1. the concept, characteristics and application of big data and artificial intelligence

The concept, characteristics and application of 1.1 big data

Big Data (Big Data) refers to the massive, diverse and rapidly changing data collection that is difficult to handle in traditional data processing methods. The characteristics of big data are usually summarized in 4V, that is, the amount of data (Volume), data type (Variety), data speed (Velocity) and data value (Value). The application field of big data is very wide, covering social, economic, political, cultural, educational, medical, scientific and technological aspects. For example, big data can be used to analyze user behavior, predict market trends, optimize resource allocation, improve management efficiency, improve public services, and promote social governance.

The Concept, Characteristics and Application of 1.2 Artificial Intelligence

Artificial intelligence (Artificial Intelligence,AI) refers to the intelligence shown by human-made systems, including perception, understanding, learning, reasoning, decision-making, creation and other capabilities. The characteristics of artificial intelligence are mainly the following:

Artificial intelligence is a technology that imitates and extends human intelligence. It can not only perform things that humans can do, but also do things that humans cannot or are unwilling to do.

Artificial intelligence is a comprehensive interdisciplinary technology, which involves computer science, mathematics, linguistics, psychology, neuroscience, biology and other fields.

Artificial intelligence is a continuously developing and evolving technology that continuously improves its performance and functionality with the improvement of data, algorithms, hardware, software and other elements.

Artificial intelligence is a technology with autonomy and adaptability, which can adjust its behavior and strategy according to changes in the environment and goals.

The application of artificial intelligence is also very extensive, covering various fields such as industry, agriculture, transportation, education, medical care, entertainment, security, and military. For example, artificial intelligence can be used to recognize images, voice, text, emotion, etc., can be used to generate text, music, art, code, etc., can be used to play games, chess, answer questions, debate, etc., can be used to control robots, driverless, smart homes, smart cities, etc.

2. the impact and value of big data and artificial intelligence on market research

2.1 big data and artificial intelligence provide more data sources and data types for market research

The core of market research is data, and the source, quality and quantity of data directly determine the effect of market research. Traditional market research mainly relies on questionnaires, interviews, observations and other active data collection methods, the limitations of these methods are the size of the data, timeliness, accuracy, representativeness and so on. Big data and artificial intelligence provide more data sources and data types for market research, such:

Social media, e-commerce, search engines, mobile applications and other network platforms have generated a large number of user behavior data, such as click, browse, purchase, comment, share, like, etc., these data can reflect the user's interests, preferences, needs, satisfaction, loyalty, etc.

Sensors, cameras, smart devices, Internet of Things and other technologies have generated a large number of physical environment data, such as temperature, humidity, light, sound, location, exercise, health, etc. These data can reflect the user's life, work, travel, consumption, etc.

Artificial intelligence can transform unstructured data, such as pictures, videos, audio, text, etc., into structured data, such as labels, classifications,AbstractThese data can reflect the user's characteristics, attitudes, emotions, opinions, etc.

These data sources and data types provide more dimensions and perspectives for market research, which can help market researchers understand the situation of users and markets more comprehensively, deeply and in real time.

2.2 big data and artificial intelligence provide stronger data analysis and data mining capabilities for market research

The purpose of market research is to obtain valuable information and insights from data, and data analysis and mining are key steps to achieve this goal. Traditional market research mainly relies on the theories and methods of statistics, economics, management and other disciplines, and the limitations of these theories and methods lie in processing power, complexity, flexibility and so on. Big data and artificial intelligence provide market research with stronger data analysis and data mining capabilities, such:

Big data and artificial intelligence can use distributed computing, cloud computing, parallel computing and other technologies to improve the speed and efficiency of data storage, transmission, and processing, and can process massive, diverse, and rapidly changing data.

Big data and artificial intelligence can use machine learning, deep learning, reinforcement learning and other technologies to improve the accuracy and reliability of data modeling, prediction, and optimization, and can handle complex, nonlinear, and dynamic data.

Big data and artificial intelligence can use data visualization, data stories, data reports and other technologies to improve the presentation, interpretation, communication and influence of data, and can handle abstract, obscure and vague data.

How 3. market researchers are using big data and artificial intelligence to improve the quality and efficiency of market research

3.1 market researchers should choose the right big data and artificial intelligence technology according to the purpose and object of market research.

The purpose and object of market research is the starting point and orientation of market research, and different purposes and objects require different data and analysis methods. Market researchers should choose the appropriate big data and artificial intelligence technology according to the purpose and object of market research to achieve the best market research effect. For example:

If the purpose of market research is to understand the basic characteristics and needs of users, market researchers can choose to use user behavior data from social media, e-commerce and other network platforms, as well as artificial intelligence technologies such as image recognition, speech recognition, and natural language processing to obtain The user's age, gender, region, occupation, income, education, interests, preferences, needs and other information.

If the purpose of market research is to understand user satisfaction and loyalty, market researchers can choose to use user feedback data such as comments, ratings, sharing, and likes, as well as artificial intelligence technologies such as sentiment analysis, opinion mining, and topic modeling. Obtain user satisfaction, loyalty, emotion, opinion, topic and other information.

If the purpose of market research is to understand the scale and trend of the market, market researchers can choose to use user search data from web platforms such as search engines and mobile applications, as well as artificial intelligence technologies such as machine learning, deep learning, and reinforcement learning to obtain market information. Scale, growth rate, competitiveness, potential, trends and other information.

3.2 market researchers should optimize and innovate the use of big data and artificial intelligence technologies based on the process and results of market research.

The process and results of market research are the implementation and evaluation of market research, and different processes and results require different optimization and innovation. Market researchers should optimize and innovate the use of big data and artificial intelligence technology based on the process and results of market research to improve the quality and efficiency of market research. For example:

In the data collection stage of market research, market researchers should pay attention to the integrity, accuracy, timeliness and representativeness of the data, avoid the lack, error, obsolescence and deviation of the data, pay attention to the safety, legality and morality of the data, and abide by the laws, norms and ethics related to the protection, use and sharing of data.

In the data analysis stage of market research, market researchers should pay attention to the relevance, validity and reliability of data, avoid data redundancy, invalidity and instability, and pay attention to the diversity, complexity and dynamics of data, and adopt data integration, cleaning, conversion, normalization and other methods, as well as data exploration, description, inference, prediction and other technologies.

In the data presentation stage of market research, market researchers should pay attention to the readability, visualization and interactivity of the data to avoid obscurity, monotony and rigidity of the data. At the same time, they should pay attention to the storytelling, situational and emotional nature of the data, and adopt the methods of data visualization, storytelling and reporting, as well as the techniques of data interpretation, communication and influence.

The Case of Using Big Data and Artificial Intelligence in Market Research by 4. Champ Consulting

Shangpu Consulting Company is a professional market research and consulting service company with rich market research experience and excellent market research team to provide customers with high-quality market research and consulting services. Shangpu Consulting actively uses big data and artificial intelligence technology in market research to provide customers with more data, deeper insights, and better decisions. The following are some of the cases provided by Champ Consulting for clients:

4.1 user profiling and market segment analysis for a FMC company.

Shangpu Consulting conducted user portraits and market segment analysis for a fast-moving consumer product company to help customers understand the characteristics, needs, preferences, behaviors, etc. of different types of users, as well as the scale, competition, and potential of different market segments. Provide a basis for customers to formulate more targeted product design and marketing strategies. Champ Consulting uses the following big data and artificial intelligence technologies:

Use user behavior data from network platforms such as social media, e-commerce, and search engines, as well as artificial intelligence technologies such as image recognition, speech recognition, and natural language processing to obtain information about users' basic characteristics, needs, and preferences, and construct user portraits.

Use user feedback data such as comments, ratings, sharing, and likes, as well as artificial intelligence technologies such as sentiment analysis, opinion mining, and topic modeling to obtain user satisfaction, loyalty, emotion, opinion, topic, and other information to evaluate user value.

Using artificial intelligence technologies such as machine learning, deep learning, and reinforcement learning to cluster users, users are divided into different market segments, such as high-end users, mid-end users, and low-end users, based on their similarity and difference.

Use data visualization, data stories, data reports and other technologies to present user portraits and market segment analysis results, as well as suggestions and solutions to customers, such as product positioning, pricing strategies, promotional activities, and channel selection for different market segments.

4.2 conducting market trend and competitor analysis for an automotive company

Shangpu Consulting Company conducts market trend and competitor analysis for an automobile company, helps customers understand the development direction, technological innovation, consumer demand, etc. of the automobile industry, as well as the product characteristics, market share, advantages and disadvantages of competitors, etc., and provides basis for customers to formulate more competitive product innovation and market development. Champ Consulting uses the following big data and artificial intelligence technologies:

Use user search data from web platforms such as search engines and mobile applications, as well as artificial intelligence technologies such as machine learning, deep learning, and reinforcement learning to obtain information on the scale, growth rate, competitiveness, potential, and trends of the automotive industry, and analyze market trends.

Use physical environment data generated by technologies such as sensors, cameras, smart devices, and the Internet of Things, as well as artificial intelligence technologies such as image recognition, speech recognition, and natural language processing, to obtain information on technological innovation, product performance, and user experience in the automotive industry, and analyze technology Advantage.

Use user behavior data from social media, e-commerce, search engines and other network platforms, as well as artificial intelligence technologies such as sentiment analysis, opinion mining, topic modeling, etc., to obtain information on competitors' product characteristics, market share, advantages and disadvantages, and analyze the competitive situation.

Use data visualization, data stories, data reports and other technologies to present the results of market trends and competitor analysis, as well as recommendations and solutions to customers, such as product innovation, technology investment, partners, etc. for market trends, as well as product differentiation, price strategies, and marketing strategies for competitors.