1. Online Education Industry Overview

Online education refers to the remote, synchronous or asynchronous teaching activities between teachers and students through Internet technology. The forms of online education include recording and broadcasting classes, live classes, interactive classes, micro classes, etc., covering all fields from preschool education to higher education, from subject education to quality education, from vocational education to lifelong education.

The advantage of online education is that it can break through the limitations of time and space, provide flexible, convenient and personalized teaching services, and meet the diverse needs of learners of different levels and needs.

As a new form of education, online education has developed rapidly in China in recent years and has been favored by the majority of consumers. In 2020, the market size of China's online education industry reached 257.3 billion billion yuan, up 35.5 percent year-on-year, and the number of users reached 0.309 billion, up 16.3 percent year-on-year. Among them, low-grade and quality education and K12 discipline training are the two growth engines of the online education market, with market shares of 24.5 and 17.9 respectively. The penetration rate and user stickiness of online education have also increased significantly in 2020 due to the new crown epidemic.

The Importance of 2. Consumer Research

Consumer research refers to the process of collecting, analyzing and interpreting consumer information to understand consumer needs, preferences, behavior, satisfaction, etc., so as to provide a basis for marketing decisions.

Consumer research is an important part of marketing, for the online education industry, has the following important significance:

Understand the current market situation and competitive situation. Consumer research can help online education companies grasp the scale, structure, distribution, trends and changes in the market, as well as competitors' products, prices, channels, promotions, brands, etc., so as to formulate reasonable market positioning and strategic planning.

Identify and meet consumer needs. Consumer research can help online education enterprises to deeply understand consumers' learning objectives, interests, habits, expectations, pain points, etc., so as to design and provide teaching products and services that meet the needs of consumers, and improve the learning effect and experience of consumers.

Establish and maintain consumer relationships. Consumer research can help online education companies obtain consumer feedback, evaluation, suggestions and complaints, so as to discover and solve consumer problems in a timely manner, improve consumer satisfaction and loyalty, and enhance consumer reputation and willingness to recommend.

Optimization and innovation of teaching mode. Consumer research can help online education companies explore the potential needs and future trends of consumers, so as to continuously optimize and innovate teaching models, such as personalized teaching, interesting teaching, interactive teaching, etc., to improve the efficiency and quality of teaching, and increase teaching Differentiation and competitiveness.

3. data collection methods

Data collection is the core link of consumer research, which refers to the process of obtaining information and data about consumers from different sources and types through various methods and tools.

The selection of data collection methods should be based on factors such as research purpose, object, content and budget, and attention should be paid to the validity, reliability and representativeness of the data to ensure the accuracy and credibility of the research results. Taking Shangpu Consulting as an example, this paper introduces the data collection method used in consumer research in the online education industry, and analyzes its advantages and limitations.

3.1 data sources

Data source refers to the object or channel of data collection, which is generally divided into two categories: first-hand data and second-hand data.

First-hand data refers to the original data obtained directly from the research objects (such as consumers, competitors, distributors, etc.), which is timely, unique and targeted, but the cost is high, the collection time is long, and there may be subjective deviation and risk of privacy leakage. The main methods of collecting first-hand data are questionnaires, interviews, observations, experiments and so on.

In the consumer research of the online education industry, Shangpu Consulting adopts a combination of first-hand data and second-hand data to improve efficient, comprehensive and accurate data collection for in-depth data analysis and interpretation.

3.2 Data Type

Data types refer to the nature or characteristics of data and are generally divided into qualitative data and quantitative data.

Qualitative data refers to data that describes the quality or characteristics of data, such as consumers' attitudes, feelings, opinions, motivations, etc., usually in the form of text, images, sounds, etc., with rich, detailed, multi-dimensional characteristics, but difficult to quantify, Statistics and induction require subjective interpretation and evaluation. Qualitative data collection methods include interviews, focus groups, case studies, and content analysis.

Quantitative data refers to data describing the amount or degree of data, such as the number, frequency, proportion, score, etc. of consumers, usually in the form of numbers, tables, charts, etc., with objective, accurate, concise characteristics, but lack of depth, background and connotation, the need for objective calculation and inference. The collection methods of quantitative data mainly include questionnaire survey, observation method, experimental method, mathematical statistics and so on.

In its consumer research in the online education industry, Shangpu Consulting uses a combination of qualitative and quantitative data to obtain comprehensive, in-depth and accurate information about consumers, while avoiding the limitations of a single data type. For example, when Shangpu Consulting conducted a survey on consumer satisfaction on an online education platform, it not only used quantitative satisfaction scores and indicators, but also used qualitative satisfaction reasons and suggestions to reveal the true feelings and needs of consumers.

3.3 Data Tools

Data tools refer to the means or carriers of data collection, which are generally divided into traditional tools and modern tools.

Traditional tools refer to tools that use paper, pens, telephones, tape recorders and other physical equipment for data collection. They have the advantages of simple operation, low cost, and wide application range, but they also have the disadvantages of low efficiency, small range, poor quality, and easy loss. The use of traditional tools mainly includes paper questionnaires, telephone interviews, and recorded interviews.

Modern tools refer to tools that use digital devices such as computers, mobile phones, and networks for data collection. They have the advantages of high efficiency, large range, good quality, and easy storage. However, they also have complex operation, high cost, poor security, and strong dependence. Disadvantages. The main methods of using modern tools are electronic questionnaires, video interviews, online observation, social media analysis and so on.

In its consumer research in the online education industry, Shangpu Consulting adopts a combination of traditional and modern tools to adapt to different data sources, types and scenarios, while making full use of the advantages of modern tools to improve the effectiveness and efficiency of data collection. For example, when Champ Consulting conducted a survey of consumer behavior on an online education platform, it used not only traditional observation methods, but also modern online observation methods to record and analyze consumer learning behaviors and processes in real time, dynamically and comprehensively.

3.4 data analysis

Data analysis refers to the process of processing, sorting, summarizing, reasoning, interpreting and evaluating the collected data in order to obtain valuable information andConclusion. The methods of data analysis can be divided into descriptive analysis, exploratory analysis, inferential analysis, and predictive analysis, depending on the type and purpose of the data.

Descriptive analysis refers to the basic description and summary of data, such as average, standard deviation, frequency, percentage, etc., to show the distribution, concentration, dispersion and change of data, which is the basis and premise of data analysis.

Exploratory analysis refers to the in-depth exploration and discovery of data, such as correlation, causality, clustering, classification, etc., to reveal the internal relations, laws and patterns of data, which is the core and focus of data analysis.

Inferential analysis refers to the scientific inference and verification of data, such as hypothesis testing, confidence interval, significance level, etc., to evaluate the reliability, validity and representativeness of data, which is the basis and guarantee of data analysis.

Predictive analytics refers to the future prediction and modeling of data, such as regression analysis, time series analysis, machine learning, etc., to predict trends, changes, and results of data, which is the purpose and value of data analysis.

In its consumer research in the online education industry, Shangpu Consulting uses a combination of descriptive analysis, exploratory analysis, inferential analysis and predictive analysis to analyze and interpret data comprehensively, deeply, accurately and effectively, so as to provide useful information and suggestions for online education enterprises. For example, when Shangpu Consulting Company conducted a survey on the consumer demand of an online education platform, it not only used descriptive analysis to show the distribution and characteristics of consumer demand, but also used exploratory analysis to discover consumer demand. Contact and regularity, as well as inferential analysis, verify the effectiveness and representativeness of consumer demand, and predictive analysis, predict consumer demand trends and changes.

4. Conclusion

Consumer research in the online education industry is an important means for online education companies to understand the market, meet demand, establish relationships, and optimize innovation, and data collection is the core link of consumer research. Taking Shangpu Consulting as an example, this paper discusses the data collection methods of consumer research in the online education industry, including data sources, data types, data tools and data analysis. This paper holds that the choice of data collection method should be based on the research purpose, object, content and budget and other factors, and should pay attention to the validity, reliability and representativeness of the data to ensure the accuracy and credibility of the research results. This paper hopes to provide some reference and enlightenment for online education enterprises and consumer researchers.