A customer satisfaction visual analysis and decision support system

Abstract

The application relates to the field of data processing and discloses a customer satisfaction visual analysis and decision support system, which comprises a data access and verification module, a main data correlation module, an index calculation module, a threshold grading module, a decision output module, a visual interaction module, a permission security module and a data storage module. The data access and verification module receives customer satisfaction survey data and performs verification according to a unique dealer code rule and a contact or questionnaire code hierarchy consistency rule, writes the verified data into an original data area and generates import records. The index calculation module forms an index result set and generates an unsatisfied mark, the threshold grading module generates an interval grading result set, and the decision output module outputs an organization hierarchy ranking result and a to-be-handled list including a sample execution progress list, a follow-up handling list and an un-repaired unsatisfied object list.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically to a customer satisfaction visualization analysis and decision support system. Background Technology

[0002] In service systems such as automobiles, home appliances, and retail chains, where dealers or directly operated outlets are the primary touchpoints, customer satisfaction surveys typically cover multiple touchpoints, including pre-sales consultation, delivery experience, maintenance and repair, and complaint handling. These surveys require horizontal and vertical comparisons by brand, time granularity, and organizational levels such as national, regional, group, and dealer levels for performance evaluation, resource allocation, and closed-loop management of improvements. With increased survey frequency and expanded channels, satisfaction data exhibits characteristics of multiple sources, batches, and interpretations, placing higher demands on the unified governance of data platforms.

[0003] Existing solutions typically use table import or API extraction to load questionnaire or touchpoint data into databases or data warehouses, and then configure indicator definitions, threshold levels, and visualization dashboards in business intelligence tools. Organizational hierarchy is usually maintained by the master data table, and dealer codes and hierarchical relationships are aggregated through scripts or view associations. Access control is generally based on role-based function authorization, and data visibility is limited by region or dealer scope. Some systems also output ranking reports and follow-up lists to promote rectification.

[0004] Because the survey data lacks unified verification and traceability records for the uniqueness of dealer codes, consistency of touchpoint or questionnaire code levels, merging of time granularity, and mapping of master data levels during the import phase, it is easy to cause matching deviations in organizational levels and time calibers of data from the same or different batches. This leads to inconsistencies in indicator calculations, grading results, rankings, and disposal lists across different reports, which are difficult to reproduce reliably and affect the reliable execution of the management's problem identification and disposal loop. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a customer satisfaction visualization analysis and decision support system. This system solves the technical problems in existing technologies, such as the difficulty in unifying the import of survey data with organizational levels and time granularity, which leads to inconsistencies in indicator calculation, threshold classification, ranking results, and pending action lists across different reports, and makes it difficult to reliably trace and reproduce the data.

[0006] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0007] A customer satisfaction visualization analysis and decision support system includes:

[0008] The module includes a data access and verification module, a master data association module, an indicator calculation module, a threshold classification module, a decision output module, a visualization interaction module, a permission security module, and a data storage module.

[0009] The data access and verification module receives customer satisfaction survey data and verifies the survey data according to preset rules. The preset rules include dealer code uniqueness rules and touchpoint or questionnaire code level consistency rules. Survey data that passes verification is written into the original data area and an import record is generated. The import record includes the import time and operator identifier. Survey data that fails verification forms a verification result with error reason identifier and is not written into the original data area.

[0010] The master data association module stores the dealer master data and its organizational hierarchy, and associates the survey data in the original data area with the dealer master data. The organizational hierarchy includes national, regional, group and dealer levels to generate an analytical data area that can be aggregated according to the organizational hierarchy.

[0011] The indicator calculation module calculates the satisfaction index based on the analysis data area and forms an indicator result set, and generates an unsatisfactory label for the sample according to the satisfaction judgment rules.

[0012] The threshold grading module stores a threshold dictionary and matches the indicator result set with the threshold dictionary to generate an interval grading result set for the corresponding indicator.

[0013] The decision output module outputs ranking results corresponding to the organizational hierarchy and a list of items to be handled based on the interval hierarchical result set. The list of items to be handled includes a sample execution progress list, a follow-up handling list, and a list of unresolved and unsatisfactory objects.

[0014] The visualization interaction module presents the indicator result set, interval classification result set, ranking results and pending list as chart components, and refreshes the chart components in response to the filtering conditions. The filtering conditions include brand, time granularity identifier, region, group and distributor, and support drill-down query and component linkage according to organizational hierarchy.

[0015] The permission security module performs identity authentication and authorization control on access requests, and implements function permission, data permission and field permission control on data access corresponding to the chart components;

[0016] The data storage module is used to store the raw data area, the analysis data area, the indicator result set, the interval hierarchical result set, the import records, and the output results of the decision output module.

[0017] Preferably, the data access and verification module includes a parsing unit, a uniqueness verification unit, a hierarchical consistency verification unit, an error identifier generation unit, an import control unit, and a record generation unit;

[0018] The parsing unit reads customer satisfaction survey data from the import medium and generates a dataset to be verified. The dataset to be verified includes a dealer code field, a touchpoint code field or a questionnaire code field, a brand identifier field, and a survey time field.

[0019] The uniqueness verification unit performs an intra-batch uniqueness verification on the dealer code field of the dataset to be verified, and performs an existence verification on the dealer code field and the dealer master data stored in the master data association module to obtain the uniqueness verification result.

[0020] The hierarchical consistency verification unit performs parent-child hierarchical consistency verification on the touch point coding field or questionnaire coding field according to the preset hierarchical mapping relationship, and obtains the hierarchical consistency verification result.

[0021] When the uniqueness verification result or the hierarchical consistency verification result fails, the error identifier generation unit writes an error reason identifier into the corresponding failed data row. The error reason identifier includes an error type identifier and an error field identifier, and generates a verification result with the error reason identifier.

[0022] The import control unit writes the dataset to be verified into the original data area when both the uniqueness verification result and the hierarchical consistency verification result are passed; if either verification result fails, it prevents the dataset to be verified from being written into the original data area.

[0023] The record generation unit generates an import record after the dataset to be verified is written into the original data area. The import record includes the import batch identifier, import time, operator identifier, number of imported data entries, number of verification successful entries, and number of verification failed entries.

[0024] Preferably, the master data association module includes a master data maintenance unit, a hierarchical relationship maintenance unit, an association key generation unit, an association processing unit, and an analysis data generation unit;

[0025] The master data maintenance unit stores dealer master data, which includes dealer code, group identifier, region identifier, and dealer status identifier.

[0026] The hierarchical relationship maintenance unit stores the organizational hierarchy, which is stored in a hierarchical table. The hierarchical table includes national nodes, regional nodes, group nodes, and distributor nodes, as well as the identifiers of the parent nodes between nodes.

[0027] The association key generation unit generates a primary key for association based on the dealer master data. The primary key includes the dealer code and the hierarchical path identifier corresponding to the dealer code. The hierarchical path identifier is generated by concatenating the national node identifier, regional node identifier, group node identifier and dealer node identifier in a preset order.

[0028] The association processing unit uses the dealer code field of the survey data in the original data area and the dealer code in the primary key as association conditions to associate the survey data with the matching dealer master data, and writes the hierarchical path identifier for the survey data after the association is completed.

[0029] The analysis data generation unit stores the survey data with hierarchical path identifiers into the analysis data area. The survey data in the analysis data area includes brand identifier fields, survey time fields, sample completion status identifiers, follow-up status identifiers, and repair status identifiers. It also performs aggregation preparation processing according to the hierarchical path identifiers so that the analysis data area can support aggregation queries by national, regional, group, and distributor levels.

[0030] Preferably, the indicator calculation module includes an indicator definition table, a calculation unit, and a marking unit;

[0031] The indicator definition table stores the indicator identifier, data field set, aggregation method, weight parameters, and calculation granularity of the satisfaction indicator. The calculation granularity includes the organizational level corresponding to the time granularity identifier and the hierarchical path identifier.

[0032] The computing unit reads the survey data with hierarchical path identifiers written in the analysis data area, uses the time granularity identifier and hierarchical path identifier as grouping keys, performs aggregation on the data field set to obtain the original value of the indicator, and performs weighted synthesis on the original value of the indicator according to the weight parameter to obtain the indicator value. The indicator result set records the indicator identifier, indicator value, time granularity identifier, hierarchical path identifier and brand identifier.

[0033] The marking unit reads the satisfaction judgment rule table, which stores the rating scale identifier, threshold parameter, and the marking type identifier corresponding to the threshold parameter.

[0034] The labeling unit calculates a sample satisfaction score for each survey sample and compares the sample satisfaction score with a threshold parameter. When the sample satisfaction score is less than the threshold parameter, a dissatisfaction label is written for the survey sample. The dissatisfaction label includes a label type identifier and a sample identifier.

[0035] Preferably, the threshold grading module includes a threshold dictionary table, a threshold item table, a matching unit, and a grading generation unit;

[0036] The threshold dictionary table stores threshold dictionary identifiers, indicator identifiers, and applicable time granularity identifiers.

[0037] The threshold item table stores multiple threshold interval items associated with the threshold dictionary identifier. Each threshold interval item includes a lower limit value, an upper limit value, an interval inclusion relationship identifier, and a hierarchical identifier. The interval inclusion relationship identifier is used to indicate the inclusion method of the interval boundary. The inclusion method of the interval boundary includes left-closed and right-open, left-open and right-closed, double-closed, and double-open.

[0038] The matching unit determines the threshold dictionary identifier that matches the indicator result set based on the indicator identifier and time granularity identifier in the indicator result set.

[0039] The hierarchical generation unit reads the corresponding indicator value for each indicator result in the indicator result set, determines the threshold interval item that matches the indicator value in the threshold item table according to the interval inclusion relationship identifier, and writes the hierarchical identifier and the grouping key of the indicator result into the interval hierarchical result set; the grouping key includes time granularity identifier and hierarchical path identifier.

[0040] Preferably, the decision output module includes a ranking generation unit, a list generation unit, and an association annotation unit;

[0041] The ranking generation unit generates ranking results based on the interval hierarchical result set according to the organizational hierarchy. The ranking results include regional ranking results and group ranking results. The ranking generation unit determines the organizational hierarchy positioning information of the ranking object by hierarchical path identifier, determines the hierarchical category of the ranking object by hierarchical identifier, and sorts the ranking objects by indicator value or the serial number value corresponding to the indicator value obtained by mapping the hierarchical identifier, generating a ranking result set including the ranking object identifier, hierarchical identifier, and ranking value.

[0042] The list generation unit generates a pending list based on the interval-level result set and the analysis data area. The pending list includes a sample execution progress list, a follow-up handling list, and a list of unrepaired unsatisfactory objects. The sample execution progress list is determined by the interval-level result corresponding to the sample completion rate indicator. The sample completion rate indicator is calculated by the number of samples marked as completed in the analysis data area and the total number of survey samples with corresponding time granularity and hierarchical path indicators in the analysis data area. The follow-up handling list is determined by the interval-level result corresponding to the follow-up completion rate indicator. The follow-up completion rate indicator is calculated by the number of samples marked as unsatisfactory and whose follow-up status is marked as completed and the total number of samples marked as unsatisfactory. The list of unrepaired unsatisfactory objects is determined by the interval-level result corresponding to the unrepair rate indicator. The unrepair rate indicator is calculated by the number of objects marked as unsatisfactory and whose repair status is marked as unrepaired and the total number of objects marked as unsatisfactory.

[0043] The association annotation unit writes association annotation information for each record in the ranking results and the list of records to be disposed of. The association annotation information includes indicator identifier, threshold dictionary identifier, classification identifier, time granularity identifier, and hierarchical path identifier, so as to establish a one-to-one correspondence between the ranking results and the list of records to be disposed of and the corresponding indicator results and interval classification results.

[0044] Preferably, the visualization interaction module includes a component configuration unit, a filtering processing unit, and a rendering unit;

[0045] The component configuration unit stores a chart component configuration table. The chart component configuration table records the component identifier, data source type identifier, data source reference identifier, dimension field set, metric field set, and display type identifier for each chart component. The data source type identifier is used to indicate that the data source of the chart component is an indicator result set, interval hierarchical result set, ranking result, or pending list. The data source reference identifier is used to indicate the data table, view, or query identifier corresponding to the chart component.

[0046] The filtering processing unit receives filtering conditions and generates a set of query conditions, which includes brand conditions, time granularity identifier conditions, regional conditions, group conditions, and distributor conditions. The filtering processing unit writes the set of query conditions into the filtering context and generates query requests for each chart component based on the data source reference identifier in the chart component configuration table.

[0047] The rendering unit receives the query request, obtains the query result of the corresponding data source, and renders and displays the query result according to the display type identifier of the chart component configuration table.

[0048] Preferably, the visualization interaction module further includes a drill-down processing unit and a linkage processing unit;

[0049] The drill processing unit receives a drill instruction, which includes the current level identifier, the target level identifier, and the selected node identifier. The drill processing unit maps the selected node identifier to a level path identifier according to the organizational hierarchy, and updates the regional conditions, group conditions, or distributor conditions corresponding to the target level identifier in the filtering context, so that the rendering unit generates a query request based on the updated filtering context.

[0050] The linkage processing unit receives the selection event of the source chart component and generates a selection context, which includes the source component identifier, the selected dimension field identifier, the selected dimension value, and the time granularity identifier value.

[0051] The component configuration unit also stores a linkage relationship configuration table, which records the mapping relationship between the source component identifier and the target component identifier set;

[0052] The linkage processing unit determines the target component identifier set associated with the source component identifier based on the linkage relationship configuration table, and writes the selected dimension value into the filtering context corresponding to the selected dimension field identifier, so that the rendering unit generates a query request for the chart component corresponding to the target component identifier set.

[0053] Preferably, the permission security module includes an authentication unit, a role permission unit, a data permission unit, a field permission unit, and a permission verification unit;

[0054] The authentication unit receives a user login request and verifies the user's identity information, which includes a user identifier and credential information. After successful verification, it generates a session token associated with the user identifier and returns the session token to the client that initiated the login request.

[0055] The role permission unit stores the mapping relationship between users and roles, as well as the mapping relationship between roles and function permissions. Function permissions are represented by a set of function identifiers, which includes data import function identifiers, master data maintenance function identifiers, indicator configuration function identifiers, threshold configuration function identifiers, dashboard configuration function identifiers, and data viewing function identifiers.

[0056] The data access unit stores the mapping relationship between users or roles and data access scopes. The data access scope is represented by a set of hierarchical path identifiers and is used to limit the regions, groups, and distributors that users or roles can access.

[0057] The field permission unit stores the mapping relationship between users or roles and field visibility rules. Field visibility rules are used to indicate the display method of sensitive fields, including plain text display, de-identified display, and invisible display.

[0058] When the permission verification unit receives an access request, it parses the session token to obtain the user identifier and determines the corresponding function permissions, data access scope, and field visibility rules based on the user identifier. When the access request is a chart component data request, the permission verification unit determines the function identifier, hierarchical path identifier, and field set involved in the access request according to the chart component configuration table, and performs function permission verification on the function identifier, data permission verification on the hierarchical path identifier, and field permission verification on the field set. If the verification passes, the access request is allowed; if the verification fails, the access request is rejected and a rejection identifier is returned.

[0059] Preferably, the data storage module includes a raw data storage unit, an analytical data storage unit, an indicator result storage unit, a hierarchical result storage unit, an import record storage unit, and a decision result storage unit;

[0060] The original data storage unit stores the survey data written by the data access and verification module, and uses the import batch identifier and sample identifier as index fields.

[0061] The analysis data storage unit stores the survey data after the hierarchical path identifier is written by the master data association module, and uses the hierarchical path identifier and time granularity identifier as partition fields.

[0062] The indicator result storage unit stores the indicator result set generated by the indicator calculation module, and uses the indicator identifier, hierarchical path identifier and time granularity identifier as a joint index.

[0063] The hierarchical result storage unit stores the interval hierarchical result set generated by the threshold hierarchical module, and uses the threshold dictionary identifier, indicator identifier, hierarchical path identifier and time granularity identifier as a joint index.

[0064] The import record storage unit stores the import records generated by the data import and verification module, and uses the import batch identifier as the index field.

[0065] The decision result storage unit stores the ranking results and the list of items to be disposed of generated by the decision output module, and records the indicator identifier, threshold dictionary identifier, hierarchical identifier, hierarchical path identifier and time granularity identifier in the ranking results and the list of items to be disposed of.

[0066] In summary, the present invention has the following main beneficial effects:

[0067] By setting up a data access and verification module during the data access phase, and performing uniqueness verification of dealer codes and consistency verification of contact code or questionnaire code hierarchy on customer satisfaction survey data, and generating import batch identifiers and import records for verification-passing data and writing them into the original data area, and outputting verification results with error reason identifiers for verification-failed data, the aim is to achieve pre-control of survey data quality and traceability of the import process. This avoids statistical caliber drift and subsequent analysis distortion caused by duplicate codes, mismatched hierarchy, and unclear batch sources, thereby providing a stable and consistent data input foundation for indicator calculation, classification, and decision output.

[0068] The master data association module maintains the distributor master data and its organizational hierarchy at the national, regional, group, and distributor levels. After associating the survey data with the distributor master data, it writes the hierarchical path identifier, time key, and time granularity identifier, achieving the goal of structured data storage under a unified organizational hierarchy and time caliber. This enables the indicator calculation module to perform grouped calculations according to time granularity and hierarchical path identifiers and form indicator result sets. The threshold grading module can perform interval matching of indicator values ​​based on the threshold dictionary to generate interval grading result sets, thereby realizing multi-dimensional aggregation analysis and same-caliber comparison across regions, groups, and distributors, reducing the risk of incomparability caused by inconsistent organizational calibers and time granularities.

[0069] The decision output module combines the interval-level result set with the organizational hierarchy to output ranking results. Based on the analysis data area and dissatisfaction markers, it generates a sample execution progress list, a follow-up handling list, and a list of unresolved unsatisfactory objects. Simultaneously, the visualization interaction module uses the chart component configuration table to graphically present the indicator result set, interval-level result set, ranking results, and pending handling list, supporting filtering, drill-down, and component linkage. This achieves the goal of transforming analysis results into actionable handling objects and a visual decision-making interface, enabling managers at different levels to locate abnormal levels and pending objects within a unified dashboard and complete data drill-down and linked queries. This improves the efficiency of problem location and the consistency of the handling loop execution. The permission security module controls functional permissions, data permissions, and field permissions to ensure clear access boundaries for different roles. Attached Figure Description

[0070] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0071] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0072] Example 1

[0073] refer to Figure 1 A customer satisfaction visualization analysis and decision support system, comprising:

[0074] The module includes a data access and verification module, a master data association module, an indicator calculation module, a threshold classification module, a decision output module, a visualization interaction module, a permission security module, and a data storage module.

[0075] The data access and verification module receives customer satisfaction survey data and verifies the survey data according to preset rules. The preset rules include dealer code uniqueness rules and touchpoint or questionnaire code level consistency rules. Survey data that passes verification is written into the original data area and an import record is generated. The import record includes the import time and operator identifier. Survey data that fails verification forms a verification result with error reason identifier and is not written into the original data area.

[0076] The master data association module stores the dealer master data and its organizational hierarchy, and associates the survey data in the original data area with the dealer master data. The organizational hierarchy includes national, regional, group and dealer levels to generate an analytical data area that can be aggregated according to the organizational hierarchy.

[0077] The indicator calculation module calculates the satisfaction index based on the analysis data area and forms an indicator result set, and generates an unsatisfactory label for the sample according to the satisfaction judgment rules.

[0078] The threshold grading module stores a threshold dictionary and matches the indicator result set with the threshold dictionary to generate an interval grading result set for the corresponding indicator.

[0079] The decision output module outputs ranking results corresponding to the organizational hierarchy and a list of items to be handled based on the interval hierarchical result set. The list of items to be handled includes a sample execution progress list, a follow-up handling list, and a list of unresolved and unsatisfactory objects.

[0080] The visualization interaction module presents the indicator result set, interval classification result set, ranking results and pending list as chart components, and refreshes the chart components in response to the filtering conditions. The filtering conditions include brand, time granularity identifier, region, group and distributor, and support drill-down query and component linkage according to organizational hierarchy.

[0081] The permission security module performs identity authentication and authorization control on access requests, and implements function permission, data permission and field permission control on data access corresponding to the chart components;

[0082] The data storage module is used to store the raw data area, the analysis data area, the indicator result set, the interval hierarchical result set, the import records, and the output results of the decision output module.

[0083] The data storage module is used to store the raw data area, the analysis data area, the indicator result set, the interval classification result set, the imported records, the ranking results and the list of pending actions, and provides read and write interfaces for each module.

[0084] During operation, the system uses the batch identifier, sample identifier, distributor code, brand identifier, and survey time field as the primary key fields, the hierarchical path identifier, time granularity identifier, and time key as the core grouping fields, and the indicator identifier, threshold dictionary identifier, and classification identifier as the core decision fields, forming a processing chain from data access, master data association, indicator calculation, classification, ranking and list output, and visualization presentation.

[0085] The data storage module includes raw data storage units, analytical data storage units, indicator result storage units, hierarchical result storage units, imported record storage units, and decision result storage units.

[0086] The raw data area is used to store the survey data after verification. It includes at least the imported batch identifier, sample identifier, distributor code field, touch point code field or questionnaire code field, brand identifier field, survey time field, and a set of rating fields. The imported batch identifier and sample identifier are used as index fields to enable traceability by batch and location by sample.

[0087] The analysis data area is used to store survey data written with hierarchical path identifiers and time keys after being associated with the master data. It includes at least the following fields: import batch identifier, sample identifier, distributor code field, brand identifier field, time granularity identifier, time key, hierarchical path identifier, hierarchical key field for aggregation, set of rating fields, dissatisfaction mark field, sample completion status identifier field, follow-up status identifier field, and repair status identifier field. The hierarchical path identifier and time granularity are used as partitioning fields to support aggregation queries by organization and time.

[0088] The indicator result set includes at least the indicator identifier, brand identifier, time granularity identifier, time key, hierarchical path identifier, indicator value and sample number, and uses the indicator identifier, hierarchical path identifier and time granularity as a joint index to support indicator query, ranking and hierarchical association.

[0089] The interval-level result set includes at least the threshold dictionary identifier, indicator identifier, brand identifier, time granularity identifier, time key, hierarchical path identifier, level identifier, and optional indicator value fields. It uses the threshold dictionary identifier, indicator identifier, hierarchical path identifier, and time granularity as a joint index to support the generation of hierarchical dashboards, rankings, and lists.

[0090] Imported records must include at least the import batch identifier, import time, operator identifier, number of imported data rows, number of rows that passed verification, and number of rows that failed verification, with the import batch identifier as the index field.

[0091] The ranking results should include at least the ranking object identifier, organizational level identifier, indicator identifier, threshold dictionary identifier, classification identifier, ranking value, brand identifier, time granularity identifier, time key, and hierarchical path identifier. The pending list should include at least the list type identifier, object identifier or sample identifier, indicator identifier, threshold dictionary identifier, classification identifier, ratio value, numerator field, denominator field, brand identifier, time granularity identifier, time key, and hierarchical path identifier, and establish a correspondence between the above decision domain fields and the indicator result set and interval classification result set.

[0092] The data access and verification module includes a parsing unit, a uniqueness verification unit, a hierarchical consistency verification unit, an error identifier generation unit, an import control unit, and a record generation unit.

[0093] The parsing unit reads customer satisfaction survey data from the import medium and generates a dataset to be verified. This dataset includes at least a dealer code field, a touchpoint code field or questionnaire code field, a brand identifier field, a survey time field, and a set of rating fields. The uniqueness verification unit performs an intra-batch uniqueness check on the dealer code field of the dataset and performs an existence check on the dealer master data stored in the master data association module, obtaining a uniqueness verification result. The hierarchical consistency verification unit performs a parent-child hierarchical consistency check on the touchpoint code field or questionnaire code field according to a preset hierarchical mapping relationship, obtaining a hierarchical consistency verification result. When either the uniqueness verification result or the hierarchical consistency verification result fails, the error identifier generation unit writes an error reason identifier to the corresponding failed data row and generates a verification result with the error reason identifier. The import control unit writes the dataset to be verified to the original data area when both the uniqueness verification result and the hierarchical consistency verification result pass; if either verification result fails, it prevents the dataset from being written to the original data area. The record generation unit generates import records after the dataset to be verified is written to the original data area and writes them to the import record storage unit.

[0094] To ensure the traceability of imported batches, the parsing unit generates an import batch identifier and a sample identifier for each data entry during each import process, so that the original data area and the imported records correspond to each other through the import batch identifier.

[0095] The master data association module includes a master data maintenance unit, a hierarchical relationship maintenance unit, an association key generation unit, an association processing unit, and an analysis data generation unit.

[0096] The master data maintenance unit stores dealer master data, which includes at least the dealer code, group identifier, region identifier, and dealer status identifier. The hierarchical relationship maintenance unit stores organizational hierarchical relationships, which are stored in a hierarchical table. The hierarchical table includes at least national nodes, regional nodes, group nodes, and dealer nodes, as well as the identifiers of the parent nodes between them.

[0097] The association key generation unit generates hierarchical path identifiers based on organizational hierarchy. The hierarchical path identifiers are generated by the following formula:

[0098] ;

[0099] in, For hierarchical path identification, As a national node identifier, For regional node identification, For group node identification, For dealer node identification, This indicates that a unique identifier is generated by splicing the components in a preset order.

[0100] To satisfy aggregation queries at different levels, the data generation unit analyzes and generates hierarchical keys based on hierarchical path identifiers:

[0101] ;

[0102] in, For the first The level corresponding to the level key, Indicates to Extracted up to the first The prefix for hierarchy.

[0103] The data generation unit generates time keys from the survey time field according to time granularity and writes them into the analysis data area: ;in, For time keys, To obtain values ​​for the survey time field, For time granularity identification, This represents the key value obtained by merging time fields according to time granularity.

[0104] The association processing unit uses the dealer code field in the survey data in the original data area and the dealer code in the dealer master data as association conditions to associate the survey data with the dealer master data, and writes a hierarchical path identifier for the survey data after the association is completed. with hierarchical key The data generation unit writes the associated data into the analysis data area, ensuring that the analysis data area includes at least the import batch identifier, sample identifier, distributor code, brand identifier, time granularity identifier, time key, hierarchical path identifier, hierarchical key, scoring field set, and status fields required for subsequent lists.

[0105] When a dealer status identifier indicates that the dealer is unavailable, the associated processing unit can, according to the configuration, mark the sample as not participating in the statistics, so that it is not included in the scope of indicator calculation and list statistics.

[0106] The indicator calculation module includes an indicator definition table, calculation units, and tagging units. The indicator definition table stores the indicator identifier, data field set, aggregation method, weight parameters, and calculation granularity for the satisfaction indicator. The calculation granularity includes time granularity and organizational hierarchy granularity. The calculation unit reads the survey data from the analysis data area, uses time granularity, time key, and hierarchical path identifier as grouping keys, and performs aggregation and weighted synthesis according to the data field set defined in the indicator definition table to obtain the indicator value and write it to the indicator result set.

[0107] When the aggregation method is mean, the first... The mean of each item is calculated by the following formula:

[0108] ;

[0109] in, For the first The mean of each item in the current group. For the first The sample at the th The scoring for each item This represents the number of samples in the current group.

[0110] The weight parameters are normalized using the following formula:

[0111] ;

[0112] in, To normalize the weights, As the weight of the question item, This represents the number of items involved in the synthesis. The index value is synthesized using the following formula:

[0113] ;

[0114] in, This refers to the indicator value. When the number of samples in a certain group... When the value is 0, the calculation unit does not perform the above mean and composite calculations, and sets the indicator value corresponding to this group to the preset default value in the indicator result set. Simultaneously, it writes a record with a sample size of 0, so that subsequent grading, ranking, and visualization can determine that this group cannot be calculated based on the sample size during reading. The marking unit reads the satisfaction judgment rule table and calculates the sample satisfaction score for each survey sample. The sample satisfaction score is compared with the threshold parameter. Compare and write the unsatisfactory flag:

[0115] ;

[0116] in, If the judgment result is unsatisfactory, The sample satisfaction score, This is the threshold parameter.

[0117] A correspondence is established between the unsatisfactory markers and the sample identifiers, and they are stored in the analysis data area or an independent marker storage structure for subsequent follow-up handling lists and unrepaired unsatisfactory object lists.

[0118] The threshold grading module includes a threshold dictionary table, a threshold item table, a matching unit, and a grading generation unit. The threshold dictionary table stores threshold dictionary identifiers, indicator identifiers, and applicable time granularity identifiers. The threshold item table stores multiple threshold interval items associated with the threshold dictionary identifiers. Each threshold interval item contains at least the lower limit value, the upper limit value, the interval inclusion relationship identifier, and the grading identifier.

[0119] The matching unit determines the threshold dictionary identifier for matching based on the indicator identifier and time granularity identifier in the indicator result set. The hierarchical generation unit reads the indicator values ​​from the indicator result set. Based on the interval inclusion relationship identifier, the hit determination is performed on each threshold interval item, and the hierarchical identifier is determined by the following formula under the left-closed and right-open inclusion relationship:

[0120] ;

[0121] in, For hierarchical identification, For the first The hierarchical identifiers corresponding to each interval item The lower limit of the interval. This represents the upper limit of the interval.

[0122] When the interval containment relationship is left-open, right-closed, double-closed, or double-open, the hierarchical generation unit performs a hit determination according to the corresponding boundary inequality rules. To avoid ambiguity caused by multiple intervals hitting simultaneously, interval items under the same threshold dictionary identifier in the threshold item table are stored in a preset order. When multiple hits exist, the hierarchical generation unit selects the interval item with the earliest preset order as the hit interval. To avoid the uncertainty of no interval hits, if the index value... If no interval item is matched, the hierarchical generation unit will set the hierarchical identifier to the preset default hierarchical level and write it into the interval hierarchical result set so that subsequent ranking and display will not be interrupted due to null values.

[0123] When writing the interval-level result set, it should include at least the threshold dictionary identifier, indicator identifier, brand identifier, time granularity identifier, time key, hierarchical path identifier, and level identifier, and correspond to the indicator result set through the indicator identifier, time granularity identifier, time key, and hierarchical path identifier.

[0124] The decision output module includes a ranking generation unit, a list generation unit, and an association annotation unit.

[0125] The ranking generation unit generates ranking results based on the interval-level result set according to organizational hierarchy. The ranking objects are organizational entities such as regions or groups. The ranking generation unit determines the ranking object identifier using a hierarchical path identifier or hierarchical key, and determines the hierarchical category of the ranking object using a hierarchical identifier. The sorting value can be an indicator value or a sequence number value mapped from the hierarchical identifier. To avoid ambiguity in sorting with the same score, when multiple ranking objects have the same sorting value, the ranking generation unit disambiguates according to the preset sorting rules of the ranking object identifier. If the ranking object identifier still cannot disambiguate, it is sorted from high to low according to the number of samples corresponding to that ranking object. If the number of samples is also the same, it is output and written to the ranking result set according to the preset stable sorting rules.

[0126] When writing ranking results, at least the following should be included: ranking object identifier, organizational level identifier, indicator identifier, threshold dictionary identifier, level identifier, sort value, brand identifier, time granularity identifier, time key and hierarchical path identifier.

[0127] The list generation unit generates a list of items to be processed based on the interval-level result set and the analysis data area. The list of items to be processed includes a sample execution progress list, a follow-up processing list, and a list of unresolved and unsatisfactory items. Under the conditions of the same brand identifier, the same time granularity identifier, the same time key, and the same hierarchical path identifier, the list generation unit forms a numerator and a denominator, and writes the ratio calculation as an algorithm into the list record.

[0128] Calculation of the ratio of the three categories of the list:

[0129] enter: , , , , , Output: , , ;

[0130] ;

[0131] in, For sample completion rate, To complete the sample size, This represents the total number of samples.

[0132] ;

[0133] in, To track the completion rate, This represents the number of follow-up items that have been completed. The number of items should be followed up.

[0134] ;

[0135] in, The unrepaired rate This represents the number of unrepaired objects. This represents the total number of dissatisfied individuals.

[0136] To avoid the ratio becoming uncalculate due to a denominator of 0, the list generation unit checks each denominator before executing Algorithm 1: when... When =0, Set to the default value and write the count denominator field to 0 in the list record; when When =0, Set to the preset default value and write 0 to the denominator field of the count; when When =0, Set the value to the default value and write the count denominator field to 0 to ensure that the list records can be stored and displayed stably.

[0137] The sample execution progress list is written in the record. , , ;

[0138] The follow-up action list is written in the record. , , The list of unrepaired and unsatisfactory items is written into the record. , , .

[0139] The association annotation unit writes association annotation information to each record in the ranking results and the list of pending disposals. The association annotation information includes at least indicator identifier, threshold dictionary identifier, hierarchical identifier, time granularity identifier, time key and hierarchical path identifier, so that the ranking results and the list of pending disposals can establish a traceable correspondence with the indicator result set and the interval hierarchical result set.

[0140] The visual interaction module includes a component configuration unit, a filtering unit, a rendering unit, a drill-down unit, and a linkage unit.

[0141] The component configuration unit stores a chart component configuration table. This table records at least the component identifier, data source type identifier, data source reference identifier, dimension field set, metric field set, and display type identifier, enabling the chart component to retrieve data from indicator result sets, interval-level result sets, ranking results, or pending lists. The filtering unit receives filter conditions and generates a query condition set. This set includes at least brand conditions, time granularity conditions, regional conditions, group conditions, and distributor conditions, and writes the query condition set into the filtering context. The rendering unit generates a query request based on the filtering context and the chart component configuration table, retrieves the query results, renders and displays the chart component, and refreshes the display when filter conditions change.

[0142] The drill-down processing unit receives drill-down instructions and updates the organizational conditions in the filter context. The drill-down instructions must include at least the current level identifier, the target level identifier, and the selected node identifier. When the selected node identifier cannot be mapped to a level path identifier, the drill-down processing unit marks the drill-down instruction as invalid and keeps the filter context unchanged, ensuring the rendering unit outputs a stable result. The linkage processing unit receives the source chart component selection event and generates a selection context. Based on the linkage relationship configuration, it determines the target component identifier set and writes the selected dimension value into the filter context to trigger a refresh of the target chart component. When the target component identifier set is empty, the linkage processing unit does not update the filter context and ends the current linkage processing.

[0143] The access control security module includes an authentication unit, a role-based access control unit, a data access control unit, a field access control unit, and an access control verification unit. The authentication unit verifies login requests and generates a session token, which is returned to the client. The role-based access control unit stores the mapping relationships between users and roles, and between roles and sets of function identifiers. The data access control unit stores the mapping relationship between users or roles and sets of hierarchical path identifiers, and the field access control unit stores the mapping relationship between users or roles and field visibility rules. The access control verification unit parses the session token to obtain the user identifier and determines the corresponding function permissions, data access scope, and field visibility rules. When a data request for a chart component is received, the access control verification unit determines the set of fields and hierarchical path identifiers involved in the request based on the chart component configuration table, and performs function permission verification, data permission verification, and field permission verification on the access request. If successful, the request is allowed; otherwise, it is rejected and a rejection flag is returned.

[0144] In this embodiment, the system first parses the customer satisfaction survey data in the imported medium using the data access and verification module. Verification is performed based on the uniqueness rules of dealer codes and the hierarchical consistency rules of touchpoint codes or questionnaire codes. Data that passes verification is written to the original data area, generating an import record containing the import batch identifier, import time, and operator identifier. Data that fails verification outputs a verification result with an error reason identifier but is not written to the original data area. Subsequently, the master data association module reads the survey data from the original data area and associates it with the dealer master data. After association, it writes the hierarchical path identifier and time key to the survey data and then writes the data to the analysis data area, allowing aggregation and querying by time granularity and organizational hierarchy. Based on this, the indicator calculation module groups and calculates the survey data in the analysis data area according to the indicator definition table, using the time key and hierarchical path identifier, to obtain satisfaction indicators and write them to the indicator result set. Simultaneously, it marks samples as unsatisfied according to the satisfaction judgment rules for subsequent statistical processing. The threshold grading module matches the indicator values ​​in the indicator result set with the threshold dictionary and generates an interval grading result set. Subsequently, the decision output module generates ranking results based on the interval-level result set according to organizational hierarchy. It then combines the analysis data area and dissatisfaction markers to generate a sample execution progress list, a follow-up handling list, and a list of unresolved dissatisfaction objects. Furthermore, it adds associated annotation information corresponding to indicator identifiers, threshold dictionary identifiers, hierarchical identifiers, time keys, and hierarchical path identifiers to the ranking results and the list of objects to be handled. The visualization interaction module retrieves data from the indicator result set, interval-level result set, ranking results, and list of objects to be handled based on the chart component configuration table. It updates the filtering context and generates query requests when filtering conditions change, drill-down instructions are triggered, or component linkage events are activated, thus refreshing the chart component display. The access control module performs identity authentication and authorization control on user access requests and verifies function permissions, data permissions, and field permissions for chart component data requests. Requests are allowed when verification passes and rejected when verification fails, with a rejection flag returned. This enables controllable access and display for different organizational levels and roles within the same system.

[0145] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A customer satisfaction visualization analysis and decision support system, characterized in that, include: The module includes a data access and verification module, a master data association module, an indicator calculation module, a threshold classification module, a decision output module, a visualization interaction module, a permission security module, and a data storage module. The data access and verification module receives customer satisfaction survey data and verifies the survey data according to preset rules. The preset rules include dealer code uniqueness rules and touchpoint or questionnaire code level consistency rules. Survey data that passes verification is written into the original data area and an import record is generated. The import record includes the import time and operator identifier. Survey data that fails verification forms a verification result with error reason identifier and is not written into the original data area. The master data association module stores the dealer master data and its organizational hierarchy, and associates the survey data in the original data area with the dealer master data. The organizational hierarchy includes national, regional, group and dealer levels to generate an analytical data area that can be aggregated according to the organizational hierarchy. The master data association module includes a master data maintenance unit, a hierarchical relationship maintenance unit, an association key generation unit, an association processing unit, and an analysis data generation unit; The master data maintenance unit stores dealer master data, which includes dealer code, group identifier, region identifier, and dealer status identifier. The association processing unit uses the dealer code field of the survey data in the original data area and the dealer code in the primary key as association conditions to associate the survey data with the matching dealer master data, and writes the hierarchical path identifier for the survey data after the association is completed. The analysis data generation unit stores the survey data with hierarchical path identifiers into the analysis data area. The survey data in the analysis data area includes brand identifier field, survey time field, sample completion status identifier, follow-up status identifier, and repair status identifier. It also performs aggregation preparation processing according to the hierarchical path identifiers so that the analysis data area can support aggregation queries by national, regional, group, and distributor levels. The indicator calculation module calculates the satisfaction index based on the analysis data area and forms an indicator result set, and generates an unsatisfactory label for the sample according to the satisfaction judgment rules. The indicator calculation module includes an indicator definition table, a calculation unit, and a marking unit; The indicator definition table stores the indicator identifier, data field set, aggregation method, weight parameters, and calculation granularity of the satisfaction indicator. The calculation granularity includes the organizational level corresponding to the time granularity identifier and the hierarchical path identifier. The computing unit reads the survey data with hierarchical path identifiers written in the analysis data area, uses the time granularity identifier and hierarchical path identifier as grouping keys, performs aggregation on the data field set to obtain the original value of the indicator, and performs weighted synthesis on the original value of the indicator according to the weight parameter to obtain the indicator value. The indicator result set records the indicator identifier, indicator value, time granularity identifier, hierarchical path identifier and brand identifier. The threshold grading module stores a threshold dictionary and matches the indicator result set with the threshold dictionary to generate an interval grading result set for the corresponding indicator. The decision output module outputs ranking results corresponding to the organizational hierarchy and a list of items to be handled based on the interval hierarchical result set. The list of items to be handled includes a sample execution progress list, a follow-up handling list, and a list of unresolved and unsatisfactory objects. The decision output module includes a ranking generation unit, a list generation unit, and an association annotation unit; The ranking generation unit generates ranking results based on the interval hierarchical result set according to the organizational hierarchy. The ranking results include regional ranking results and group ranking results. The ranking generation unit determines the organizational hierarchy positioning information of the ranking object by hierarchical path identifier, determines the hierarchical category of the ranking object by hierarchical identifier, and sorts the ranking objects by indicator value or the serial number value corresponding to the indicator value obtained by mapping the hierarchical identifier, generating a ranking result set including the ranking object identifier, hierarchical identifier, and ranking value. The visualization interaction module presents the indicator result set, interval classification result set, ranking results and pending list as chart components, and refreshes the chart components in response to the filtering conditions. The filtering conditions include brand, time granularity identifier, region, group and distributor, and support drill-down query and component linkage according to organizational hierarchy. The permission security module performs identity authentication and authorization control on access requests, and implements function permission, data permission and field permission control on data access corresponding to the chart components; The permission security module includes an authentication unit, a role permission unit, a data permission unit, a field permission unit, and a permission verification unit. The authentication unit receives user login requests and verifies user identity information, which includes user identifier and credential information. After successful verification, a session token associated with the user's identifier is generated and returned to the client that initiated the login request. The role permission unit stores the mapping relationship between users and roles, as well as the mapping relationship between roles and function permissions. Function permissions are represented by a set of function identifiers, which includes data import function identifiers, master data maintenance function identifiers, indicator configuration function identifiers, threshold configuration function identifiers, dashboard configuration function identifiers, and data viewing function identifiers. The data access unit stores the mapping relationship between users or roles and data access scopes. The data access scope is represented by a set of hierarchical path identifiers and is used to limit the regions, groups, and distributors that users or roles can access. The field permission unit stores the mapping relationship between users or roles and field visibility rules. Field visibility rules are used to indicate the display method of sensitive fields, including plain text display, de-identified display, and invisible display. The data storage module is used to store the raw data area, the analysis data area, the indicator result set, the interval hierarchical result set, the import records, and the output results of the decision output module.

2. The customer satisfaction visualization analysis and decision support system according to claim 1, characterized in that, The data access and verification module includes a parsing unit, a uniqueness verification unit, a hierarchical consistency verification unit, an error identifier generation unit, an import control unit, and a record generation unit. The parsing unit reads customer satisfaction survey data from the import medium and generates a dataset to be verified. The dataset to be verified includes a dealer code field, a touchpoint code field or a questionnaire code field, a brand identifier field, and a survey time field. The uniqueness verification unit performs an intra-batch uniqueness verification on the dealer code field of the dataset to be verified, and performs an existence verification on the dealer code field and the dealer master data stored in the master data association module to obtain the uniqueness verification result. The hierarchical consistency verification unit performs parent-child hierarchical consistency verification on the touch point coding field or questionnaire coding field according to the preset hierarchical mapping relationship, and obtains the hierarchical consistency verification result. When the uniqueness verification result or the hierarchical consistency verification result fails, the error identifier generation unit writes an error reason identifier into the corresponding failed data row. The error reason identifier includes an error type identifier and an error field identifier, and generates a verification result with the error reason identifier. The import control unit writes the dataset to be verified into the original data area when both the uniqueness verification result and the hierarchical consistency verification result are passed; if either verification result fails, it prevents the dataset to be verified from being written into the original data area. The record generation unit generates an import record after the dataset to be verified is written into the original data area. The import record includes the import batch identifier, import time, operator identifier, number of imported data entries, number of verification successful entries, and number of verification failed entries.

3. The customer satisfaction visualization analysis and decision support system according to claim 2, characterized in that, The hierarchical relationship maintenance unit stores the organizational hierarchy, which is stored in a hierarchical table. The hierarchical table includes national nodes, regional nodes, group nodes, and distributor nodes, as well as the identifiers of the parent nodes between nodes. The association key generation unit generates a primary key for association based on the dealer master data. The primary key includes the dealer code and the hierarchical path identifier corresponding to the dealer code. The hierarchical path identifier is generated by concatenating the national node identifier, regional node identifier, group node identifier and dealer node identifier in a preset order.

4. The customer satisfaction visualization analysis and decision support system according to claim 3, characterized in that, The marking unit reads the satisfaction judgment rule table, which stores the rating scale identifier, threshold parameter, and the marking type identifier corresponding to the threshold parameter. The labeling unit calculates a sample satisfaction score for each survey sample and compares the sample satisfaction score with a threshold parameter. When the sample satisfaction score is less than the threshold parameter, a dissatisfaction label is written for the survey sample. The dissatisfaction label includes a label type identifier and a sample identifier.

5. The customer satisfaction visualization analysis and decision support system according to claim 4, characterized in that, The threshold grading module includes a threshold dictionary table, a threshold item table, a matching unit, and a grading generation unit; The threshold dictionary table stores threshold dictionary identifiers, indicator identifiers, and applicable time granularity identifiers. The threshold item table stores multiple threshold interval items associated with the threshold dictionary identifier. Each threshold interval item includes a lower limit value, an upper limit value, an interval inclusion relationship identifier, and a hierarchical identifier. The interval inclusion relationship identifier is used to indicate the inclusion method of the interval boundary. The inclusion method of the interval boundary includes left-closed and right-open, left-open and right-closed, double-closed, and double-open. The matching unit determines the threshold dictionary identifier that matches the indicator result set based on the indicator identifier and time granularity identifier in the indicator result set. The hierarchical generation unit reads the corresponding indicator value for each indicator result in the indicator result set, determines the threshold interval item that matches the indicator value in the threshold item table according to the interval inclusion relationship identifier, and writes the hierarchical identifier and the grouping key of the indicator result into the interval hierarchical result set; the grouping key includes time granularity identifier and hierarchical path identifier.

6. The customer satisfaction visualization analysis and decision support system according to claim 5, characterized in that, The list generation unit generates a list to be processed based on the interval hierarchical result set and the analysis data area. The list to be processed includes a sample execution progress list, a follow-up processing list, and a list of unrepaired and unsatisfactory objects. The sample execution progress list is determined by the interval classification results corresponding to the sample completion rate indicator. The sample completion rate indicator is calculated by the number of samples marked as completed in the analysis data area and the total number of survey samples with corresponding time granularity and hierarchical path indicators in the analysis data area. The follow-up action list is determined by the interval classification results corresponding to the follow-up completion rate indicator. The follow-up completion rate indicator is calculated by the number of samples marked as unsatisfactory and whose follow-up status is marked as completed and the total number of samples marked as unsatisfactory. The list of unrepaired and unsatisfactory objects is determined by the interval classification results corresponding to the unrepair rate index. The unrepair rate index is calculated by the number of objects marked as unsatisfactory and whose repair status is marked as unrepaired, and the total number of objects marked as unsatisfactory. The association annotation unit writes association annotation information for each record in the ranking results and the list of records to be disposed of. The association annotation information includes indicator identifier, threshold dictionary identifier, classification identifier, time granularity identifier, and hierarchical path identifier, so as to establish a one-to-one correspondence between the ranking results and the list of records to be disposed of and the corresponding indicator results and interval classification results.

7. The customer satisfaction visualization analysis and decision support system according to claim 6, characterized in that, The visual interaction module includes a component configuration unit, a filtering processing unit, and a rendering unit; The component configuration unit stores a chart component configuration table. The chart component configuration table records the component identifier, data source type identifier, data source reference identifier, dimension field set, metric field set, and display type identifier for each chart component. The data source type identifier is used to indicate that the data source of the chart component is an indicator result set, interval hierarchical result set, ranking result, or pending list. The data source reference identifier is used to indicate the data table, view, or query identifier corresponding to the chart component. The filtering processing unit receives filtering conditions and generates a set of query conditions, which includes brand conditions, time granularity identifier conditions, regional conditions, group conditions, and distributor conditions. The filtering processing unit writes the set of query conditions into the filtering context and generates query requests for each chart component based on the data source reference identifier in the chart component configuration table. The rendering unit receives the query request, obtains the query result of the corresponding data source, and renders and displays the query result according to the display type identifier of the chart component configuration table.

8. The customer satisfaction visualization analysis and decision support system according to claim 7, characterized in that, The visualization interaction module also includes a drilling processing unit and a linkage processing unit; The drill processing unit receives a drill instruction, which includes the current level identifier, the target level identifier, and the selected node identifier. The drill processing unit maps the selected node identifier to a level path identifier according to the organizational hierarchy, and updates the regional conditions, group conditions, or distributor conditions corresponding to the target level identifier in the filtering context, so that the rendering unit generates a query request based on the updated filtering context. The linkage processing unit receives the selection event of the source chart component and generates a selection context, which includes the source component identifier, the selected dimension field identifier, the selected dimension value, and the time granularity identifier value. The component configuration unit also stores a linkage relationship configuration table, which records the mapping relationship between the source component identifier and the target component identifier set; The linkage processing unit determines the target component identifier set associated with the source component identifier based on the linkage relationship configuration table, and writes the selected dimension value into the filtering context corresponding to the selected dimension field identifier, so that the rendering unit generates a query request for the chart component corresponding to the target component identifier set.

9. A customer satisfaction visualization analysis and decision support system according to claim 8, characterized in that, When the permission verification unit receives an access request, it parses the session token to obtain the user identifier and determines the corresponding function permissions, data access scope, and field visibility rules based on the user identifier. When the access request is a chart component data request, the permission verification unit determines the function identifier, hierarchical path identifier, and field set involved in the access request according to the chart component configuration table, and performs function permission verification on the function identifier, data permission verification on the hierarchical path identifier, and field permission verification on the field set. If the verification passes, the access request is allowed; if the verification fails, the access request is rejected and a rejection identifier is returned.

10. A customer satisfaction visualization analysis and decision support system according to claim 9, characterized in that, The data storage module includes a raw data storage unit, an analysis data storage unit, an indicator result storage unit, a hierarchical result storage unit, an import record storage unit, and a decision result storage unit; The original data storage unit stores the survey data written by the data access and verification module, and uses the import batch identifier and sample identifier as index fields. The analysis data storage unit stores the survey data after the hierarchical path identifier is written by the master data association module, and uses the hierarchical path identifier and time granularity identifier as partition fields. The indicator result storage unit stores the indicator result set generated by the indicator calculation module, and uses the indicator identifier, hierarchical path identifier and time granularity identifier as a joint index. The hierarchical result storage unit stores the interval hierarchical result set generated by the threshold hierarchical module, and uses the threshold dictionary identifier, indicator identifier, hierarchical path identifier and time granularity identifier as a joint index. The import record storage unit stores the import records generated by the data import and verification module, and uses the import batch identifier as the index field. The decision result storage unit stores the ranking results and the list of items to be disposed of generated by the decision output module, and records the indicator identifier, threshold dictionary identifier, hierarchical identifier, hierarchical path identifier and time granularity identifier in the ranking results and the list of items to be disposed of.

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