Intelligent Label Processing Method, System and Medium Based on Customer Management Technology

Abstract

The embodiments of the present application provide an intelligent label processing method, system and medium based on customer management technology. The method includes: obtaining customer data, preprocessing the customer data to obtain processed data; analyzing and classifying the processed data based on big data to obtain a classification result, and classifying customers according to the classification result to obtain customer types; setting a label system, matching the customer types according to the label system to establish customer labels; obtaining customer demand information, setting a customer security level based on the customer demand information, encrypting the customer labels based on the customer security level to obtain encrypted data; and generating corresponding access keys; by analyzing customer data and performing customer type classification processing, different customer labels are established for different types of customers according to the label system, and security levels are established and encrypted for customers with different needs, thereby improving the security of customer data.

Description

Technical Field

[0001] This application relates to the technical field of customer label management. Specifically, it relates to an intelligent label processing method, system and medium based on customer management technology. Background Art

[0002] Currently, there is a customer grouping system in the marketing system. This system classifies based on the data of customer grouping records of customer basic information. The existing customer grouping system cannot flexibly describe the characteristics of electricity customers, has insufficient descriptive information, cannot refine specific customer groups, cannot screen user groups with certain common characteristics, is not flexible enough when describing the characteristics of a single user, and at the same time, the definition of grouping does not have business meaning and cannot provide more help in business.

[0003] The existing description of customer characteristics is more based on the basic information of customers, which cannot meet the description requirements of customer characteristics. Moreover, the existing customer label management cannot classify and process according to customer types, cannot establish different customer labels for different types of customers, cannot establish security levels and encrypt for customers with different needs, and the security of customer management is relatively poor. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide an intelligent label processing method, system and medium based on customer management technology. By analyzing customer data and performing customer type classification processing, different customer labels are established for different types of customers according to the label system, and security levels are established and encrypted for customers with different needs, thereby improving the security of customer data.

[0005] The embodiments of this application also provide an intelligent label processing method based on customer management technology, including:

[0006] Obtain customer data, preprocess the customer data to obtain processed data;

[0007] Analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types;

[0008] Set a label system, match the customer types according to the label system, and establish customer labels;

[0009] Obtain customer demand information, set a customer security level based on the customer demand information, and encrypt the customer labels based on the customer security level to obtain encrypted data;

[0010] Transmit the encrypted data to the terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in the database.

[0011] Optionally, in the intelligent label processing method based on customer management technology described in the embodiments of the present application, obtaining customer data, preprocessing the customer data to obtain processed data, specifically including:

[0012] Obtain customer data, extract features from the customer data to obtain customer feature data;

[0013] Perform logistic regression, decision tree, and clustering analysis on the customer feature data to obtain optimized feature data;

[0014] Determine whether the optimized feature data is within a set feature interval;

[0015] If it is within the set feature interval, generate processed data;

[0016] If it is not within the set feature interval, generate correction information, and adjust the parameters of logistic regression, decision tree, and clustering analysis based on the correction information.

[0017] Optionally, in the intelligent label processing method based on customer management technology described in the embodiments of the present application, analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types, specifically including:

[0018] Obtain the processed data, analyze the processed data based on big data, classify the processed data to obtain processed data of multiple categories;

[0019] Analyze the classification accuracy of the processed data of multiple categories based on classification rules;

[0020] Adjust the classification of the processed data based on the classification accuracy to obtain a classification result;

[0021] Obtain customer ID information, analyze the customer ID information based on the classification result, and classify the customers to obtain customer types.

[0022] Optionally, in the intelligent label processing method based on customer management technology described in the embodiments of the present application, set a label system, match the customer types according to the label system, and establish customer labels, specifically including:

[0023] Set a label system based on big data, match the customer types according to the label system to obtain a matching degree;

[0024] Determine whether the matching degree is greater than or equal to a set matching degree threshold;

[0025] If it is greater than or equal to the set matching degree threshold, generate customer labels;

[0026] If it is less than the set matching degree threshold, the customer tags are adjusted according to the tag system.

[0027] Optionally, in the intelligent tag processing method based on customer management technology described in the embodiments of the present application, customer demand information is obtained, a customer security level is set based on the customer demand information, and the customer tags are encrypted based on the customer security level to obtain encrypted data, which specifically includes:

[0028] Obtain customer demand information, analyze the customer security requirements according to the customer demand information, and obtain customer security requirement information;

[0029] Set the corresponding customer security level based on the customer security requirement information;

[0030] Establish an encryption level based on the customer security level, and set an encryption key according to the encryption level;

[0031] Encrypt the customer data according to the encryption key to obtain encrypted data.

[0032] Optionally, in the intelligent tag processing method based on customer management technology described in the embodiments of the present application, the encrypted data is transmitted to the terminal in real time, and a corresponding access key is generated, and the encrypted data and the corresponding access key are stored in the database, which specifically includes:

[0033] Obtain the encrypted data, and analyze the encryption level according to the encrypted data;

[0034] Establish an encryption key according to the encryption level, and generate an access key corresponding to the level according to the encryption key;

[0035] Analyze the compatibility between the encryption key and the access key;

[0036] Judge whether the compatibility meets the set compatibility threshold;

[0037] If the set compatibility requirement is met, store the encrypted data and the corresponding access key in the database;

[0038] If the set compatibility threshold is not met, regenerate the access key.

[0039] In a second aspect, an intelligent tag processing system based on customer management technology is provided in the embodiments of the present application. The system includes: a memory and a processor. The memory includes a program of the intelligent tag processing method based on customer management technology. When the program of the intelligent tag processing method based on customer management technology is executed by the processor, the following steps are implemented:

[0040] Obtain customer data, preprocess the customer data to obtain processed data;

[0041] Analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types;

[0042] Set up a label system, match the customer types according to the label system, and establish customer labels;

[0043] Obtain customer requirement information, set a customer security level based on the customer requirement information, and encrypt the customer labels based on the customer security level to obtain encrypted data;

[0044] Transmit the encrypted data to the terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in the database.

[0045] Optionally, in the intelligent label processing system based on customer management technology described in the embodiments of the present application, obtain customer data, preprocess the customer data to obtain processed data, specifically including:

[0046] Obtain customer data, extract features from the customer data to obtain customer feature data;

[0047] Perform logistic regression, decision tree, and clustering analysis on the customer feature data to obtain optimized feature data;

[0048] Judge whether the optimized feature data is within a set feature interval;

[0049] If it is within the set feature interval, generate processed data;

[0050] If it is not within the set feature interval, generate correction information, and adjust the parameters of logistic regression, decision tree, and clustering analysis based on the correction information.

[0051] Optionally, in the intelligent label processing system based on customer management technology described in the embodiments of the present application, analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types, specifically including:

[0052] Obtain the processed data, analyze the processed data based on big data, classify the processed data to obtain processed data of multiple categories;

[0053] Analyze the classification accuracy of the processed data of multiple categories based on classification rules;

[0054] Adjust the classification of the processed data based on the classification accuracy to obtain a classification result;

[0055] Obtain customer ID information, analyze the customer ID information based on the classification result, and classify the customers to obtain customer types.

[0056] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium, which includes a program for an intelligent label processing method based on customer management technology. When the program for the intelligent label processing method based on customer management technology is executed by a processor, the steps of the intelligent label processing method based on customer management technology as described in any one of the above are implemented.

[0057] As can be seen from the above, an intelligent label processing method, system and medium based on customer management technology provided by an embodiment of the present application obtain customer data, preprocess the customer data to obtain processed data; analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types; set a label system, match the customer types according to the label system to establish customer labels; obtain customer demand information, set a customer security level based on the customer demand information, encrypt the customer labels based on the customer security level to obtain encrypted data; transmit the encrypted data to a terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in a database; by analyzing customer data and performing customer type classification processing, different customer labels are established for different types of customers according to the label system, and security levels are established and encrypted for customers with different needs, thereby improving the security of customer data. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0059] Figure 1 It is a flowchart of the intelligent label processing method based on customer management technology provided by an embodiment of the present application;

[0060] Figure 2 It is a flowchart of the customer data preprocessing method of the intelligent label processing method based on customer management technology provided by an embodiment of the present application;

[0061] Figure 3 It is a flowchart of the customer type analysis method of the intelligent label processing method based on customer management technology provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0063] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for differential description and cannot be understood as indicating or implying relative importance.

[0064] Please refer to Figure 1 , Figure 1 which is a flowchart of an intelligent tag processing method based on customer management technology in some embodiments of the present application. This intelligent tag processing method based on customer management technology is used in a terminal device. This intelligent tag processing method based on customer management technology includes the following steps:

[0065] S101, obtain customer data, preprocess the customer data to obtain processed data;

[0066] S102, analyze and classify the processed data based on big data to obtain a classification result, and classify the customers according to the classification result to obtain customer types;

[0067] S103, set up a tag system, match the customer types according to the tag system, and establish customer tags;

[0068] S104, obtain customer demand information, set a customer security level based on the customer demand information, and encrypt the customer tags based on the customer security level to obtain encrypted data;

[0069] S105, transmit the encrypted data to the terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in a database.

[0070] It should be noted that by analyzing customer data and classifying the customer data, different customer tags are established for different categories of customer data, thereby improving the management security of customer data.

[0071] Please refer to Figure 2 ,Figure 2 This is a flowchart of a customer data preprocessing method for an intelligent tag processing method based on customer management technology in some embodiments of the present application. According to the embodiments of the present invention, customer data is obtained, and the customer data is preprocessed to obtain processed data, specifically including:

[0072] S201, obtain customer data, extract features from the customer data to obtain customer feature data;

[0073] S202, perform logistic regression, decision tree, and clustering analysis on the customer feature data to obtain optimized feature data;

[0074] S203, determine whether the optimized feature data is within a set feature interval;

[0075] S204, if it is within the set feature interval, generate processed data;

[0076] S205, if it is not within the set feature interval, generate correction information, and adjust the parameters of logistic regression, decision tree, and clustering analysis based on the correction information.

[0077] It should be noted that by performing feature analysis and processing on customer data, and analyzing whether the feature data is within a set feature interval, the analysis parameters are dynamically adjusted to improve the accuracy of data analysis.

[0078] Please refer to Figure 3 , Figure 3 This is a flowchart of a customer type analysis method for an intelligent tag processing method based on customer management technology in some embodiments of the present application. According to the embodiments of the present invention, the processed data is analyzed and classified based on big data to obtain a classification result, and the customers are classified according to the classification result to obtain customer types, specifically including:

[0079] S301, obtain the processed data, analyze the processed data based on big data, classify the processed data to obtain processed data of multiple categories;

[0080] S302, analyze the classification accuracy of the processed data of multiple categories based on classification rules;

[0081] S303, adjust the classification of the processed data based on the classification accuracy to obtain a classification result;

[0082] S304, obtain customer ID information, analyze the customer ID information based on the classification result, and classify the customers to obtain customer types.

[0083] It should be noted that by analyzing the classification accuracy of the processed data and matching it with the customer ID information, the customer types are accurately classified.

[0084] According to an embodiment of the present invention, a tag system is set up, the customer type is matched according to the tag system, and customer tags are established, specifically including:

[0085] Set up a tag system based on big data, match the customer type according to the tag system, and obtain the matching degree;

[0086] Judge whether the matching degree is greater than or equal to the set matching degree threshold;

[0087] If it is greater than or equal to the set matching degree threshold, generate customer tags;

[0088] If it is less than the set matching degree threshold, adjust the customer tags according to the tag system.

[0089] It should be noted that by establishing customer tags for different types of customers through the tag system, the matching degree between the customer tags and the customer type is ensured, and the accuracy of the customer tags is improved.

[0090] According to an embodiment of the present invention, obtain customer demand information, set a customer security level based on the customer demand information, and encrypt the customer tags based on the customer security level to obtain encrypted data, specifically including:

[0091] Obtain customer demand information, analyze the customer security requirements according to the customer demand information, and obtain customer security requirement information;

[0092] Set a corresponding customer security level based on the customer security requirement information;

[0093] Establish an encryption level based on the customer security level, and set an encryption key according to the encryption level;

[0094] Encrypt the customer data according to the encryption key to obtain encrypted data.

[0095] It should be noted that by analyzing the customer security requirements, different encryption levels are established, and the customer data is encrypted at different levels, thereby improving data security.

[0096] According to an embodiment of the present invention, transmit the encrypted data to the terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in the database, specifically including:

[0097] Obtain the encrypted data, and analyze the encryption level according to the encrypted data;

[0098] Establish an encryption key according to the encryption level, and generate an access key of the corresponding level according to the encryption key;

[0099] Analyze the cooperation degree between the encryption key and the access key;

[0100] Determine whether the matching degree meets the set matching degree threshold;

[0101] If the set matching degree requirement is met, store the encrypted data and the corresponding access key in the database;

[0102] If the set matching degree threshold is not met, regenerate the access key.

[0103] It should be noted that by analyzing the matching degree between the encryption level and the access key, it is ensured that the access key can quickly access and extract customer data, improving the access efficiency of customer data.

[0104] In a second aspect, an embodiment of the present application provides an intelligent tag processing system based on customer management technology. The system includes: a memory and a processor. The memory includes a program of an intelligent tag processing method based on customer management technology. When the program of the intelligent tag processing method based on customer management technology is executed by the processor, the following steps are implemented:

[0105] Obtain customer data, preprocess the customer data to obtain processed data;

[0106] Analyze and classify the processed data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types;

[0107] Set a tag system, match the customer types according to the tag system, and establish customer tags;

[0108] Obtain customer demand information, set a customer security level based on the customer demand information, and encrypt the customer tags based on the customer security level to obtain encrypted data;

[0109] Transmit the encrypted data to the terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in the database.

[0110] It should be noted that by analyzing customer data and classifying customer data, different customer tags are established for different categories of customer data, improving the management security of customer data.

[0111] According to an embodiment of the present invention, obtaining customer data, preprocessing the customer data to obtain processed data specifically includes:

[0112] Obtain customer data, extract features from the customer data to obtain customer feature data;

[0113] Perform logistic regression, decision tree, and clustering analysis on the customer feature data to obtain optimized feature data;

[0114] Determine whether the optimized feature data is within the set feature interval;

[0115] If it is within the set feature interval, generate processing data;

[0116] If it is not within the set feature interval, generate correction information and adjust the parameters of logistic regression, decision tree, and clustering analysis based on the correction information.

[0117] It should be noted that by performing feature analysis and processing on customer data and analyzing whether the feature data is within the set feature interval, the analysis parameters are dynamically adjusted to improve the accuracy of data analysis.

[0118] According to the embodiments of the present invention, analyze and classify the processing data based on big data to obtain a classification result, and classify customers according to the classification result to obtain customer types, specifically including:

[0119] Obtain the processing data, analyze the processing data based on big data, and classify the processing data into multiple categories of processing data;

[0120] Analyze the classification accuracy of multiple categories of processing data based on classification rules;

[0121] Adjust the classification of the processing data based on the classification accuracy to obtain a classification result;

[0122] Obtain customer ID information, analyze the customer ID information based on the classification result, and classify the customers to obtain customer types.

[0123] It should be noted that by analyzing the classification accuracy of the processing data and matching it with the customer ID information, the customer types can be accurately classified.

[0124] According to the embodiments of the present invention, set a label system, match the customer types according to the label system, and establish customer labels, specifically including:

[0125] Set a label system based on big data, match the customer types according to the label system, and obtain a matching degree;

[0126] Determine whether the matching degree is greater than or equal to the set matching degree threshold;

[0127] If it is greater than or equal to the set matching degree threshold, generate customer labels;

[0128] If it is less than the set matching degree threshold, adjust the customer labels according to the label system.

[0129] It should be noted that by establishing customer tags for different types of customers through the tag system, the matching degree between customer tags and customer types is ensured, and the accuracy of customer tags is improved.

[0130] According to an embodiment of the present invention, obtaining customer demand information, setting a customer security level based on the customer demand information, and encrypting the customer tags based on the customer security level to obtain encrypted data, specifically including:

[0131] Obtaining customer demand information, analyzing the customer security requirements according to the customer demand information to obtain customer security requirement information;

[0132] Setting a corresponding customer security level based on the customer security requirement information;

[0133] Establishing an encryption level based on the customer security level, and setting an encryption key according to the encryption level;

[0134] Encrypting the customer data according to the encryption key to obtain encrypted data.

[0135] It should be noted that by analyzing the customer security requirements, different encryption levels are established, so as to encrypt the customer data at different levels and improve the data security.

[0136] According to an embodiment of the present invention, transmitting the encrypted data to the terminal in real time, generating a corresponding access key, and storing the encrypted data and the corresponding access key in the database, specifically including:

[0137] Obtaining the encrypted data, and analyzing the encryption level according to the encrypted data;

[0138] Establishing an encryption key according to the encryption level, and generating an access key of the corresponding level according to the encryption key;

[0139] Analyzing the cooperation degree between the encryption key and the access key;

[0140] Judging whether the cooperation degree meets the set cooperation degree threshold;

[0141] If the set cooperation degree requirement is met, storing the encrypted data and the corresponding access key in the database;

[0142] If the set cooperation degree threshold is not met, regenerating the access key.

[0143] It should be noted that by analyzing the cooperation degree between the encryption level and the access key, it is ensured that the access key can quickly access and extract the customer data, and the access efficiency of the customer data is improved.

[0144] The third aspect of the present invention provides a computer-readable storage medium, which includes an intelligent label processing method program based on customer management technology. When the intelligent label processing method program based on customer management technology is executed by a processor, the steps of the intelligent label processing method based on customer management technology as described in any one of the above are implemented.

[0145] An intelligent label processing method, system and medium based on customer management technology disclosed by the present invention obtain customer data, preprocess the customer data to obtain processed data, analyze and classify the processed data based on big data to obtain a classification result, classify customers according to the classification result to obtain customer types, set a label system, match the customer types according to the label system to establish customer labels, obtain customer demand information, set a customer security level based on the customer demand information, encrypt the customer labels based on the customer security level to obtain encrypted data, transmit the encrypted data to a terminal in real time, generate a corresponding access key, and store the encrypted data and the corresponding access key in a database. By analyzing customer data and performing customer type classification processing, different customer labels are established for different types of customers according to the label system, and a security level is established and encrypted for customers with different demands, thereby improving the security of customer data.

[0146] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the couplings between the various components shown or discussed, or direct couplings, or communication connections, can be through some interfaces, and the indirect couplings or communication connections of devices or units can be electrical, mechanical or other forms.

[0147] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0148] In addition, each functional unit in the embodiments of the present invention can be all integrated in one processing unit, or each unit can be separately used as one unit, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0149] Those of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments. The foregoing storage medium includes various media that can store program codes, such as removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0150] Alternatively, if the above integrated units of the present invention are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The foregoing storage medium includes various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. An intelligent label processing method based on customer management technology, characterized in that: include: Acquire customer data, perform feature extraction on the customer data, and obtain customer feature data; Perform logistic regression, decision tree and cluster analysis on customer feature data to obtain optimized feature data; Determining whether the optimized feature data is within a set feature interval; If it is within the set characteristic interval, the processing data is generated; If it is not in the set feature interval, correction information is generated, and the logistic regression, decision tree and cluster analysis parameters are adjusted based on the correction information; Acquire processing data, analyze the processing data based on big data, classify the processing data into categories, and obtain processing data of multiple categories; Analyze the classification accuracy of processed data of multiple categories based on classification rules; Adjust the classification of the processed data based on the classification accuracy to obtain a classification result; Obtain customer ID information, analyze the customer ID information based on the classification results, classify the customers, and obtain customer types; Set up a label system based on big data, match customer types according to the label system, and obtain the matching degree; Determining whether the matching degree is greater than or equal to a set matching degree threshold; If it is greater than or equal to the set matching threshold, a customer tag is generated; If it is less than the set matching threshold, the customer label is adjusted according to the label system; Obtain customer demand information, analyze customer security requirements based on the customer demand information, and obtain customer security requirement information; Set the corresponding customer security level based on the customer security requirement information; Establish encryption levels based on customer security levels and set encryption keys according to encryption levels; Encrypting the customer data according to the encryption key to obtain encrypted data; Obtaining encrypted data, and analyzing the encryption level based on the encrypted data; Establish an encryption key according to the encryption level, and generate an access key of the corresponding level according to the encryption key; Analyze the compatibility between encryption keys and access keys; Determining whether the degree of cooperation meets a set degree of cooperation threshold; If the set cooperation requirements are met, the encrypted data and the corresponding access key are stored in the database; If the set compliance threshold is not met, the access key is regenerated.

2. An intelligent label processing system based on customer management technology, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program of an intelligent label processing method based on customer management technology, and when the program of the intelligent label processing method based on customer management technology is executed by the processor, the following steps are implemented: Acquire customer data, perform feature extraction on the customer data, and obtain customer feature data; Perform logistic regression, decision tree and cluster analysis on customer feature data to obtain optimized feature data; Determining whether the optimized feature data is within a set feature interval; If it is within the set characteristic interval, the processing data is generated; If it is not in the set feature interval, correction information is generated, and the logistic regression, decision tree and cluster analysis parameters are adjusted based on the correction information; Acquire processing data, analyze the processing data based on big data, classify the processing data into categories, and obtain processing data of multiple categories; Analyze the classification accuracy of processed data of multiple categories based on classification rules; Adjust the classification of the processed data based on the classification accuracy to obtain a classification result; Obtain customer ID information, analyze the customer ID information based on the classification results, classify the customers, and obtain customer types; Set up a label system based on big data, match customer types according to the label system, and obtain the matching degree; Determining whether the matching degree is greater than or equal to a set matching degree threshold; If it is greater than or equal to the set matching threshold, a customer tag is generated; If it is less than the set matching threshold, the customer label is adjusted according to the label system; Obtain customer demand information, analyze customer security requirements based on the customer demand information, and obtain customer security requirement information; Set the corresponding customer security level based on the customer security requirement information; Establish encryption levels based on customer security levels and set encryption keys according to encryption levels; Encrypting the customer data according to the encryption key to obtain encrypted data; Obtaining encrypted data, and analyzing the encryption level based on the encrypted data; Establish an encryption key according to the encryption level, and generate an access key of the corresponding level according to the encryption key; Analyze the compatibility between encryption keys and access keys; Determining whether the degree of cooperation meets a set degree of cooperation threshold; If the set cooperation requirements are met, the encrypted data and the corresponding access key are stored in the database; If the set compliance threshold is not met, the access key is regenerated.

3. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes an intelligent label processing method program based on customer management technology. When the intelligent label processing method program based on customer management technology is executed by a processor, the steps of the intelligent label processing method based on customer management technology as described in claim 1 are implemented.

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