The Concept, Characteristics and Development Status of Artificial Intelligence and Big Data in 1.

The Concept, Characteristics and Development Status of 1.1 Artificial Intelligence

Artificial intelligence (Artificial Intelligence,AI) is a discipline that studies, develops and applies computer systems to simulate, extend and expand human intelligence. Its goal is to enable computers to perform tasks that usually require human intelligence, such as perception, understanding, learning, reasoning, decision-making, creation, etc. The main technologies of artificial intelligence include machine learning, deep learning, natural language processing, computer vision, speech recognition, image recognition, knowledge graph, expert system, robot, etc.

The development of artificial intelligence has experienced three waves, namely the first wave from 1956 to 1974, the second wave from 1980 to 1987, and the third wave from 2012 to the present. The first wave was mainly symbolism, focusing on logical reasoning and knowledge representation, with representative results such as the Turing test, the general problem solver, and the El iza dialogue system. The second wave is mainly based on connectionism, focusing on neural networks and parallel distributed processing, representing the results of reverse propagation algorithms, Hopfield networks, Boltzmann machines and so on. The third wave is mainly based on statistical learning, focusing on big data and deep learning, representing AlphaGo, Siri, Watson, Turing Dog and so on.

At present, artificial intelligence is in the climax of the third wave, and its development is driven by the following factors: first, the explosive growth of data provides rich training materials and application scenarios; second, the exponential improvement of computing power provides strong computing power support and technological innovation; third, the continuous evolution of algorithms provides more efficient learning models and optimization methods; fourth, the active guidance of policies provides a good development environment and strategic direction.

The Concept, Characteristics and Development Status of 1.2 Big Data

Big Data (Big Data) refers to the collection of data that is not enough to be processed by traditional data processing applications, which has the characteristics of mass, high speed, diversity, value and difficulty, and requires new processing models to have stronger decision-making power, insight and innovation. The main technologies of big data include data collection, data storage, data management, data analysis, data visualization, data security, etc.

The development of big data has gone through three stages, namely, the era of big data 1.0 from 2000 to 2008, the era of big data 2.0 from 2009 to 2015, and the era of big data 3.0 from 2016 to the present. The era of big data 1.0 is mainly dominated by Internet companies, focusing on data collection and storage, representing technologies such as Hadoop, MapReduce, and NoSQL. The era of big data 2.0 mainly focuses on e-commerce, finance, manufacturing and other industries, focusing on data analysis and mining, representing technologies such as Spark, Storm, and Mahout. The era of big data 3.0 is mainly based on artificial intelligence, Internet of Things, cloud computing and other fields, focusing on the application and value of data, representing technologies such as TensorFlow, Keras, and PyTorch.

At present, big data is in a period of rapid development in the era of big data 3.0, and its development is driven by the following factors: first, the diversification of data sources provides a wider range of data types and dimensions; second, the cloudification of data platforms provides more flexible data services and solutions; third, the intelligence of data analysis provides more accurate data insight and prediction; fourth, the scenario of data application provides more data empowerment and innovation.

2. the Impact and Value of Artificial Intelligence and Big Data on Market Research

2.1 the Impact of Artificial Intelligence and Big Data on Market Research

Artificial intelligence and big data, as the most cutting-edge and disruptive technologies today, have had a profound impact on market research, mainly in the following aspects:

(1) Change the data source and data quality of market research. Traditional market research mainly relies on questionnaires, interviews, observations and other actively obtained data, which often have problems such as small quantity, low quality, poor timeliness and high cost. The application of artificial intelligence and big data enables market research to use the Internet, Internet of Things, social media and other channels to obtain more passive data, such as user behavior data, user feedback data, user portrait data, etc. These data have the advantages of large quantity, high quality, good timeliness and low cost, which can provide more comprehensive, real and timely information support for market research.

(2) Changed the data processing and data analysis of market research. Traditional market research mainly relies on statistical analysis, descriptive analysis, hypothesis testing and other methods, which often have limitations, complexity, subjectivity and other issues. The application of artificial intelligence and big data enables market research to use machine learning, deep learning, natural language processing and other technologies to carry out more advanced processing and analysis of data, such as data cleaning, data conversion, data mining, data modeling, Data visualization, etc., these technologies have the advantages of intelligence, automation, objectivity, etc, it can provide more accurate, effective and valuable insights and suggestions for market research.

(3) Changed the data application and data value of market research. Traditional market research mainly relies on reports, charts, presentations and other forms to present the results and significance of data to customers. These forms often have problems such as lag, static, and one-way. The application of artificial intelligence and big data enables market research to provide customers with the application and value of data by means of intelligent systems, intelligent platforms and intelligent services, such as data-driven decision support, data-driven product innovation and data-driven service optimization. These methods have the advantages of real-time, dynamics and interactivity, it can provide more timely, flexible and personalized solutions and experiences for market research.

2.2 the Value of Artificial Intelligence and Big Data to Market Research

Artificial intelligence and big data, as the most innovative and transformative technologies today, have brought great value to market research, mainly in the following aspects:

(1) Improve the efficiency and quality of market research. The application of artificial intelligence and big data can greatly reduce the time cost and labor cost of market research, improve the speed and scale of market research, improve the accuracy and reliability of market research, and reduce the error and deviation of market research, so as to make market research more efficient and better quality.

(2) Expand the scope and depth of market research. The application of artificial intelligence and big data can break through the space and time limitations of market research, cover a wider range of markets and users, and at the same time, it can also tap the potential and hidden information of market research. in-depth understanding of the needs, preferences, behavior, psychology, etc. of the market and users, so as to make market research more extensive and in-depth exploration.

(3) Innovative methods and models of market research. The application of artificial intelligence and big data can go beyond the traditional methods and models of market research, such as questionnaires, interviews, observations, etc., and introduce more new methods and models, such as social media analysis, sentiment analysis, semantic analysis, and network analysis., Image analysis, video analysis, etc., so that market research is more diverse and innovative.

(4) Promote the intelligence and personalization of market research. The application of artificial intelligence and big data can make market research make better use of the intelligent and personalized characteristics of data, such as self-learning, self-optimization and self-adaptation of data, and realize the intelligent and personalized management, analysis, application and value of market research, so as to make market research more intelligent and personalized service.

Future Trends and Prospects of 3. Market Research

Future Trends in 3.1 Market Research

Based on the impact and value of artificial intelligence and big data, the future trend of market research can be summarized as follows:

(1) Data ecology. The data of market research will no longer be isolated, scattered and static, but will form an organic, integrated and dynamic data ecosystem to realize comprehensive data collection, efficient storage, intelligent management, in-depth analysis, extensive application and continuous optimization, forming a data-driven market research closed loop.

(2) data governance. The data of market research will no longer be disorderly, irregular and impossible, but follow certain data governance principles, data governance framework and data governance mechanism to realize the standardization, standardization, legalization, security and ethics of data, so as to ensure the quality and credibility of data.

(3) to achieve data sharing and collaboration. Data sharing and collaboration refers to the process of maximizing the value and optimizing the benefits of data through the openness, exchange, integration and optimization of data on the premise of ensuring data security and privacy, with the aim of achieving data collaboration, innovation and win-win results. Market research to achieve data sharing and collaboration, it is necessary to establish data trust, promote the flow of data, enhance data collaboration, improve the efficiency of data, to achieve data sharing and collaboration.

4. Conclusion

Market research is an important strategic decision support activity, and its development has been deeply influenced by artificial intelligence and big data, and has also gained great value from artificial intelligence and big data. The future trend of market research is data-driven, scenario-based and collaborative market research, and the future outlook of market research is to build a data ecosystem, strengthen data governance, train data talents, promote data standardization, and realize data sharing and collaborative market research. Market research should make full use of the advantages of artificial intelligence and big data, and also pay attention to avoid its risks and challenges, so as to realize the development of high quality, high efficiency and high value of market research.