School uniform data analysis method and device, medium and product

Abstract

The invention relates to the technical field of data analysis, in particular to a school uniform data analysis method and device, a medium and a product, and the method comprises the steps: carrying out multi-dimensional mining analysis based on school uniform sales data, and determining a multi-dimensional mining analysis result. And then, display mode selection is performed based on the multi-dimensional mining analysis result, and a data display mode set is determined, so that the visualization effect of the data is improved, and the multi-dimensional mining analysis result is more visual and vivid. And finally, performing data filling display based on the multi-dimensional mining analysis result and the data display form set, determining data display content corresponding to each dimension of mining analysis, and sending the data display content corresponding to multiple dimensions to a display interface, so as to realize visual display of the multi-dimensional mining analysis result of the school uniform sales data. By performing multi-dimensional mining analysis on the school uniform sales data, the deep value behind the school uniform sales data can be mined, which is helpful for enterprises to optimize resource allocation and improve decision-making efficiency and accuracy.

Description

Technical Field

[0001] The present application relates to the technical field of data analysis, and in particular to a school uniform data analysis method, device, medium and product. Background Art

[0002] In the rapidly changing clothing market, school uniforms, as a symbol of school culture and student identity, their sales data is not only a direct reflection of the company's operating conditions, but also a valuable resource for understanding market demand, predicting market trends, and optimizing product design and sales strategies.

[0003] In terms of data processing and analysis, school uniform sales data is an important source of information reflecting market demand, product popularity and market trends. Its analysis methods and means directly affect the decision-making efficiency and market competitiveness of school uniform sales companies. In related technologies, school uniform data analysis methods often focus on simple data statistics and comparisons, lacking the ability to deeply mine sales data and conduct correlation analysis, making it difficult to fully and accurately reflect market dynamics and consumer demand.

[0004] Therefore, how to provide a school uniform data analysis method that can mine the deep value of sales data is an urgent problem to be solved by technical personnel in this field. Summary of the invention

[0005] The purpose of this application is to provide a school uniform data analysis method, device, medium and product to solve at least one of the above technical problems.

[0006] The above invention objectives of the present application are achieved through the following technical solutions: In the first aspect, the present application provides a school uniform data analysis method, device, medium and product, which adopts the following technical solutions: A school uniform data analysis method, comprising: Acquire school uniform sales data, perform multidimensional mining analysis based on the school uniform sales data, and determine the multidimensional mining analysis results; Selecting a display method based on the multidimensional mining analysis results to determine a data display form set, wherein the data display form set provides at least one data display form for each aspect of the analysis results of the multidimensional mining analysis results; Data filling and display are performed based on the multi-dimensional mining and analysis results and the data display form set, the data display content corresponding to each dimensional mining and analysis is determined, and the data display content corresponding to the multiple dimensions is sent to the display interface to achieve a visual display of the multi-dimensional mining and analysis results of school uniform sales data.

[0007] By adopting the above technical solution, multidimensional mining analysis is performed based on school uniform sales data to determine the results of multidimensional mining analysis, wherein the multidimensional mining analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis. Then, based on the results of multidimensional mining analysis, the display method is selected to determine the data display form set, which helps to more intuitively display the key features in the analysis results, improve the visualization effect of the data, and make the multidimensional mining analysis results more intuitive and vivid. Finally, data filling and display are performed based on the multidimensional mining analysis results and the data display form set, the data display content corresponding to each dimension mining analysis is determined, and the data display content corresponding to the multidimensional data is sent to the display interface to realize the visualization of the multidimensional mining analysis results of school uniform sales data. By performing multidimensional mining analysis on school uniform sales data, the deep-level value behind the school uniform sales data can be excavated, which helps enterprises optimize resource allocation and improve decision-making efficiency and accuracy.

[0008] In a preferred example, the present application may be further configured as follows: after performing data filling and display based on the multi-dimensional mining analysis results and the data display form set, and determining the data display content corresponding to each dimensional mining analysis, the application may further include: Based on the data display content corresponding to each dimension mining analysis, anomaly and significance evaluation is performed to determine the significance analysis result, wherein the anomaly and significance evaluation is used to screen out the mining and analysis dimensions that have a significant impact on business decisions; Obtaining user viewing needs, and determining target data display content from the data display content corresponding to each dimension through mining and analysis based on the significance analysis results and the user viewing needs, wherein the user viewing needs are the user's requirements and preferences for personalized data viewing; Accordingly, sending the data display contents corresponding to the multiple dimensions to the display interface includes: The target data display content is sent to the display interface.

[0009] In a preferred example, the present application may be further configured as follows: performing multidimensional mining analysis based on the school uniform sales data to determine the multidimensional mining analysis results includes: Performing a sales trend analysis based on the school uniform sales data to determine a sales trend analysis result, wherein the sales trend analysis is used to identify a trend in the sales volume of school uniforms; Performing product structure analysis based on the school uniform sales data to determine a product structure analysis result, wherein the product structure analysis is used to analyze the sales of school uniforms of different specifications; Performing sales channel analysis based on the school uniform sales data to determine sales channel analysis results, wherein the sales channel analysis is used to analyze the school uniform sales in different sales channels; Performing customer behavior analysis based on the school uniform sales data to determine the customer behavior analysis results, wherein the customer behavior analysis is used to analyze the customer's consumption habits and determine the customer's needs and preferences; A market competition analysis is performed based on the school uniform sales data to determine the market competition analysis results, wherein the market competition analysis is used to compare the sales of competitors in the same industry and determine the market competition situation.

[0010] In a preferred example, the present application may be further configured as follows: selecting a display method based on the multi-dimensional mining analysis result to determine a data display form set includes: Selecting a display method based on the sales trend analysis result and determining that the data display format is a line chart; Selecting a display method based on the product structure analysis result and determining that the data display form is a bar chart; Selecting a display method based on the sales channel analysis results and determining that the data display format is a pie chart; Selecting a display method based on the customer behavior analysis results to determine that the data display form is a scatter plot and a heat map; A display method is selected based on the market competition analysis results, and the data display form is determined to be a radar chart; The correspondence between the multi-dimensional mining analysis results and the data display forms is comprehensively considered to determine a data display form set.

[0011] In a preferred example, the present application may be further configured as follows: after performing multidimensional mining analysis based on the school uniform sales data and determining the multidimensional mining analysis results, the application may further include: An optimization adjustment analysis is performed based on the multi-dimensional mining analysis results to determine sales optimization information, wherein the sales optimization information includes: procurement plan optimization, product structure optimization, sales channel optimization, product recommendation optimization, and competition strategy optimization.

[0012] In a preferred example, the present application can be further configured as follows: When a school uniform delivery order is detected, current school uniform inventory data is obtained, storage location analysis is performed based on the school uniform delivery order and the current school uniform inventory data, and shelf information of school uniforms to be picked is determined; When a school uniform entry order is detected, the current school uniform inventory data is obtained, and the entry location analysis is performed based on the school uniform entry order and the current school uniform inventory data to determine the shelf information of the school uniforms to be entered; By using wireless radio frequency identification technology, school uniform entry information and school uniform exit information are obtained in real time, and based on the school uniform entry information and school uniform exit information, the current school uniform inventory data is updated in real time, so that the school uniform inventory data reflects the school uniform inventory status in real time.

[0013] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned school uniform data analysis method.

[0014] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute the above-mentioned school uniform data analysis method.

[0015] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program, and when the computer program is executed by a processor, the school uniform data analysis method is implemented.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: Based on the school uniform sales data, multidimensional mining analysis is performed to determine the results of the multidimensional mining analysis, where the multidimensional mining analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis. Then, based on the results of the multidimensional mining analysis, the display method is selected to determine the data display form set, which helps to more intuitively display the key features in the analysis results, improve the visualization of the data, and make the multidimensional mining analysis results more intuitive and vivid. Finally, based on the multidimensional mining analysis results and the data display form set, data filling and display are performed to determine the data display content corresponding to each dimension of mining analysis, and the data display content corresponding to each dimension is sent to the display interface to realize the visualization of the multidimensional mining analysis results of school uniform sales data. By performing multidimensional mining analysis on school uniform sales data, the deep-level value behind the school uniform sales data can be excavated, which helps enterprises optimize resource allocation and improve decision-making efficiency and accuracy.

[0017] Conduct sales trend analysis based on school uniform sales data to determine the results of sales trend analysis, conduct product structure analysis based on school uniform sales data to determine the results of product structure analysis, conduct sales channel analysis based on school uniform sales data to determine the results of sales channel analysis, conduct customer behavior analysis based on school uniform sales data to determine the results of customer behavior analysis, conduct market competition analysis based on school uniform sales data to determine the results of market competition analysis. Conducting multi-dimensional mining and analysis based on school uniform sales data will help companies fully understand market conditions, make accurate decisions, and improve operational efficiency and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a school uniform data analysis method according to one embodiment of the present application; Figure 2 It is a structural schematic diagram of a school uniform data analysis device according to one embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device according to one embodiment of the present application. DETAILED DESCRIPTION

[0019] The following combination Figures 1 to 3 This application is described in further detail.

[0020] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0021] In order to make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application. It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the data related to the object is involved in the embodiment of the present application, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in accordance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiment, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiment also needs to be implemented with the authorization and consent of the object.

[0022] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0023] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0024] The embodiment of the present application provides a school uniform data analysis method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102 and step S103, wherein: Step S101: Acquire school uniform sales data, perform multidimensional mining analysis based on the school uniform sales data, and determine the multidimensional mining analysis results.

[0025] For the embodiments of the present application, school uniform sales data, as an important source of information reflecting market demand, product popularity and market trends, contains rich market information and rules. Through data mining technology, the market rules behind the school uniform sales data can be mined, such as seasonal fluctuations, customer purchasing behavior patterns, product life cycle, etc., so that companies can understand the deep value of sales data, which is of great significance for improving the market competitiveness of school uniform companies and optimizing product design and sales strategies.

[0026] Therefore, school uniform sales data is obtained, and the school uniform sales data includes but is not limited to: sales volume, sales revenue, sales channels, sales regions, customer groups, product types, price ranges, sales seasons, return and exchange rates, customer satisfaction, etc. Then, multidimensional mining analysis is performed based on the school uniform sales data to determine the multidimensional mining analysis results, which include sales trend analysis results, product structure analysis results, sales channel analysis results, customer behavior analysis results, and market competition analysis results. The presentation form of the multidimensional mining analysis results can be a summary of mining conclusions, highlighting of key data, etc., which is not limited in the embodiments of the present application. For sales trend analysis, data mining technology can help us understand the overall dynamics of the school uniform market and predict future sales trends of school uniforms, so that school uniform companies can adjust their sales strategies in a timely manner. For product structure analysis, it is easy to understand the market demand for different types of school uniforms, which helps school uniform companies adjust their product structure according to market demand. For sales channel analysis, we analyze the sales of different sales channels (for example, online shopping malls, offline stores, school cooperation, etc.) to understand the contribution and sales efficiency of each channel, so as to optimize the sales channel and improve sales efficiency. For customer behavior analysis, we analyze customers' purchase records, consumption habits and other information to understand their needs and preferences, so as to formulate personalized marketing strategies. For market competition analysis, we compare the sales, market share and other information of competitors in the same industry to understand the market competition situation, which helps to formulate differentiated competition strategies and enhance market competitiveness.

[0027] Step S102: selecting a display method based on the multidimensional mining analysis results to determine a data display form set, wherein the data display form set provides at least one data display form for each analysis result of the multidimensional mining analysis results; Step S103: Perform data filling and display based on the multi-dimensional mining analysis results and the data display form set, determine the data display content corresponding to each dimensional mining analysis, and send the data display content corresponding to the multiple dimensions to the display interface to achieve a visual display of the multi-dimensional mining analysis results of school uniform sales data.

[0028] For the embodiments of the present application, there are multiple data display forms, and different data display forms have differences in the accuracy and efficiency of transmitting information. Therefore, selecting different data display forms for mining and analysis results of different dimensions helps to more intuitively display the key features in the analysis results, improve the visualization effect of the data, and make the multi-dimensional mining and analysis results more intuitive and vivid. Therefore, based on the multi-dimensional mining and analysis results, the display method is selected to determine the data display form set, and the data display form set provides at least one data display form for each aspect of the analysis results of the multi-dimensional mining and analysis results. There are many specific implementation processes for selecting the display method, which are no longer limited in the embodiments of the present application. In one feasible method, the display method is selected based on the sales trend analysis results, and the data display form is determined to be a line graph; the display method is selected based on the product structure analysis results, and the data display form is determined to be a bar graph; the display method is selected based on the sales channel analysis results, and the data display form is determined to be a pie chart; the display method is selected based on the customer behavior analysis results, and the data display form is determined to be a scatter plot and a heat map; the display method is selected based on the market competition analysis results, and the data display form is determined to be a radar chart; the correspondence between the multi-dimensional mining analysis results and the data display form is comprehensively determined to determine a set of data display forms.

[0029] Finally, data filling and display are performed based on the multi-dimensional mining analysis results and the data display form set, the data display content corresponding to each dimension mining analysis is determined, and the data display content corresponding to each dimension is sent to the display interface to realize the visualization of the multi-dimensional mining analysis results of school uniform sales data. By converting complex school uniform sales data and multi-dimensional mining analysis results into intuitive and easy-to-understand visualization charts, it helps decision makers to quickly capture key information, helps enterprises optimize resource allocation, and improves decision-making efficiency and accuracy.

[0030] It can be seen that in the embodiment of the present application, a multidimensional mining analysis is performed based on the school uniform sales data to determine the multidimensional mining analysis results, wherein the multidimensional mining analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis. Then, based on the multidimensional mining analysis results, the display method is selected to determine the data display form set, which helps to more intuitively display the key features in the analysis results, improve the visualization effect of the data, and make the multidimensional mining analysis results more intuitive and vivid. Finally, data filling and display are performed based on the multidimensional mining analysis results and the data display form set, and the data display content corresponding to each dimension mining analysis is determined, and the data display content corresponding to the multidimensional is sent to the display interface to realize the visualization display of the multidimensional mining analysis results of the school uniform sales data. By performing multidimensional mining analysis on the school uniform sales data, the deep-level value behind the school uniform sales data can be excavated, which helps enterprises optimize resource allocation and improve decision-making efficiency and accuracy.

[0031] Furthermore, in order to improve the pertinence and effectiveness of data display, in the embodiment of the present application, data filling and display are performed based on the multi-dimensional mining analysis results and the data display form set, and after determining the data display content corresponding to each dimensional mining analysis, it also includes: Based on the data display content corresponding to each dimension of mining and analysis, anomaly and significance evaluation is performed to determine the significance analysis results. Among them, anomaly and significance evaluation is used to screen out mining and analysis dimensions that have a significant impact on business decisions; For the embodiments of the present application, since the visual presentation of the multi-dimensional mining and analysis results will be relatively large, in order to ensure that the visual presentation content is truly critical and valuable, reduce information overload, and improve the pertinence and effectiveness of data presentation, after determining the data presentation content corresponding to each dimensional mining and analysis, the data presentation content is screened based on the important impact on business decisions and user viewing needs.

[0032] Specifically, an abnormality and significance evaluation is performed based on the data display content corresponding to each dimension of mining and analysis to determine the significance analysis result, wherein the abnormality and significance evaluation is used to screen out the mining and analysis dimensions that have a significant impact on business decisions. For the abnormality and significance evaluation, the electronic device pre-stores the abnormality and significance evaluation criteria for each dimension, and the data display content of the corresponding dimension is evaluated according to the abnormality and significance evaluation criteria to determine whether the mining and analysis dimension has significance. Regarding the significance evaluation criteria, each mining and analysis dimension is respectively provided with an evaluation criteria that meets the corresponding characteristics. For the sales trend analysis dimension, the significance evaluation criteria can be evaluated from two aspects: trend significance and turning point identification. Among them, trend significance is used to evaluate whether the trend of sales data changing over time is significant, which can usually be evaluated by calculating the slope of the trend line, R² value (coefficient of determination) or performing time series analysis (such as ARIMA model); turning point identification is to identify turning points in sales data (such as slowing growth, sudden decline, etc.) and evaluate whether these turning points are statistically significant. For product structure analysis, the significance evaluation criteria can be evaluated from two aspects: product contribution and product portfolio optimization. Product contribution is used to evaluate the contribution of different product categories to total sales by calculating sales share, growth rate and other indicators, and comparing whether these indicators change significantly in different time periods or different market regions. Product portfolio optimization analyzes whether there are redundant or inefficient products in the product portfolio, and whether there are potential high-growth opportunities, that is, by comparing sales performance under different product portfolios, evaluate whether the impact of optimizing product portfolio on overall sales is significant. For sales channel analysis, the significance evaluation criteria can be evaluated from two aspects: channel efficiency and channel growth potential. Channel efficiency evaluates sales, cost, profit margin and other indicators of different sales channels (such as online, offline, distributors, etc.), and compares whether these indicators differ significantly between different channels. Channel growth potential analyzes the growth trend and market share changes of each channel, and evaluates whether there are channels with greater growth potential. For customer behavior analysis, the significance evaluation criteria can be evaluated from the perspective of customer loyalty, evaluating customer repurchase rate, purchase frequency, average order value and other indicators, and comparing whether these indicators change significantly in different customer groups or different time periods. For market competition analysis, the significance evaluation criteria can be evaluated from two aspects: market share and competitive advantage. Market share is evaluated by evaluating the company's market share and its changing trend, and comparing whether these changes are significantly different from the performance of competitors; competitive advantage is used to analyze whether the company's competitive advantages (such as price, quality, service, etc.) are significantly different from those of competitors. Finally, the mining and analysis dimensions with significant characteristics are marked to facilitate the subsequent selection of data display content.

[0033] Obtain user viewing needs, and determine target data display content from the corresponding data display content in each dimension based on the significance analysis results and user viewing needs, wherein user viewing needs are user's requirements and preferences for personalized data viewing; Accordingly, the data display contents corresponding to the multiple dimensions are sent to the display interface, including: Send the target data display content to the display interface.

[0034] For the embodiment of the present application, the user's viewing needs are obtained. The user's viewing needs can be selected by clicking the corresponding button on the display interface to select the mining and analysis dimensions desired by the user, that is, the user's viewing needs are the user's requirements and preferences for personalized data viewing. Then, based on the significance analysis results and the user's viewing needs, the target mining and analysis dimensions are determined, and based on the target mining and analysis dimensions, the target data display content is determined from the data display content corresponding to each dimension mining and analysis. Finally, the target data display content is sent to the display interface.

[0035] It can be seen that in the embodiment of the present application, in order to ensure that the content of the visual display is truly critical and valuable, reduce information overload, and improve the pertinence and effectiveness of data display, the data display content corresponding to each dimension is mined and analyzed for anomalies and significance assessment, and the significance analysis results are determined. The anomalies and significance assessments are used to screen out the mining and analysis dimensions that have an important impact on business decisions. Then, the user's viewing needs are obtained, and based on the significance analysis results and the user's viewing needs, the target data display content is determined from the data display content corresponding to each dimension of the mining and analysis.

[0036] Furthermore, in order to fully understand the market situation, make accurate decisions, and improve operational efficiency and market competitiveness, in the embodiment of the present application, multi-dimensional mining analysis is performed based on school uniform sales data to determine the multi-dimensional mining analysis results, including: Performing sales trend analysis based on school uniform sales data to determine sales trend analysis results, wherein the sales trend analysis is used to identify the trend of changes in school uniform sales; Conduct product structure analysis based on school uniform sales data to determine the product structure analysis results, where product structure analysis is used to analyze the sales of school uniforms of different specifications; Conduct sales channel analysis based on school uniform sales data to determine sales channel analysis results, where sales channel analysis is used to analyze school uniform sales in different sales channels; Conduct customer behavior analysis based on school uniform sales data and determine the results of customer behavior analysis, where customer behavior analysis is used to determine customer consumption habits and customer needs and preferences; Conduct market competition analysis based on school uniform sales data to determine the results of the market competition analysis. The market competition analysis is used to compare the sales of competitors in the same industry and determine the market competition situation.

[0037] For the embodiment of the present application, multi-dimensional mining and analysis based on school uniform sales data helps the company to fully understand the market situation, make accurate decisions, and improve operational efficiency and market competitiveness. Among them, the multi-dimensional mining and analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis.

[0038] Specifically, a sales trend analysis is performed based on the school uniform sales data to determine the sales trend analysis results, wherein the sales trend analysis is used to identify the changing trend of school uniform sales volume, that is, the sales trend analysis identifies the changing trend of sales volume through analysis of sales data, including but not limited to: seasonal fluctuations, long-term growth or downward trends, etc.; of course, based on trend analysis, future sales can be predicted to provide a basis for formulating production plans, procurement plans and sales strategies; then, the changing trend of sales volume and future sales conditions are recorded in the sales trend analysis results.

[0039] Conduct product structure analysis based on school uniform sales data to determine the product structure analysis results. Product structure analysis is used to analyze the sales of school uniforms of different specifications. That is, by analyzing the sales of school uniforms of different styles, sizes, and colors, we can understand which school uniform products are more popular and which school uniform products are unsalable, so as to adjust product design and launch new styles and colors that better meet market demand, etc. The sales of school uniforms of different specifications will be recorded in the product structure analysis results.

[0040] Conduct sales channel analysis based on school uniform sales data to determine the sales channel analysis results, where sales channel analysis is used to analyze the school uniform sales in different sales channels, that is, analyze the sales in different sales channels (for example, online shopping malls, offline stores, school cooperation, etc.) to understand the contribution and sales efficiency of each channel; so as to optimize the sales channel layout according to the contribution and sales efficiency of each channel, improve sales efficiency and customer satisfaction; finally, record the contribution and sales efficiency of each channel in the sales channel analysis results.

[0041] Conduct customer behavior analysis based on school uniform sales data to determine the results of the customer behavior analysis. Customer behavior analysis is used to analyze customers' consumption habits and determine their needs and preferences. That is, analyze customers' purchase records, consumption habits and other information to understand their needs and preferences, so as to provide customers with personalized product recommendations and services and improve their purchasing experience and satisfaction. Finally, the needs and preferences of different types of customers are recorded in the customer behavior analysis results.

[0042] Conduct market competition analysis based on school uniform sales data and determine the results of the market competition analysis. Market competition analysis is used to compare the sales of competitors in the same industry and determine the market competition situation. That is, compare the sales, market share and other information of competitors in the same industry to understand the market competition situation, so as to discover one's own advantages and disadvantages, formulate differentiated competition strategies and enhance market competitiveness.

[0043] It can be seen that in the embodiments of the present application, a sales trend analysis is performed based on the school uniform sales data to determine the sales trend analysis results, a product structure analysis is performed based on the school uniform sales data to determine the product structure analysis results, a sales channel analysis is performed based on the school uniform sales data to determine the sales channel analysis results, a customer behavior analysis is performed based on the school uniform sales data to determine the customer behavior analysis results, and a market competition analysis is performed based on the school uniform sales data to determine the market competition analysis results. Multi-dimensional mining and analysis based on school uniform sales data helps companies to fully understand the market situation, make accurate decisions, and improve operational efficiency and market competitiveness.

[0044] Furthermore, in order to enable the visual data display form to comprehensively and accurately present the mining analysis results, in the embodiment of the present application, the display mode is selected based on the multi-dimensional mining analysis results, and a data display form set is determined, including: Select the display method based on the sales trend analysis results and determine that the data display format is a line chart; Select the display method based on the product structure analysis results and determine that the data display format is a bar chart; Select the display method based on the sales channel analysis results and determine that the data display format is a pie chart; Select the display method based on the customer behavior analysis results, and determine the data display format as scatter plot and heat map; Based on the market competition analysis results, the display method is selected and the data display format is determined to be a radar chart; Based on the correspondence between the multi-dimensional mining analysis results and the data display forms, a set of data display forms is determined.

[0045] For the embodiments of the present application, the analysis results of different mining and analysis dimensions have different characteristics. Therefore, a corresponding data display form that can characterize the characteristics of the analysis results is selected so that the visual data display form can comprehensively and accurately present the mining and analysis results.

[0046] Specifically, since the sales trend analysis results are mainly used to identify the changing trend of school uniform sales, and future sales can be predicted based on trend analysis, a line chart is selected as the data display format to intuitively display the changing trend of school uniform sales. Since the product structure analysis results mainly display the sales of school uniforms of different styles, sizes, and colors, a bar chart is selected as the data display format, and a grouped bar chart is preferred, that is, style, size, or color is used as the basis for grouping, and columns of different colors or textures are used in each group to represent the sales volume or sales of different school uniform products. The grouped bar chart can clearly show the sales comparison between different products in the same group, which helps to quickly identify which products (such as specific styles, sizes, and colors) are more popular. Since the sales channel analysis results mainly display the sales situation, contribution and sales efficiency of different sales channels (for example, online shopping malls, offline stores, school cooperation, etc.), the pie chart data display format is selected to show the proportion of each sales channel in the total sales. The pie chart can intuitively reflect the sales contribution of each sales channel, which is convenient for quickly understanding the importance of each channel. It can also help identify which channel is the main source of sales through clear marking of colors and labels.

[0047] Since the results of customer behavior analysis mainly show the needs, preferences, purchase records, and consumption habits of different types of customers, a data display form combining scatter plots and heat maps is selected, that is, a scatter plot is used to show the purchase behavior of customers on different school uniform products or school uniform product categories, where the horizontal axis can be the school uniform product category, the vertical axis can be the purchase frequency or purchase amount, and the color or size of the point can represent the purchase intensity. At the same time, a heat map is superimposed on the basis of the scatter plot, and the color depth is used to represent the density of customer groups and purchase hotspots. Since the results of market competition analysis mainly show the comparison of information such as sales and market share with competitors in the same industry, a radar chart is selected as a data display form, and a radar chart is used to show the performance of different competitors in various dimensions (for example, sales, market share, brand awareness, customer satisfaction, etc.), where each dimension corresponds to an axis on the radar chart, and the performance of each competitor forms a polygon on the chart. The radar chart can display the data of multiple variables at the same time, and intuitively reflect the advantages and disadvantages of each competitor in various dimensions through the shape and area of ​​the graph, which helps to comprehensively evaluate the comprehensive strength of competitors. Finally, the correspondence between the results of multi-dimensional mining analysis and the data display form is integrated to determine the data display form set.

[0048] It can be seen that in the embodiment of the present application, when executing the display method selection, the display method selection is performed based on the sales trend analysis results, and the data display form is determined to be a line graph; the display method selection is performed based on the product structure analysis results, and the data display form is determined to be a bar graph; the display method selection is performed based on the sales channel analysis results, and the data display form is determined to be a pie chart; the display method selection is performed based on the customer behavior analysis results, and the data display form is determined to be a scatter plot and a heat map; the display method selection is performed based on the market competition analysis results, and the data display form is determined to be a radar chart; finally, the correspondence between the multi-dimensional mining analysis results and the data display form is determined to determine the data display form set. Select the corresponding data display form that can characterize the characteristics of the analysis results, so that the visual data display form can comprehensively and accurately present the mining analysis results.

[0049] Furthermore, in order to improve the sales efficiency of enterprises, reduce costs, and enhance market competitiveness, in the embodiment of the present application, multidimensional mining analysis is performed based on school uniform sales data. After determining the multidimensional mining analysis results, it also includes: Based on the results of multi-dimensional mining analysis, optimization and adjustment analysis is performed to determine sales optimization information, where sales optimization information includes: procurement plan optimization, product structure optimization, sales channel optimization, product recommendation optimization, and competition strategy optimization.

[0050] For the embodiment of the present application, after determining the results of the multidimensional mining analysis, an optimization adjustment analysis is performed based on the results of the multidimensional mining analysis to determine the sales optimization information so that school uniform companies can adjust various dimensions of school uniform sales according to the sales optimization information, which helps to improve the company's sales efficiency, reduce costs, and enhance market competitiveness.

[0051] Specifically, for procurement plan optimization, according to the sales forecast results, the procurement quantity and procurement time are reasonably planned to avoid inventory backlog or shortage, and the performance of different suppliers is analyzed to optimize supplier selection to ensure the balance between procurement cost and quality. For product structure optimization, based on the data of best-selling and slow-selling products in the product structure analysis results, the product structure is adjusted to increase or reduce the production of corresponding products, pay attention to market trends and changes in customer demand, develop new products that meet market demand, and eliminate unpopular old products. For sales channel optimization, based on the effects and potential of different sales channels in the sales channel analysis results, the channel layout is optimized to improve sales coverage and market share. For product recommendation optimization, based on the customer's purchase history and preference data in the customer behavior analysis results, personalized school uniform product recommendations are implemented to improve customer satisfaction and purchase conversion rate. For competition strategy optimization, based on the sales of competitors in the same industry in the market competition situation, differentiated competition strategies are formulated, such as price strategy, product strategy, and marketing strategy, which will help win market share.

[0052] It can be seen that in the embodiment of the present application, optimization and adjustment analysis is performed based on the results of multidimensional mining analysis to determine sales optimization information, wherein the sales optimization information includes: procurement plan optimization, product structure optimization, sales channel optimization, product recommendation optimization, and competition strategy optimization. The optimization and adjustment analysis facilitates school uniform companies to adjust various dimensions of school uniform sales according to sales optimization information, which helps to improve corporate sales efficiency, reduce costs, and enhance market competitiveness.

[0053] Furthermore, in order to ensure the accuracy and timeliness of school uniform inventory data, in the embodiment of the present application, it also includes: When a school uniform delivery order is detected, the current school uniform inventory data is obtained, and the storage location analysis is performed based on the school uniform delivery order and the current school uniform inventory data to determine the shelf information for the school uniforms to be picked; When a school uniform entry order is detected, the current school uniform inventory data is obtained, and the entry location analysis is performed based on the school uniform entry order and the current school uniform inventory data to determine the shelf information of the school uniforms to be entered; Utilize wireless radio frequency identification technology to obtain school uniform incoming and outgoing information in real time, and based on the school uniform incoming and outgoing information, update the current school uniform inventory data in real time, so that the school uniform inventory data can reflect the school uniform inventory status in real time.

[0054] For the embodiment of the present application, in the process of analyzing the school uniform sales data, the inventory data reflects the supply situation and historical sales trends of school uniforms. Through inventory data management, school uniform companies can respond to changes in market demand more quickly. Therefore, in the process of school uniform inventory data management, storage location analysis and warehousing location analysis operations are performed to intelligently determine the optimal shelf information, which helps to reduce picking and storage time and improve the operating efficiency of school uniform storage warehouses. At the same time, wireless radio frequency identification technology is used to obtain and update school uniform inventory data in real time, ensuring the accuracy and timeliness of school uniform inventory data.

[0055] Specifically, when a school uniform delivery order is detected, the type, quantity, size and other information of the school uniforms to be shipped recorded in the school uniform delivery order are determined, and the school uniform inventory database is queried to obtain the current school uniform inventory data. The inventory database records the inventory quantity, storage location (for example, shelf number, number of layers, location, etc.), size distribution and other detailed information of each school uniform. Then, based on the delivery demand on the school uniform delivery order and the current school uniform inventory data, the storage location analysis is performed to determine the shelf information of the school uniforms to be picked. When performing the storage location analysis, the distance between the shelves, the walking path of the pickers, the weight and volume of the shipped school uniforms and other factors are comprehensively considered. The shelf information of the school uniforms to be picked includes but is not limited to the shelf number, number of layers and other information, which is used to guide the pickers to quickly and accurately find and pick the shipped school uniforms.

[0056] When a school uniform entry form is detected, the type, quantity, size, color, batch number, production date and other information of the school uniform recorded in the school uniform entry form is determined, and the school uniform inventory database is queried to obtain the current school uniform inventory data. The inventory database records the inventory quantity, storage location (for example, shelf number, number of layers, location, etc.), size distribution and other detailed information of each school uniform. Of course, the remaining capacity and free positions in the warehouse are also recorded. Then, based on the school uniform entry form and the current school uniform inventory data, the entry position analysis is performed to determine the shelf information of the school uniforms to be entered into the warehouse. When performing the entry position analysis, priority is given to shelves with sufficient remaining capacity and easy management, and factors such as the type, size, and color of the school uniforms are considered. Similar or related school uniforms are stored in adjacent locations as much as possible to facilitate subsequent outbound delivery and inventory. The shelf information of the school uniforms to be entered into the warehouse includes but is not limited to: storage shelves, number of layers and grid information, which is used to guide the pickers to quickly and accurately place the school uniforms to be entered into the warehouse at the corresponding positions.

[0057] Before school uniforms are put into storage, RFID tags will be attached to each uniform and relevant information will be entered. At the same time, RFID readers will be set up at the entrance and exit of the warehouse to read the information in the RFID tags, so that the wireless radio frequency identification technology can be used to obtain the school uniform storage information and school uniform outbound information in real time, so that the school uniform inventory data can reflect the school uniform inventory status in real time. Automatic reading and updating of inventory data reduces manual operations, improves work efficiency, and ensures the accuracy and timeliness of school uniform inventory data.

[0058] It can be seen that in the embodiment of the present application, when a school uniform delivery order is detected, the current school uniform inventory data is obtained, and the storage location analysis is performed based on the school uniform delivery order and the current school uniform inventory data to determine the shelf information of the school uniforms to be picked. When a school uniform entry order is detected, the current school uniform inventory data is obtained, and the entry location analysis is performed based on the school uniform entry order and the current school uniform inventory data to determine the shelf information of the school uniforms to be entered. At the same time, wireless radio frequency identification technology is used to obtain school uniform entry information and school uniform delivery information in real time, and based on the school uniform entry information and school uniform delivery information, the current school uniform inventory data is updated in real time, so that the school uniform inventory data can reflect the school uniform inventory status in real time, ensuring the accuracy and timeliness of the school uniform inventory data.

[0059] The above-mentioned embodiment introduces a school uniform data analysis method from the perspective of method flow, and the following embodiment introduces a school uniform data analysis device from the perspective of a virtual module or a virtual unit. Please refer to the following embodiments for details.

[0060] The present application embodiment provides a school uniform data analysis device, such as Figure 2 As shown, the school uniform data analysis device may specifically include: The multidimensional mining analysis module 210 is used to obtain school uniform sales data, perform multidimensional mining analysis based on the school uniform sales data, and determine the multidimensional mining analysis results; A display mode selection module 220 is used to select a display mode based on the multidimensional mining analysis results and determine a data display form set, wherein the data display form set provides at least one data display form for each analysis result of the multidimensional mining analysis results; The data filling and display module 230 is used to perform data filling and display based on the multi-dimensional mining analysis results and the data display form set, determine the data display content corresponding to each dimensional mining analysis, and send the data display content corresponding to the multiple dimensions to the display interface, so as to realize the visual display of the multi-dimensional mining and analysis results of school uniform sales data.

[0061] For the embodiment of the present application, a multidimensional mining analysis is performed based on the school uniform sales data to determine the results of the multidimensional mining analysis, wherein the multidimensional mining analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis. Then, based on the results of the multidimensional mining analysis, a display method is selected to determine a set of data display forms, which helps to more intuitively display the key features in the analysis results, improve the visualization of the data, and make the results of the multidimensional mining analysis more intuitive and vivid. Finally, data filling and display are performed based on the multidimensional mining analysis results and the data display form set, the data display content corresponding to each dimension mining analysis is determined, and the data display content corresponding to the multidimensional data is sent to the display interface to realize the visualization of the results of the multidimensional mining analysis of the school uniform sales data. By performing multidimensional mining analysis on the school uniform sales data, the deep-level value behind the school uniform sales data can be excavated, which helps enterprises optimize resource allocation and improve decision-making efficiency and accuracy.

[0062] In a possible implementation of the embodiment of the present application, the school uniform data analysis device further includes: The display content selection module is used to perform anomaly and significance evaluation based on the data display content corresponding to each dimension mining and analysis, and determine the significance analysis results. Among them, the anomaly and significance evaluation is used to screen out the mining and analysis dimensions that have a significant impact on business decisions; Obtain user viewing needs, and determine target data display content from the corresponding data display content in each dimension based on the significance analysis results and user viewing needs, wherein user viewing needs are user's requirements and preferences for personalized data viewing; Accordingly, when executing the sending of the data display contents corresponding to the multiple dimensions to the display interface, the data filling and display module 230 is used to: Send the target data display content to the display interface.

[0063] In a possible implementation of the embodiment of the present application, when the multidimensional mining analysis module 210 performs multidimensional mining analysis based on school uniform sales data and determines the multidimensional mining analysis results, it is used to: Performing sales trend analysis based on school uniform sales data to determine sales trend analysis results, wherein the sales trend analysis is used to identify the trend of changes in school uniform sales; Conduct product structure analysis based on school uniform sales data to determine the product structure analysis results, where product structure analysis is used to analyze the sales of school uniforms of different specifications; Conduct sales channel analysis based on school uniform sales data to determine sales channel analysis results, where sales channel analysis is used to analyze school uniform sales in different sales channels; Conduct customer behavior analysis based on school uniform sales data and determine the results of customer behavior analysis, where customer behavior analysis is used to determine customer consumption habits and customer needs and preferences; Conduct market competition analysis based on school uniform sales data to determine the results of the market competition analysis. The market competition analysis is used to compare the sales of competitors in the same industry and determine the market competition situation.

[0064] In a possible implementation of the embodiment of the present application, when the display mode selection module 220 performs display mode selection based on the multi-dimensional mining analysis result and determines the data display form set, it is used to: Select the display method based on the sales trend analysis results and determine that the data display format is a line chart; Select the display method based on the product structure analysis results and determine that the data display format is a bar chart; Select the display method based on the sales channel analysis results and determine that the data display format is a pie chart; Select the display method based on the customer behavior analysis results, and determine the data display format as scatter plot and heat map; Based on the market competition analysis results, the display method is selected and the data display format is determined to be a radar chart; Based on the correspondence between the multi-dimensional mining analysis results and the data display forms, a set of data display forms is determined.

[0065] In a possible implementation of the embodiment of the present application, the school uniform data analysis device further includes: The optimization and adjustment analysis module is used to perform optimization and adjustment analysis based on the results of multi-dimensional mining analysis to determine sales optimization information, where the sales optimization information includes: procurement plan optimization, product structure optimization, sales channel optimization, product recommendation optimization, and competition strategy optimization.

[0066] In a possible implementation of the embodiment of the present application, the school uniform data analysis device further includes: The inventory management module is used to obtain the current school uniform inventory data when a school uniform delivery order is detected, perform storage location analysis based on the school uniform delivery order and the current school uniform inventory data, and determine the shelf information of the school uniforms to be picked; When a school uniform entry order is detected, the current school uniform inventory data is obtained, and the entry location analysis is performed based on the school uniform entry order and the current school uniform inventory data to determine the shelf information of the school uniforms to be entered; Utilize wireless radio frequency identification technology to obtain school uniform incoming and outgoing information in real time, and based on the school uniform incoming and outgoing information, update the current school uniform inventory data in real time, so that the school uniform inventory data can reflect the school uniform inventory status in real time.

[0067] Technical personnel in the relevant field can clearly understand that, for the convenience and brevity of description, the specific working process of the school uniform data analysis device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0068] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0069] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0070] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0071] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0072] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0073] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0074] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0075] The embodiment of the present application provides a computer program product, which includes a computer program, which implements the method in any of the above embodiments when executed by a processor. Compared with the related art, the embodiment of the present application performs multidimensional mining analysis based on school uniform sales data to determine the multidimensional mining analysis results, wherein the multidimensional mining analysis includes: sales trend analysis, product structure analysis, sales channel analysis, customer behavior analysis and market competition analysis. Then, based on the multidimensional mining analysis results, the display method is selected to determine the data display form set, which helps to more intuitively display the key features in the analysis results, improve the visualization effect of the data, and make the multidimensional mining analysis results more intuitive and vivid. Finally, based on the multidimensional mining analysis results and the data display form set, data filling and display are performed, the data display content corresponding to each dimension mining analysis is determined, and the data display content corresponding to the multidimensional is sent to the display interface to realize the visualization display of the multidimensional mining analysis results of school uniform sales data. By performing multidimensional mining analysis on school uniform sales data, the deep-level value behind the school uniform sales data can be mined, which helps enterprises optimize resource allocation and improve decision-making efficiency and accuracy.

[0076] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0077] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A school uniform data analysis method, characterized in that: include: Acquire school uniform sales data, perform multidimensional mining analysis based on the school uniform sales data, and determine the multidimensional mining analysis results; Selecting a display method based on the multidimensional mining analysis results to determine a data display form set, wherein the data display form set provides at least one data display form for each aspect of the analysis results of the multidimensional mining analysis results; Data filling and display are performed based on the multi-dimensional mining and analysis results and the data display form set, the data display content corresponding to each dimensional mining and analysis is determined, and the data display content corresponding to the multiple dimensions is sent to the display interface to achieve a visual display of the multi-dimensional mining and analysis results of school uniform sales data.

2. The school uniform data analysis method according to claim 1, characterized in that: After performing data filling and display based on the multi-dimensional mining analysis results and the data display form set and determining the data display content corresponding to each dimensional mining analysis, the method further includes: Based on the data display content corresponding to each dimension mining analysis, anomaly and significance evaluation is performed to determine the significance analysis result, wherein the anomaly and significance evaluation is used to screen out the mining and analysis dimensions that have a significant impact on business decisions; Obtaining user viewing needs, and determining target data display content from the data display content corresponding to each dimension through mining and analysis based on the significance analysis results and the user viewing needs, wherein the user viewing needs are the user's requirements and preferences for personalized data viewing; Accordingly, sending the data display contents corresponding to the multiple dimensions to the display interface includes: The target data display content is sent to the display interface.

3. The school uniform data analysis method according to claim 1, characterized in that: The performing multidimensional mining analysis based on the school uniform sales data to determine the multidimensional mining analysis results includes: Performing a sales trend analysis based on the school uniform sales data to determine a sales trend analysis result, wherein the sales trend analysis is used to identify a trend in the sales volume of school uniforms; Performing product structure analysis based on the school uniform sales data to determine a product structure analysis result, wherein the product structure analysis is used to analyze the sales of school uniforms of different specifications; Performing sales channel analysis based on the school uniform sales data to determine sales channel analysis results, wherein the sales channel analysis is used to analyze the school uniform sales in different sales channels; Performing customer behavior analysis based on the school uniform sales data to determine the customer behavior analysis results, wherein the customer behavior analysis is used to analyze the customer's consumption habits and determine the customer's needs and preferences; A market competition analysis is performed based on the school uniform sales data to determine the market competition analysis results, wherein the market competition analysis is used to compare the sales of competitors in the same industry and determine the market competition situation.

4. The school uniform data analysis method according to claim 3, characterized in that: The selecting of a display mode based on the multi-dimensional mining analysis result to determine a set of data display forms includes: Selecting a display method based on the sales trend analysis result and determining that the data display format is a line chart; Selecting a display method based on the product structure analysis result and determining that the data display form is a bar chart; Selecting a display method based on the sales channel analysis results and determining that the data display format is a pie chart; Selecting a display method based on the customer behavior analysis results to determine that the data display form is a scatter plot and a heat map; A display method is selected based on the market competition analysis results, and the data display form is determined to be a radar chart; The correspondence between the multi-dimensional mining analysis results and the data display forms is comprehensively considered to determine a data display form set.

5. The school uniform data analysis method according to claim 3, characterized in that: After performing multidimensional mining analysis based on the school uniform sales data and determining the multidimensional mining analysis results, the method further includes: An optimization adjustment analysis is performed based on the multi-dimensional mining analysis results to determine sales optimization information, wherein the sales optimization information includes: procurement plan optimization, product structure optimization, sales channel optimization, product recommendation optimization, and competition strategy optimization.

6. The school uniform data analysis method according to claim 1, characterized in that: Also includes: When a school uniform delivery order is detected, current school uniform inventory data is obtained, storage location analysis is performed based on the school uniform delivery order and the current school uniform inventory data, and shelf information of school uniforms to be picked is determined; When a school uniform entry order is detected, the current school uniform inventory data is obtained, and the entry location analysis is performed based on the school uniform entry order and the current school uniform inventory data to determine the shelf information of the school uniforms to be entered; By using wireless radio frequency identification technology, school uniform entry information and school uniform exit information are obtained in real time, and based on the school uniform entry information and school uniform exit information, the current school uniform inventory data is updated in real time, so that the school uniform inventory data reflects the school uniform inventory status in real time.

7. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the school uniform data analysis method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the school uniform data analysis method described in any one of claims 1 to 6.

9. A computer program product, characterized in that It comprises a computer program, wherein the computer program is executed by a processor to perform the school uniform data analysis method according to any one of claims 1 to 6.

Images