Data analysis of 1. consumer research

The data analysis of consumer research refers to the process of processing, sorting, summarizing, analyzing and interpreting the collected consumer-related data. The purpose is to discover the laws, trends, patterns, relationships and insights behind the data, and provide marketing decisions. Basis and guidance. The data analysis of consumer research can be divided into the following steps:

1. Data cleaning

Data cleaning refers to the process of quality checking and error correction of the original data, including deleting or modifying missing values, abnormal values, duplicate values, inconsistent values, etc., to make the data more accurate, complete, consistent and reliable. There are many ways to clean data, such as using statistical software, programming languages, spreadsheets and other tools for automatic or manual data cleaning, or using professional data cleaning services or platforms for data cleaning. The importance of data cleaning is self-evident, because the quality of data directly affects the results and credibility of data analysis.

2. Data exploration

Data exploration refers to the process of preliminary observation and description of the cleaned data, including calculating the basic statistics of data (such as mean, standard deviation, maximum, minimum, median, quantile, etc.), drawing data graphs (such as histogram, pie chart, line chart, scatter chart, box chart, etc.), testing the distribution of data (such as normal distribution, skewed distribution, peak distribution, etc.), analyzing the correlation of data (such as Pearson correlation coefficient, Spearman correlation coefficient, determination coefficient, etc.) wait. The purpose of data exploration is to have a general understanding of the data, discover the characteristics, changes, differences and connections of the data, and provide direction and basis for further data analysis. There are also many ways to explore data, such as using statistical software, programming languages, spreadsheets and other tools for data exploration, or using professional data exploration services or platforms for data exploration.

3. Data Modeling

Data modeling refers to the process of more in-depth analysis and mining of data, including the use of various statistical models, machine learning models, artificial intelligence models, etc. to predict, classify, cluster, correlate, regression, cause and effect, optimization and other analysis of data, so as to obtain more valuable information and insights. The purpose of data modeling is to understand and interpret the data at a higher level, discover the reasons, effects, effects and meanings behind the data, and provide support and basis for the formulation and evaluation of marketing strategies. There are also many ways to model data, such as using statistical software, programming languages, spreadsheets, and other tools for data modeling, or using professional data modeling services or platforms for data modeling.

Data Presentation of 2. Consumer Research

The data presentation of consumer research refers to the process of presenting the results of data analysis to the target audience in a clear, concise and powerful way. The purpose is to enable the audience to quickly, accurately and comprehensively understand the meaning and value of the data, so as to generate resonance, trust and action. The data presentation of consumer research can be divided into the following steps:

1. Identify the target audience

Identifying the target audience is the process of identifying the object and purpose of the data presentation, including analyzing the characteristics, needs, expectations, interests, levels, attitudes, etc. of the audience, as well as the objectives, information, and,Conclusionrecommendations, etc. The purpose of determining the target audience is to develop appropriate strategies and methods for data presentation so that data presentation can effectively convey information and influence the audience. There are many ways to determine the target audience, such as using audience analysis tools, questionnaires, interviews, observations, etc., or using professional audience analysis services or platforms for audience analysis.

2. Choose the appropriate format

Selecting the appropriate format refers to the process of selecting the most suitable form and medium for displaying data according to the target audience and the results of data analysis, including selecting graphics, tables, text, audio, video, animation, interaction and other methods of data, as well as selecting data reports, presentations, articles, posters, web pages, applications, games and other media. The purpose of selecting the appropriate format is to improve the visualization, comprehensibility, memorability, infectability and operability of the data, so that the data presentation can attract, inspire and guide the audience. There are many ways to choose the right format, such as using data visualization tools, presentation software, text editors, audio and video editors, animators, interactive designers, and other tools for data presentation, or using professional data presentation services or platforms for data presentation.

3. Create a persuasive story

Creating persuasive stories refers to the process of organizing and expressing the results of data analysis in a logical, emotional, and meaningful way, including constructing the background, problems, analysis, results,Conclusion, suggestions and other elements, as well as the use of data comparison, contrast, analogy, metaphor, story, case, evidence, citation and other techniques, so as to form a complete, coherent, vivid and powerful data story. The purpose of creating persuasive stories is to enhance the logic, emotion and meaning of the data, so that the data presentation can persuade, move and inspire the audience. There are many ways to create persuasive stories, such as using story structure tools, story element tools, story technique tools and other tools to create data stories, or using professional data story creation services or platforms to create data stories.

Data Analysis and Presentation of 3. Consumer Research

In order to better illustrate the principles and methods of data analysis and presentation of consumer research, this paper will introduce some practical cases, which are part of the consumer research projects conducted by the Shangpu Consulting Company for its clients, which are representative and reference.

2. A survey of consumer behavior of a cosmetic brand

A cosmetics brand is a well-known high-end cosmetics manufacturer in China. In order to adapt to the changes in the market and the needs of consumers, it commissioned Shangpu Consulting to conduct a consumer behavior survey to understand its existing and potential consumers. Purchase behavior and use behavior, as well as comparison and difference with competitors.

Shangpu Consulting has adopted a variety of data collection methods, including online questionnaires, telephone interviews, mysterious customers, social media analysis, etc., and collected more than 1000 valid consumer data, covering consumers' basic information, purchase behavior, use behavior, satisfaction score, important attributes, loyalty, recommend willingness, improvement suggestions, etc.

The data collected was analyzed by Champ Consulting for data cleansing, data exploration and data modeling, and the following key findings and insights were obtained:

Consumers' overall satisfaction with the cosmetics brand was high, with an average rating of 4.1 (out of 5), higher than the industry average and the ratings of major competitors.

Consumers have a high evaluation of the product quality, effect, safety, packaging and brand image of the cosmetics brand, but their evaluation of its product type, price, promotion and after-sales service is low.

Consumers have high loyalty and willingness to recommend the cosmetics brand. About 75% of consumers said they would buy the brand's cosmetics again, and about 80% of consumers said they would recommend the brand's cosmetics to others.

Consumers have certain rules and characteristics of the purchase behavior and use behavior of the cosmetics brand. For example, consumers are more inclined to buy the brand's cosmetics online than in physical stores; consumers are more inclined to use the brand's cosmetics on holidays or special occasions, rather than in daily life; consumers are more inclined to use the brand's skin care products than makeup products.

Consumers are different from competitors in the ranking and weighting of important attributes of the cosmetics brand. Consumers of the brand pay more attention to product quality, effectiveness and safety, while consumers of competitors pay more attention to product type, price and promotion.

Consumers' satisfaction and loyalty to the cosmetics brand are affected by multiple factors, the most important of which are product quality, effectiveness and safety. Changes in these three factors can explain about consumer satisfaction and loyalty. 50% of the change.

Based on the results of the data analysis, Champ Consulting chose the appropriate format and medium, created a persuasive story, and produced a detailed data report for the management and marketing team of the cosmetics brand, including the following parts:

The cover of the data report contains the title, subtitle, date, author and customer information of the data report, as well as the logo of the cosmetics brand and the logo of Shangpu Consulting.

The table of contents of the data report contains the titles and page numbers of the sections and subsections of the data report, as well as the titles and page numbers of the appendices and references of the data report.

Data reportingAbstract, contains the background, purpose, method, results of the data report,Conclusionand a summary of the recommendations, and the data reportedKeywords。

Data reportingText, contains the following chapters and subsections:

Chapter 1: Introduction, contains the background, purpose, scope and structure of the data report.

Chapter 2: Methods, including the introduction of data collection and data analysis methods, as well as the evaluation of data reliability and validity.

Chapter 3: Results, contains the presentation of the results of the data analysis, as well as the presentation of graphics, tables, text and audio of the data.

Chapter IV:Conclusion, contains a summary of the results of the data analysis, as well as a summary of the patterns, trends, patterns, relationships, and insights of the data.

Chapter 5: Recommendations, which contains results based on data analysis andConclusionSpecific, feasible and targeted marketing strategies and actions for the management and marketing team of the cosmetics brand.

The appendix of the data report contains supplementary materials for the data report, such as raw data, detailed data, statistical models, machine learning models, artificial intelligence models, etc.

The references of the data report contain the relevant literature, materials, websites and other information cited in the data report, and are arranged and marked in accordance with the internationally accepted format.

The story of the data report is this:

The cosmetics brand is a well-known domestic high-end cosmetics manufacturer, with excellent product quality, effect, safety, packaging and brand image, highly recognized and loved by consumers, its consumer satisfaction, loyalty and willingness to recommend are higher than the industry average and the main competitors.

However, the cosmetics brand is also facing some challenges and opportunities, its product category, price, promotion and after-sales service and other aspects still need to be improved, its consumer purchase behavior and use behavior have certain rules and characteristics, its consumer's important attributes and weight are different from those of competitors, and its consumer satisfaction and loyalty are affected by many factors, the most important factors are product quality, effectiveness and safety.

Therefore, the cosmetics brand needs to analyze the results andConclusion, formulate and implement effective marketing strategies and actions to improve its competitiveness and brand image in the market, increase its consumer satisfaction and loyalty, expand its consumer size and share, and achieve its long-term development and success.