1. Introduction

Consumer research refers to the process of collecting, analyzing and interpreting consumer-related data to understand consumer characteristics, needs, preferences, behavior and psychology, so as to provide a basis and guidance for a company's market strategy and product innovation. Consumer research is an important tool in the consumer goods and retail industry. It can help companies gain insight into consumer needs and pain points, discover market opportunities and potential, optimize product design and marketing mix, enhance brand influence and customer loyalty, and enhance competitive advantage and profitability. ability.

With the development of digital technology, especially the wide application of big data, artificial intelligence and social media, consumer research is also facing new opportunities and challenges. On the one hand, these technologies provide more data sources, analysis tools and communication channels for consumer research. For example:

Big data: Big data refers to a collection of data with large scale, diverse types and low value density. Big data can reflect the behavior characteristics and psychological state of consumers from multiple dimensions, such as purchase records, browsing history, location information, social networks, etc. Big data can help companies achieve comprehensive insight into consumers, discover potential needs and market opportunities, and improve marketing effectiveness and customer satisfaction.

Artificial intelligence: Artificial intelligence refers to machines or systems made by people with a certain degree of intelligence. Artificial intelligence can effectively collect, clean, integrate and analyze big data through machine learning, natural language processing, image recognition and other technologies to generate valuable insights and suggestions. Artificial intelligence can help enterprises improve the efficiency and accuracy of consumer research, and realize the automation and intelligence of consumer research.

Social media: Social media is a form of media that is user-centric and enables information sharing, communication and collaboration through Internet platforms. Social media allows consumers to express their opinions, feelings and comments on the Internet, forming consumer generated content (UGC). Social media can help companies obtain real feedback and word-of-mouth from consumers, establish interaction and relationships with consumers, and enhance brand awareness and reputation.

On the other hand, these technologies also bring new challenges and risks to consumer research. For example:

Data quality: Data quality refers to the accuracy, completeness, consistency, timeliness, and availability of data. The quality of data directly affects the reliability and validity of consumer research. However, due to the diversity and complexity of data sources, errors, missing, redundancy, inconsistency, obsolescence and tampering may occur in the process of data collection, storage, transmission and processing, resulting in the decline of data quality. Therefore, consumer research needs to take effective data quality management measures to ensure the authenticity and validity of the data.

Data security: Data security refers to the confidentiality, integrity and availability of data. The level of data security directly affects the legitimacy and morality of consumer research. However, due to the sensitivity and value of data, data collection, storage, transmission and processing may be subject to external attacks, theft, leakage and abuse, resulting in data security threats. Therefore, consumer research needs to comply with relevant laws, regulations and ethical principles, protect consumers' right to privacy and informed consent, and prevent data abuse and misuse.

Data analysis: Data analysis refers to the process of processing, summarizing, interpreting and evaluating data. The level of data analysis directly affects the depth and breadth of consumer research. However, due to the mass and complexity of the data, there may be some problems in the process of data analysis, such as inappropriate methods, inaccurate models, unstable results and unclear interpretation, which lead to the deviation and error of data analysis. Therefore, consumer research needs to select appropriate data analysis methods and tools, establish effective data analysis models and frameworks, and generate meaningful data analysis results and insights.

To sum up, the impact and value of big data, artificial intelligence and social media on consumer research are two-sided, with both opportunities and challenges, advantages and risks. Consumer research needs to make full use of the advantages of these technologies, while dealing with the risks of these technologies, to achieve innovation and development of consumer research. This paper discusses the impact and value of big data, artificial intelligence and social media on consumer research, as well as the future trends and prospects of consumer research, from the three aspects of consumer research data sources, analysis methods and communication methods.

2. data sources

Data sources refer to the ways and channels of obtaining data on which consumer research depends. The diversity and richness of data sources directly affect the coverage and dimensions of consumer research. Traditional consumer research data sources mainly include questionnaires, interviews, observational studies, experimental studies, etc. These data sources usually require consumer researchers to actively design, organize and execute consumer research, and these data sources are usually structured, limited, passive and static. Big data, artificial intelligence and social media provide more data sources for consumer research, which are usually unstructured, unlimited, active and dynamic. For example:

Big data: Big data can obtain consumer data from multiple channels and platforms, such as e-commerce, mobile payment, smart devices, and the Internet of Things. The data may reflect consumer buying behavior, payment habits, usage, changes in preferences, etc. Big data allows consumer researchers to obtain more consumer data, expand the coverage and dimensions of consumer research, and improve the comprehensiveness and objectivity of consumer research.

Artificial intelligence: Artificial intelligence can interact with consumers through intelligent Q & A, intelligent dialogue, intelligent recommend, etc., to obtain consumer data, such as demand, opinion, evaluation, satisfaction, etc. These data can reflect the consumer's psychological state, emotional tendency, values, etc. Artificial intelligence can enable consumer researchers to obtain deeper consumer data, increase the depth and fineness of consumer research, and improve the depth and subjectivity of consumer research.

Social media: Social media can obtain consumer data from multiple platforms and applications, such as Weibo, WeChat, Douyin, Little Red Book, etc. These data may reflect the consumer's social behavior, social relationships, social influence, etc. Social media allows consumer researchers to obtain a wider range of consumer data, expand the breadth and scope of consumer research, and improve the breadth and diversity of consumer research.

It can be seen that big data, artificial intelligence and social media provide more data sources for consumer research, making consumer research data richer and more diverse, and better reflecting the real situation and needs of consumers. However, these data sources also require consumer researchers to pay attention to the quality and safety of data, avoid data errors and abuse, and protect consumers' interests and rights.

3. analysis method

Analytical methods refer to the methods and techniques used in consumer research for the processing and interpretation of data. The effectiveness and innovation of analytical methods directly affect the results and value of consumer research. Traditional consumer research analysis methods mainly include descriptive analysis, correlation analysis, causal analysis, etc., these analysis methods usually require consumer researchers to manually select, apply and explain, these analysis methods are usually linear, deterministic, normative and static. Big data, artificial intelligence and social media provide more analytical methods for consumer research, which are often nonlinear, uncertain, flexible and dynamic. For example:

Big data: Big data can effectively extract, display and monitor consumer data through data mining, data visualization, data dashboards and other technologies to generate valuable information and knowledge. Big data allows consumer researchers to discover the laws and trends of consumer data, reveal consumer needs and pain points, predict consumer behavior and reactions, and provide consumer insights and suggestions.

Artificial intelligence: Artificial intelligence can effectively learn, understand and optimize consumer data through machine learning, deep learning, reinforcement learning and other technologies to generate valuable models and strategies. Artificial intelligence allows consumer researchers to analyze the complexity and diversity of consumer data, identify consumer characteristics and preferences, adapt to consumer changes and needs, and achieve consumer personalization and customization.

Social media: Social media can effectively classify, aggregate and measure consumer data through sentiment analysis, topic analysis, network analysis and other technologies, and generate valuable labels and indicators. Social media allows consumer researchers to evaluate the emotions and attitudes of consumer data, grasp consumer topics and interests, analyze consumer networks and influences, and enhance consumer participation and loyalty.

It can be seen that big data, artificial intelligence and social media provide more analytical methods for consumer research, making the analysis of consumer research more effective and innovative, and more able to generate valuable results and value. However, these analytical methods also require consumer researchers to pay attention to the analysis and interpretation of the data, avoid data deviations and errors, and ensure the accuracy and credibility of the data.

4. mode of transmission

Communication mode refers to the way and channel of data sharing and communication used in consumer research. The convenience and interactivity of communication directly affect the influence and effect of consumer research. Traditional consumer research communication methods mainly include report presentation, demonstration display, conference discussion, etc. These communication methods usually require consumer researchers to actively produce, publish and communicate. These communication methods are usually one-way, limited, passive and static. Big data, artificial intelligence and social media provide more communication methods for consumer research, which are usually two-way, unlimited, active and dynamic. For example:

Big data: Big data can effectively store, transmit and calculate consumer data through cloud computing, blockchain, edge computing and other technologies to achieve data sharing and collaboration. Big data can enable consumer researchers to realize the security and efficiency of consumer data, promote the flow and utilization of consumer data, increase the value and impact of consumer data, and realize the openness and transparency of consumer data.

Artificial intelligence: Artificial intelligence can effectively convert, present and generate consumer data through speech recognition, image recognition, natural language generation and other technologies, and realize the expression and creation of data. Artificial intelligence can enable consumer researchers to realize the diversity and enrichment of consumer data, improve the readability and understanding of consumer data, enhance the attraction and infection of consumer data, and realize the vividness and interest of consumer data.

Social media: Social media can effectively publish, disseminate and interact with consumers' data through platforms and applications such as Weibo, WeChat, Douyin, Little Red Riding Book, etc., to achieve data communication and exchange. Social media can enable consumer researchers to realize the rapid and extensive consumer data, expand the dissemination and influence of consumer data, enhance the feedback and interaction of consumer data, and realize the participation and co-creation of consumer data.

It can be seen that big data, artificial intelligence and social media provide more communication methods for consumer research, making the dissemination of consumer research more convenient and interactive, and enhancing the influence and effect of consumer research. However, these communication methods also require consumer researchers to pay attention to the communication and exchange of data, avoid misunderstanding and conflict of data, and maintain the consistency and coordination of data.

5. Conclusion

This paper discusses the impact and value of big data, artificial intelligence and social media on consumer research, as well as the future trends and prospects of consumer research, from the three aspects of consumer research data sources, analysis methods and communication methods. This paper holds that big data, artificial intelligence and social media provide more data sources, analysis methods and communication methods for consumer research, making consumer research data richer and more diverse, analysis more effective and innovative, and communication more convenient and interactive, so as to improve the comprehensiveness, depth, universality, diversity, effectiveness, innovation, convenience and interaction of consumer research. However, these technologies also bring new challenges and risks to consumer research, such as data quality, security, analysis and dissemination. Consumer researchers need to take effective measures to ensure the authenticity, validity, accuracy, credibility, security, legality, morality, consistency and coordination of data. This paper argues that the future of consumer research will be a data-centric, technology-driven, value-oriented, innovation-oriented, cooperation-based, consumer-centric consumer research era.