canaux, d'interpréter les intentions du consommateur, de détecter l'état cognitif des consommateurs et d'utiliser la stratégie de personnalisation appropriée pour générer et afficher des contenus marketing personnali
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Sacchetti, Giacomo. "L’impatto degli Analytics: come i Big Data stanno cambiando le aziende." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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In questa tesi affronto il mondo dei big data e di come stanno avendo impatto sulle aziende. Vengono affrontati casi di studio come Cambridge Analytica, le elezioni Americane del 2016 e la Brexit. Si affronta anche vari aspetti di gestione e estrazione dei dati negli algoritmi di suggestione dei vari provider di servizi, quali netflix, amazon etc...
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Books on the topic "Big data in marketing"

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Yun, Mi-jŏng. Pik teit'ŏ nŭn ŏttŏk'e mak'et'ing ŭi mugi ka toenŭn'ga. K'ŭllaudŭ Nain, 2020.

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missing], [name. Statistical modeling and analysis for database marketing: Effective techniques for mining big data. Chapman and Hall, 2003.

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Segard, Olivier, and Lamia Mamlouk. Big Data and Marketing. Wiley & Sons, Incorporated, John, 2016.

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Marketing digital y big data. Funcas, 2021.

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Gerald, David. Big Data and Firm Marketing Performance: When Companies Need to Rethink Themselves ,big Data Marketing ,big Data Technologies for Business. Independently Published, 2021.

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Chaston, Ian. Online Marketing and Big Data Exploration. Palgrave Macmillan, 2015.

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Chaston, Ian. Online Marketing and Big Data Exploration. Palgrave Macmillan, 2015. http://dx.doi.org/10.1057/9781137488961.

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Big Data and Firm Marketing Performance. Independently Published, 2022.

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Bell, Richard. Big Data and Firm Marketing Performance. Independently Published, 2021.

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Chaston, I. Internet Marketing and Big Data Exploitation. Palgrave Macmillan Limited, 2015.

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Book chapters on the topic "Big data in marketing"

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Holland, Heinrich. "Big Data Marketing." In Digitales Dialogmarketing. Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-28959-1_10.

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Hua, Hongbing. "Big Data Substance Marketing." In Mobile Marketing Management. Productivity Press, 2019. http://dx.doi.org/10.4324/9780429030871-10.

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Wilson, Alan I. "Secondary data, customer databases and big data analytics." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_3.

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Nethi, Srinivas Dinakar, Venkata Rajasekhar Moturu, and Krishnaveer Abhishek Challa. "Web Analytics for Digital Marketing." In Big Data Analytics. Auerbach Publications, 2022. http://dx.doi.org/10.1201/9781003307761-5.

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Mathew, Sibichan K., Shelly Rathee, and Michael Burns. "Reinventing Fashion Business: Big Data Analytics." In Fashion Marketing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82571-2_12.

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Gentsch, Peter. "Big Data." In Künstliche Intelligenz für Sales, Marketing und Service. Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-19147-4_2.

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Gentsch, Peter. "Big Data." In Künstliche Intelligenz für Sales, Marketing und Service. Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-25376-9_2.

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Pera, Krishna. "Building a Data-Driven Marketing Strategy1." In Big Data for Big Decisions. Auerbach Publications, 2022. http://dx.doi.org/10.1201/9781003321347-11.

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Paul, Tripti, and Sandip Rakshit. "Big Data Analytics for Marketing Intelligence." In Big Data Analytics. Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003175711-12.

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Srinivasan, S. "Marketing Applications Using Big Data." In Studies in Big Data. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53817-4_18.

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Conference papers on the topic "Big data in marketing"

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Aljumah, Ahmad Ibrahim, Mohammed T. Nuseir, Ghaleb El Refae, Ahmad Al-Hiyari, and M. Issam Mahho. "Enhancing Business Performance Through Data-Driven Digital Marketing and Big Data Capabilities." In 2024 Global Congress on Emerging Technologies (GCET). IEEE, 2024. https://doi.org/10.1109/gcet64327.2024.10934166.

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Choi, Jin-A., and Cyril S. Ku. "Examining Platform Strategy for Influencer Marketing Using Text Mining." In 2024 IEEE/ACIS 9th International Conference on Big Data, Cloud Computing, and Data Science (BCD). IEEE, 2024. http://dx.doi.org/10.1109/bcd61269.2024.10743091.

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Nusantara, Redi, Amron Amron, Febrianur Ibnu Fitroh Sukono Putra, and Yohan Wismantoro. "New E-Marketing Strategies Through Big Data Optimization in Fisheries MSMEs." In 2024 International Seminar on Application for Technology of Information and Communication (iSemantic). IEEE, 2024. https://doi.org/10.1109/isemantic63362.2024.10762656.

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Nazarov, A. D. "Big Data Driven Marketing." In Proceedings of the International Scientific and Practical Conference on Digital Economy (ISCDE 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/iscde-19.2019.3.

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Bengel, Andy, Amin Shawki, and Dippy Aggarwal. "Simplifying web analytics for digital marketing." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363968.

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Geronazzo, Angela, and Markus Ziegler. "QMLEx: Data Driven Digital Transformation in Marketing Analytics." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671890.

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Adnan Raouf, Raad, and Omar Ali Ismael. "Quality 4.0 and Big Data Marketing: A Systematic Literature Review." In The 5th International Scientific Conference on Administrative and Financial Sciences (CIC-ISCAFS'2025). Cihan University-Erbil, 2025. https://doi.org/10.24086/icafs2025/paper.1762.

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Abstract— This paper explores the logical relationships between two new concepts, Quality 4.0 and Big Data-driven Marketing. The review of literature provides a view of the theoretical underpinning and implementation of Quality 4.0 and big data-driven marketing. Research questions will concentrate on the dependency relationship between Quality 4.0 and big data marketing and the problems faced in carrying them out jointly. Quality 4.0 integration and big data marketing bring encouraging relationships, e.g., using predictive analytics for enhancing quality and personalizing the customers’ experi
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Pabedinskait�, Arnoldina, Vida Davidavicien�, and Pauliu Mili�auskas. "Big Data Driven E-Commerce Marketing." In The 8th International Scientific Conference "Business and Management 2014". Vilnius Gediminas Technical University Publishing House Technika, 2014. http://dx.doi.org/10.3846/bm.2014.079.

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Ye, Xin, Wen Liu, Longgang Li, and Yaning Zhang. "Utilizing big data in tourism marketing." In 3rd International Symposium on Social Science (ISSS 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/isss-17.2017.54.

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Shuai, Hong-Han, Chih-Ya Shen, Hsiang-Chun Hsu, et al. "Revenue maximization for telecommunications company with social viral marketing." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363886.

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Reports on the topic "Big data in marketing"

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Zhang, Ruirui, Shan Xue, and Leslie D. Burns. Investigation of Micro-blogging marketing strategy of Fashion brand: via big data and machine learning methodology. Iowa State University, Digital Repository, 2015. http://dx.doi.org/10.31274/itaa_proceedings-180814-153.

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Zwitter, Andrej J., and Amelia Hadfield. Governing Big Data. Librello, 2014. http://dx.doi.org/10.12924/pag2014.02010001.

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Gawade, Rushikesh. Big data and big dollars are changing cricket. Edited by Chris Bartlett. Monash University, 2023. http://dx.doi.org/10.54377/783a-d051.

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Gildea, Timothy R. Big Data health Physics. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1603973.

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Goldstein, Itay, Chester Spatt, and Mao Ye. Big Data in Finance. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28615.

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Big data en salud digital. Chair Alberto Urueña López and José María San Segundo Encinar. ONTSI : Fundación Vodafone España, 2017. http://dx.doi.org/10.30923/5896-8.

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Alewijn, M. Big data - Banana origin determination. Wageningen Food Safety Research, 2020. http://dx.doi.org/10.18174/516096.

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Doucet, Rachel A., Deyan M. Dontchev, Javon S. Burden, and Thomas L. Skoff. Big Data Analytics Test Bed. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada589903.

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Farboodi, Maryam, Roxana Mihet, Thomas Philippon, and Laura Veldkamp. Big Data and Firm Dynamics. National Bureau of Economic Research, 2019. http://dx.doi.org/10.3386/w25515.

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Li, Junteng. ADL Data Capturing System: A Big Data Approach. Iowa State University, 2019. http://dx.doi.org/10.31274/cc-20240624-116.

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