Analysis of market research methods in the era of big data

The new market research methods in the era of big data make it possible to restore the real consumption process without interference, and intelligent information processing technology makes low-cost, large-sample quantitative research become a reality, which will promote the study of consumer behavior and consumer psychology to reach a new level and help FMCG companies capture business opportunities more accurately. This will promote the research of consumer behavior and consumer psychology to a new level, and help FMCG enterprises capture business opportunities more accurately. Market research methods in the era of big data?1. Internet-based market research improves efficiency and reduces costs. Internet research has the incomparable convenience and economy of traditional research methods. FMCG companies establish market research boards in their portals, and then mail new products to consumers, consumers can easily complete the questionnaire by clicking on the website after the trial, and its convenience greatly reduces the labor and material inputs of market research, and makes consumers more willing to participate in market research. At the same time, the interactivity of the network research makes the enterprise in the new product is still in the conceptual stage can be utilized 3D simulation technology for product testing, through the interaction with consumers, so that consumers are directly involved in product development, so as to better meet market demand. 2, mining network social platform information has become a new means to study consumer attitudes and psychology? Facebook, QQ, Weibo, WeChat and other social platforms have increasingly become an indispensable social tool for the new generation of consumer groups, and consumers of fast-moving consumer goods tend to have a very high degree of herding, so the mining of information for social platforms has become a new means of researching consumer trends. For example, we can statistically analyze consumers' interest and preference for certain functional products through microblog comments, which is very helpful for studying consumer attitudes and psychology. What's more, this kind of information belongs to the active disclosure of consumers, and the authenticity of the information is higher compared with the passive mining in the form of interviews. 3、Mobile terminal provides real-time and dynamic consumer information. With the popularization of 3G network and smart phones, market research has penetrated into the field of mobile terminals. A large number of cell phone APP applications (e.g. QR code scanning, etc.) provide the possibility of real-time collection of consumer information, and the information analysis of mobile terminals will play an inestimable role in the point of purchase, product penetration and repurchase rate, and evaluation of the effect of incentive promotions. 4、Retail terminal information collection system helps enterprises understand the market? At present, PC-POS system is widely used in retail terminals. As long as the barcode of the product is scanned, information such as the name of the product purchased by the consumer, specification, purchase price, retail price, and the place of purchase can be easily collected. By building a complete retail terminal information collection system, FMCG enterprises can grasp the dynamic information of commercial channels and adjust their marketing strategies at the right time.? Intelligent information collection, storage and analysis?1. Large-capacity data warehouse? Data warehouse has the characteristics of large capacity, clear theme, high integration, relative stability, reflecting historical changes, etc., which can effectively support FMCG enterprises to carry out big data analysis and application. The data warehouse can mine data resources more effectively and can provide analysis reports according to daily, weekly, monthly, quarterly and yearly cycles, which helps marketers formulate marketing strategies more effectively. ?2, professional and efficient search engine? Travel search, blog search, shopping search, online yellow pages search and other professional search engines have been widely used, FMCG companies can build a professional search engine according to their own characteristics, the relevant corporate information, product information, consumer evaluation information, business services information and other data for intelligent search, classification and collection, the formation of a highly specialized, comprehensive commercial search engine. ?3, mathematical analysis model based on cloud computing? The key to market research is to gain insight into consumer demand, and the mathematical analysis model based on cloud computing can reduce fragmented information into a complete chain of information on the consumption process to better help marketers study consumer behavior and consumer psychology. These fragmented information include consumer value information, purchase information, and product review information posted by consumers at different times, in different locations, and on different web applications. Intelligent analysis based on cloud computing, on the one hand, can help market researchers to conduct a comprehensive analysis of consumer behavior and consumer psychology, and on the other hand, the characteristics of low cost and high efficiency of cloud computing are very suitable for FMCG enterprises with huge amounts of data. Problems in the use of big data? Traditional market research includes qualitative research and quantitative research, qualitative research based on symposiums is limited by the host's interview skills, and quantitative research based on street intercept interviews, although based on rigorous sampling theory, can not fully represent the overall objective situation. The revolutionary research methods in the era of big data provide market researchers with the possibility of observing consumers as "invisible people", and the statistical analysis of large sample size makes the research results closer to the real state of the market. At the same time, the new methods and tools in the era of big data also bring new problems, one is how to intelligently retrieve and analyze non-quantitative data such as text, graphics, video, and so on, and the other is how to prevent excessive collection of information and fully protect consumer privacy. Although there are still certain technical obstacles, it is undeniable that big data market research has an unlimited and broad application prospects.

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