E-commerce platform management method

Abstract

The invention discloses an e-commerce platform management method, relates to the technical field of e-commerce, and has the advantages that market changes and user demands can be quickly responded by calculating an e-commerce platform customer satisfaction numerical value, an e-commerce platform marketing strategy adjustment index and an e-commerce platform operation effect value in real time; the user feedback data is applied to the optimization process of the platform operation strategy, so that the user demand is accurately met, the user experience is improved, meanwhile, the dynamic strategy optimization enables the platform to flexibly adjust the operation strategy according to different market environments and user behaviors, the adaptability and innovativeness of the platform are enhanced, and the user experience is improved. And finally, a scientific basis is provided for strategy optimization through big data calculation and analysis, and the accuracy and effectiveness of decision making are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce, and in particular to an e-commerce platform management method. Background Art

[0002] With the rapid development of the Internet, e-commerce platform management has become an important channel for people to trade goods. In a broad sense, e-commerce platform is a collection of electronic technical means for all participants in business activities and supporting enterprises to conduct trading activities. In a narrow sense, it is a platform for enterprises and consumers to sell, provide services, etc. on the basis of the Internet. In order to ensure and improve user experience and platform competitiveness, e-commerce platform needs to continuously optimize its operating strategy.

[0003] However, the current e-commerce platform management methods mostly adopt fixed marketing strategies in the process of use, which are poorly adaptable to the rapid changes in the market and the diversified needs of users, and cannot be effectively and quickly adjusted, which makes the e-commerce platform slow to respond to market competition and changes in user needs, thus affecting the user experience and platform revenue, resulting in poor management results and being unfavorable to the efficient development of the e-commerce platform;

[0004] Specifically: Existing management methods are mostly based on regular market research and data analysis to adjust strategies, which cannot respond to rapid changes in the market in a timely manner;

[0005] In addition, the existing management methods mostly adopt fixed operating strategies that cannot adapt to diverse market demands and user preferences, which limits the platform's innovation ability and market competitiveness. Summary of the invention

[0006] The purpose of the present invention is to provide an e-commerce platform management method to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solution: an e-commerce platform management method, comprising the following steps:

[0008] Data collection and analysis: Collect data from e-commerce platforms, including sales data, customer feedback, advertising effectiveness, inventory status, and analyze and classify the collected data to analyze the customer return rate and the average score of customer evaluation;

[0009] Comprehensive management, including:

[0010] First, the collected customer return rate values, average customer evaluation scores, and marketing strategy customer satisfaction values ​​are substituted into the e-commerce platform customer satisfaction algorithm unit for calculation to obtain the e-commerce platform customer satisfaction value;

[0011] Next, the e-commerce platform satisfaction value and the customer return rate value are substituted into the e-commerce platform marketing strategy management algorithm unit to calculate the e-commerce platform marketing strategy adjustment index;

[0012] Afterwards, the calculated customer satisfaction value of the e-commerce platform and the marketing strategy adjustment index of the e-commerce platform are substituted into the e-commerce platform operation effect management algorithm unit to calculate the e-commerce platform operation effect value;

[0013] Then, the e-commerce platform operation effect value is further calculated to calculate a new PD value, which optimizes the original PD value in the e-commerce platform customer satisfaction algorithm unit to adjust the weight of the marketing strategy customer satisfaction value, thereby affecting the calculated values ​​of the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit, and optimizing the e-commerce platform management system method through iteration;

[0014] Adjustment and management: Analyze the calculated operational effectiveness values ​​of the e-commerce platform, and make corresponding adjustments and optimizations to adjust and manage the inventory and marketing strategies of the e-commerce platform.

[0015] Optionally, a data mining module, a correlation information analysis module, a computer, a data management and storage module, and a policy adjustment management module are used;

[0016] The data mining module is used to collect and mine user behavior data, purchase records and evaluation details from the e-commerce platform and pre-process the information data, and upload this part of the data to the associated information analysis module, the associated information analysis module is used to discover the association relationship between commodities, and group the user's associated information according to the user's purchase behavior and preference habit data, and then upload this part of the data to the computer, and the data management and storage module in the computer performs data storage, backup and recovery management to ensure the security and integrity of the data, and then upload this part of the data to the strategy adjustment management module, the strategy adjustment management module can calculate the collected user behavior data, purchase records and evaluation details to obtain the e-commerce platform customer satisfaction value, the e-commerce platform marketing strategy adjustment index and the e-commerce platform operation effect value, so as to achieve comprehensive optimization and management of the e-commerce platform customer satisfaction, marketing strategy and inventory management benefits, and can also re-substitute the e-commerce platform operation effect value into the e-commerce platform customer satisfaction value after calculation to continuously optimize the overall algorithm unit system;

[0017] The strategy adjustment management module includes: an e-commerce platform customer satisfaction algorithm unit, an e-commerce platform marketing strategy management algorithm unit and an e-commerce platform operation effect management algorithm unit.

[0018] Optionally, the e-commerce platform customer satisfaction algorithm unit is as follows:

[0019]

[0020] Y = (1-PB);

[0021] Among them: PA e-commerce platform customer satisfaction value;

[0022] T o is the order processing time;

[0023] T m is the maximum acceptable processing time;

[0024] PB is the customer return rate value;

[0025] PC is the average score of customer reviews;

[0026] A is the full score of customer evaluation;

[0027] X is the score value that converts order processing time into satisfaction;

[0028] Y is a measure of customer return rate;

[0029] α, β and γ are X, Y and The weight coefficient of

[0030] PF is the potential impact of e-commerce platform marketing strategy on customer satisfaction;

[0031] PD is the weight coefficient of the customer satisfaction value of the marketing strategy.

[0032] Optionally, the e-commerce platform marketing strategy management algorithm unit is as follows:

[0033]

[0034] Among them: CA is the e-commerce platform marketing strategy adjustment index;

[0035] Z is the ratio of competitor’s advertising investment to the maximum advertising investment;

[0036] CB is the advertising investment of competitors;

[0037] CC is the maximum advertising investment;

[0038] ω and φ are Z and (a*T o +b*PB+c*PC) weight coefficient;

[0039] a, b, c are T o , weight coefficients of PB and PC.

[0040] Optionally, the e-commerce platform operation effect management algorithm unit is as follows:

[0041] DA = (e*PA + f*CA-1)*DB;

[0042] Among them: DA is the operational effect value of the e-commerce platform;

[0043] e and f are the weight coefficients of PA and CA respectively.

[0044] Optionally, the e-commerce platform operation effect management algorithm unit is further as follows:

[0045] First, PD x =DA+PD old ;

[0046] Next, use the new PD x The value is re-substituted into the PD value involved in the calculation in the e-commerce platform customer satisfaction algorithm unit to optimize and iterate the initial PD value, and the e-commerce platform customer satisfaction algorithm unit, the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit are cyclically iterated, and the iteration stops when the number of iterations reaches six.

[0047] Optionally, the devices used by the data management and storage module include a database and a data storage device, the database is used to store data on the e-commerce platform, including: customer data information, order data information and product information, and the data storage device is used to increase the large capacity to back up and archive historical data.

[0048] Optionally, the data management and storage module further includes a monitoring and alarm unit, which includes: a log analysis system, a monitoring server and an alarm notification system.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The three algorithm units of the present invention constitute a complete and efficient management system method for an e-commerce platform. The effects of the three algorithm units individually and in combination are:

[0051] The customer satisfaction algorithm unit of the first e-commerce platform can perform comprehensive calculations based on customer satisfaction and ratings, so that users can understand the advantages and potential problems of the platform in a timely manner;

[0052] The second e-commerce platform marketing strategy management algorithm unit can perform comprehensive calculations based on customer satisfaction and competitor advertising, making it easier to adjust the current marketing strategy and actual operating conditions;

[0053] The third e-commerce platform operation effect management algorithm unit can perform comprehensive calculations on the e-commerce platform customer satisfaction value and the e-commerce platform marketing strategy adjustment index to obtain the e-commerce platform operation effect value as a quantitative indicator of the e-commerce platform operation effect. By analyzing the change trend of the value, users can optimize the current e-commerce platform operation strategy as a whole.

[0054] Fourthly, the results calculated by the e-commerce platform operation effect management algorithm unit can be substituted into the e-commerce platform customer satisfaction algorithm unit to continuously iterate and optimize the calculations of the three algorithms, thereby enabling adjacent algorithms to have correlations in calculation and effect, and also having the characteristics of iterative and cyclic optimization, thereby optimizing and improving self-use according to actual customer satisfaction, so as to attract more customers to use this platform and improve the intelligence and practicality of this platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A method flow chart of the e-commerce platform management method;

[0056] Figure 2 This is a schematic diagram of the overall structure of the e-commerce platform management method. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Regarding this e-commerce platform management method, it is different from the existing e-commerce platform management methods. During the operation process, the existing e-commerce platforms mostly adopt fixed marketing strategies, which are unable to make dynamic adjustments according to market changes and user needs. This will cause the platform to be slow to respond to market competition and changes in user needs, thereby affecting the user experience and platform revenue. The present e-commerce platform management method can quickly respond to market changes and user needs through real-time calculation and analysis of customer satisfaction, e-commerce platform marketing strategy adjustment index and strategy adjustment value, improve the timeliness of strategy adjustment, and thus more accurately meet user needs and enhance user experience.

[0059] Example 1: Please refer to Figure 1 to Figure 2 This embodiment provides an e-commerce platform management method, comprising the following steps:

[0060] Data collection and analysis: Collect data from e-commerce platforms, including sales data, customer feedback, advertising effectiveness, inventory status, and analyze and classify the collected data to analyze the customer return rate and the average score of customer evaluation;

[0061] Comprehensive management, including:

[0062] First, the collected customer return rate values, average customer evaluation scores, and marketing strategy customer satisfaction values ​​are substituted into the e-commerce platform customer satisfaction algorithm unit for calculation to obtain the e-commerce platform customer satisfaction value;

[0063] Next, the e-commerce platform satisfaction value and the customer return rate value are substituted into the e-commerce platform marketing strategy management algorithm unit to calculate the e-commerce platform marketing strategy adjustment index;

[0064] Afterwards, the calculated customer satisfaction value of the e-commerce platform and the marketing strategy adjustment index of the e-commerce platform are substituted into the e-commerce platform operation effect management algorithm unit to calculate the e-commerce platform operation effect value;

[0065] Then, the e-commerce platform operation effect value is further calculated to calculate a new PD value, which optimizes the original PD value in the e-commerce platform customer satisfaction algorithm unit to adjust the weight of the marketing strategy customer satisfaction value, thereby affecting the calculated values ​​of the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit, and optimizing the e-commerce platform management system method through iteration;

[0066] Adjustment and management: Analyze the calculated operational effectiveness values ​​of the e-commerce platform, and make corresponding adjustments and optimizations to adjust and manage the inventory and marketing strategies of the e-commerce platform.

[0067] This e-commerce platform management method uses a data mining module, a correlation information analysis module, a computer, a data management and storage module, and a strategy adjustment management module;

[0068] The data mining module is used to collect and mine user behavior data, purchase records and evaluation details from the e-commerce platform and pre-process the information data, and upload this part of the data to the related information analysis module. The related information analysis module is used to discover the association relationship between commodities, and group the user's related information according to the user's purchase behavior and preference habit data, and then upload this part of the data to the computer. The data management and storage module in the computer performs data storage, backup and recovery management to ensure the security and integrity of the data, and then upload this part of the data to the strategy adjustment management module. The strategy adjustment management module can calculate the collected user behavior data, purchase records and evaluation details to obtain the e-commerce platform customer satisfaction value, the e-commerce platform marketing strategy adjustment index and the e-commerce platform operation effect value, so as to achieve comprehensive optimization and management of the e-commerce platform customer satisfaction, marketing strategy and inventory management benefits, and can also re-substitute the e-commerce platform operation effect value into the e-commerce platform customer satisfaction value after calculation to continuously optimize the overall algorithm unit system;

[0069] The strategy adjustment management module includes: e-commerce platform customer satisfaction algorithm unit, e-commerce platform marketing strategy management algorithm unit and e-commerce platform operation effect management algorithm unit.

[0070] In this embodiment: the three algorithms of the present invention constitute a complete and efficient management system method for an e-commerce platform. Each of the three algorithms plays a substantial role in the management of the platform. The combination of the three algorithms can more intuitively show the problems and trends of the platform to users. First, the e-commerce platform customer satisfaction algorithm unit can perform comprehensive calculations based on customer satisfaction and scores, so that users can understand the advantages and potential problems of the platform. The e-commerce platform marketing strategy management algorithm unit can perform comprehensive calculations based on customer satisfaction and competitors' advertising, so as to facilitate the adjustment of the current marketing strategy and actual operating conditions. The e-commerce platform operation effect management algorithm unit can perform comprehensive calculations on the e-commerce platform customer satisfaction value and the e-commerce platform marketing strategy adjustment index to obtain the e-commerce platform operation effect value as a quantitative indicator of the e-commerce platform operation effect. Analyzing the changing trend of this value makes it easier for users to optimize the current e-commerce platform operation strategy as a whole. The combination of the three algorithm units can achieve comprehensive optimization of the e-commerce platform, including improving customer satisfaction, optimizing marketing strategies, operation results and inventory management. In addition, through iteration, the e-commerce platform can dynamically adjust the operation strategy according to market changes and internal conditions to maintain competitive advantages, and continuously optimize the operation strategy and operation results to help reduce operating costs and improve operational efficiency. It can also optimize and improve its own use based on actual customer satisfaction to attract more customers to use the platform and improve customer stickiness. The management method of this e-commerce platform can collect and analyze data in real time, and respond quickly to market changes and customer needs. This high efficiency and real-time nature help e-commerce platforms maintain their leading position in the highly competitive market.

[0071] See also Figure 1 to Figure 2 ,The algorithm units of customer satisfaction of e-commerce platform are as follows:

[0072]

[0073] Y = (1-PB);

[0074] Among them: PA e-commerce platform customer satisfaction value;

[0075] T o is the order processing time;

[0076] T m is the maximum acceptable processing time;

[0077] PB is the customer return rate value;

[0078] PC is the average score of customer reviews;

[0079] A is the full score of customer evaluation;

[0080] X is the score value that converts order processing time into satisfaction;

[0081] Y is a measure of customer return rate;

[0082] α, β, and γ are X, Y, and The weight coefficient of

[0083] PF is the potential impact of e-commerce platform marketing strategy on customer satisfaction;

[0084] PD is the weight coefficient of the customer satisfaction value of the marketing strategy.

[0085] In this embodiment: first, PF is calculated as the potential impact value of the marketing strategy of the e-commerce platform on customer satisfaction. For example, the e-commerce platform is implementing a marketing strategy, which is to improve customer satisfaction by improving customer service. In order to intuitively reflect the impact of this strategy on customer satisfaction, it is reflected through PF. However, this strategy may only be one of the factors affecting customer satisfaction, and PD is needed to adjust the impact of PF in the overall satisfaction calculation. The calculation of PD is related to the relationship between the e-commerce platform operation effect management algorithm unit and the feedback and substitution iteration. When this algorithm unit is actually used, PA directly provides an indicator to reflect customer satisfaction with the e-commerce platform service, and customer satisfaction is an important basis for the e-commerce platform to adjust its operation strategy. If the satisfaction is low, it may be necessary to improve services, optimize products, and adjust marketing strategies. Therefore, the calculation of PA is particularly important in the management of the e-commerce platform, which is related to the sustainable and stable development of the e-commerce platform. When customer satisfaction is stable and improved, it helps to improve the competitiveness and influence of the e-commerce platform.

[0086] See also Figure 1 to Figure 2 ,The e-commerce platform marketing strategy management algorithm units are as follows:

[0087]

[0088] Among them: CA is the e-commerce platform marketing strategy adjustment index;

[0089] Z is the ratio of competitor’s advertising investment to the maximum advertising investment;

[0090] CB is the advertising investment of competitors;

[0091] CC is the maximum advertising investment;

[0092] ω and is Z and (a*T o +b*PB+c*PC) weight coefficient;

[0093] a, b, c are T o, weight coefficients of PB and PC.

[0094] In this embodiment: the e-commerce platform marketing strategy management algorithm unit obtains the e-commerce platform marketing strategy adjustment index through further calculation of the e-commerce platform customer satisfaction algorithm unit. In actual application, CA can calculate the e-commerce platform marketing strategy adjustment index according to the actual market situation, that is, CB and customer satisfaction, so that the marketing strategy is more flexible and adaptable to market changes, and by adjusting the marketing strategy, the e-commerce platform can place advertisements more effectively, thereby improving advertising efficiency and return rate, and according to CA, it can also optimize the marketing strategy, thereby helping to attract traffic to the e-commerce platform.

[0095] See also Figure 1 to Figure 2 ,The e-commerce platform marketing strategy management algorithm units are as follows:

[0096] The e-commerce platform operation effect management algorithm units are as follows:

[0097] DA = (e*PA + f*CA-1)*DB;

[0098] Among them: DA is the operational effect value of the e-commerce platform;

[0099] e and f are the weight coefficients of PA and CA respectively.

[0100] In this embodiment: the e-commerce platform marketing strategy management algorithm unit combines the e-commerce platform customer satisfaction value and the e-commerce platform marketing strategy adjustment index to perform comprehensive calculations to obtain the e-commerce platform operation effect value. The calculation of this value can be used as a quantitative indicator of the e-commerce platform operation effect. By analyzing the change trend of DA, it is convenient for users to reconstruct and optimize the current e-commerce platform operation strategy. In the process of e-commerce platform management, users need to make various decisions continuously, such as price adjustment and promotion activity management. DA can be used as a decision support tool to provide managers with excellent data support to facilitate users to make decisions. DA can also be used as a means of risk assessment to help users identify and assess potential risks and formulate corresponding risk response measures. Finally, by regularly monitoring the change trend of DA, users can achieve real-time monitoring of the operation of the e-commerce platform, which has the effect of killing two birds with one stone.

[0101] DA has the characteristics of comprehensive calculation, so it is optimized for the inventory of e-commerce platforms, which can help the platforms optimize inventory management, reduce inventory costs, and improve operational efficiency. Good inventory conditions help reduce the risks of inventory backlogs and out-of-stocks.

[0102] See also Figure 1 to Figure 2 , the e-commerce platform operation effect management algorithm unit is further as follows:

[0103] First, PD x =DA+PD old ;

[0104] Next, use the new PD x The value is re-substituted into the PD value involved in the calculation of the e-commerce platform customer satisfaction algorithm unit to optimize and iterate the initial PD value, and the e-commerce platform customer satisfaction algorithm unit, the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit are cyclically iterated, and the iteration stops when the number of iterations reaches six.

[0105] In this embodiment: firstly, the calculation results of the e-commerce platform customer satisfaction algorithm unit can be continuously changed and influenced through this iterative form, thereby continuously influencing the calculation results of the three algorithm units of the present invention to achieve an iterative and optimized form, more specifically:

[0106] Firstly, the algorithm unit of the present invention is dynamically adaptable, and the potential impact of the marketing strategy of the e-commerce platform on customer satisfaction is continuously affected by iteratively adjusting the value of PD. For example, when the result of DA indicates that it is necessary to increase the investment of a certain strategy or resource, the e-commerce platform can respond and adjust quickly.

[0107] Secondly: By constantly adjusting the value of PD, which is a process of optimizing resource allocation, e-commerce platforms can find the best resource allocation plan, and thus achieve the best indicators such as customer satisfaction and profit to a certain extent;

[0108] Next: Different from the fixed management decision-making method, this method can respond to market changes by continuously optimizing the PD value, and can adjust data and response strategies quickly and conveniently, thereby avoiding the situation of missing market opportunities;

[0109] And: Since the optimization of PD value is based on the customer satisfaction value of PA e-commerce platform, this form of optimization and adjustment can directly meet customer needs and improve customer satisfaction, thereby improving the development of this e-commerce platform.

[0110] In the specific implementation process, the three algorithm units in the method are used to form a system of the e-commerce platform management method. First, the collected customer return rate value and the average score of customer evaluation are substituted into the e-commerce platform customer satisfaction algorithm unit to obtain the e-commerce platform customer satisfaction value. The calculation of this value can provide users with an intuitive indicator to reflect the customer's satisfaction with the e-commerce platform service, which is convenient for optimizing products and adjusting marketing strategies. Then, the e-commerce platform customer satisfaction value is further calculated to obtain the e-commerce platform marketing strategy adjustment index, so that the marketing strategy is more flexible and adaptable to market changes, and the e-commerce platform can place advertisements more effectively by adjusting the marketing strategy. Finally, the e-commerce platform marketing strategy adjustment index and the e-commerce platform customer satisfaction value are comprehensively calculated to obtain the e-commerce platform operation effect value, which can be used as a quantitative indicator of the e-commerce platform operation effect to modify and optimize the current e-commerce platform operation strategy, and this value can be further substituted into and affect the calculation of the e-commerce platform customer satisfaction algorithm unit, so that the overall algorithm unit is continuously optimized and iterated, with excellent dynamics.

[0111] Embodiment 2, based on the above embodiment:

[0112] See also Figure 1 and Figure 2 The devices used in the data management and storage module include database and data storage devices. The database is used to store data on the e-commerce platform, including customer data information, order data information and product information. The data storage device is used to increase the capacity to back up and archive historical data.

[0113] In this embodiment: the database and the data storage device are used in combination to store, archive and back up the data information collected on the e-commerce platform and the information before and after calculation, and to repair the data in a timely manner when the data is lost or damaged, which helps to improve the stability of the system operation.

[0114] The data management and storage module also includes a monitoring and alarm unit, which includes: a log analysis system, a monitoring server and an alarm notification system.

[0115] In this embodiment: first, the monitoring server is used to perform performance analysis, troubleshooting and real-time monitoring of the e-commerce platform, and monitor the operating status and performance indicators of the e-commerce platform in real time; the log analysis system analyzes the system logs to timely locate and discover security risks; the alarm notification system can provide timely feedback and notify the administrator when an abnormal situation occurs in the system, thereby ensuring that the problem can be handled in a timely manner.

[0116] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An e-commerce platform management method, characterized in that: The following steps are involved: Data collection and analysis: Collect data from e-commerce platforms, including sales data, customer feedback, advertising effectiveness, inventory status, and analyze and classify the collected data to analyze the customer return rate and the average score of customer evaluation; Comprehensive management, including: First, the collected customer return rate values, average customer evaluation scores, and marketing strategy customer satisfaction values ​​are substituted into the e-commerce platform customer satisfaction algorithm unit for calculation to obtain the e-commerce platform customer satisfaction value; Next, the e-commerce platform satisfaction value and the customer return rate value are substituted into the e-commerce platform marketing strategy management algorithm unit to calculate the e-commerce platform marketing strategy adjustment index; Afterwards, the calculated customer satisfaction value of the e-commerce platform and the marketing strategy adjustment index of the e-commerce platform are substituted into the e-commerce platform operation effect management algorithm unit to calculate the e-commerce platform operation effect value; Then, the e-commerce platform operation effect value is further calculated to calculate a new PD value, which optimizes the original PD value in the e-commerce platform customer satisfaction algorithm unit to adjust the weight of the marketing strategy customer satisfaction value, thereby affecting the calculated values ​​of the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit, and optimizing the e-commerce platform management system method through iteration; Adjustment and management: Analyze the calculated operational effectiveness values ​​of the e-commerce platform, and make corresponding adjustments and optimizations to adjust and manage the inventory and marketing strategies of the e-commerce platform.

2. The e-commerce platform management method according to claim 1, characterized in that: The e-commerce platform management method adopts the following processing modules: Data mining module, correlation information analysis module, computer, data management and storage module and strategy adjustment management module; The data mining module is used to collect and mine user behavior data, purchase records and evaluation details from the e-commerce platform and pre-process the information data, and upload this part of the data to the associated information analysis module, the associated information analysis module is used to discover the association relationship between commodities, and group the user's associated information according to the user's purchase behavior and preference habit data, and then upload this part of the data to the computer, and the data management and storage module in the computer performs data storage, backup and recovery management to ensure the security and integrity of the data, and then upload this part of the data to the strategy adjustment management module, the strategy adjustment management module can calculate the collected user behavior data, purchase records and evaluation details to obtain the e-commerce platform customer satisfaction value, the e-commerce platform marketing strategy adjustment index and the e-commerce platform operation effect value, so as to achieve comprehensive optimization and management of the e-commerce platform customer satisfaction, marketing strategy and inventory management benefits, and can also re-substitute the e-commerce platform operation effect value into the e-commerce platform customer satisfaction value after calculation to continuously optimize the overall algorithm unit system; The strategy adjustment management module includes an e-commerce platform customer satisfaction algorithm unit, an e-commerce platform marketing strategy management algorithm unit and an e-commerce platform operation effect management algorithm unit.

3. The e-commerce platform management method according to claim 2, characterized in that: The e-commerce platform customer satisfaction algorithm unit is as follows: Y = (1-PB); Among them: PA e-commerce platform customer satisfaction value; T o is the order processing time; T m is the maximum acceptable processing time; PB is the customer return rate value; PC is the average score of customer reviews; A is the full score of customer evaluation; X is the score value that converts order processing time into satisfaction; Y is a measure of customer return rate; α, β and γ are X, Y and The weight coefficient of PF is the potential impact of e-commerce platform marketing strategy on customer satisfaction; PD is the weight coefficient of the customer satisfaction value of the marketing strategy; The e-commerce platform marketing strategy management algorithm unit is as follows: Among them: CA is the e-commerce platform marketing strategy adjustment index; Z is the ratio of competitor’s advertising investment to the maximum advertising investment; CB is the advertising investment of competitors; CC is the maximum advertising investment; ω and is Z and (a*T o +b*PB+c*PC) weight coefficient; a, b, c are T o , weight coefficients of PB and PC.

4. The e-commerce platform management method according to claim 3, characterized in that: The e-commerce platform operation effect management algorithm unit is as follows: DA = (e*PA + f*CA-1)*DB; Among them: DA is the operational effect value of the e-commerce platform; e and f are the weight coefficients of PA and CA respectively.

5. The e-commerce platform management method according to claim 4, characterized in that: The e-commerce platform operation effect management algorithm unit is further as follows: First, PD x =DA+PD old ; Next, use the new PD x The value is re-substituted into the PD value involved in the calculation in the customer satisfaction algorithm unit of the e-commerce platform to optimize and iterate the initial PD value.

6. The e-commerce platform management method according to claim 5, characterized in that: During the calculation process of the e-commerce platform operation effect management algorithm unit, the e-commerce platform customer satisfaction algorithm unit, the e-commerce platform marketing strategy management algorithm unit and the e-commerce platform operation effect management algorithm unit are looped and iterated, and the loop is stopped when the number of iterations reaches six.

7. The e-commerce platform management method according to claim 2, characterized in that: The devices used by the data management and storage module include a database and a data storage device, and the database is used to store data on the e-commerce platform; The data on the e-commerce platform includes: customer data information, order data information and product information, and the data storage device is used to increase the large capacity to back up and archive historical data.

8. The e-commerce platform management method according to claim 2, characterized in that: The data management and storage module also includes a monitoring and alarm unit, which includes a log analysis system, a monitoring server and an alarm notification system.

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