Definition of Digital Transformation 1. Market Research

The digital transformation of market research refers to the process of using digital technology and platform to realize the automation, intelligence, visualization and interaction of market research in the aspects of data collection, processing, analysis, presentation and application, so as to improve the efficiency, quality and influence of market research. The digital transformation of market research is not only the technological upgrading of market research, but also the thinking change and mode innovation of market research.

Drivers of Digital Transformation 2. Market Research

The digital transformation of market research is the inevitable result of market research adapting to and leading market changes. The motivation for the digital transformation of market research is mainly as follows:

changes in the market environment. With the trend of globalization, digitization, socialization and personalization, the market environment has become more complex, dynamic and diversified, and market demand, competitors, consumer behavior and preferences are also constantly changing and evolving. This requires market research to capture and analyze market information quickly, accurately, comprehensively and deeply, and provide enterprises with timely, effective and insightful market insights and suggestions.

Growth of data resources. With the popularization and application of digital technology, a large amount of data is generated in the market, including structured data (such as sales data, transaction data, inventory data, etc.) and unstructured data (such as social media data, web data, video data, voice data, etc.). These data not only cover all aspects of the market, but also have real-time, diversity and richness, providing more data sources and data dimensions for market research.

development of digital technology. With the development and maturity of digital technologies such as cloud computing, big data, artificial intelligence, Internet of Things, and blockchain, market research has more digital methods and tools that can achieve rapid data collection, efficient processing, intelligent analysis, and Vivid presentation and effective application. These digital technologies not only improve the efficiency and quality of market research, but also expand the scope and depth of market research, so that market research can find more market opportunities and challenges.

Increase the value of market research. With the digital transformation of market research, the value of market research is not only reflected in providing market information and analysis for enterprises, but also in providing market insights and suggestions for enterprises, helping enterprises to formulate and implement market strategies and marketing strategies, and improving their market competitiveness and profitability. The digital transformation of market research also enables market research to better coordinate and integrate with other businesses and departments of the enterprise to form a data-driven market decision-making system.

The process of digital transformation 3. market research

The process of digital transformation of market research can be divided into the following four stages:

Digital preparation phase. The purpose of this stage is to do the basic work for the digital transformation of market research, including formulating the objectives, strategies and plans of digital transformation, evaluating the current situation and needs of digital transformation, establishing the organization and team of digital transformation, cultivating the culture and awareness of digital transformation, and selecting and introducing the methods and tools of digital transformation.

Digital implementation phase. The purpose of this stage is to apply the methods and tools of digital transformation to all aspects of market research, including data collection, processing, analysis, presentation and application, so as to realize the automation, intelligence, visualization and interaction of market research. This phase requires attention to the quality, security and compliance of the data, as well as the applicability, reliability and ease of use of the methods and tools.

Digital assessment phase. The purpose of this phase is to evaluate the effectiveness and value of the digital transformation of market research, including the improvement of the efficiency, quality and influence of digital transformation on market research, and the support and promotion of digital transformation on the enterprise's market strategy and marketing strategy. This stage requires the establishment of digital transformation evaluation indicators and methods, as well as the collection and analysis of digital transformation feedback and recommendations.

Digital optimization phase. The purpose of this stage is to optimize and improve the digital transformation of market research according to the evaluation results of the digital transformation of market research, including adjusting the objectives, strategies and plans of the digital transformation, improving the organization and team of the digital transformation, strengthening the culture and awareness of the digital transformation, and updating and upgrading the methods and tools of the digital transformation. This phase requires constant attention to market changes and needs, as well as the development and innovation of digital technologies.

Methods and tools for digital transformation 4. market research

The methods and tools for the digital transformation of market research can be divided into the following categories according to the various aspects of market research:

Methods and tools for data collection. Data collection is the first step in market research and the source of data for market research. Methods and tools for data collection include the following:

Online surveys. Online survey is a method of using the Internet platform to send questionnaires to target respondents through e-mail, web pages, social media, mobile applications, etc., to collect their feedback and opinions. The advantage of online survey is that it can collect data quickly, low cost, wide coverage and high efficiency, and can realize real-time update and analysis of data. There are many tools for online surveys, such as SurveyMonkey, Qualtrics, Google Forms, etc.

Web crawler. Web crawlers are methods that use programs to automatically crawl and extract relevant data from the Internet. The advantage of web crawler is that it can collect massive, diverse and rich data, and can customize the source, type, format and frequency of the data. There are many tools for web crawlers, such as Scrapy, Beautiful Soup, Selenium, etc.

IoT devices. IoT devices refer to smart devices that can collect and transmit data through network connections, such as smart phones, smart watches, smart speakers, smart cars, and smart homes. The advantage of IoT devices is that they can collect real-time, accurate, and detailed data, and can realize remote control and management of data. There are many tools for IoT devices, such as Arduino, Raspberry Pi, Amazon Echo, etc.

Methods and tools for data processing. Data processing is the second step of market research and the data base of market research. Data processing methods and tools, including the following:

Data cleaning. Data cleaning refers to the process of quality checking and error correction of collected data, such as removing duplicate data, missing data, abnormal data, inconsistent data, etc. The advantage of data cleaning is that it can improve the accuracy, completeness and consistency of data and provide reliable data for subsequent data analysis. There are many tools for data cleaning, such as Excel, OpenRefine, Trifacta, etc.

Data conversion. Data transformation refers to the process of transforming the format and structure of collected data, such as converting unstructured data into structured data, or converting data into a format suitable for specific analysis methods. The advantage of data conversion is that it can improve the readability, usability and compatibility of data, and provide suitable data for subsequent data analysis. There are many tools for data conversion, such as Python, R, SQL, etc.

Data integration. Data integration refers to the process of merging and integrating data from different sources, types, and formats, such as linking and merging sales data, transaction data, inventory data, social media data, and so on. The advantage of data integration is that it can improve the completeness, multidimension and richness of data, and provide comprehensive data for subsequent data analysis. There are many tools for data integration, such as Hadoop, Spark, Tableau, etc.

Methods and tools for data analysis. Data analysis is the third step of market research and the data core of market research. Methods and tools for data analysis include the following:

Statistical analysis. Statistical analysis is the process of describing, inferring, predicting, and optimizing data using mathematical and statistical methods, such as calculating the average, variance, correlation, regression, classification, and clustering of data. The advantage of statistical analysis is that it can reveal the patterns, trends, differences and relationships of data and provide quantitative analysis and evidence for market research. There are many tools for statistical analysis, such as SPSS, SAS, Stata, etc.

Text analysis. Text analysis is the process of processing, understanding, generating and applying text data using natural language processing methods, such as text segmentation, part-of-speech tagging, named entity recognition, sentiment analysis,Abstractgeneration, machine translation, etc. The advantage of text analysis is that it can mine the semantics, sentiment, theme and intention of text data, and provide qualitative analysis and insight for market research. There are many tools for text analysis, such as NLTK, Gensim, BERT, etc.

Image analysis. Image analysis is the process of processing, identifying, generating and applying image data using computer vision methods, such as image compression, enhancement, feature extraction, face recognition, object detection, style transfer, etc. The advantage of image analysis is that it can identify the content, attributes, style and context of image data and provide qualitative analysis and insight for market research. There are many tools for image analysis, such as OpenCV, TensorFlow, GAN, etc.

Methods and tools for data presentation. Data presentation is the fourth step of market research and the data expression of market research. The methods and tools for data presentation include the following:

Data visualization. Data visualization is the process of converting data into an intuitive, easy-to-understand, and beautiful visual form using graphs, charts, maps, dashboards, etc. The advantage of data visualization is that it can highlight the focus, comparison, correlation and distribution of data, and provide vivid display and explanation for market research. There are many tools for data visualization, such as Excel, Power BI, D3.js, etc.

Data storytelling. Data storytelling is the process of using text, voice, video, animation and other methods to combine data with story elements, such as plot, characters, conflicts, climax, etc., to build a logical, emotional, and influential story. The advantage of data storytelling is that it can stimulate the emotion, resonance, inspiration and action of the data, and provide interesting narration and dissemination for market research. There are many tools for data storytelling, such as PowerPoint, Storybird, Lumen5, etc.

data interaction. Data interaction is the process of using web pages, mobile applications, virtual reality, augmented reality and other methods to combine data with user interaction and feedback to achieve dynamic, real-time, personalized presentation and application of data. The advantage of data interaction is that it can increase the participation, experience, satisfaction and loyalty of data, and provide flexible exploration and application for market research. There are many tools for data interaction, such as HTML, CSS, JavaScript, React, Unity, etc.

Methods and tools for data application. Data application is the fifth step of market research and the data value of market research. Data application methods and tools, including the following:

Data-driven decision making. Data-driven decision-making is the process of using the results of data analysis to provide the basis and guidance for the enterprise's market strategy and marketing strategy. The advantage of data-driven decision-making is that it can improve the accuracy, effectiveness and timeliness of decision-making, and provide protection for the market competitiveness and profitability of enterprises. There are many tools for data-driven decision making, such as Excel, Power BI, Tableau, etc.

Data-driven innovation. Data-driven innovation is the process of using insights from data analytics to provide inspiration and direction for a company's market and marketing innovations. The advantage of data-driven innovation is that it can improve the feasibility, sustainability and differentiation of innovation, and power the market growth and brand influence of enterprises. There are many tools for data-driven innovation, such as Python, R, TensorFlow, etc.

Data-driven optimization. Data-driven optimization is the process of using feedback from data analysis to provide evaluation and recommendations for market optimization and marketing optimization. The advantage of data-driven optimization is that it can improve the pertinence, effectiveness and continuity of optimization, and support the market efficiency and customer satisfaction of enterprises. There are many tools for data-driven optimization, such as Google Analytics, Facebook Insights, Optimizely, etc.

The Effectiveness and Value of Digital Transformation 5. on Market Research

The effectiveness and value of the digital transformation of market research can be measured in the following ways:

The effect and value of market research itself. The digital transformation of market research can improve the efficiency, quality and impact of market research, as follows:

Improve the efficiency of market research. The digital transformation of market research can make use of digital technology and platform to realize the automation, intelligence, visualization and interaction of market research, so as to save the time, cost and manpower of market research, and improve the speed, scale and scope of market research.

Improve the quality of market research. The digital transformation of market research can use digital technology and platforms to achieve the quality, security and compliance of market research data, improve the accuracy, completeness and consistency of market research, and improve the depth, breadth and insight of market research analysis.

Increase the impact of market research. The digital transformation of market research can use digital technology and platforms to realize the readability, usability and compatibility of market research data, improve the intuitiveness, understandability and aesthetics of market research display, and improve the participation, experience and satisfaction of market research dissemination.

The effect and value of the enterprise's market strategy and marketing strategy. The digital transformation of market research can support and promote the market strategy and marketing strategy of enterprises, as follows:

Support the company's market strategy. The digital transformation of market research can provide enterprises with timely, effective and insightful market insights and suggestions, help enterprises formulate and implement market strategies that meet market demand, competitive situation, consumer behavior and satisfaction, and improve their market competitiveness and profitability.

Promote the marketing strategy of the enterprise. The digital transformation of market research can provide companies with inspiration and direction for market innovation and marketing innovation, help companies develop and promote market products and services that meet market opportunities and challenges, and improve their market growth and brand influence.

Optimize your business's market efficiency and customer satisfaction. The digital transformation of market research can provide enterprises with market optimization and marketing optimization for evaluation and recommendations, help enterprises improve and adjust market processes and marketing activities that meet market feedback and customer needs, and improve their market efficiency and customer satisfaction.

A Case Study of Digital Transformation 6. on Market Research

In order to better explain the theory and practice of digital transformation of market research, this article will combine the specific cases of market research services provided by Shangpu Consulting Company to show the process, methods and tools of digital transformation of market research, as well as the effect and value of digital transformation.

Case 1: Market research services for market demand forecasting and product positioning for an automobile manufacturer

The purpose and background of the market research: The automaker plans to launch a new electric vehicle in the next three years. It needs to understand the scale of demand in the target market, the competitive landscape, consumer preferences and purchase intentions, and determine the product's pricing, function and The best combination of design and other aspects.

the process and methods of market research:

Data collection: use online survey method to send questionnaires to potential consumers in the target market to collect information on their cognition, attitude, demand and willingness of electric vehicles. At the same time, use web crawler method to capture and extract data related to electric vehicles from the Internet, including market size, competitors, product parameters, user comments and other data.

Data processing: use data cleaning methods to carry out quality inspection and error correction on the collected data, remove duplicate data, missing data, abnormal data, inconsistent data, etc., use data conversion methods to transform the format and structure of the collected data, convert unstructured data into structured data, or convert data into a format suitable for specific analysis methods, and use data integration methods, merge and integrate data from different sources, types, and formats, and associate and integrate data from online surveys with data from web crawlers.

Data analysis: the process of describing, inferring, predicting and optimizing the data by using the method of statistical analysis, calculating the average value, variance, correlation, regression, classification and clustering of the data, revealing the law, trend, difference and relationship of the data, providing quantitative analysis and evidence for market demand prediction and product positioning, and using the method of text analysis, the process of processing, understanding, generating and applying text data, word segmentation, part-of-speech tagging, named entity recognition, sentiment analysis, and,AbstractGeneration, machine translation, etc., to mine the semantics, sentiment, themes and intentions of text data to provide qualitative analysis and insights for market demand forecasting and product positioning.

Data presentation: use data visualization methods to convert data into intuitive, easy-to-understand, and beautiful visual forms, highlight the focus, comparison, correlation and distribution of data, provide vivid display and explanation for market demand prediction and product positioning, use data storytelling methods, combine data with story elements, and build a logical, emotional, and influential story, stimulate the emotion, resonance, inspiration and action of data, provide interesting narration and dissemination for market demand prediction and product positioning, use the method of data interaction, combine data with user interaction and feedback, realize the dynamic, real-time and personalized presentation and application of data, and increase the participation, experience, satisfaction and loyalty of data, provide flexible exploration and application for market demand forecasting and product positioning.

Data application: use data-driven decision-making methods to provide basis and guidance for the enterprise's market strategy and marketing strategy, help enterprises to formulate and implement market strategy and marketing strategy in line with market demand, competitive situation, consumer behavior and satisfaction, improve the market competitiveness and profitability of enterprises, and use data-driven innovation methods to provide inspiration and direction for the enterprise's market innovation and marketing innovation, help enterprises to develop and promote market products and services that meet market opportunities and challenges, improve market growth and brand influence, use data-driven optimization methods to provide evaluation and suggestions for enterprise market optimization and marketing optimization, help enterprises improve and adjust market processes and marketing activities that meet market feedback and customer needs, and improve enterprise market efficiency and customer satisfaction.

Effectiveness and value of market research: The automaker has achieved the following results and value through the digital transformation of market research:

Improve the efficiency, quality and influence of market research. The digital transformation of market research has enabled the automaker to collect and analyze large amounts of data in a short period of time, improving the speed, scale and scope of market research, while ensuring the quality, safety and compliance of data, improving the accuracy, completeness and consistency of market research, and enabling the automaker to present and disseminate data in a lively, interesting and flexible way, it improves the intuitiveness, understandability and aesthetics of market research, and increases the participation, experience and satisfaction of market research.

It supports the market strategy and marketing strategy of the enterprise. The digital transformation of market research enables the automobile manufacturer to accurately predict the demand scale, competition pattern, consumer preference and purchase intention of the target market, provides the basis and guidance for the enterprise's market strategy and marketing strategy, helps the enterprise to formulate and implement the market strategy and marketing strategy in line with the market demand, competition situation, consumer behavior and satisfaction, and improves the market competitiveness and profitability of the enterprise, it also enables the automaker to flexibly carry out market innovation and marketing innovation, providing impetus for the company's market growth and brand influence.

Optimize the market efficiency and customer satisfaction of the enterprise. The digital transformation of market research enables the automobile manufacturer to collect and analyze market feedback and customer needs in a timely manner, provides evaluation and suggestions for the enterprise's market optimization and marketing optimization, helps the enterprise to improve and adjust the market process and marketing activities that meet the market feedback and customer needs, and improves the market efficiency and customer satisfaction of the enterprise.

Case 2: providing market research services for market segmentation and product customization for a clothing brand

The purpose and background of the market research: The clothing brand plans to launch a new customized clothing service in the next year. It needs to understand the consumer characteristics, needs and preferences of the target market, and determine the best combination of style, function and design of the product.

the process and methods of market research:

Data collection: use the method of Internet of things devices to provide smart watches, smart clothes, smart shoes, etc. to potential consumers in the target market, collect their body data, exercise data, health data and other information, and at the same time use the method of web crawler to capture and extract clothing-related data from the Internet, including market trends, competitors, product parameters, user comments and other data.

Data processing: use data cleaning methods to carry out quality inspection and error correction on the collected data, remove duplicate data, missing data, abnormal data, inconsistent data, etc., use data conversion methods to transform the format and structure of the collected data, convert unstructured data into structured data, or convert data into a format suitable for specific analysis methods, and use data integration methods, combine and integrate data from different sources, types, and formats, and associate and integrate data from IoT devices with data from web crawlers.

Data analysis: the process of describing, inferring, predicting and optimizing the data by using the method of statistical analysis, calculating the average value, variance, correlation, regression, classification and clustering of the data, revealing the law, trend, difference and relationship of the data, providing quantitative analysis and evidence for market segmentation and product customization, and using the method of image analysis, the process of processing, recognition, generation and application of image data, image compression, enhancement, feature extraction, face recognition, object detection, style transfer, etc., identify the content, attributes, style and context of image data, and provide qualitative analysis and insight for market segmentation and product customization.

Data presentation: use data visualization methods to convert data into intuitive, easy-to-understand and beautiful visual forms, highlight the focus, comparison, correlation and distribution of data, provide vivid display and explanation for market segmentation and product customization, use data storytelling methods, combine data with story elements, and build a logical, emotional and influential story, stimulate the emotion, resonance, inspiration and action of data, provide interesting narration and dissemination for market segmentation and product customization, and realize data application by combining data interaction with user interaction and feedback.

Data application: use data-driven decision-making methods to provide basis and guidance for the enterprise's market strategy and marketing strategy, help enterprises to formulate and implement market strategy and marketing strategy in line with consumer characteristics, needs and preferences, improve the market competitiveness and profitability of enterprises, and use data-driven innovation methods to provide inspiration and direction for the enterprise's market innovation and marketing innovation, help enterprises to develop and promote market products and services in line with consumer style, function and design, improve market growth and brand influence, use data-driven optimization methods to provide evaluation and suggestions for market optimization and marketing optimization, help enterprises improve and adjust market processes and marketing activities in line with consumer feedback and demand, and improve market efficiency and customer satisfaction.

The effect and value of market research: The clothing brand has obtained the following effects and values through the digital transformation of market research:

Improve the efficiency, quality and influence of market research. The digital transformation of market research enables the clothing brand to collect and analyze a large amount of data in a short time, improves the speed, scale and scope of market research, ensures the quality, safety and compliance of data, improves the accuracy, integrity and consistency of market research, and enables the clothing brand to present and disseminate data in a vivid, interesting and flexible way, it improves the intuitiveness, understandability and aesthetics of market research, and increases the participation, experience and satisfaction of market research.

It supports the market strategy and marketing strategy of the enterprise. The digital transformation of market research enables the clothing brand to accurately subdivide the consumer characteristics, needs and preferences of the target market, provides the basis and guidance for the enterprise's market strategy and marketing strategy, helps the enterprise to formulate and implement the market strategy and marketing strategy in line with the consumer characteristics, needs and preferences, and improves the market competitiveness and profitability of the enterprise, it also enables the clothing brand to flexibly carry out market innovation and marketing innovation, which provides impetus for the market growth and brand influence of the enterprise.

Optimize the market efficiency and customer satisfaction of the enterprise. The digital transformation of market research enables the clothing brand to collect and analyze consumer feedback and demand in a timely manner, provides evaluation and suggestions for the market optimization and marketing optimization of the enterprise, helps the enterprise to improve and adjust the market process and marketing activities in line with consumer feedback and demand, and improves the market efficiency and customer satisfaction of the enterprise.