E-commerce operation data processing analysis interaction platform

Abstract

The invention discloses an e-commerce operation data processing and analysis interaction platform, and relates to the technical field of e-commerce platforms. The data interaction management center is in communication connection with a data acquisition and integration module, a multi-dimensional evaluation system construction module, an evaluation index trend analysis module, an inventory management analysis module, a monitoring and early warning module and a data visualization module, and all the modules are in electric signal connection; and the data acquisition and integration module is used for collecting data of each dimension of the e-commerce platform. Various key data on the e-commerce platform are captured in real time through real-time data monitoring and converted into a visual chart, an early warning mechanism is automatically triggered according to a preset early warning rule and threshold value, and an early warning notice is sent to related personnel once abnormal fluctuation of the data occurs, so that an operation team can quickly respond to market changes, and the operation efficiency of the e-commerce platform is improved. Therefore, the operation efficiency of the e-commerce platform is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce platforms, and particularly to an e-commerce operation data processing, analysis and interaction platform. Background Art

[0002] With the continuous progress of Internet technology and the change of consumers' shopping habits, the e-commerce industry has shown an explosive growth trend. The traditional offline shopping mode has gradually been replaced by online shopping. E-commerce platforms have become one of the main channels for consumers to shop. This trend has driven the increasing demand of e-commerce enterprises for data processing and analysis in order to better understand market dynamics, consumer behavior and competitor situations. As a huge data source, e-commerce platforms generate a large amount of data every day, including users' behavior data, transaction data, commodity data, etc. These data contain huge commercial value and can help enterprises deeply understand the market, analyze user needs, and optimize operation and sales strategies.

[0003] In the prior art, due to the fact that the operation status of e-commerce platforms is easily affected by changes in the market environment, it is difficult to identify business fluctuations in a timely manner, which affects the accuracy of operation early warning. Therefore, how to comprehensively consider multi-dimensional evaluation indicators to improve the evaluation accuracy of e-commerce operation status and respond to potential market risks in advance is the problem we need to solve. For this reason, an e-commerce operation data processing, analysis and interaction platform is proposed herein. Summary of the Invention

[0004] The purpose of the present invention is to provide an e-commerce operation data processing, analysis and interaction platform to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is: An e-commerce operation data processing, analysis and interaction platform, including a data interaction management center, which is communicatively connected with a data collection and integration module, a multi-dimensional evaluation system construction module, an evaluation index trend analysis module, an inventory management analysis module, a monitoring and early warning module, and a data visualization module. Among them, the modules are electrically connected to each other; The data collection and integration module is used to collect various dimensions of data of the e-commerce platform, including users' behavior data (browsing, searching, purchasing, etc.), transaction data, inventory data, advertising data, commodity information, customer service data, etc., and integrate them to obtain an operation data sequence; The multi-dimensional evaluation system construction module, based on the e-commerce operation requirements, defines multi-dimensional evaluation indicators for evaluating the operation status, namely transaction evaluation indicators and user activity indicators, to provide a comprehensive and in-depth evaluation of the operation status and help operators quickly identify business fluctuations and potential risks; The evaluation index trend analysis module is used to analyze each multi-dimensional evaluation index for the operation status evaluation one by one, and determine the change trend of each evaluation index of the operation status; The inventory management analysis module monitors and analyzes inventory data, analyzes the sales demand trend, optimizes the inventory management strategy, reduces the inventory cost, improves the inventory turnover rate, and ensures the timeliness and stability of commodity supply; The monitoring and warning module monitors and analyzes real-time data, combines the change trend of each evaluation index with the inventory analysis result, identifies the anomalies and risks in e-commerce operation, and triggers the warning mechanism to identify abnormal fluctuations in advance and quickly take measures to reduce risks; The data visualization module is used to display the analysis and warning results through data visualization tools, help management quickly understand the business status, regularly generate data reports, provide decision-making support for the management layer, and help comprehensively understand various data indicators of e-commerce operation.

[0006] A further improvement of the technical solution of the present invention lies in that: the data collection and integration module specifically includes: According to the requirements of e-commerce operation, clarify the data types to be collected, including user behavior data, transaction data, inventory data, advertising data, commodity information, and customer service data; Based on the data structure of the target e-commerce platform, configure data collection parameters and execute data collection tasks, and obtain the latest data in real time from data sources of various data types of e-commerce operation through the API interface; Preprocess the collected data, including steps of data cleaning, data conversion, and data summarization. Among them, duplicate records are removed, incorrect data is corrected, and missing values are filled through data cleaning. The data is converted into a unified format and standard through data conversion, and data from different sources is merged to facilitate subsequent processing, improve the quality and consistency of the data, and reduce analysis deviations caused by data problems; Associate the information from different data sources according to the unique identifier of the user ID, and merge the related data into a comprehensive data set to form a complete operation data sequence; Build a data warehouse based on the MySQL relational database, store the e-commerce operation data related to the operation data sequence, and formulate a data backup plan to perform data backup regularly.

[0007] A further improvement of the technical solution of the present invention lies in that: the multi-dimensional evaluation system construction module specifically includes: Traverse the relevant data of the operation data sequence, and clarify the multi-dimensional evaluation indexes for the operation status evaluation in combination with the e-commerce operation requirements, including transaction evaluation indexes and user activity indexes; Analyze the transaction evaluation indicators, determine the sub-transaction evaluation indicators including order conversion rate, order volume, return rate, and repurchase rate, and preset the standard values of each sub-transaction evaluation indicator in combination with the transaction evaluation indicator data of the previous evaluation period. Among them, the order conversion rate is the proportion of users who complete purchases among those who visit the website, the order volume is the total number of orders completed within the evaluation period, the return rate is the proportion of orders returned within the evaluation period, and the repurchase rate is the proportion of users who make repeat purchases within the evaluation period; Analyze the user activity indicators, determine the sub-user activity indicators including the average user visit frequency, new user growth rate, and number of active users, and preset the standard values of each sub-user activity indicator in combination with the user activity indicator data of the previous evaluation period. Among them, the average user visit frequency is the average number of visits per user within the evaluation period, the new user growth rate is the growth rate of new users in the evaluation period, and the number of active users is the number of users with activity records within the evaluation period; Based on the determined sub-transaction evaluation indicators and sub-user activity indicators, capture the associated data of the sub-transaction evaluation indicators and sub-user activity indicators in the current evaluation period and the previous evaluation period from the operation data sequence.

[0008] A further improvement of the technical solution of the present invention lies in that: the evaluation indicator trend analysis module specifically includes: Conduct comparative analysis respectively according to the captured multi-dimensional evaluation indicator data in the current evaluation period and the previous evaluation period; For the transaction evaluation indicators, analyze each sub-transaction evaluation indicator in the two evaluation periods and the preset standard values of each sub-transaction evaluation indicator, calculate the transaction status evaluation index, and analyze the change trend of the transaction evaluation indicators in the current evaluation period; For the user activity indicators, analyze each sub-user activity indicator in the two evaluation periods and the preset standard values of each sub-user activity indicator, calculate the user activity evaluation index, and analyze the change trend of the user activity indicators in the current evaluation period; Plot the values of the transaction evaluation indicators and user activity indicators in the current evaluation period and the previous evaluation period into a time series graph to visually display their change trends and identify the trends of each indicator rising, falling, or remaining stable.

[0009] A further improvement of the technical solution of the present invention lies in that: the expression of the transaction status evaluation index is: ; In the formula, is the transaction status evaluation index, is the actual value of the th sub-transaction evaluation indicator in the current evaluation period, is the preset standard value of the th sub-transaction evaluation indicator, is the index of the sub - transaction evaluation metrics, , representing the order conversion rate, order volume, return rate, and repurchase rate respectively, is the order conversion rate for the current evaluation period, is the order volume for the current evaluation period, is the return rate for the current evaluation period, is the repurchase rate for the current evaluation period, is the preset standard value of the order conversion rate, is the preset standard value of the order volume, is the preset standard value of the return rate, is the preset standard value of the repurchase rate, ranges from 0 to 1; The expression of the user activity evaluation index is: ; In the formula, is the user activity evaluation index, is the actual value of the th sub - user activity metric for the current evaluation period, is the preset standard value of the th sub - user activity metric, is the index of the sub - user activity metric, , representing the average user access frequency, new user growth rate, and number of active users respectively, is the average user access frequency for the current evaluation period, is the new user growth rate for the current evaluation period, is the number of active users for the current evaluation period, is the preset standard value of the average user access frequency, is the preset standard value of the new user growth rate, is the preset standard value of the number of active users, ranges from 0 to 1.

[0010] A further improvement of the technical solution of the present invention lies in: The inventory management analysis module specifically includes: Extract the inventory data of the current evaluation period and the previous period from the data warehouse, including inventory quantity, inbound records, outbound records, commodity sales data, etc., and count the current inventory quantity, and classify and summarize by stock - keeping unit; Analyze the inventory changes between the previous evaluation period and the current evaluation period, and analyze the inventory turnover rate of each stock - keeping unit, identify the commodity units that have not been sold for a long time in the inventory, and then mark them to comprehensively understand the current inventory situation, identify potential problems, and provide a basis for subsequent optimization measures; According to the inventory changes, analyze the sales volume and average inventory of each inventory holding unit during the current evaluation period, calculate the inventory trend index in combination with the average sales volume of all inventory holding units, analyze the sales demand trend, and identify the short - comings of inventory management. If the inventory turnover rate of some inventory holding units is low and the sales volume fluctuates greatly, it indicates that there may be inventory backlog problems in these inventory holding units. If the inventory turnover rate of some inventory holding units is high but there are frequent stock - outs, it means that these inventory holding units may need to increase inventory or adjust the replenishment strategy. Based on the analysis results of the sales demand trend and inventory levels, optimize the inventory management strategy. For the identified slow - moving products, propose handling suggestions including promotional activities, discount sales, or returns to the supplier. For high - turnover products, prioritize ensuring sufficient inventory to reduce the risk of out - of - stock.

[0011] A further improvement of the technical solution of the present invention is that the expression of the inventory trend index is: ; In the formula, is the inventory trend index, is the number of inventory holding units, is the th inventory holding unit's sales volume during the evaluation period, is the th inventory holding unit's average inventory during the evaluation period, is the average sales volume of all inventory holding units during the evaluation period, The value range of is between 0 and 1. When the sales volume of each inventory holding unit is close to its average inventory and the sales volume fluctuation is small, each term in the formula will approach 1. Therefore,

[0012] A further improvement of the technical solution of the present invention is that the monitoring and warning module specifically includes: Extract the latest data in real - time from various data sources of the e - commerce platform, obtain the transaction status evaluation index, user activity evaluation index, and inventory trend index of the current evaluation period, analyze the change trends of each index, and comprehensively understand the overall operation status of the e - commerce platform; According to the importance and influence degree of each index, assign different weights to them, combine the transaction status evaluation index, user activity evaluation index, and inventory trend index with their respective weights, and calculate the abnormal warning coefficient; Based on the analysis results of the abnormal warning coefficient of the previous evaluation period, set the warning threshold T, compare the abnormal warning coefficient with the warning threshold, and determine the risk level of the current operation status; When the abnormal warning coefficient deviates from the warning threshold, the warning mechanism is automatically triggered, and warning notifications are sent to relevant personnel via email, SMS, and the message center. The warning notifications include the warning name, warning details, and warning time information. After receiving the warning notifications, the relevant personnel quickly analyze the cause of the problem, formulate targeted solutions based on the cause of the problem, and implement them as soon as possible.

[0013] A further improvement of the technical solution of the present invention is that the expression of the abnormal warning coefficient is: ; In the formula, is the abnormal warning coefficient, is the trading status evaluation index of the current period, is the standard value of the trading status evaluation index of the previous evaluation period, is the weight of the trading status evaluation index, reflecting its importance in the overall risk assessment, is the user activity evaluation index of the current period, [ is the standard value of the user activity evaluation index of the previous evaluation period, is the weight of the user activity evaluation index, reflecting its importance in the overall risk assessment, is the inventory trend index of the current period, is the standard value of the inventory trend index of the previous evaluation period, is the weight of the inventory trend index, reflecting its importance in the overall risk assessment, is a adjustment factor, taking a positive value, used to control the change rate of the exponential function, The value range of is between 0 and 1. When each index is very close to the standard value of its previous evaluation period, each term in the formula will approach 1. Therefore, being close to 1 indicates that the operation status is very ideal.

[0014] A further improvement of the technical solution of the present invention is that the data visualization module specifically includes: Obtain relevant data of the trading status evaluation index, user activity evaluation index, and inventory trend index of the current evaluation period, and use Tableau to create a comprehensive dashboard to centrally display the relevant data and charts of each index, highlight the abnormal points in the current evaluation period, and provide detailed information and recommended measures; Add filters to the dashboard to allow users to select corresponding time periods, product categories, and regional conditions, dynamically update the chart content, and support users to click on the data points in the chart to further view detailed sub-data or related data; Set the generation cycle of the operation report according to business requirements, including an overview section, a detailed analysis section, and a warning and recommendation section. Use the automatic report generation function of Tableau to automatically generate and send the report.

[0015] Due to the adoption of the above technical solution, the technical progress achieved by the present invention compared with the prior art is as follows: 1. The present invention provides an e-commerce operation data processing and analysis interaction platform. Through real-time data monitoring, various key data on the e-commerce platform can be captured immediately and converted into intuitive visual charts. According to preset warning rules and thresholds, the warning mechanism is automatically triggered. Once the data shows abnormal fluctuations, a warning notice is sent to relevant personnel, enabling the operation team to quickly respond to market changes and timely adjust operation strategies, thereby significantly improving the operation efficiency of the e-commerce platform.

[0016] 2. The present invention provides an e-commerce operation data processing and analysis interaction platform. By constructing a comprehensive data processing and analysis interaction platform, the latest business data can be obtained in real time and decisions can be made quickly. According to the comprehensively calculated abnormal warning coefficient, potential operation risks can be identified, and combined with the detected abnormal fluctuations or risks, the warning mechanism is automatically triggered to ensure the stable operation of the e-commerce platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a schematic diagram of the system function module of the present invention; Figure 2 It is a schematic diagram of the working process of the evaluation index trend analysis module of the present invention; Figure 3 It is a schematic diagram of the working process of the monitoring and warning module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0020] Example 1, as Figure 1 、 Figure 2As shown in the figure, the present invention provides an e-commerce operation data processing and analysis interaction platform, which includes a data interaction management center. The data interaction management center is communicatively connected to a data collection and integration module, a multi-dimensional evaluation system construction module, an evaluation index trend analysis module, an inventory management analysis module, a monitoring and early warning module, and a data visualization module. Among them, the modules are electrically connected to each other; The data collection and integration module is used to collect various dimensions of data on the e-commerce platform, including user behavior data (browsing, searching, purchasing, etc.), transaction data, inventory data, advertising data, product information, and customer service data, etc., and integrate and obtain an operation data sequence. According to the requirements of e-commerce operation, clarify the data types to be collected, including user behavior data, transaction data, inventory data, advertising data, product information, and customer service data. Based on the data structure of the target e-commerce platform, configure data collection parameters and execute data collection tasks, and obtain the latest data in real time from the data sources of various data types of e-commerce operation through the API interface. Perform preprocessing on the collected data, including the steps of data cleaning, data conversion, and data summarization. Among them, duplicate records are removed, incorrect data is corrected, and missing values are filled through data cleaning. The data is converted into a unified format and standard through data conversion, and data from different sources is merged to facilitate subsequent processing, improve the quality and consistency of the data, and reduce analysis deviations caused by data problems. Information from different data sources is associated according to the unique identifier of the user ID, and the associated data is merged into a comprehensive data set to form a complete operation data sequence. Build a data warehouse based on the MySQL relational database, store the e-commerce operation data related to the operation data sequence, and formulate a data backup plan to perform data backup regularly; Multi-dimensional Evaluation System Construction Module. Based on the e-commerce operation requirements, it clarifies the multi-dimensional evaluation indicators for evaluating the operation status, which are transaction evaluation indicators and user activity indicators respectively, provides a comprehensive and in-depth evaluation of the operation status, helps operators quickly identify business fluctuations and potential risks, traverses the relevant data in the operation data sequence, and clarifies the multi-dimensional evaluation indicators for evaluating the operation status in combination with the e-commerce operation requirements, including transaction evaluation indicators and user activity indicators. Analyze the transaction evaluation indicators, determine the sub-transaction evaluation indicators including order conversion rate, order volume, return rate and repurchase rate, and combine the transaction evaluation indicator data of the previous evaluation period to preset the standard values of each sub-transaction evaluation indicator. Among them, the order conversion rate is the proportion of users who visit the website and complete the purchase, the order volume is the total number of orders completed within the evaluation period, the return rate is the proportion of orders returned within the evaluation period, and the repurchase rate is the proportion of users who make repeated purchases within the evaluation period. Analyze the user activity indicators, determine the sub-user activity indicators including the average number of visits per user, the growth rate of new users and the number of active users, and combine the user activity indicator data of the previous evaluation period to preset the standard values of each sub-user activity indicator. Among them, the average number of visits per user is the average number of visits per user within the evaluation period, the growth rate of new users is the growth rate of new users added in the evaluation period, and the number of active users is the number of users with activity records within the evaluation period. Based on the determined sub-transaction evaluation indicators and sub-user activity indicators, capture the correlation data of the sub-transaction evaluation indicators and sub-user activity indicators in the current evaluation period and the previous evaluation period from the operation data sequence; Evaluation Indicator Trend Analysis Module. It is used to analyze each of the multi-dimensional evaluation indicators for evaluating the operation status one by one, determine the change trends of each evaluation indicator of the operation status, and conduct a comparative analysis respectively according to the captured multi-dimensional evaluation indicator data in the current evaluation period and the previous evaluation period. For the transaction evaluation indicators, analyze each sub-transaction evaluation indicator in the two evaluation periods and the preset standard values of each sub-transaction evaluation indicator, calculate the transaction status evaluation index, and analyze the change trend of the transaction evaluation indicators in the current evaluation period. For the user activity indicators, analyze each sub-user activity indicator in the two evaluation periods and the preset standard values of each sub-user activity indicator, calculate the user activity evaluation index, and analyze the change trend of the user activity indicators in the current evaluation period. Plot the values of the transaction evaluation indicators and user activity indicators in the current evaluation period and the previous evaluation period into a time series graph to visually display their change trends and identify the trends of each indicator rising, falling or remaining stable; Furthermore, the expression of the transaction status evaluation index is: ; In the formula, is the transaction status evaluation index, is the actual value of the th sub-transaction evaluation indicator in the current evaluation period, is the standard value of the th sub - transaction evaluation indicator, is the index of the sub - transaction evaluation indicator, which respectively represent the order conversion rate, order volume, return rate, and repurchase rate, is the order conversion rate in the current evaluation period, is the order volume in the current evaluation period, is the return rate in the current evaluation period, is the repurchase rate in the current evaluation period, is the preset standard value of the order conversion rate, is the preset standard value of the order volume, is the preset standard value of the return rate, is the preset standard value of the repurchase rate, ranges from 0 to 1. When each sub - transaction evaluation indicator is very close to its preset standard value, each term in the formula will approach 1. Therefore, being close to 1 indicates that the trading situation is very ideal. When one or more sub - transaction evaluation indicators are far from their preset standard values, the corresponding terms in the formula will approach 0, resulting in being close to 0, indicating a poor trading situation; The expression of the user activity evaluation index is: ; In the formula, is the user activity evaluation index, is the actual value of the th sub - user activity indicator in the current evaluation period, is the preset standard value of the th sub - user activity indicator, is the index of the sub - user activity indicator, which respectively represent the average user access frequency, new user growth rate, and number of active users, is the average user access frequency in the current evaluation period, is the new user growth rate in the current evaluation period, is the number of active users in the current evaluation period, is the preset standard value of the average user access frequency, is the preset standard value of the new user growth rate, is the preset standard value of the number of active users, ranges from 0 to 1. When each sub - user activity indicator is very close to its preset standard value and the actual value is not lower than the standard value, each term in the formula will approach 1. Therefore, Close to 1 indicates that the user activity is very ideal. When one or more sub-user activity metrics deviate far from their preset standard values, or the actual values are lower than the standard values, the corresponding terms in the formula will approach 0, resulting in Close to 0 indicates poor user activity; Inventory management analysis module, monitors and analyzes inventory data, analyzes sales demand trends, optimizes inventory management strategies, reduces inventory costs, improves inventory turnover rate, ensures the timeliness and stability of commodity supply, extracts inventory data of the current evaluation period and the previous period from the data warehouse, including inventory quantity, inbound records, outbound records, commodity sales data, etc., and counts the current inventory quantity, classifies and summarizes by stock keeping unit, analyzes the inventory changes between the previous evaluation period and the current evaluation period, and analyzes the inventory turnover rate of each stock keeping unit, identifies the commodity units that have not been sold for a long time in the inventory, and then marks them, comprehensively understands the current inventory situation, identifies potential problems, provides a basis for subsequent optimization measures, according to the inventory changes, analyzes the sales quantity and average inventory quantity of each stock keeping unit within the current evaluation period, and calculates the inventory trend index in combination with the average sales quantity of all stock keeping units, analyzes the sales demand trend, clarifies the shortcoming of inventory management. If the inventory turnover rate of some stock keeping units is low and the sales quantity fluctuates greatly, it indicates that there may be inventory backlog problems for that stock keeping unit. If the inventory turnover rate of some stock keeping units is high but there are frequent out-of-stock situations, it indicates that that stock keeping unit may need to increase inventory or adjust the replenishment strategy. Based on the analysis results of the sales demand trend and the inventory level, optimize the inventory management strategy. For the identified slow-moving products, put forward treatment suggestions including promotional activities, discount sales or returning to the supplier. For high-turnover products, give priority to ensuring sufficient inventory to reduce the risk of out-of-stock; Furthermore, the expression of the inventory trend index is: ; In the formula, is the inventory trend index, is the number of stock keeping units, is the th sales quantity of the stock keeping unit within the evaluation period, is the th average inventory quantity of the stock keeping unit within the evaluation period, is the average sales quantity of all stock keeping units within the evaluation period, The value range of Close to 1 indicates that the inventory management situation is very ideal. When the sales volume of one or more stock keeping units is much lower than their average inventory levels, or the sales volume fluctuates greatly, the corresponding terms in the formula will approach 0, resulting in Close to 0 indicates that the inventory management situation is poor; The monitoring and warning module monitors and analyzes real-time data, combines the change trends of various evaluation indicators with the inventory analysis results, identifies anomalies and risks in e-commerce operations, and triggers the warning mechanism to identify abnormal fluctuations in advance and quickly take measures to reduce risks; The data visualization module is used to display the analysis and warning results through data visualization tools, help management quickly understand the current business situation, regularly generate data reports, provide decision-making support for management, and help comprehensively understand various data indicators of e-commerce operations.

[0021] Embodiment 2, as Figure 3 shown, on the basis of Embodiment 1, the present invention provides a technical solution: Preferably, the monitoring and warning module specifically includes: Extract the latest data in real time from various data sources of the e-commerce platform, obtain the transaction status evaluation index, user activity evaluation index, and inventory trend index of the current evaluation period, analyze the change trends of each index, comprehensively understand the overall operation status of the e-commerce platform, assign different weights to them according to the importance and influence degree of each index, combine the transaction status evaluation index, user activity evaluation index, and inventory trend index with their respective weights, calculate the abnormal warning coefficient, based on the analysis result of the abnormal warning coefficient in the previous evaluation period, set the warning threshold T, compare the abnormal warning coefficient with the warning threshold, determine the risk level of the current operation status, when the abnormal warning coefficient deviates from the warning threshold, automatically trigger the warning mechanism, and send warning notifications to relevant personnel by means of emails, text messages, and the message center. The warning notifications include warning names, warning details, and warning time information. After receiving the warning notifications, relevant personnel quickly analyze the cause of the problem, formulate targeted solutions according to the cause of the problem, and implement them as soon as possible; Further, the expression of the abnormal warning coefficient is: ; In the formula, is the abnormal warning coefficient, is the transaction status evaluation index of the current period, is the standard value of the transaction status evaluation index in the previous evaluation period, is the weight of the transaction status evaluation index, reflecting its importance in the overall risk assessment, is the user activity evaluation index of the current period, is the standard value of the user activity evaluation index in the previous evaluation period, is the weight of the user activity evaluation index, reflecting its importance in the overall risk assessment. is the inventory trend index for the current period. is the standard value of the inventory trend index for the previous evaluation period. is the weight of the inventory trend index, reflecting its importance in the overall risk assessment. is the adjustment factor, taking a positive value, used to control the change rate of the exponential function. ranges from 0 to 1. When each index is very close to the standard value of its previous evaluation period, each term in the formula will approach 1. Therefore, being close to 1 indicates that the operation status is very ideal. When one or more indices are far lower than the standard value of their previous evaluation period, the corresponding terms in the formula will approach 0, resulting in being close to 0, indicating that there are relatively large operation risks. The data visualization module specifically includes: Obtain the relevant data of the transaction status evaluation index, user activity evaluation index, and inventory trend index for the current evaluation period, and use Tableau to create a comprehensive dashboard to centrally display the relevant data and charts of each index, highlight the abnormal points in the current evaluation period, provide detailed information and recommended measures, add filters in the dashboard to allow users to select the corresponding time period, commodity category, and regional conditions, dynamically update the chart content, and support users to click on the data points in the chart to further view the detailed sub-data or associated data. Set the generation cycle of the operation report according to business requirements, including an overview section, a detailed analysis section, and a warning and recommendation section, and use the automatic report generation function of Tableau to automatically generate and send reports.

[0022] As described above, it is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claimed rights.

Claims

1. An e-commerce operation data processing, analysis and interaction platform, including a data interaction management center, characterized in that: The data interaction management center is communicatively connected to a data collection and integration module, a multi-dimensional evaluation system construction module, an evaluation index trend analysis module, an inventory management analysis module, a monitoring and warning module, and a data visualization module. Among them, the modules are electrically connected to each other; The data collection and integration module is used to collect data of various dimensions of the e-commerce platform and integrate and obtain an operation data sequence; The multi-dimensional evaluation system construction module, based on the e-commerce operation requirements, clarifies the multi-dimensional evaluation indexes for evaluating the operation status, which are respectively the transaction evaluation index and the user activity index; The evaluation index trend analysis module is used to analyze each of the multi-dimensional evaluation indexes for evaluating the operation status one by one to determine the change trend of each evaluation index of the operation status; The inventory management analysis module monitors and analyzes inventory data, analyzes the sales demand trend, and optimizes the inventory management strategy; The monitoring and warning module monitors and analyzes real-time data, combines the change trend of each evaluation index and the inventory analysis result, identifies the anomalies and risks of e-commerce operation, and triggers the warning mechanism; The data visualization module is used to display the analysis and warning results through data visualization tools.

2. The e-commerce operation data processing, analysis and interaction platform according to claim 1, wherein: The data collection and integration module specifically includes: According to the requirements of e-commerce operation, clarify the data types to be collected, including user behavior data, transaction data, inventory data, advertising data, product information, and customer service data; Based on the data structure of the target e-commerce platform, configure data collection parameters and execute data collection tasks, and obtain the latest data in real time from the data sources of various data types of e-commerce operation through the API interface; Preprocess the collected data, including the steps of data cleaning, data conversion, and data summarization; Associate the information from different data sources according to the unique identifier of the user ID, and merge the related data into a comprehensive data set to form a complete operation data sequence; Build a data warehouse based on the MySQL relational database, store the e-commerce operation data related to the operation data sequence, and formulate a data backup plan to perform data backup regularly.

3. The e-commerce operation data processing and analysis interactive platform according to claim 2, characterized in that: The multi-dimensional evaluation system construction module specifically includes: Traverse the relevant data of the operation data sequence, and clarify the multi-dimensional evaluation indexes for evaluating the operation status in combination with the e-commerce operation requirements, including the transaction evaluation index and the user activity index; Analyze the transaction evaluation index, determine the sub-transaction evaluation indexes including the order conversion rate, order volume, return rate, and repurchase rate, and preset the standard values of each sub-transaction evaluation index in combination with the transaction evaluation index data of the previous evaluation period; Analyze the user activity index, determine the sub-user activity indexes including the average user access frequency, new user growth rate, and active user number, and preset the standard values of each sub-user activity index in combination with the user activity index data of the previous evaluation period; Based on the determined sub-transaction evaluation indexes and sub-user activity indexes, grab the associated data of the sub-transaction evaluation indexes and sub-user activity indexes of the current evaluation period and the previous evaluation period from the operation data sequence.

4. An e-commerce operation data processing, analysis and interaction platform according to claim 3, characterized in that: The evaluation index trend analysis module specifically includes: Conduct comparative analysis separately based on the multi-dimensional evaluation index data of the current evaluation period and the previous evaluation period captured. For the transaction evaluation index, analyze the sub-transaction evaluation indexes of the two evaluation periods and the preset standard values of each sub-transaction evaluation index, calculate the transaction status evaluation index, and analyze the change trend of the transaction evaluation index in the current evaluation period. For the user activity index, analyze the sub-user activity indexes of the two evaluation periods and the preset standard values of each sub-user activity index, calculate the user activity evaluation index, and analyze the change trend of the user activity index in the current evaluation period. Plot the values of the transaction evaluation index and the user activity index in the current evaluation period and the previous evaluation period as a time series graph to visually display their change trends and identify the trends of each index rising, falling, or remaining stable.

5. The e-commerce operation data processing and analysis interactive platform according to claim 4, characterized in that: The expression of the transaction status evaluation index is: ； In the formula, is the trading status evaluation index, is the actual value of the th sub-trading evaluation index in the current evaluation period, is the preset standard value of the th sub-trading evaluation index, is the index of the sub-trading evaluation index, , which respectively represent the order conversion rate, order volume, return rate and repurchase rate, ranges from 0 to 1; The expression of the user activity evaluation index is: ； In the formula, is the user activity evaluation index, This is the current assessment cycle The actual value of the active indicator of each sub-user, For the preset The standard value of the active indicator of each sub-user, The index of the sub-user's active indicator. , respectively represent the average user access frequency, new user growth rate and number of active users, The value range is between 0 and 1.

6. The e-commerce operation data processing, analysis and interaction platform according to claim 5, characterized in that: The inventory management analysis module specifically includes: Extract the inventory data of the current evaluation period and the previous period from the data warehouse, including inventory quantity, inbound records, outbound records, and commodity sales data, and count the current inventory quantity, and classify and summarize by stock keeping unit. Analyze the inventory changes between the previous evaluation period and the current evaluation period, and analyze the inventory turnover rate of each stock keeping unit to identify the commodity units that have not been sold for a long time in the inventory, and then mark them. Based on the inventory changes, analyze the sales quantity and average inventory of each stock keeping unit in the current evaluation period, and calculate the inventory trend index in combination with the average sales quantity of all stock keeping units, analyze the sales demand trend, and clarify the short board of inventory management. Optimize the inventory management strategy based on the analysis results of the sales demand trend and the inventory level.

7. An e-commerce operation data processing, analysis and interaction platform according to claim 6, characterized in that: The expression of the inventory trend index is: ； Wherein, is the inventory trend index, is the quantity of stock keeping units, is the th sales quantity of the stock keeping unit during the evaluation period, is the th average inventory of the stock keeping unit during the evaluation period, is the average sales quantity of all stock keeping units during the evaluation period, ranges from 0 to 1.

8. An e-commerce operation data processing, analysis and interaction platform according to claim 7, characterized in that: The monitoring and warning module specifically includes: Extract the latest data in real time from various data sources of the e-commerce platform, and obtain the transaction status evaluation index, user activity evaluation index, and inventory trend index of the current evaluation period, analyze the change trends of each index, and comprehensively understand the overall operation status of the e-commerce platform. Assign different weights to each index according to its importance and influence degree, combine the transaction status evaluation index, user activity evaluation index, and inventory trend index with their respective weights, and calculate the abnormal warning coefficient. Based on the analysis results of the abnormal warning coefficient in the previous evaluation period, set the warning threshold T, compare the abnormal warning coefficient with the warning threshold, and determine the risk level of the current operation status. When the abnormal warning coefficient deviates from the warning threshold, automatically trigger the warning mechanism and send warning notifications to relevant personnel via email, text message, and message center.

9. An e-commerce operation data processing, analysis and interaction platform according to claim 8, characterized in that: The expression of the abnormal warning coefficient is: ； In the formula, is the abnormal warning coefficient, is the trading status evaluation index of the current period, is the standard value of the trading status evaluation index of the previous evaluation period, is the weight of the trading status evaluation index, is the user activity evaluation index of the current period, is the standard value of the user activity evaluation index of the previous evaluation period, is the weight of the user activity evaluation index, is the inventory trend index of the current period, is the standard value of the inventory trend index of the previous evaluation period, is the weight of the inventory trend index, is the adjustment factor, taking a positive value, used to control the change rate of the exponential function, The value range of is between 0 and 1.

10. The e-commerce operation data processing and analysis interactive platform according to claim 9, characterized in that: The data visualization module specifically includes: Obtain the relevant data of the transaction status evaluation index, user activity evaluation index, and inventory trend index of the current evaluation period, and create a comprehensive dashboard using Tableau to centrally display the relevant data and charts of each index, highlight the abnormal points in the current evaluation period, and provide detailed information and recommended measures. Add filters to the dashboard to allow users to select corresponding time periods, product categories, and regional conditions, dynamically update the chart content, and support users to click on data points in the chart to further view detailed sub-data or associated data; Set the generation cycle of operation reports according to business requirements, including an overview section, a detailed analysis section, and a warning and recommendation section, and use Tableau's automatic report generation function to automatically generate and send reports.

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