Macarena Estevez , María Teresa Ballestar , Jorge Sainz
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We conducted a comprehensive survey on beer consumption in Spain, covering all conversion funnel stages, from Brand Awareness to Purchase. The study was replicated using four prominent LLMs: ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and LlaMa (Meta), and the results of these LLMs were compared with those of the traditional survey using a collection of statistical methods. Our results show that LLMs are valuable for market research, offering significant insights as reliable proxies. This represents a competitive advantage by making studies of this kind more accessible and cost-effective, benefitting companies of all sizes. However, LLMs cannot fully replicate traditional methods and present result variability, introducing risks in decision-making because of potential errors in data generation that are complex to estimate without benchmarking.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"10 5","pages":"Article 100796"},"PeriodicalIF":15.5000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Market research and knowledge using Generative AI: the power of Large Language Models\",\"authors\":\"Macarena Estevez , María Teresa Ballestar , Jorge Sainz\",\"doi\":\"10.1016/j.jik.2025.100796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Generative artificial intelligence (GAI) is rapidly transforming the marketing industry with its capabilities in data analysis, personalisation, strategic optimisation, and content generation, providing powerful tools for businesses aiming to establish or maintain a strong brand position. This research examines the application of Large Language Models (LLMs) for market research, enabling marketers to create insights that capture the complexities of market behaviour and customer psychology, helping them to connect with their target audiences more meaningfully and effectively. Particularly, it aims to evaluate the extent to which GAI can replicate traditional market research. We conducted a comprehensive survey on beer consumption in Spain, covering all conversion funnel stages, from Brand Awareness to Purchase. The study was replicated using four prominent LLMs: ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and LlaMa (Meta), and the results of these LLMs were compared with those of the traditional survey using a collection of statistical methods. Our results show that LLMs are valuable for market research, offering significant insights as reliable proxies. 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However, LLMs cannot fully replicate traditional methods and present result variability, introducing risks in decision-making because of potential errors in data generation that are complex to estimate without benchmarking.</div></div>\",\"PeriodicalId\":46792,\"journal\":{\"name\":\"Journal of Innovation & Knowledge\",\"volume\":\"10 5\",\"pages\":\"Article 100796\"},\"PeriodicalIF\":15.5000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Innovation & Knowledge\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2444569X25001416\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Innovation & Knowledge","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2444569X25001416","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Market research and knowledge using Generative AI: the power of Large Language Models
Generative artificial intelligence (GAI) is rapidly transforming the marketing industry with its capabilities in data analysis, personalisation, strategic optimisation, and content generation, providing powerful tools for businesses aiming to establish or maintain a strong brand position. This research examines the application of Large Language Models (LLMs) for market research, enabling marketers to create insights that capture the complexities of market behaviour and customer psychology, helping them to connect with their target audiences more meaningfully and effectively. Particularly, it aims to evaluate the extent to which GAI can replicate traditional market research. We conducted a comprehensive survey on beer consumption in Spain, covering all conversion funnel stages, from Brand Awareness to Purchase. The study was replicated using four prominent LLMs: ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and LlaMa (Meta), and the results of these LLMs were compared with those of the traditional survey using a collection of statistical methods. Our results show that LLMs are valuable for market research, offering significant insights as reliable proxies. This represents a competitive advantage by making studies of this kind more accessible and cost-effective, benefitting companies of all sizes. However, LLMs cannot fully replicate traditional methods and present result variability, introducing risks in decision-making because of potential errors in data generation that are complex to estimate without benchmarking.
期刊介绍:
The Journal of Innovation and Knowledge (JIK) explores how innovation drives knowledge creation and vice versa, emphasizing that not all innovation leads to knowledge, but enduring innovation across diverse fields fosters theory and knowledge. JIK invites papers on innovations enhancing or generating knowledge, covering innovation processes, structures, outcomes, and behaviors at various levels. Articles in JIK examine knowledge-related changes promoting innovation for societal best practices.
JIK serves as a platform for high-quality studies undergoing double-blind peer review, ensuring global dissemination to scholars, practitioners, and policymakers who recognize innovation and knowledge as economic drivers. It publishes theoretical articles, empirical studies, case studies, reviews, and other content, addressing current trends and emerging topics in innovation and knowledge. The journal welcomes suggestions for special issues and encourages articles to showcase contextual differences and lessons for a broad audience.
In essence, JIK is an interdisciplinary journal dedicated to advancing theoretical and practical innovations and knowledge across multiple fields, including Economics, Business and Management, Engineering, Science, and Education.