Arseam

International Journal of Marketing & Financial Management

DATA-DRIVEN PRODUCT DEVELOPMENT FOR MARKETPLACES: ENHANCING SELLER CAPABILITIES AND CUSTOMER VALUE

Srikrishna Jayaram

Srikrishna Jayaram Senior Product Manager India.

DOI : https://doi.org/10.53882/IJMFM.2024.1201005 Page No : 82-94

Published Online : 2024-06-30

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Data has emerged as a potent source of competitive advantage in contemporary business-to-business (B2B) sectors, allowing providers to develop improved and completely new value propositions. Many businesses, however, find it difficult to turn the massive volumes of data produced by their operations into goods that can be sold. To tackle this issue, this study looks at methods for reselling and making money off of data in B2B markets. It draws attention to the connections between different value propositions and certain data-related issues and capabilities. Furthermore, by showing how industrial companies may use, package, and market data in B2B marketplaces, the results add to the body of knowledge on digital servitization and data monetization. Regarding the strategy and skill criteria for effective data monetization in B2B companies, this report offers managers insightful information.

Keywords: Data monetization, Digital servitization, Value proposition, B2B markets, Strategic capabilities.

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Jayaram S. (2024), “Data-Driven Product Development For Marketplaces: Enhancing Seller Capabilities And Customer Value”, International Journal of Marketing & Financial Management, Volume 12, Issue 1, 2024, pp 82-94. DOI : https://doi.org/10.53882/IJMFM.2024.1201005

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REFERENCES

Alhonen, et. al (2018). Value Creation through the Integration of Sales and Marketing: SMARKETING. Haaga-Helia Publications 1/2018, 30 p. Retrieved From: https://www.academia.edu/101456603/Value_creation_through_the_integration_of_sales_and_marketing_SMARKETING
Ansari, S. A, et. al (2023). Multi video summarization using query based deep optimization algorithm. International Journal of Machine Learning and Cybernetics. DOI: https://doi.org/10.1007/s13042-023-01852-3
Ansari, S. A. et. al (2018). A Review on Multisource Data Analysis using soft computing Techniques. In 2018 4th International Conference on Computing Communication and Automation (ICCCA) (pp. 1-6). IEEE. DOI: http://dx.doi.org/10.1109/CCAA.2018.8777551
Ansari, S. A. et. al (2022). A fusion of dolphin swarm optimization and improved sine cosine algorithm for automatic detection and classification of objects from surveillance videos. Measurement, 192, 110921. DOI: https://doi.org/10.1016/j.measurement.2022.110921
Ansari, S. A. et. al (2023). A Comprehensive Study on Video Captioning Techniques, Benchmark Datasets and QoS Metrics. In 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1598-1603). IEEE. Retrieved From: https://vufind-test.katalog.k.utb.cz/SummonRecord/FETCH-ieee_primary_101125243?sid=77480263
Ansari, S. A., et. al (2020). A review on video analytics its challenges and applications. Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals: Proceedings of GUCON 2019, 169-182. DOI: http://dx.doi.org/10.1007/978-981-15-0339-9_14
Ansari, S.A., et al. (2024). MetaV: A Pioneer in feature Augmented Meta-Learning Based Vision Transformer for Medical Image Classification. Interdiscip Sci Comput Life Sci (2024). DOI: https://doi.org/10.1007/s12539-024-00630-1
Bharathy, S. S. P. D. et. al (2017). Hand Gesture Recognition for Physical Impairment Peoples. SSRG International Journal of Computer Science and Engineering (SSRG-IJCSE), 6-10. DOI: https://doi.org/10.14445/23488387/IJCSE-V4I10P102
Camarinha-Matos, et. al (2018). Collaborative networks of cognitive systems, the proceedings of the 19th IFIP/SOCOLNET Working Conference on Virtual Enterprises, Pro-Ve 2018, Cardiff, UK, and September 17-19: 325-336. DOI: http://dx.doi.org/10.1007/978-3-319-99127-6
Laxminarayana Korada, et. al (2024). Artificial Intelligence on the Administration Of Financial Markets. Retrieved From: https://nano-ntp.com/index.php/nano/article/view/2493
Quach, et al., (2022). Digital technologies: tensions in privacy and data. J. Acad. Market. Sci. 50 (6), 1299–1323. Retrieved From: https://link.springer.com/article/10.1007/s11747-022-00845-y
Raddats, C., et al., (2019). Servitization: a contemporary thematic review of four major research streams. Ind. Market. Manag. 83, 207–223. DOI: https://doi.org/10.1016/j.indmarman.2019.03.015
Raddats, C., et. al (2022). Creating value in servitization through digital service innovations. Ind. Market. Manag. 104, 1–13. DOI: https://doi.org/10.1016/j.indmarman.2022.04.002
Reim, Wiebke, et. al (2015). Product–service systems (PSS) business models and tactics – a systematic literature review. J. Clean. Prod. 97, 61–75. DOI: https://doi.org/10.1016/j.jclepro.2014.07.003
Sujithra, M., et. al (2022). A Study on Psychological Stress of Working Women In Educational Institution Using Machine Learning. In 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-7). IEEE. DOI: https://doi.org/10.1109/ICCCNT54827.2022.9984460
Suresh, K., et. al (2019). A novel key exchange algorithm for security in internet of things. Indones. J. Electr. Eng. Comput. Sci, 16(3), 1515-1520. DOI: http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1515-1520
Valkokari, K., et. al (2018). Business Impacts of Technology Disruption – A Design Science Approach to Cognitive Systems’ Adoption within Collaborative. DOI: http://dx.doi.org/10.1007/978-3-319-99127-6_29
Vargo, S.L et. al (2004). Evolving to a New Dominant Logic for Marketing. Journal of Marketing, 68(1): 1-17. DOI: https://doi.org/10.1509/jmkg.68.1.1.24036
Vargo, S.L., et. al (2016). Institutions and Axioms: An Extension and Update of Service-Dominant Logic. Journal of Academy of Marketing Science, 44: 5-23. Retrieved From: https://link.springer.com/article/10.1007/s11747-015-0456-3
Yin, R.K. (2014). Case Study Research: Design and Methods. 5th edition, Thousand Oaks: Sage Publications. DOI: http://dx.doi.org/10.3138/cjpe.30.1.108

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