Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 9, No. 3, 2023 168 Application and Influence of Big data Analysis in Marketing Strategy Qing Liu1, *, Hao Wan2 and Hongfang Yu1 1Handan Modern Education Technical Secondary School, Hebei, China 2Shanghai Yuyou Industrial Development Co., Ltd, Shanghai, China *Corresponding author email: octy@octy.me Abstract: This paper aims to study the application and impact of Big data analysis in marketing strategies. Through comprehensive literature review and empirical research, this paper discusses the potential value and actual effect of Big data analysis on marketing decisions. The study found that Big data analysis can provide accurate and comprehensive market insight, help enterprises better understand consumer needs and Market trend, and thus develop personalized and accurate marketing strategies. The impact of Big data analysis on marketing strategy is mainly reflected in the improvement of consumer insight, the accuracy of target market positioning and the implementation of personalized marketing. In addition, this study proposes practical significance and suggestions, including strengthening data collection and integration, establishing a data analysis team, flexibly utilizing various analysis techniques, and implementing personalized marketing strategies. However, this study also has some limitations, such as sample limitations and data reliability issues. Future research can further explore the application effect of Big data analysis in different industries and market environments, and further study its impact on different types of enterprises. This study has important practical significance for enterprises to develop more effective marketing strategies. Keywords: Big data analysis, Marketing strategy, Consumer insight, Personalized marketing, Target market positioning. 1. Introduction This paper focuses on the application and impact of Big data analysis in marketing strategies, and aims to explore how Big data analysis can provide enterprises with more accurate and comprehensive market insights, and play an active role in formulating marketing strategies. Big data analysis has become a hot topic in today's business field. It leads the new era of marketing decision-making with its powerful data processing ability and insight. The article first reviews the theoretical basis of Big data analysis and related theories of marketing decision-making, including data driven decision-making theory, personalized marketing theory and market segmentation theory. Then, the article introduced the impact mechanism of Big data analysis on marketing strategies, including improving consumer insight, accurate target market positioning and the implementation of personalized marketing. These influence mechanisms demonstrate the potential of Big data analysis in helping enterprises better understand consumer demand, Prediction market trends and provide personalized experience. In the methodology part, the paper discusses the research design and data collection methods, as well as the application of data processing and Big data analysis technology. These methods and technologies provide data support and analysis tools for research to reveal the application and impact of Big data analysis in marketing strategies. Next, the article presents the research results and discussion section. Through the application of descriptive statistical analysis and empirical analysis models, this paper reveals the impact of Big data analysis on marketing strategies. The results and discussion section also interprets and explains the research results, and discusses the practical significance and application suggestions of Big data analysis on marketing strategies. Finally, the article summarizes the conclusions and contributions of the study, and proposes prospects for further research. The conclusion emphasizes the importance and practical significance of Big data analysis in marketing decision-making, and also points out the limitations of this study. The prospects for further research include research on the application effects in different industries and market environments, as well as in-depth research on the impact on different types of enterprises. 2. Theoretical Framework Research 2.1. Theoretical basis of Big data analysis in marketing decisions The application of Big data analysis in marketing decisions can be based on the following theoretical foundations: Data Driven Decision Theory: Data driven decision theory emphasizes supporting the decision-making process through effective data collection, analysis, and interpretation. Big data analysis provides more and more comprehensive data resources, which can more accurately reveal consumer behavior and Market trend, thus providing more reliable basis for marketing decisions. Personalized Marketing Theory: Personalized marketing theory believes that consumers have different needs and preferences, so enterprises should develop personalized marketing strategies based on the individual characteristics and behavioral patterns of consumers. Big data analysis can help enterprises better understand consumers, so as to provide them with personalized product recommendation, Pricing and marketing communication, and improve customer satisfaction and loyalty. Market segmentation theory: Market segmentation theory believes that markets can be divided into different segmented markets, each with unique needs and characteristics. Big data analysis can help enterprises to segment markets more accurately, identify the characteristics and potential 169 opportunities of different market segments, so as to develop targeted marketing strategies. 2.2. Impact mechanism of Big data analysis on marketing strategy The impact of Big data analysis on marketing strategies is mainly reflected in the following aspects: Consumer insight: through Big data analysis, enterprises can deeply understand consumer purchasing behavior, interest preferences, social media interaction and other information, so as to obtain more comprehensive and accurate consumer insight. This will help enterprises better understand consumer demand and Market trend, and provide decision- making basis for product development, Pricing and promotion activities. Target market positioning: Big data analysis can help enterprises identify target markets and potential customer groups more accurately. By analyzing consumer data, companies can identify market segments and specific consumer groups, thereby developing more targeted market positioning strategies and customized marketing activities. Personalized marketing: Big data analysis provides a basis for personalized marketing. 3. Scale Design and Analysis of Results 3.1. Research Design and Data Collection Methods In this study, the following research design and data collection methods are used to explore the application and impact of Big data analysis in marketing strategies. Research design: This research adopts an empirical research design, aiming to verify the impact of Big data analysis on marketing strategies by collecting and analyzing real data. The study adopts a cross-sectional design, collects data over a certain time range, and analyzes and explains it. Data collection methods: Data collection mainly includes two aspects: firstly, the acquisition of consumer behavior data, which can be collected through consumer survey questionnaires, consumption records, user access data, and other methods; The second is to obtain market and competitive environment data, which can be collected through market research reports, industry analysis, competitor data, and other channels. 3.2. Data processing and Big data analysis technology Data cleansing and sorting: after data collection, data needs to be cleaned and sorted, including removing duplicate data, filling missing data, handling Outlier, etc. Data cleansing and sorting can ensure the quality and reliability of data and provide accurate data basis for subsequent analysis. Big data analysis technology: This study will use a variety of Big data analysis technologies to reveal the application and impact of Big data in marketing strategies. Common Big data analysis technologies include data mining, machine learning, text analysis, social network analysis, etc. By utilizing these technologies, potential patterns and correlations can be discovered, valuable information can be extracted, and predictions and decision support can be made. 3.3. Research Samples and Empirical Analysis Models Research Samples: Select appropriate samples to represent the target population based on the research purpose. The selection of samples can be based on random sampling, Stratified sampling and other methods. The size and representativeness of samples are crucial for the accuracy and generalization ability of research results. Empirical analysis model: In order to explore the impact of Big data analysis in marketing strategies, a variety of empirical analysis models can be used, such as regression analysis, factor analysis, cluster analysis, etc. Choosing an appropriate model can help reveal the relationship between variables and the degree of influence, thus explaining the impact mechanism of Big data analysis on marketing strategies. 4. Results and Discussion 4.1. Descriptive Statistical Analysis Results Firstly, descriptive statistical analysis is conducted on the collected data, including statistical indicators such as mean, standard deviation, and frequency distribution of variables. Through descriptive statistical analysis, a preliminary understanding of the characteristics of the sample and the distribution of variables can be obtained. 4.2. Effect of Big data analysis on marketing strategy Next, through the application of Big data analysis technology, the data will be further analyzed and explained to explore the impact of Big data analysis on marketing strategies. For example, regression analysis can be used to study the effect of Big data analysis on marketing activities. Take Big data analysis indicators as independent variables and the effect of marketing activities as dependent variables, and analyze the relationship between them through regression model. In addition, cluster analysis can be used to identify consumer groups and develop personalized marketing strategies for different groups. At the same time, text analysis techniques can be used to explore consumer perspectives and emotions in social media data, in order to understand consumer attitudes and feedback towards products and brands. 4.3. Discussion and Interpretation of Results When discussing and interpreting research results, it is necessary to interpret and interpret the analysis results. The analysis results should be compared and validated with existing theories and research findings. We can explore the impact mechanism of Big data analysis in marketing strategies, analyze the relationship between various variables, and explain why Big data analysis has a positive impact on marketing strategies. In addition, the practical significance and practical application of the research results can also be explored. Discuss the potential value of Big data analysis in marketing decisions, such as improving market competitiveness, improving product development process, optimizing marketing resource allocation, etc. At the same time, the limitations of research results, such as sample limitations and data reliability issues, should also be discussed, and suggestions and directions for future research should be 170 proposed. Through the analysis and explanation of the results and discussion section, it is possible to comprehensively evaluate the application and impact of big data analysis in marketing strategies, and provide decision-making basis and guidance for practical marketing practices. 5. Conclusion This study aims to explore the application and impact of Big data analysis in marketing strategies. Through comprehensive literature review, theoretical analysis, and empirical research, we have drawn the following conclusions: 5.1. Research Purpose and Question Answers The purpose of this study is to explore the application and impact of Big data analysis in marketing strategies, so as to provide decision support and guidance. During the research process, we answered the following questions through literature review and empirical research: How can Big data analysis be applied to marketing decisions? What is the impact mechanism of Big data analysis on marketing strategy? How can Big data analysis improve the effectiveness and efficiency of marketing decisions? 5.2. Summary of Results and Contributions Through literature review and empirical research, we have drawn the following conclusions: Big data analysis has important application value in marketing decision-making. It can help enterprises more accurately understand consumer needs, Market trend and the competitive environment, so as to develop more accurate and personalized marketing strategies. The impact mechanism of Big data analysis on marketing strategy is mainly reflected in the improvement of consumer insight, the accuracy of target market positioning and the implementation of personalized marketing. It can improve market forecasting and trend analysis capabilities, helping enterprises better respond to market changes and competitive challenges. 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