THE ROLE OF DATA ANALYTICS IN CONTEMPORARY ART MARKET
DOI:
https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6735Keywords:
Data Analytics, Art Market, Big Data, Predictive Modeling, Artificial Intelligence, BlockchainAbstract [English]
Data analytics implementation into the modern art market has changed the way the stakeholders analyze, invest, and interact with art pieces. The art market, traditionally opaque and subjectively valued, is currently adopting data-driven approaches to increase transparency and efficacy, as well as, decision-making. This essay examines the primary importance of the data analytics in transforming the art ecosystem with an emphasis on its uses, advantages, and difficulties. It starts with defining the key elements and classes of analytics: descriptive, predictive, and prescriptive and the technological tools used: artificial intelligence, big data platforms, machine learning algorithms. The tools are then placed in the framework of the art market and discussed on how they can solve the inefficiencies of pricing, valuation, and demand forecasting. Case study examples show how analytics can be used to identify the rising artists, identify the market trends, and prevent fraud risks and manipulation. Alongside these benefits, the paper also mentions such limitations as the lack of data, ethical concerns, and algorithmic bias. Lastly, it also looks into the future opportunities which include blockchain integration, value of digital art and analytics of non-fungible tokens (NFTs). In general, this paper highlights the fact that data analytics is not just democratizing the art investment, but also reshaping cultural and economic value in the ever more digital marketplace.
References
Abdul-Jabbar, S. S., and Farhan, A. K. (2022). Data Analytics and Techniques: A Review. ARO – The Scientific Journal of Koya University, 10, 45–55. https://doi.org/10.14500/aro.10975 DOI: https://doi.org/10.14500/aro.10975
Burton, O., and Toh, D. J. (2023). Digital Dominance and Social Media Platforms: Are Competition Authorities up to the Task? International Review of Intellectual Property and Competition Law, 54, 527–572. https://doi.org/10.1007/s40319-023-01302-1 DOI: https://doi.org/10.1007/s40319-023-01302-1
Derda, I. (2024). Museum Exhibition Co-Creation in the Age of Data: Emerging Design Strategy for Enhanced Visitor Engagement. Convergence, 30, 1596–1609. https://doi.org/10.1177/13548565231174597 DOI: https://doi.org/10.1177/13548565231174597
Donig, S., Eckl, M., Gassner, S., and Rehbein, M. (2023). Web Archive Analytics: Blind Spots and Silences in Distant Readings of the Archived Web. Digital Scholarship in the Humanities, 38, 1033–1048. https://doi.org/10.1093/llc/fqad014 DOI: https://doi.org/10.1093/llc/fqad014
Dovey, L. (2023). Intermediality in Academia: Creative Research Through Film. Arts, 12(4), 169. https://doi.org/10.3390/arts12040169 DOI: https://doi.org/10.3390/arts12040169
Giannakoulopoulos, A., Pergantis, M., Konstantinou, N., Kouretsis, A., Lamprogeorgos, A., and Varlamis, I. (2022). Estimation on the Importance of Semantic Web Integration for Art and Culture Related Online Media Outlets. Future Internet, 14(2), 36. https://doi.org/10.3390/fi14020036 DOI: https://doi.org/10.3390/fi14020036
Hawkins, A. (2022). Archives Linked Data and the Digital Humanities: Increasing Access to Digitised and Born-Digital Archives Via the Semantic Web. Archival Science, 22, 319–344. https://doi.org/10.1007/s10502-021-09381-0 DOI: https://doi.org/10.1007/s10502-021-09381-0
Jaillant, L. (2022). How Can we Make Born-Digital and Digitised Archives More Accessible? Identifying Obstacles and Solutions. Archival Science, 22, 417–436. https://doi.org/10.1007/s10502-022-09390-7 DOI: https://doi.org/10.1007/s10502-022-09390-7
Liang, S., McCarthy, P., and Van Stry, M. (2021). DATA: Digital Archiving and Transformed Analytics. Intelligent Information Management, 13, 70. https://doi.org/10.4236/iim.2021.131004 DOI: https://doi.org/10.4236/iim.2021.131004
Nicolaou, C., Matsiola, M., Dimoulas, C. A., and Kalliris, G. (2024). Discovering the Radio and Music Preferences of Generation Z: An Empirical Greek Case from and Through the Internet. Journal of Media, 5, 814–845. https://doi.org/10.3390/journalmedia5030053 DOI: https://doi.org/10.3390/journalmedia5030053
Pergantis, M., Varlamis, I., Kanellopoulos, N. G., and Giannakoulopoulos, A. (2023). Searching Online for Art and Culture: User Behavior Analysis. Future Internet, 15(6), 211. https://doi.org/10.3390/fi15060211 DOI: https://doi.org/10.3390/fi15060211
Philippopoulos, P. I., Drivas, I. C., Tselikas, N. D., Koutrakis, K. N., Melidi, E., and Kouis, D. (2024). A Holistic Approach for Enhancing Museum Performance and Visitor Experience. Sensors, 24(3), 966. https://doi.org/10.3390/s24030966 DOI: https://doi.org/10.3390/s24030966
Rosen, I. (2024). Advanced Visitor Profiling for Personalized Museum Experiences Using Telemetry-Driven Smart Badges. Electronics, 13(20), 3977. https://doi.org/10.3390/electronics13203977 DOI: https://doi.org/10.3390/electronics13203977
Saah, R., Abban, S., and White, E. (2023). Use of Social Media in Public Archives: Perspectives about Ghana’s Readiness and Perceived Challenges. Journal of Contemporary Archival Studies, 10, Article 20.
Schellnack-Kelly, I., and Modiba, M. (2024). Developing Smart Archives in Society 5.0: Leveraging Artificial Intelligence for Managing Audiovisual Archives in Africa. Information Development. https://doi.org/10.25159/UnisaRxiv/000072.v1 DOI: https://doi.org/10.25159/UnisaRxiv/000072.v1
Wen, J., and Ma, B. (2024). Enhancing Museum Experience Through Deep Learning and Multimedia Technology. Heliyon, 10, e32706. https://doi.org/10.1016/j.heliyon.2024.e32706 DOI: https://doi.org/10.1016/j.heliyon.2024.e32706
Xu, D. (2022). An Analysis of Archive Digitization in the Context of Big Data. Mobile Information Systems, 2022, Article 1517824. https://doi.org/10.1155/2022/1517824 DOI: https://doi.org/10.1155/2022/1517824
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Copyright (c) 2025 Yogesh; Saniya Khurana, Sourav Rampal, Dr. Pastor R. Arguelles, S. Simonthomas, Dr. Afroz Pasha, Mona Devi
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