Market research is a method to understand the current situation and trends of the market by collecting, analyzing and interpreting data. Market research can help companies and organizations develop effective marketing strategies to improve competitiveness and profitability. The core of market research is data, and the quality and value of data directly affect the effectiveness and credibility of market research. Therefore, market research companies need to use effective data collection and processing technologies to improve the quality and value of data.

Champu Consulting Group is a well-known market research and consulting firm that provides quantitative and qualitative market research services covering a wide range of industries and sectors. Champ Consulting Group has a professional data collection and processing team, using advanced technology and methods to provide customers with high-quality and high-value data and insights. Taking Shangpu Consulting Group as an example, this article introduces the main steps and methods of data collection and processing of market research companies, including data sources, data types, data cleaning, data analysis and data presentation. The paper also explores the challenges and opportunities of data collection and processing for market research firms, as well as future trends.

Data source

Data sources refer to the channels and methods through which market research companies obtain data. Data sources can be divided into two categories: primary data and secondary data.

First-hand data refers to data that market research companies collect directly from the target market or respondents, and is usually designed to meet a specific research purpose. First-hand data has the advantage of being more accurate, relevant, timely, and unique, but is also more expensive, time-consuming, and difficult to obtain. The first-hand data collection methods commonly used by market research companies are: questionnaires, interviews, observations, experiments, and neuromarketing.

Questionnaire survey refers to a data collection method that designs a series of questions and issues or sends questionnaires to a certain number and types of respondents to obtain their opinions, attitudes, behaviors and characteristics. The questionnaire survey can be divided into offline questionnaire survey and online questionnaire survey. Offline questionnaire survey refers to the distribution or sending of paper or electronic questionnaires to respondents through face-to-face, telephone, mail, etc. Online questionnaires refer to questionnaires that are distributed or sent to respondents through the Internet, mobile devices, social media, etc. The advantages of online surveys are that they are faster, cheaper, more convenient and more extensive, but they are also more susceptible to interference, deception and low response rates. The Shangpu Consulting Group uses its own Shangpu online platform to provide customers with online questionnaire services. Champ's online platform has more5000Ten thousand registered users, covered100Multiple countries and regions to quickly, accurately and efficiently collect data from target respondents based on customer needs.

Interviews refer to data collection methods that engage in one-to-one or many-to-one conversations with respondents to capture their deeper thoughts, feelings, motivations, and experiences. Interviews can be divided into structured interviews, semi-structured interviews and unstructured interviews. Structured interviews refer to interviews in which questions are asked to the interviewees according to pre-designed questions and sequences. Semi-structured interviews refer to interviews that ask questions to the interviewees according to pre-designed topics and instructions, but with the flexibility to adjust the questions and order. Unstructured interviews refer to interviews that do not have pre-designed questions and sequences, but randomly ask questions to the interviewees according to their answers and situations. Interviews have the advantage of being deeper, more flexible, more realistic and richer, but also more subjective, more complex, more time-consuming and more difficult to analyze. The interview methods commonly used by market research companies are: face-to-face interview, telephone interview, video interview and focus group interview. The Shangpu Consulting Group uses its own developed Shangpu interview platform to provide customers with video interviews and focus group interviews. The Champu interview platform can record, transcribe and translate the content of the interview in real time, and can also use artificial intelligence and machine learning technology to analyze the content of the interview,KeywordsExtract and categorize topics.

Observation refers to the actual and natural data collection method by directly or indirectly observing the behavior, reaction and environment of the interviewee in order to obtain them. Observations can be divided into participatory and non-participatory observations. Participatory observation refers to the observation that the observer participates in the activity or scene of the interviewee and communicates and interacts with the interviewee. Non-participatory observation refers to the observation that the observer does not participate in the activity or scene of the interviewee, but only observes as an observer. The advantages of observation are more objective, more intuitive, more realistic and more comprehensive, but it is also more difficult to control, record, explain and sample.

Market research companies commonly used observation methods are: field observation, laboratory observation, remote observation and eye tracking observation. Shangpu Consulting Group uses its own Shangpu observation platform to provide customers with remote observation and eye tracking observation services. The Shangpu observation platform can remotely observe the behavior and reaction of the interviewees through webcams, smart phones, tablets and other devices. At the same time, it can also record and analyze the eye movement and gaze of the interviewees through the eye tracker. data.

Experiments are data collection methods that manipulate one or more variables under controlled conditions to observe and measure their effects on another or more variables to obtain causal relationships. Experiments can be divided into laboratory experiments and scene experiments. Laboratory experiments refer to experiments on subjects in an artificially set environment. A scenario experiment is an experiment in which an experiment is performed on a subject in a real or simulated environment. Experiments have the advantage of being more scientific, more precise, more controllable and more repeatable, but they are also more complex, more expensive, more time-consuming and more difficult to generalize. The experimental methods commonly used by market research companies are:A/Btests, multifactorial tests, randomized controlled trials, and mock purchase experiments. Shangpu Consulting Group uses its own developed Shangpu experimental platform to provide customers with a variety of experimental services. The Shangpu experimental platform can design and execute different experimental schemes according to the needs of customers. At the same time, it can also use artificial intelligence and machine learning technology to carry out statistical analysis and causal inference on the experimental results.

Neuromarketing refers to data collection methods that measure and analyze respondents' brain activity, physiological responses, and mental states through the use of neuroscience techniques and methods to obtain their subconscious and irrational data. Neuromarketing has the advantage of being deeper, more direct, more authentic and more persuasive, but also more complex, more expensive, more intrusive and harder to explain. The neuromarketing techniques commonly used by market research companies are electroencephalography, functional magnetic resonance imaging, galvanic skin response, heart rate variability and facial expression recognition. Shangpu Consulting Group uses its own development of the Shangpu neural platform to provide customers with neural marketing services. The Champ Neural Platform can measure and analyze respondents' neural and emotional responses by using a variety of neuroscience equipment and software, and can also use artificial intelligence and machine learning techniques to visualize and interpret neural marketing data.

Secondary data refers to data obtained by market research companies from existing data sources or institutions, usually collected for general research purposes. Second-hand data has the advantage of being cheaper, faster, more extensive and more readily available, but also more outdated, less relevant, less accurate and less unique. The second-hand data sources commonly used by market research companies are: internal data, external data, business data and public data.

Internal data refers to the data that a market research company obtains from its own business activities or systems, such as sales data, customer data, financial data and website data. Internal data has the advantage of being more familiar, more controllable, more trusted and more confidential, but also more limited, more fragmented, less standard and less compatible. Internal data analysis tools commonly used by market research companies are: spreadsheets, databases, data warehouses, and data mining. Champu Consulting Group uses its own internal platform developed by Champu to provide customers with internal data analysis and management services. The internal platform of Champu can collect, integrate, clean, transform, store, query and report the internal data of customers. At the same time, it can also use artificial intelligence and machine learning technology to carry out pattern recognition, correlation analysis and predictive analysis of internal data.

External data refers to data obtained by market research companies from sources or institutions other than their own, such as competitor data, industry data, market data and social data. The advantages of external data are that it is more comprehensive, more diverse, more objective and more valuable, but it is also more difficult to obtain, more difficult to verify, more difficult to compare and more difficult to adapt. External data acquisition tools commonly used by market research companies are: web crawlers,API、RSSand blockchain. Champ Consulting Group uses its own external platform developed by Champ to provide customers with services for the acquisition and utilization of external data. The Shangpu external platform can automatically or semi-automatically crawl, extract, filter, integrate and update external data from a variety of networks and platforms, as well as use artificial intelligence and machine learning techniques for semantic analysis, sentiment analysis and public opinion analysis of external data.

Business data is data that market research firms purchase or subscribe to from professional data providers or institutions, such as Nielsen, Condé Nast, Avery Consulting, and Goldman Sachs. The advantages of commercial data are more professional, more authoritative, more systematic and more standard, but it is also more expensive, less flexible, less timely and less unique. Common business data analysis tools used by market research companies are: reports, charts, dashboards, and data visualizations. Shangpu Consulting Group uses its own developed Shangpu business platform to provide customers with business data analysis and presentation services. The Shangpu business platform can interpret, compare, summarize and summarize business data subscribed or purchased by customers, and can also use artificial intelligence and machine learning techniques to classify, cluster, regression and classify business data.

Public data refers to data obtained by market research companies for free or at low prices from public data sources or institutions, such as government data, educational data, scientific research data and non-governmental organization data. Public data has the advantage of being more open, transparent, reliable, and socially valuable, but it is also more fragmented, less complete, less consistent, and less accessible. Common public data acquisition tools used by market research companies are: portals, open data platforms, data sharing platforms, and data collaboration platforms. The Shangpu Consulting Group uses its own developed Shangpu public platform to provide customers with services for the acquisition and utilization of public data. The Champ Public Platform can automatically or semi-automatically search, download, integrate, and update public data from a variety of public data sources and institutions, as well as use artificial intelligence and machine learning techniques to label, complement, align, and fuse public data.

Data Type

Data type refers to the form and characteristics of data collected by market research companies. Data types can be divided into two broad categories: quantitative data and qualitative data.

Quantitative data refers to data that can be represented and analyzed numerically or statistically, such as age, income, rating, and frequency. The advantages of quantitative data are that it is more objective, more accurate, more quantifiable and more inferential, but it is also more indifferent, more superficial, more prone to bias and over-interpretation. The quantitative data collection methods commonly used by market research companies are: questionnaires, experiments, and neuromarketing. The quantitative data analysis methods commonly used by market research companies are: descriptive statistics, inferential statistics, hypothesis testing and multivariate analysis. Shangpu Consulting Group uses its own developed Shangpu quantitative platform to provide customers with quantitative data collection and analysis services. The Shangpu quantitative platform can collect, store, calculate, display and interpret the quantitative data of customers, and can also use artificial intelligence and machine learning techniques to select features, reduce dimensions, cluster and classify quantitative data.

Qualitative data refers to data that can be represented and analyzed in words or images, such as opinions, feelings, motivations, and experiences. The advantages of qualitative data are that it is more subjective, more profound, easier to understand and more innovative, but it is also more vague, less accurate, more difficult to quantify and more difficult to infer. The qualitative data collection methods commonly used by market research companies are: interviews, observations, and neuromarketing. The qualitative data analysis methods commonly used by market research companies are: content analysis, discourse analysis, narrative analysis and phenomenological analysis. Shangpu Consulting Group uses its own developed Shangpu qualitative platform to provide customers with qualitative data collection and analysis services. The Shangpu qualitative platform can collect, store, encode, classify and interpret customer qualitative data, as well as use artificial intelligence and machine learning techniques for text mining, image recognition, speech recognition and natural language processing of qualitative data.

Data cleaning

Data cleaning refers to the process by which market research companies check, correct and delete the collected data to improve the quality and consistency of the data. The purpose of data cleaning is to remove errors, duplicates, missing and abnormal parts of the data, so that the data is more accurate, more complete, more standardized and more effective. The steps of data cleaning include: data review, data validation, data repair, and data filtering.

Data review refers to the initial observation and examination of data to identify potential problems and errors in the data. The methods of data review are: data description, data distribution, data relationship and data visualization. Data description refers to the method of statistics and display of the basic characteristics of the data, such as the number, average, standard deviation, maximum and minimum values of the data. Data distribution refers to the method of analyzing and displaying the distribution pattern of data, such as the skewness, kurtosis, normality, and outliers of the data. Data relationships are methods of analyzing and demonstrating correlation and causality between data, such as correlation coefficients, covariances, regressions, and causal graphs of data. Data visualization refers to the method of graphically and dynamically displaying the form and characteristics of data, such as bar charts, line charts, pie charts, and scatter plots of data. Champ Consulting Group uses its own developed Champ Review Platform to provide data review services to its customers. The Shangpu review platform can quickly, comprehensively and intuitively review customer data, and can also use artificial intelligence and machine learning technology to automatically identify and prompt data problems and errors.

Data verification refers to the steps of testing data to determine whether the data meets the expected requirements and conditions. Data validation methods include: data format, data range, data consistency, and data integrity. Data format refers to the method of verifying the form and structure of data, such as the type, length, decimal point and separator of the data. Data range refers to the method of testing the range of values of data, such as the maximum, minimum, extreme and reasonable values of the data. Data consistency refers to the method of testing the logic and semantics of data, such as the definition, meaning, units, and rules of the data. Data integrity refers to the method of checking the completeness and integrity of data, such as missing, null, duplicate and redundant data. Shangpu Consulting Group uses its own developed Shangpu verification platform to provide customers with data verification services. The Shangpu verification platform can conduct strict, detailed and accurate verification of customer data. At the same time, it can also use artificial intelligence and machine learning technology to automatically detect and report data discrepancies and irrationality.

Data repair is the process of making necessary modifications and deletions to data to correct errors and inconsistencies in the data. Data repair methods include data replacement, data interpolation, data deletion, and data merging. Data replacement refers to the method of replacing wrong data with correct data, such as replacing outliers or wrong values with averages, medians, or modes. Data interpolation refers to the method of using reasonable data to fill in the missing data, such as linear interpolation, polynomial interpolation or regression interpolation. Data deletion refers to a method of deleting useless or harmful data, such as deleting duplicate data, redundant data, or irrelevant data. Data merging refers to the method of merging multiple data sources or data sets into one data source or data set, such as joining, merging, or intersection. Champ Consulting Group uses its own developed Champ Repair Platform to provide customers with data repair services. The Shangpu repair platform can automatically or semi-automatically repair customer data, and can also use artificial intelligence and machine learning technology to evaluate and optimize the repair effect of data.

Data filtering refers to the necessary selection and extraction of data to extract useful and valuable parts of the data. Data filtering methods include: data sorting, data grouping, data filtering, and data sampling. Data sorting refers to a method of sorting or arranging data according to certain rules or criteria, such as according to the size, order, or importance of the data. Data grouping refers to the method of grouping or classifying data according to certain conditions or characteristics, such as according to the type, category or attribute of the data. Data filtering refers to the method of filtering or filtering data according to certain conditions or criteria, such as according to the scope, keywords or logic of the data. Data sampling is a method of extracting a portion of data from the data as a representation, such as by proportion, randomness, or stratification of the data. Champ Consulting Group uses its own developed Champ Screening Platform to provide customers with data screening services. The Shangpu screening platform can perform flexible, efficient and accurate screening of customer data. At the same time, it can also use artificial intelligence and machine learning technology to verify and evaluate the data screening results.

Data analysis

Data analysis refers to the process by which market research companies process, interpret and present cleaned data in order to obtain the meaning and value of the data. The purpose of data analytics is to extract information from data, discover knowledge, generate insights, and support decision making. The steps of data analysis include: data exploration, data modeling, data evaluation, and data presentation.

Data exploration refers to the preliminary analysis and exploration of data to understand the basic characteristics and structure of the data. The methods of data exploration are: data description, data distribution, data relationship and data visualization. Data description refers to the method of statistics and display of the basic characteristics of the data, such as the number, average, standard deviation, maximum and minimum values of the data. Data distribution refers to the method of analyzing and displaying the distribution pattern of data, such as the skewness, kurtosis, normality, and outliers of the data. Data relationships are methods of analyzing and demonstrating correlation and causality between data, such as correlation coefficients, covariances, regressions, and causal graphs of data. Data visualization refers to the method of graphically and dynamically displaying the form and characteristics of data, such as bar charts, line charts, pie charts, and scatter plots of data. The Shangpu Consulting Group uses its own developed Shangpu Exploration Platform to provide customers with data exploration services. The Shangpu Discovery platform can quickly, comprehensively and intuitively explore the customer's data. At the same time, it can also use artificial intelligence and machine learning technology to automatically identify and summarize the characteristics and structure of the data.

Data modeling is the step of further analyzing and modeling data to discover patterns and patterns in the data. Data modeling methods include data mining, machine learning, deep learning and artificial intelligence. Data mining refers to the use of statistical and computational methods to discover useful and meaningful information and knowledge from large amounts of data, such as patterns, associations, clustering and classification of data. Machine learning refers to methods that allow computers to learn and optimize from data, such as regression, classification, clustering, and recommend of data. Deep learning refers to the use of multi-layer neural networks to efficiently learn and recognize complex data, such as image recognition, speech recognition, natural language processing, and reinforcement learning. Artificial intelligence refers to methods that allow computers to have human intelligence and capabilities, such as semantic understanding of data, sentiment analysis, dialogue generation, and creative generation. Champu Consulting Group uses its own developed Champu modeling platform to provide customers with data modeling services. The Champu modeling platform can model customer data in depth, efficiently and accurately, and can also use artificial intelligence and machine learning techniques to automatically discover and interpret data patterns and patterns.

Data evaluation refers to the steps of evaluating and validating the results of data analysis and modeling to determine the credibility and validity of the data. The methods of data evaluation are: data quality, data effect, data value and data ethics. Data quality refers to the methods used to assess the accuracy, completeness, consistency, and timeliness of data, such as data errors, biases, variances, and updates. Data effect refers to the method of evaluating the effect and performance of data analysis and modeling, such as data accuracy, recall rate,F1value andAUCvalue, etc. Data value refers to the method of evaluating the value and significance of data analysis and modeling, such as the amount of data information, knowledge, insight and decision-making. Data ethics refers to methods that assess the ethics and responsibilities of data analysis and modeling, such as data privacy, security, fairness, and interpretability. Champ Consulting Group uses its own developed Champ Evaluation Platform to provide customers with data evaluation services. The Shangpu evaluation platform can conduct a comprehensive, objective and scientific evaluation of customer data. At the same time, it can also use artificial intelligence and machine learning technology to automatically optimize and improve the evaluation results of the data.

Data presentation is the step of presenting and communicating the results of the analysis and modeling of data to convey the meaning and value of the data. Data presentation methods include: data reports, data charts, data dashboards, and data stories. Data reporting is a method of describing and interpreting the results of data analysis and modeling in words and numbers, such as data summaries, conclusions, recommendations, and limitations. Data charts are methods of using graphs and images to present and interpret the results of data analysis and modeling, such as histograms, line charts, pie charts, and scatter plots of data. Data dashboards are a way to present and interpret the results of data analysis and modeling in a dynamic and interactive manner, such as data sliders, buttons, drop-down menus, and maps. A data story is a method of presenting and interpreting the results of data analysis and modeling in a story and emotional manner, such as the context, conflict, climax, and ending of the data. The Shangpu Consulting Group uses its own developed Shangpu presentation platform to provide customers with data presentation services. The Champu presentation platform can provide a clear, beautiful and interesting presentation of customer data, as well as automatic generation and customization of data presentation results using artificial intelligence and machine learning techniques.