{"id":6781,"date":"2026-04-08T20:49:13","date_gmt":"2026-04-08T12:49:13","guid":{"rendered":"https:\/\/moresourcing.com\/gain-consumer-insight-with-generative-ai\/"},"modified":"2026-04-08T20:49:13","modified_gmt":"2026-04-08T12:49:13","slug":"gain-consumer-insight-with-generative-ai","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/ko\/gain-consumer-insight-with-generative-ai\/","title":{"rendered":"Gain Consumer Insight With Generative AI"},"content":{"rendered":"

<\/p>\n

\n

1.<\/b> N. Arora, I. Chakraborty, and Y. Nishimura, \u201cAI-Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators,\u201d\u00a0Journal of Marketing\u00a089, no. 2 (March 2025): 43-70, https:\/\/doi.org\/10.1177\/00222429241276529<\/a>; and \u201cGlobal Market Research Report<\/a>\u201d (Esomar, 2025).<\/p>\n

2.<\/b> K. Zhang, X. Yang, Y. Wang, et al., \u201cArtificial Intelligence in Drug Development,\u201d Nature Medicine 31, no. 1 (January 2025): 45-59, https:\/\/doi.org\/10.1038\/s41591-024-03434-4<\/a>.<\/p>\n

3.<\/b> G. Aher, R.I. Arriaga, and A.T. Kalai, \u201cUsing Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies,\u201d in ICML \u201923: Proceedings of the 40th International Conference on Machine Learning (JMLR.org, July 2023), 337-371; and L.P. Argyle, E.C. Busby, N. Fulda, et al., \u201cOut of One, Many: Using Language Models to Simulate Human Samples,\u201d Political Analysis 31, no. 3 (July 2023): 337-351, https:\/\/doi.org\/10.1017\/pan.2023.2<\/a>.<\/p>\n

4.<\/b> O. Toubia, G.Z. Gui, T. Peng, et al., \u201cDatabase Report: Twin-2K-500: A Data Set for Building Digital Twins of Over 2,000 People Based on Their Answers to Over 500 Questions,\u201d Marketing Science 44, no. 6 (November-December 2025): 1446-1455, https:\/\/doi.org\/10.1287\/mksc.2025.0262<\/a>.<\/p>\n

5.<\/b> A.R. Andreasen, \u201c\u2018Backward\u2019 Market Research<\/a>,\u201d Harvard Business Review 63, no. 3 (May 1985): 176-182.<\/p>\n

6.<\/b> D. Jurafsky and J.H. Martin, \u201cSpeech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition With Language Models<\/a>,\u201d 3rd ed. (draft), PDF file (self-published, August 2025), https:\/\/web.stanford.edu.<\/p>\n

7.<\/b> E. Brynjolfsson, B. Chandar, and R. Chen, \u201cCanaries in the Coal Mine? Six Facts About the Recent Employment Effects of Artificial Intelligence<\/a>,\u201d working paper, Stanford Digital Economy Lab, August 2025.<\/p>\n<\/p><\/div>\n

#Gain #Consumer #Insight #Generative<\/p>","protected":false},"excerpt":{"rendered":"

1. N. Arora, I. Chakraborty, and Y. Nishimura, \u201cAI-Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators,\u201d\u00a0Journal of Marketing\u00a089, no. 2 (March 2025): 43-70, https:\/\/doi.org\/10.1177\/00222429241276529; and \u201cGlobal Market Research Report\u201d (Esomar, 2025). 2. K. Zhang, X. Yang, Y. Wang, et al., \u201cArtificial Intelligence in Drug Development,\u201d Nature Medicine 31, no. 1 (January […]<\/p>","protected":false},"author":1,"featured_media":6782,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[9],"tags":[],"class_list":["post-6781","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-management"],"acf":[],"yoast_head":"\nGain Consumer Insight With Generative AI - MORE SOURCING LTD<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/moresourcing.com\/ko\/gain-consumer-insight-with-generative-ai\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Gain Consumer Insight With Generative AI\" \/>\n<meta property=\"og:description\" content=\"1. N. Arora, I. Chakraborty, and Y. Nishimura, \u201cAI-Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators,\u201d\u00a0Journal of Marketing\u00a089, no. 2 (March 2025): 43-70, https:\/\/doi.org\/10.1177\/00222429241276529; and \u201cGlobal Market Research Report\u201d (Esomar, 2025). 2. K. Zhang, X. Yang, Y. 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