Industrial market research refers to market research and analysis of producers, distributors, purchasers and users of industrial products or services to understand the size, structure, demand, competition, trends, etc. of the market, and to provide basis and guidance for strategic decision-making. Compared with consumer market research, industrial market research has the following characteristics:

Industrial products or services are usually intermediate products or inputs, not directly to the final consumer, but through a complex industrial chain or supply chain to transfer value;

Demand for industrial products or services is influenced by downstream industries or end markets and is derivative and cyclical;

The purchase process of industrial products or services involves multiple decision-making levels and participants, and needs to consider technical performance, quality standards, price cost, delivery time and other factors;

The competitive landscape of industrial products or services is usually stable, but there are also potential threats such as technological innovation, new entrants, and substitutes;

Market information for industrial products or services is relatively opaque and needs to be obtained through a variety of channels and means.

Due to the complexity and professionalism of industrial market research, it is necessary to follow scientific methods and processes, otherwise it is easy to fall into some misunderstandings and traps, which will affect the quality and effectiveness of the research. This paper summarizes the common misunderstandings and traps from the aspects of the objectives, objects, methods, data and analysis of industrial market research, and puts forward corresponding suggestions to avoid and solve them.

1. Goal Setting Aspects

Goal setting is the first and most important step in industrial market research. The goal setting should be clear about the theme, scope, content, purpose and significance of the research, and provide guidance for the follow-up research design. The following pitfalls and pitfalls may arise in the goal-setting process:

Goals are too broad or too specific. Too broad objectives will lead to a lack of focus and depth of research, unable to draw valuable conclusions; too specific objectives will lead to research too narrow and one-sided, unable to reflect the full picture and dynamics of the market.

Goals do not match actual needs. Some researchers do not fully understand the real needs of customers when setting goals, but determine them based on their own experience or preferences, which may lead to inconsistent research results and customer expectations, or even unable to meet the customer's decision-making needs.

The target does not match the resource. Some researchers do not take into account their own or clients' resource conditions, such as time, budget, personnel, technology, etc., when setting goals, which may lead to difficulties and risks in the research process, or the inability to complete the research tasks on time and quality.

To avoid and address these pitfalls, the following principles are recommended for goal setting:

Objectives should be feasible, measurable, relevant and clear. Feasibility means that the goal should be in line with the actual situation of the market and the actual needs of the customer, not too high or too low; measurability means that the goal should be able to be measured and evaluated through data or indicators, not vague or subjective; relevance means that the goal should be related to the customer's strategic objectives and decision-making issues, not deviated or redundant; clarity means that the goal should clearly express the theme, scope, content, purpose and significance of the research, without ambiguity or confusion.

The goal should be fully communicated and confirmed with the customer. Before setting goals, it is necessary to conduct in-depth communication and exchanges with customers to understand their background, needs, expectations, problems, etc. in order to determine the appropriate research topics and scope; after setting goals, it is necessary to report and feedback to customers in a timely manner. Solicit customer opinions and suggestions in order to adjust and improve research content and methods.

Targets should be reasonably matched and allocated with resources. When setting goals, we should make reasonable research plans and arrangements according to our own or customers' resource conditions, such as time, budget, personnel, technology, etc., to avoid waste or shortage of resources; when implementing goals, we should adjust the allocation and use of resources in time according to the progress and effect of research, so as to avoid the shortage or idleness of resources.

2. Object Selection Aspects

Object selection is the second step of industrial market research, but also a very critical step. The object selection should be based on the research objectives and methods to determine the type, quantity, characteristics, sources, etc. of the research object, and provide the basis for subsequent data collection. The following pitfalls and pitfalls may arise in the object selection process:

The object is too single or too diverse. Too single object will lead to the lack of representativeness and universality of the research, which can not reflect the diversity and complexity of the market; too diverse object will lead to the lack of pertinence and effectiveness of the research, which can not reflect the core characteristics and key factors of the market.

Object does not match target. When selecting objects, some researchers do not determine the type, quantity, characteristics, etc. of the objects according to the research objectives, but randomly select or rely on ready-made objects, which may lead to inconsistency between the research results and the research objectives, or even unable to answer the research questions.

Object does not match method. When selecting objects, some researchers do not determine the source, acquisition method, sampling method, etc. of the object according to the research method, but use inappropriate or irregular object selection methods, which may lead to the quality and reliability of the research data being affected, and even deviations and errors.

In order to avoid and solve these pitfalls and pitfalls, it is recommended to follow the following principles in object selection:

The object should be representative, diverse, targeted and effective. Representation means that the object should be able to reflect the overall characteristics and laws of the market, and should not deviate or be biased. Diversity means that the object should be able to reflect the differences and complexity of the market, and should not be ignored or simplified. Targeted means that the object should be able to reflect the core characteristics and key factors of the market, and should not be redundant or irrelevant. Validity means that the object should be able to provide effective and usable data, not invalid or invalid.

The object is sufficiently matched and corresponding to the target. When selecting objects, the type, quantity and characteristics of objects should be determined according to the research objectives, such as producers, distributors, purchasers, users, etc., as well as their scale, region, industry, functions, etc.; at the same time, the key points and difficulties of the objects should be determined according to the research problems, such as demand, satisfaction, loyalty, switching willingness, etc.

Objects should be reasonably matched and selected with methods. When selecting objects, the source, acquisition method and sampling method of the objects should be determined according to the research method, such as second-hand data, first-hand data, quantitative data, qualitative data, etc., as well as their channels, sources, quality and reliability. At the same time, the sampling method, sampling frame, sampling unit and sampling proportion of the objects should be determined according to the research design.

Application of 3. methods

The application of methods is the third and very important step in industrial market research. Methods According to the research objectives and objects, the appropriate data collection and analysis methods should be selected to provide support for the subsequent presentation of the results. The following misunderstandings and traps may occur in the application of the method:

The method is too simple or too complex. Too single method will lead to the lack of multi-dimensional and multi-angle vision, can not fully and in-depth understanding of the market; too complex method will lead to research increase unnecessary difficulty and cost, can not effectively and efficiently complete the research.

Method does not match target. Some researchers do not choose the appropriate data collection and analysis methods according to the research objectives, but blindly follow or imitate other people's methods, which may lead to inconsistent research results and research objectives, or even unable to answer research questions.

Method does not match object. Some researchers do not choose the appropriate data collection and analysis methods according to the research object, but use inapplicable or non-standard methods, which may lead to the quality and reliability of the research data being affected, and even bias and error.

In order to avoid and solve these misunderstandings and pitfalls, it is recommended to follow the following principles when applying the method:

The method should have applicability, diversity, rationality and effectiveness. Applicability means that the method should conform to the theme, scope and content of the research, and should not deviate or surpass it. Diversity means that the method should be able to collect and analyze data from multiple dimensions and angles, and should not be single or one-sided. Rationality means that the method should conform to scientific logic and norms, and should not be random or confused. Effectiveness means that the method should be able to provide effective and credible data and results, don't be ineffective or unreliable.

Methods should be adequately matched and selected with the target. In the use of methods, according to the research objectives to choose the appropriate data collection and analysis methods, such as quantitative methods, qualitative methods, mixed methods, as well as their advantages and disadvantages, applicable conditions, operating steps, etc.; at the same time, according to the research problem to choose the appropriate data types, indicators, models, tools, etc., as well as their meaning, calculation methods, application scenarios.

Methods should be reasonably matched and used with objects. In the use of methods, according to the research object to choose the appropriate data collection and analysis methods, such as questionnaires, interviews, observation experiments, as well as their design, implementation, evaluation, etc.; at the same time, according to the characteristics of the object and feedback to adjust and optimize the use of methods, such as increasing or reducing the problem, change or maintain the order, improve or reduce the difficulty.

4. Data Processing

Data processing is the fourth and crucial step in industrial market research. According to the research methods and results, data processing should be carried out to clean, organize, summarize and analyze the collected data, so as to provide the basis for the subsequent results. The following pitfalls and pitfalls may occur in the process of data processing:

Data is too cluttered or too lean. Too cluttered data can lead to a lack of structure and logic in research that clearly demonstrates the characteristics and patterns of the market; too streamlined data can lead to a lack of detail and depth in research that accurately explains the causes and effects of the market.

Data does not match target. When processing data, some researchers do not determine the type, quantity, quality, etc. of the data according to the research objectives, but arbitrarily select or ignore some of the data, which may lead to inconsistency between the research results and the research objectives, or even unable to answer the research questions.

The data does not match the method. Some researchers do not determine the source, acquisition method, sampling method, etc. of the data according to the research method, but use inappropriate or irregular data processing methods, which may lead to the quality and reliability of the research data being affected, and even deviations and errors.

In order to avoid and solve these misunderstandings and traps, it is recommended to follow the following principles when processing data:

Data should be complete, clear, accurate and valid. Completeness means that the data should be able to cover all relevant aspects of the market and should not omit or delete important data. Clarity means that the data should be able to present the structure and logic of the market and should not be confused or vague data. Accuracy means that the data should be able to reflect the real situation of the market and should not be wrong or distorted. Validity means that the data should be able to support and verify the results and conclusions of the research, don't have irrelevant or invalid data.

The data is adequately matched and filtered against the target. When processing data, the type, quantity and quality of data should be determined according to the research objectives, such as quantitative data, qualitative data, first-hand data, second-hand data, etc., as well as their source, reliability, validity period, etc.; at the same time, the key and difficult points of data should be determined according to the research problems, such as demand, satisfaction, loyalty, switching willingness, etc.

The data should be reasonably matched and analyzed with the method. When processing data, the source, acquisition method and sampling method of data should be determined according to the research method, such as questionnaire survey, interview interview, observation experiment, etc., as well as their design, implementation and evaluation, etc. At the same time, the analysis method, index, model and tool of data should be determined according to the research design, such as description statistics, hypothesis test, regression analysis, cluster analysis, etc, and their calculation methods, application scenarios, etc.

Presentation of 5. results

The presentation of results is the fifth and very important step in industrial market research. The results should be presented according to the research objectives and data, the results and conclusions of the study are summarized, displayed, explained and suggested, so as to provide reference and reference for the customer's decision-making. The following pitfalls and pitfalls may arise in the process of presenting the results:

The results are too simple or too complex. Too simple results will lead to the lack of persuasion and value of the research, unable to attract and meet the interests and needs of customers; too complex results will lead to the lack of readability and usability of the research, can not be clearly and effectively communicated to customers.

The result does not match the target. When presenting the results, some researchers do not determine the content, form and level of the results according to the research objectives, but display or ignore some of the results at will, which may lead to inconsistency between the research results and the research objectives, or even fail to answer the research questions.

The results do not match the data. When presenting the results, some researchers do not determine the accuracy, reliability, and validity of the results based on the research data, but subjectively interpret or tamper with some of the results, which may lead to inconsistencies between the research results and the research data, and even deviations and errors.

In order to avoid and solve these pitfalls and pitfalls, it is recommended to follow the following principles when presenting the results:

The results should be complete, clear, accurate and effective. Completeness means that the results should be able to cover all relevant aspects of the research, and important results should not be omitted or deleted. Clarity means that the results should be able to present the structure and logic of the research, and should not be confused or vague. Accuracy means that the results should reflect the real situation of the research and should not be wrong or distorted. Validity means that the results should be able to support and verify the objectives and problems of the research, don't have irrelevant or invalid results.

The results are adequately matched and correspond to the target. When presenting the results, the content, form and level of the results should be determined according to the research objectives, such as summary, display, explanation, suggestions, etc., as well as their purpose, significance, method, etc.; at the same time, the key and difficult points of the results should be determined according to the research questions, such as demand, satisfaction, loyalty, willingness to switch, etc.

The results should be reasonably matched and analyzed with the data. When presenting the results, the accuracy, reliability and validity of the results should be determined according to the research data, such as data source, data quality, data analysis, etc., as well as their basis, evidence, logic, etc.; at the same time, the presentation of the results should be adjusted and optimized according to the characteristics and feedback of the data, such as adding or reducing charts, changing or maintaining colors, improving or reducing accuracy, etc.

6. Case Introduction

Case presentation is the sixth step in industrial market research and a very valuable step. The case introduction should select appropriate customer cases according to the research objectives and results, show the application and effect of industrial market research, and provide reference and reference for customers. The following pitfalls and pitfalls may arise during the introduction of the case:

Too few or too many cases. Too few cases will lead to the lack of practicality and credibility of the research, unable to prove the value and significance of industrial market research, and too many cases will lead to the lack of focus and prominence of the research, unable to highlight the advantages and characteristics of industrial market research.

Case does not match target. When selecting cases, some researchers do not determine the type, quantity, characteristics, etc. of the cases according to the research objectives, but randomly select or rely on ready-made cases, which may lead to inconsistency between the cases and the research objectives, and even fail to reflect the research theme and scope.

Case does not match results. When selecting cases, some researchers do not determine the content, form and level of the case according to the research results, but subjectively fabricate or exaggerate some cases, which may lead to inconsistency between the case and the research results, and even deviation and error.

In order to avoid and solve these misunderstandings and pitfalls, it is recommended to follow the following principles when introducing cases:

The case should be practical, credible, focused and prominent. Practicality means that the case should be able to reflect the operation and effect of industrial market research in practical application, and should not be fictitious or exaggerated; credibility means that the case should be able to provide real and reliable data and evidence, and should not be wrong or distorted; focus means that the case should be able to highlight the help and contribution of industrial market research to customer decision-making, and should not be redundant or irrelevant cases; protrusiveness means that the case should be able to demonstrate the advantages and characteristics of industrial market research, not mediocre or ordinary cases.

Cases should be adequately matched and selected with the objectives. When selecting a case, the type, quantity and characteristics of the case should be determined according to the research objectives, such as industry, product, service, problem, solution, etc., as well as their relevance, representativeness and typicality; at the same time, the content, form and level of the case should be determined according to the research problems, such as background, process, result, evaluation, suggestion, etc, and their purpose, meaning, manner, etc.

Cases should be reasonably matched and analyzed with the results. When selecting cases, the content, form and level of the cases should be determined according to the research results, such as data, charts, models, tools, etc., as well as their basis, evidence, logic, etc.; at the same time, the selection of cases should be adjusted and optimized according to the characteristics and feedback of the results, such as adding or reducing cases, changing or maintaining the order, improving or reducing details, etc.

Below, we will combine the service experience of Shangpu Consulting in the field of industrial market research, introduce some specific cases, and show how we use professional tools and techniques to provide customers with high-quality industrial market research reports.

Case 1: An auto parts manufacturer wants to understand the scale of demand, competitive landscape and future trends in the Chinese market in order to develop a reasonable market entry strategy. We provide the following services to this customer:

Through second-hand data collection and analysis, we have determined the overall scale, structure, and growth rate of China's auto parts market, and predicted the development trend in the next five years;

Through first-hand data collection and analysis, we identified the main demand drivers, demand distribution characteristics, demand trends and other segments of the Chinese auto parts market, and assessed the attractiveness of each segment;

Through competitor analysis, we identify the main competitors in China's auto parts market and their product lines, pricing strategies, channel layout, market share and other competitive situations, and analyze the strengths and weaknesses of each competitor;

Through the customer satisfaction survey, we understand the main buyers of China's auto parts market and their procurement process, procurement standards, procurement preferences and other procurement, and evaluate the image and evaluation of suppliers in the eyes of buyers;

Through market entry strategy recommendations, we provided the customer with specific recommendations on target positioning, product positioning, price positioning, and channel positioning for the Chinese auto parts market, and predicted the benefits and risks of market entry.

Case 2: A chemical raw material supplier wants to understand the supply and demand balance, price fluctuations and import and export situation in the European market in order to formulate a reasonable production and sales plan. We provide the following services to this customer:

Through secondary data collection and analysis, we determined the basic situation of the overall supply and demand, supply and demand structure, supply and demand growth rate of the European chemical raw material market, and predicted the supply and demand balance in the next five years;

Through first-hand data collection and analysis, we identified the main suppliers, distributors, end users and other market participants in the European chemical raw material market, and analyzed their market behavior such as production capacity, sales volume and inventory;

Through price analysis, we identify the main price influencing factors, price fluctuation patterns, price forecasting models and other price conditions in the European chemical raw material market, and provide price forecasts for the coming year;

Through the import and export analysis, we identify the main import and export countries, import and export volume, import and export price difference and other import and export situation of the European chemical raw material market, and analyze the impact of import and export on market supply and demand and price;

Through the production and sales plan proposal, we provided the customer with specific suggestions for the production plan, sales plan, inventory management, risk control and other specific suggestions for the European chemical raw material market, and evaluated the benefits and risks of the plan implementation.