Marketing Metrics as a Tool for Analyzing Scientific Production

Authors

DOI:

https://doi.org/10.5195/biblios.2025.1290

Keywords:

marketing metrics, metric studies of information, AIDA model, informetric studies

Abstract

Objective. This research aims to explore the application of Visualization Metrics as a tool to understand the dispersion and impact of scientific production, using an adaptation of the AIDA Model to map the stages of Viewing, Downloading, and Citing scientific documents. Method. The study employs an exploratory approach, using data on views, downloads, and citations of scientific articles obtained from the SciELO database. The adaptation of the AIDA Model was applied to analyze user behavior in three main stages: Viewing, Downloading, and Citing. In addition, retention calculations were performed to assess the effectiveness of each stage in the user journey. Results. The findings indicate a significant variation in viewing and download metrics over the years, with particular emphasis on 2018, which showed a notable discrepancy between views and downloads. The retention calculation revealed that most users who view a document do not download it, and those who do are mostly Master’s and Undergraduate students. These results suggest the need for more targeted dissemination strategies to increase retention and the eventual citation of documents. Conclusions. Visualization Metrics, when analyzed in conjunction with the AIDA Model, provide a detailed understanding of user behavior regarding scientific documents. This study highlights the importance of employing these metrics to optimize scientific dissemination strategies, enhance the visibility of articles, and thus strengthen their academic impact.

Author Biographies

Skrol Salustiano, Universidade Federal do Rio de Janeiro

PhD candidate in Information Science at the Graduate Program in Information Science at the Brazilian Institute of Information in Science and Technology - IBICT in partnership with ECO/UFRJ, Master's degree in Information Science from IBICT/UFRJ (2019), specialist in Institutional Communication Management (UCB), Bachelor's degree in Social Communication (Faesa). Researcher in Information Metrics, Data Management, Folksonomy, and Digital Linguistic Structures.

Fabio Castro Gouveia, Universidade Federal do Rio de Janeiro

Fábio Castro Gouveia is a Public Health Technologist at Fiocruz, assigned to perform the executive role of Head of the Institutional Monitoring Division (DINST) at the Brazilian Institute of Science and Technology Information (IBICT). He is the leader of the Science, Data, Networks, and Metrics Research Group (Scimetrics) and is also a researcher at the Zika Social Sciences Network (https://fiocruz.tghn.org/zikanetwork/). Gouveia is a biologist with a master's degree in Microbiology and Immunology and a doctorate in Biological Chemistry (Education, Management, and Dissemination of Biosciences). He completed a short postdoctoral fellowship as a Visiting Fellow at Katolieke Universiteit Leuven (Belgium) through the 2009 Coimbra Group Scholarships Programme for young professors and researchers from Latin American universities. In 2020, Gouveia and Elaine Rabello were the winners of the Altmetric Research Award for Promising Altmetrics Research. He is a permanent professor in the Graduate Program in Information Science in partnership with IBICT/Eco-UFRJ. Gouveia conducts research in the field of Information Science, with an emphasis on Information Metrics Studies (Scientometrics, Webometrics, Altmetrics, and Science, Technology, and Innovation Indicators), Digital Methods, STS, Data Science, Artificial Intelligence, and Blockchain Technology, and in the area of Scientific Dissemination and Health Communication, with an emphasis on studies on the internet and social media.

References

Aida. Oxford Reference. https://doi.org/10.1093/oi/authority.20110803095432783

Bar-Ilan, J., Haustein, S., Peters, I., Priem, J., Shema, H., & Terliesner, J. (2012). Beyond citations: Scholars’ visibility on the social Web. arXiv. https://doi.org/10.48550/ARXIV.1205.5611

Barry, T. E. (1987). The Development of the Hierarchy of Effects: An Historical Perspective. Current Issues and Research in Advertising, 10(1–2), 251–295. https://doi.org/10.1080/01633392.1987.10504921 DOI: https://doi.org/10.1007/978-1-4757-4614-3_1

Bollen, J., Sompel, H. V. de, H., A., & Chute, R. (2009). A principal component analysis of 39 scientific impact measures. PLOS ONE, 4(6), e6022. https://doi.org/10.1371/journal.pone.0006022 DOI: https://doi.org/10.1371/journal.pone.0006022

Cardona, E. A. S. (2021). Marketing científico: Investigadores y prosumidores en la ciencia. Poiésis, 41, 14–22. https://doi.org/10.21501/16920945.4217 DOI: https://doi.org/10.21501/16920945.4217

Demachki, É., & Maricato, J. D. M. (2022). Coverage of data sources and correlations between altmetrics and citation indicators: The case of a brazilian portal of open access journals. Serials Review, 48(1–2), 151–166. https://doi.org/10.1080/00987913.2022.2066967 DOI: https://doi.org/10.1080/00987913.2022.2066967

DiBartola, S. P., & Hinchcliff, K. W. (2017). Metrics and the scientific literature: Deciding what to read. Journal of Veterinary Internal Medicine, 31(3), 629–632. https://doi.org/10.1111/jvim.14732 DOI: https://doi.org/10.1111/jvim.14732

Fang, Z., Costas, R., Tian, W., Wang, X., & Wouters, P. (2021). How is science clicked on Twitter? Click metrics for Bitly short links to scientific publications. Journal of the Association for Information Science and Technology, 72(7), 918–932. https://doi.org/10.1002/asi.24458 DOI: https://doi.org/10.1002/asi.24458

Gholampour, S., Lim, W. M., Lund, B. D., Noruzi, A., Elahi, A., Saboury, A. A., Nawaz, R., & Gholampour, B. (2024). Does social media contribute to research impact? An Altmetric study of highly-cited marketing research. Total Quality Management & Business Excellence, 35(13–14), 1671–1701. https://doi.org/10.1080/14783363.2024.2393339 DOI: https://doi.org/10.1080/14783363.2024.2393339

Glushko, C. (2016) Viewability is a big part of the journey, but it’s not the destination. MarTech. https://martech.org/viewability-big-part-journey-not-destination/

Gorraiz, J., Gumpenberger, C., & Schlögl, C. (2014). Usage versus citation behaviours in four subject areas. Scientometrics, 101(2), 1077–1095. https://doi.org/10.1007/s11192-014-1271-1 DOI: https://doi.org/10.1007/s11192-014-1271-1

Kardes, F. R., Cline, T. W., & Cronley, M. L. (2014). Consumer behavior (2nd edition.). South-Western.

Kavic, M. S., & Satava, R. M. (2021). Scientific literature and evaluation metrics: Impact factor, usage metrics, and altmetrics. JSLS : Journal of the Society of Laparoscopic & Robotic Surgeons, 25(3), e2021.00010. https://doi.org/10.4293/JSLS.2021.00010/ DOI: https://doi.org/10.4293/JSLS.2021.00010

Kotler, P., & Keller, K. L. (2012). Marketing management (14th ed.). Prentice Hall.

Kluyver, T., Ragan-Kelley, B., PÉRez, F., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P., Avila, D., n, Abdalla, S., Willing, C., & Team, J. D. (2016). Jupyter Notebooks – a publishing format for reproducible computational workflows. Em Positioning and Power in Academic Publishing: Players, Agents and Agendas (p. 87–90). IOS Press. https://doi.org/10.3233/978-1-61499-649-1-87 DOI: https://doi.org/10.3233/978-1-61499-649-1-87

Freitas, J. L., Bufrem, L. S., & Grácio, M. C. C. (2019). O Interdomínio dos Estudos Métricos da Informação em Medicina: Aproximação entre discurso e prática de seus pesquisadores. Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação, 24(56), 01–22. https://doi.org/10.5007/1518-2924.2019.e65348 DOI: https://doi.org/10.5007/1518-2924.2019.e65348

Maricato, J. D. M., & Martins, D. L. (2018). Altmetria: Complexidades, desafios e novas formas de mensuração e compreensão da comunicação científica na web social. Biblios Journal of Librarianship and Information Science, 68, 48–68. https://doi.org/10.5195/biblios.2017.358 DOI: https://doi.org/10.5195/biblios.2017.358

Mohammadi, E., & Thelwall, M. (2014). m endeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the Association for Information Science and Technology, 65(8), 1627–1638. https://doi.org/10.1002/asi.23071 DOI: https://doi.org/10.1002/asi.23071

Nwagwu, W. E., & Onyancha, B. (2015). Back to the beginning—The journal is dead, long live science. The Journal of Academic Librarianship, 41(5), 669–679. https://doi.org/10.1016/j.acalib.2015.06.005 DOI: https://doi.org/10.1016/j.acalib.2015.06.005

Oliveira, E. F. T. D., & Gracio, M. C. C. (2011). Indicadores bibliométricos em ciência da informação: Análise dos pesquisadores mais produtivos no tema estudos métricos na base Scopus. Perspectivas em Ciência da Informação, 16(4), 16–28. https://doi.org/10.1590/S1413-99362011000400003 DOI: https://doi.org/10.1590/S1413-99362011000400003

Priem, J. (2015). Altmetrics (Chapter from beyond bibliometrics: Harnessing multidimensional indicators of scholarly impact). arXiv. https://doi.org/10.48550/ARXIV.1507.01328 DOI: https://doi.org/10.7551/mitpress/9445.003.0019

Priem, J., & Hemminger, B. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(2). https://doi.org/10.5210/fm.v15i7.2874 DOI: https://doi.org/10.5210/fm.v15i7.2874

Radlinski, F., Kurup, M., & Joachims, T. (2010). Evaluating search engine relevance with click-based metrics. Em J. Fürnkranz & E. Hüllermeier (Orgs.), Preference Learning (p. 337–361). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-14125-6_16 DOI: https://doi.org/10.1007/978-3-642-14125-6_16

Santos, P. W. Q. D., & Albuquerque, J. P. S. D. (2018). Altmetria: Uma nova lente para os estudos métricos da informação. Biblionline, 13(3), 3. https://doi.org/10.22478/ufpb.1809-4775.2017v13n3.35874 DOI: https://doi.org/10.22478/ufpb.1809-4775.2017v13n3.35874

Santos, R. V., & Araújo, R. F. D. (2025). Repositórios Institucionais da América do Sul: Análise da visibilidade da produção científica na web social. Cuadernos de Educación y Desarrollo, 17(2), e7646. https://doi.org/10.55905/cuadv17n2-122 DOI: https://doi.org/10.55905/cuadv17n2-122

Sales, DP (2022). Critérios, política e procedimentos para a admissão e a permanência de periódicos na Coleção SciELO Brasil: área de Humanidades. Boletim Técnico do PPEC, 9, e024011-e024011. https://www.scielo.br/media/files/20220900-criterios-scielo-brasil.pdf

Salustiano, S., & Gouveia, F. C. (2025). dataset: Métricas do marketing como ferramenta de análise da produção científica [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.27022852 DOI: https://doi.org/10.5195/biblios.2025.1290

Schlögl, C., Gorraiz, J., Gumpenberger, C., Jack, K., & Kraker, P. (2014). Comparison of downloads, citations and readership data for two information systems journals. Scientometrics, 101(2), 1113–1128. https://doi.org/10.1007/s11192-014-1365-9 DOI: https://doi.org/10.1007/s11192-014-1365-9

Shocker, A. D., Ben-Akiva, M., Boccara, B., & Nedungadi, P. (1991). Consideration set influences on consumer decision-making and choice: Issues, models, and suggestions. Marketing Letters, 2(3), 181–197. https://doi.org/10.1007/BF02404071 DOI: https://doi.org/10.1007/BF02404071

Van Raan, A. F. J. (2004). Sleeping Beauties in science. Scientometrics, 59(3), 467–472. https://doi.org/10.1023/B:SCIE.0000018543.82441.f1 DOI: https://doi.org/10.1023/B:SCIE.0000018543.82441.f1

Wang, L., Ramachandran, A., & Chaintreau, A. (2016). Measuring click and share dynamics on social media: A reproducible and validated approach. Proceedings of the International AAAI Conference on Web and Social Media, 10(2), 108–113. https://doi.org/10.1609/icwsm.v10i2.14841 DOI: https://doi.org/10.1609/icwsm.v10i2.14841

Wijaya, B. S. (2012). The development of hierarchy of effects model in advertising. International Research Journal of Business Studies, 5(1), 73-85. https://www.academia.edu/23497016/The_Development_of_Hierarchy_of_Effects_Model_in_Advertising DOI: https://doi.org/10.21632/irjbs.5.1.73-85

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Published

2025-12-16

How to Cite

Salustiano, S., & Castro Gouveia, F. (2025). Marketing Metrics as a Tool for Analyzing Scientific Production. Biblios Journal of Librarianship and Information Science, (esp.), e018. https://doi.org/10.5195/biblios.2025.1290

Issue

No. esp. (2025)

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Original

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Copyright (c) 2025 Skrol Salustiano, Fabio de Castro Gouveia

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