现代科技的迅速发展使大数据及人工智能的应用深入到各个领域,也包含饮食健康方面。利用大数据和人工智能技术对北京市轻食消费趋势进行研究,可以帮助品牌方更好地了解市场现状和趋势,优化营销策略和供应链管理,推动健康饮食文化的发展...现代科技的迅速发展使大数据及人工智能的应用深入到各个领域,也包含饮食健康方面。利用大数据和人工智能技术对北京市轻食消费趋势进行研究,可以帮助品牌方更好地了解市场现状和趋势,优化营销策略和供应链管理,推动健康饮食文化的发展。本文旨在研究北京市轻食市场现存的能动和障碍,并对此提出可行性建议,推动北京轻食市场发展。本项目运用问卷调查的方式进行调研,针对不同群体发放了AB卷,最终发放问卷387份,有效问卷364份,数据均通过了信效度检验。此次调查对有效数据进行了描述性统计、因子分析、聚类分析、对应分析、构建结构方程模型,具体分析了被调查者的基本情况、轻食选择偏好,并对消费者进行市场细分,消费障碍分析。根据分析结果得出以下结论:味道是影响消费者购买的主要因素;营养健康功能是轻食的核心竞争力;轻食销量易受季节影响;不同的消费者群体具有不同的消费特征;轻食门店的覆盖范围达到一定饱和度;轻食宣传普及率较低。基于上述分析,提出以下可行性建议:推广策略:精准定位顾客需求,实现个性化推广;利用算法挖掘消费者购买偏好。营销策略:巧用社交媒体,制定多元化营销策略;注重消费者反馈与优化。The rapid development of modern technology has enabled the application of big data and artificial intelligence to penetrate into various fields, including dietary health. Using big data and artificial intelligence technology to study the consumption trend of light food in Beijing can help brands better understand the current situation and trends of the market, optimize marketing strategies and supply chain management, and promote the development of healthy food culture. The purpose of this paper is to study the existing dynamics and obstacles of the light food market in Beijing, and put forward feasible suggestions to promote the development of the light food market in Beijing. In this project, 387 questionnaires and 364 valid questionnaires were finally distributed, and the data passed the reliability and validity test. The survey carried out descriptive statistics, factor analysis, cluster analysis, correspondence analysis, and structural equation model construction of effective data, specifically analyzed the basic situation of the respondents, light food choice preferences, and carried out market segmentation and consumption barrier analysis of consumers. According to the analysis results, the following conclusions are drawn: taste is the main factor influencing consumer purchase;Nutrition and health function is the core competitiveness of light food;The sales of light food are susceptible to seasonal influences;Different consumer groups have different consumption characteristics;The coverage of light food stores has reached a certain saturation;The popularity of light food promotion is low. Based on the above analysis, the following feasible suggestions are proposed: promotion strategy: accurately locate customer needs and achieve personalized promotion;Use algorithms to mine consumers’ purchase preferences. Marketing strategy: making good use of social media to develop diversified marketing strategies and focusing on consumer feedback and optimization.展开更多
文摘现代科技的迅速发展使大数据及人工智能的应用深入到各个领域,也包含饮食健康方面。利用大数据和人工智能技术对北京市轻食消费趋势进行研究,可以帮助品牌方更好地了解市场现状和趋势,优化营销策略和供应链管理,推动健康饮食文化的发展。本文旨在研究北京市轻食市场现存的能动和障碍,并对此提出可行性建议,推动北京轻食市场发展。本项目运用问卷调查的方式进行调研,针对不同群体发放了AB卷,最终发放问卷387份,有效问卷364份,数据均通过了信效度检验。此次调查对有效数据进行了描述性统计、因子分析、聚类分析、对应分析、构建结构方程模型,具体分析了被调查者的基本情况、轻食选择偏好,并对消费者进行市场细分,消费障碍分析。根据分析结果得出以下结论:味道是影响消费者购买的主要因素;营养健康功能是轻食的核心竞争力;轻食销量易受季节影响;不同的消费者群体具有不同的消费特征;轻食门店的覆盖范围达到一定饱和度;轻食宣传普及率较低。基于上述分析,提出以下可行性建议:推广策略:精准定位顾客需求,实现个性化推广;利用算法挖掘消费者购买偏好。营销策略:巧用社交媒体,制定多元化营销策略;注重消费者反馈与优化。The rapid development of modern technology has enabled the application of big data and artificial intelligence to penetrate into various fields, including dietary health. Using big data and artificial intelligence technology to study the consumption trend of light food in Beijing can help brands better understand the current situation and trends of the market, optimize marketing strategies and supply chain management, and promote the development of healthy food culture. The purpose of this paper is to study the existing dynamics and obstacles of the light food market in Beijing, and put forward feasible suggestions to promote the development of the light food market in Beijing. In this project, 387 questionnaires and 364 valid questionnaires were finally distributed, and the data passed the reliability and validity test. The survey carried out descriptive statistics, factor analysis, cluster analysis, correspondence analysis, and structural equation model construction of effective data, specifically analyzed the basic situation of the respondents, light food choice preferences, and carried out market segmentation and consumption barrier analysis of consumers. According to the analysis results, the following conclusions are drawn: taste is the main factor influencing consumer purchase;Nutrition and health function is the core competitiveness of light food;The sales of light food are susceptible to seasonal influences;Different consumer groups have different consumption characteristics;The coverage of light food stores has reached a certain saturation;The popularity of light food promotion is low. Based on the above analysis, the following feasible suggestions are proposed: promotion strategy: accurately locate customer needs and achieve personalized promotion;Use algorithms to mine consumers’ purchase preferences. Marketing strategy: making good use of social media to develop diversified marketing strategies and focusing on consumer feedback and optimization.
