Data display method and device, equipment and storage medium

Abstract

The invention discloses a data display method and device, equipment and a storage medium, and relates to the field of label management, and the method comprises the steps: generating sales personnel portrait label data according to sales data information; creating label definition data based on the salesman portrait label data, establishing an association relationship between the label definition data and the salesman portrait label data, and constructing a salesman portrait label corresponding to the salesman portrait label data based on the association relationship; determining the label type of the sales personnel portrait label and generating a label tree, and generating a group portrait according to the label tree; and querying sales personnel portrait label data in the group portrait, and generating a data trend chart through the data display page for data display. The association relationship between the tag definition data and the salesman portrait tag data is established, and the data query and statistics of the salesman portrait tag can be realized through business process operation in different scenes, so that the management of the salesman tag based on the portrait tag data is realized.

Description

Technical Field

[0001] The present invention relates to the field of tag management, and in particular to a data display method, device, equipment and storage medium. Background Art

[0002] Currently, in the application scenarios of label data, traditional label application technology generally has the following phenomena or problems:

[0003] The tag application scenario is single, and the data that can be obtained or viewed are all fixed data content. It is impossible to flexibly adjust the settings according to the user's ideas. It lacks flexibility and diversity of application scenarios. In addition, the change and maintenance of the scenario are complicated, long-term, and costly.

[0004] The flexibility of label data analysis is poor. It is impossible to flexibly perform cross-analysis and correlation analysis of label data, and it is also unable to meet the needs of different users to set personalized custom labels and realize secondary processing, combination calculation and analysis of different labels.

[0005] Tag application scenarios lack self-service settings, and users cannot design scenario applications by themselves, which reduces the diversity and richness of applications and cannot form application sedimentation and accumulation. In addition, it is impossible to easily track changes in data application results over a period of time, which increases the difficulty of application. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a data display method, device, equipment and storage medium, establish an association relationship between label definition data and salesperson portrait label data, and realize data query and statistics of salesperson portrait labels in business process operations in different scenarios, thereby realizing the management of salesperson labels based on portrait label data. The specific scheme is as follows:

[0007] In a first aspect, the present application provides a data display method, comprising:

[0008] Collect sales data information corresponding to each salesperson, and generate corresponding salesperson portrait label data based on the sales data information;

[0009] Based on the salesperson portrait label data, corresponding label definition data is created according to preset label settings, and an association relationship between the label definition data and the salesperson portrait label data is established, and a salesperson portrait label corresponding to the salesperson portrait label data is constructed based on the association relationship;

[0010] Determine the tag type corresponding to the salesperson portrait tag, generate a tag tree corresponding to the salesperson portrait tag according to the tag type, and generate a group portrait of the salesperson portrait tag data according to the tag tree;

[0011] The salesperson portrait label data corresponding to the target salesperson is queried in the group portrait according to preset data query conditions, and a corresponding data trend chart is generated according to the salesperson portrait label data for data display through a preset data display page.

[0012] Optionally, constructing the salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship includes:

[0013] Determine the data type of the salesperson portrait label data, and construct a label type corresponding to the salesperson portrait label and a data table field of a preset label data table according to the data type;

[0014] A sales staff portrait label corresponding to the sales staff portrait label data is constructed according to the association relationship, the label type and the data table field.

[0015] Optionally, generating a tag tree corresponding to the salesperson portrait tag according to the tag type includes:

[0016] Circularly storing the salesperson portrait tags into corresponding preset tag categories according to the tag types, and constructing a corresponding tag tree based on the preset tag categories;

[0017] The step of cyclically storing the salesperson portrait tags to corresponding preset tag categories according to the tag types includes:

[0018] The salesperson portrait labels of the label types of numerical type, enumeration type, date type and text type are cyclically stored in the corresponding first preset label category;

[0019] And / or, the salesperson portrait labels whose label types are numerical and enumeration types are cyclically stored in the corresponding second preset label classification;

[0020] And / or, the salesperson portrait label whose label type is numerical is cyclically stored in the corresponding third preset label category.

[0021] Optionally, generating a group portrait of the salesperson portrait label data according to the label tree includes:

[0022] Based on the label tree, the salesperson portrait label or the preset label condition is stored in the preset label data table according to the preset group type; the group type includes a static group and a dynamic group;

[0023] Or, based on the tag tree and according to the field name of the data table field corresponding to the salesperson portrait tag, the salesperson portrait tag is stored in the preset tag data table;

[0024] Or, based on the tag tree and according to the data table fields, tag grouping settings and tag grouping data ranges corresponding to the salesperson portrait tags, the salesperson portrait tags are stored in the preset tag data table;

[0025] Or, based on the label tree and according to the salesperson portrait label whose label type is a numerical type, a new numerical salesperson portrait label or an enumeration type salesperson portrait label is generated, and then the new numerical salesperson portrait label or the enumeration type salesperson portrait label is stored in the preset label data table;

[0026] The group portrait of the salesperson portrait label data is generated according to the preset label data table.

[0027] Optionally, before searching the group portrait for the salesperson portrait label data corresponding to the target salesperson according to the preset data query condition, the method further includes:

[0028] A tag query strategy corresponding to the group portrait is created based on the tag tree, so that the salesperson portrait tag data corresponding to the target salesperson is queried in the group portrait according to the preset data query conditions through the tag query strategy.

[0029] Optionally, querying the salesperson portrait label data corresponding to the target salesperson in the group portrait according to a preset data query condition includes:

[0030] Querying the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset dynamic structured query statement and the preset data query condition;

[0031] Determine whether the salesperson portrait label data meets the preset data query conditions, and if it meets the preset data query conditions, generate a corresponding message through a preset message template, and send the message to the target salesperson.

[0032] Optionally, generating a corresponding data trend chart for data display according to the salesperson portrait tag data through a preset data display page includes:

[0033] Generate a corresponding click event based on the tag query strategy, and jump to the preset data display page through the click event;

[0034] Generate the corresponding data trend chart based on the sales personnel portrait label data, and display the data trend chart on the preset data display page.

[0035] In a second aspect, the present application provides a salesperson data display device, comprising:

[0036] A data collection module is used to collect sales data information corresponding to each salesperson and generate corresponding salesperson portrait label data according to the sales data information;

[0037] A label generation module, used to create corresponding label definition data based on the salesperson portrait label data according to preset label settings, and establish an association relationship between the label definition data and the salesperson portrait label data, and construct a salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship;

[0038] A portrait generation module, used to determine the tag type corresponding to the salesperson portrait tag, generate a tag tree corresponding to the salesperson portrait tag according to the tag type, and generate a group portrait of the salesperson portrait tag data according to the tag tree;

[0039] The data display module is used to query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query conditions, and generate a corresponding data trend chart for data display based on the salesperson portrait label data through a preset data display page.

[0040] In a third aspect, the present application provides an electronic device, comprising a processor and a memory; wherein the memory is used to store a computer program, and the computer program is loaded and executed by the processor to implement the aforementioned data display method.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, which implements the aforementioned data display method when executed by a processor.

[0042] In this application, firstly, the sales data information corresponding to each salesperson is collected, and the corresponding salesperson portrait label data is generated according to the sales data information, and then the corresponding label definition data is created according to the preset label setting based on the salesperson portrait label data, and the association relationship between the label definition data and the salesperson portrait label data is established, so as to construct the salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship, and then determine the label type corresponding to the salesperson portrait label, and generate the label tree corresponding to the salesperson portrait label according to the label type, and after generating the group portrait of the salesperson portrait label data according to the label tree, the salesperson portrait label data corresponding to the target salesperson is queried in the group portrait according to the preset data query conditions, and the corresponding data trend chart is generated according to the salesperson portrait label data through the preset data display page for data display. In this way, the portrait label is designed from different angles of the salesperson, the salesperson portrait label data is generated by processing, and then the association relationship between the label definition data and the salesperson portrait label data is established through the label setting, so that the encapsulation of the label definition data can be completed according to the business process operation of the user in different scenarios, and the query and statistics based on the salesperson portrait label data can be realized, and then the query results are displayed in the scene. Through the above technical solution, different links can be connected in series through strategies, and the association, encapsulation and analysis of label definitions and portrait label data in some links can be realized, thereby realizing data-driven full-link closed-loop management of sales personnel based on portrait label data, which helps users to flexibly implement label applications according to different needs and scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0044] Figure 1 A flow chart of a data display method provided for this application;

[0045] Figure 2 A data processing flow chart of a salesperson portrait label provided for this application;

[0046] Figure 3 A flow chart of a specific data display method provided for this application;

[0047] Figure 4 A schematic diagram of the structure of a salesperson data display device provided in this application;

[0048] Figure 5A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Current label application technologies generally have the problems of single label application scenarios and poor flexibility in label data analysis. It is impossible to flexibly perform correlation analysis of label data, and it is impossible to meet the personalized settings of different users. However, the present application can establish an association between label definition data and sales personnel portrait label data, thereby enabling business process operations in different scenarios, realizing data query and statistics of sales personnel portrait labels, and thus realizing the management of sales personnel labels based on portrait label data.

[0051] See also Figure 1 As shown, an embodiment of the present invention discloses a data display method, including:

[0052] Step S11: Collect sales data information corresponding to each salesperson, and generate corresponding salesperson portrait label data based on the sales data information.

[0053] In this embodiment, Figure 2 As shown, first, the sales data information corresponding to each salesperson can be collected, and the corresponding salesperson portrait label data can be generated based on the sales data information. Specifically, since the portrait label can be designed from different angles such as the basic information, performance information, and behavior information of the salesperson in this embodiment, the salesperson's basic law, underwriting, quotation, claim settlement, behavior tracking and other types of data information can be collected and integrated through big data technology. At the same time, the salesperson's behavior data can also be collected, such as the sales operation behavior in the order application, so as to generate the corresponding salesperson portrait label data. It should be pointed out that in the process of collecting data, the data collection and subsequent processing flow can be realized through the data processing layer, and the processing method of the above-mentioned data processing layer is mainly offline batch data processing. In a specific embodiment, Spark can be combined with Hive to realize offline batch data processing.

[0054] Step S12: creating corresponding label definition data based on the sales staff portrait label data according to preset label settings, establishing an association relationship between the label definition data and the sales staff portrait label data, and constructing a sales staff portrait label corresponding to the sales staff portrait label data based on the association relationship.

[0055] In this embodiment, after collecting various sales data of the salesperson, such as Figure 2 As shown, the steps of establishing the label corresponding to the salesperson can be performed. Specifically, the corresponding label definition data can be created based on the salesperson portrait label data according to the preset label settings, and the association relationship between the label definition data and the salesperson portrait label data can be established, and the salesperson portrait label corresponding to the salesperson portrait label data can be constructed based on the association relationship. And when constructing the salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship, the data type of the salesperson portrait label data can be determined first, and the label type corresponding to the salesperson portrait label and the data table field of the preset label data table can be constructed according to the data type, and then the salesperson portrait label corresponding to the salesperson portrait label data can be constructed according to the association relationship, the label type and the data table field.

[0056] Specifically, in this embodiment, the establishment of a label is to convert the fields of the salesperson portrait label data table. For example, the label data table fields can be divided into four types for conversion: numeric type, enumeration type, date type, and text type. Then, label definition data, fields for storing salesperson portrait labels, and data types of portrait labels are created in the label setting to complete the addition and modification of labels, thereby establishing an association relationship between salesperson portrait labels and label storage.

[0057] Step S13, determine the tag type corresponding to the sales staff portrait tag, generate a tag tree corresponding to the sales staff portrait tag according to the tag type, and generate a group portrait of the sales staff portrait tag data according to the tag tree.

[0058] In this embodiment, Figure 2 As shown, a corresponding group portrait can be generated based on the sales staff portrait label. Specifically, the label type corresponding to the sales staff portrait label can be determined, and a label tree corresponding to the sales staff portrait label can be generated based on the label type, and a group portrait of the sales staff portrait label data can be generated based on the label tree.

[0059] Step S14: query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query conditions, and generate a corresponding data trend chart for data display based on the salesperson portrait label data through a preset data display page.

[0060] In this embodiment, after the group portrait is generated, the subsequent strategy creation step can be performed. Specifically, before querying the salesperson portrait tag data, a tag query strategy corresponding to the group portrait can be created based on the tag tree through the preset condition factor module, the preset message template module, and the preset attention indicator module, so that the salesperson portrait tag data corresponding to the target salesperson can be queried in the group portrait according to the preset data query conditions through the tag query strategy. After querying the salesperson portrait tag data corresponding to the target salesperson in the group portrait according to the preset data query conditions, the corresponding data trend chart can be generated according to the salesperson portrait tag data through the preset data display page for data display.

[0061] It should be pointed out that in this embodiment, the strategy creation is divided into a condition factor module, a message template module and a focus indicator module. Among them, the condition factor module and the message template module can store four types of label data (numeric type, enumeration type, date type, text type) in the label classification through a recursive algorithm loop to form a label tree. Specifically, the function of the condition factor module is to use labels to perform secondary filtering on the sales staff in the group, which can be implemented in a dynamic SQL (Structured Query Language) manner. At the same time, based on the above label classification, the label can be divided into four ways to implement dynamic SQL: in the where condition, the numeric label and the date label are spliced ​​with the operator and the data range, the enumeration type determines whether they are equal, and the text type uses the like fuzzy query. And the message template module can write the message content in the page, and the indicator data in the message content is replaced by the label of the message template part. In this way, as long as there is a message template, the sales staff who have been screened twice by the condition factor module can be sent the corresponding message content. Through the above technical solution, the conditional factor module will store the label field, operator and comparison numbers or labels, and the message template module will save the message content and the corresponding message content English field, and for the message template module and the conditional factor module, the storage is a one-to-many storage format.

[0062] The attention indicator module stores two types of label data (numeric type and enumeration type) in the label classification through a recursive algorithm loop to form a label tree. In other words, the labels selected by the attention indicator module are divided into numerical type and enumeration type. The numerical type needs to set the group and the data range of the group. The enumeration value in the enumeration type is the corresponding group. In this way, the attention indicator module can store the corresponding label fields and group settings in a structure where one field corresponds to multiple groups. The above-mentioned strategy creation process helps to realize the automation of data change tracking. By setting action groups and attention labels in the strategy and combining it with the preset timed task mechanism, it can automatically form a trend distribution chart of the result changes of action groups and attention labels, notification reach, and task completion.

[0063] After the user creates an excellent strategy template, the administrator will publish the strategy template according to the star rating. After that, all users can view, copy and call the strategy template. The strategy library also introduces the five-force model of the organization and the recommendation of excellent templates. The five-force model will display five capabilities in a pentagonal data format. The five capabilities are "organizational operation capability", "intelligent application capability", "professional sales capability", "sustainable recruitment capability" and "differentiated management capability". Each capability displays the "national average score", "national highest score" and "branch score". The excellent template recommendation displays the strategy template of the branch company based on the selection of different themes. In this way, the recommendation of excellent strategy templates by theme can be realized through the corresponding five-force model of the organization of each institution, and efficient strategy application can be realized through one-click call.

[0064] In this embodiment, the sales data information corresponding to each salesperson can be collected, and the corresponding salesperson portrait label data can be generated according to the sales data information. Then, based on the salesperson portrait label data, the corresponding label definition data is created according to the preset label setting, and the association relationship between the label definition data and the salesperson portrait label data is established, so as to construct the salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship, and then determine the label type corresponding to the salesperson portrait label, and generate the label tree corresponding to the salesperson portrait label according to the label type, and after generating the group portrait of the salesperson portrait label data according to the label tree, the salesperson portrait label data corresponding to the target salesperson is queried in the group portrait according to the preset data query conditions, and the corresponding data trend chart is generated according to the salesperson portrait label data through the preset data display page for data display. In this way, through the above technical solution, different links can be connected in series through strategies, and the association, encapsulation and analysis of the label definition and the portrait label data under some links are realized, thereby realizing the closed-loop management of the whole link of sales personnel driven by data based on the portrait label data, which helps users to flexibly realize the application of labels according to different needs and scenarios.

[0065] Based on the previous embodiment, it can be seen that the present application can establish an association relationship between label definition data and salesperson portrait label data, thereby realizing data query and statistics of salesperson portrait labels. Next, the present embodiment will elaborate on the process of querying salesperson portrait label data and displaying it. Figure 3 As shown, the embodiment of the present application discloses a specific data display method, including:

[0066] Step S21: Create corresponding label definition data based on the sales staff portrait label data according to preset label settings, establish an association relationship between the label definition data and the sales staff portrait label data, and construct a sales staff portrait label corresponding to the sales staff portrait label data based on the association relationship.

[0067] Step S22, determine the tag type corresponding to the sales staff portrait tag, generate a tag tree corresponding to the sales staff portrait tag according to the tag type, and generate a group portrait of the sales staff portrait tag data according to the tag tree.

[0068] In this embodiment, when generating a label tree corresponding to a salesperson portrait label according to the label type, the salesperson portrait labels of the label types of numeric type, enumeration type, date type and text type can be stored cyclically in the corresponding preset label classification through the preset condition module and the preset result column module; and / or, the salesperson portrait labels of the label types of numeric type and enumeration type can be stored cyclically in the corresponding preset label classification through the preset distribution indicator module; and / or, the salesperson portrait labels of the label type of numeric type can be stored cyclically in the corresponding preset label classification through the preset custom module. Then, the corresponding label tree can be constructed based on the preset label classification. Correspondingly, when generating a group portrait of salesperson portrait label data according to the label tree, the salesperson portrait label or the preset label condition can be stored in the preset label data table according to the preset group portrait group type through the preset condition module according to the label tree, wherein the static group stores the salesperson list that can be queried by the preset condition, and the dynamic group stores the preset label condition; the salesperson portrait label is stored in the preset label data table according to the field name of the data table field corresponding to the salesperson portrait label through the preset result column module; the salesperson portrait label is stored in the preset label data table according to the corresponding data table field, label group setting and label group data range of the salesperson portrait label through the preset distribution indicator module; a new numerical salesperson portrait label or enumeration salesperson portrait label is generated according to the salesperson portrait label of the numerical label type through the preset custom module, and the salesperson portrait label is stored in the preset label data table. Then, a group portrait of the salesperson portrait label data is generated according to the preset label data table. It should also be pointed out that when the sales staff portrait labels or preset label conditions are stored in the preset label data table through the preset condition module, if the group portrait is a static group, the list of sales staff that can be queried by the preset conditions can be stored in the preset label data table; if the group portrait is a dynamic group, the preset label conditions are stored in the preset label data table.

[0069] It should be pointed out that, in the process of generating a group portrait in this embodiment, the group is mainly divided into a condition module, a result column module, a distribution indicator module and a custom module.

[0070] Among them, in a specific embodiment, the condition module and the result column module store four types of label data (numeric type, enumeration type, date type, text type) into the label classification through a recursive algorithm loop to form a label tree. And it can be understood that in this embodiment, a label can be selected in the label tree to query the salesperson list. Therefore, since the labels of the condition module and the result column module are changed when querying the salesperson list, a dynamic SQL method can be designed to implement the query. Specifically, for the labels in the condition module, the labels are divided into four ways to implement dynamic SQL. In the where condition, the numeric label and the date label are spliced ​​with the operator and the data range, the enumeration type determines whether they are equal, and the text type uses the like fuzzy query; for the label of the result column module, the label field name can be spliced ​​into the result column of the query statement to implement dynamic SQL, and finally the springJDBCTemplate technology is used to implement the salesperson query, so as to define the salesperson range. It should also be pointed out that when the conditional module is storing, when the option of the organization is selected in the condition, there may be a large amount of data at this time, so the organization data is stored in the table by associating each organization with the group id; when the option of the organization is not selected in the condition, the amount of data is small, and the organization data can be converted into a json string format and stored in a field of the group table in the form of text. Correspondingly, the result column module will store the field name corresponding to the checked result column label. In this way, by selecting different labels and setting different conditions through the conditional module when creating a group portrait, at this time, due to the different sales personnel circled by the group portrait, the differentiation of the circle group is realized, thus forming a closed-loop management of the entire PDCA (Plan, Do, Check and Act) link, through differentiated grouping and personalized implementation strategies, the task is issued, and the management from "analysis to policy" is realized.

[0071] In another specific embodiment, the distribution indicator module stores two types of label data (numeric type and enumeration type) in the label classification through a recursive algorithm loop to form a label tree. Specifically, the distribution indicator first queries the salesperson list through the design of dynamic sql, and then selects the label in the distribution indicator label tree. The labels selected here are divided into numerical type and enumeration type, wherein the numerical type needs to set the group and the data range of the group, and the enumeration value in the enumeration type is the corresponding group. After that, the data range or enumeration value is determined according to the queried salesperson label data, and the corresponding group is selected for data statistics and recording, and the corresponding group portrait distribution map can be generated. It should be pointed out that since the distribution indicator module can select multiple labels, when there are multiple group portrait distribution maps in a group, frequent calls to the interface will seriously affect the server performance, so all group portrait distribution maps can be processed at one time using a multi-threaded method. Correspondingly, when storing, the distribution indicator module will store information such as the label field, group setting, and group data range when storing. In this way, you can use the distribution indicator module to select the labels you want to distribute through the label tree, and set the label grouping, that is, the segmentation of the label value, and then select the icon type you want to display, such as a bar chart, to form a grouped distribution icon display, thereby achieving cross-chart distribution. In other words, in the group portrait, you can select any single label or any combination of labels to form a cross-chart group distribution, and you can drill down on the portrait details of the group distribution results. In addition, for numerical result column labels, you can also analyze the secondary calculation results of the labels, which improves the flexibility and diversity of label analysis.

[0072] The flexibility and diversity of label analysis, in another specific embodiment, the custom module can store the numerical label data into the label classification through a recursive algorithm loop to form a label tree. And if the current label data cannot meet the business scenario, you can create a custom module label to meet the needs. It should be pointed out that the labels of the custom module are divided into formula type and group type. The formula type custom label is to add, subtract, multiply and divide multiple labels to form a new numerical label. Here, the Spring Expression Language expression will be used to verify the formula to prevent the generation of formulas that cannot be calculated; the group type label is to set the group and the data range of the group for the label, and convert the numerical label that meets the data range into an enumeration type label. Correspondingly, when querying later, if there is a formula type custom label, when querying the salesperson list, the formula in the label will be replaced with the label field name, and then spliced ​​into the result column of the query statement for query; if there is a group type custom label, when querying the salesperson list, it will first be compared according to the queried label data to obtain the corresponding group value. In this way, since the custom part can be saved separately in the page, in order to ensure the data consistency between the group and the custom module, the custom part on the page will first cache the data in the session. Only when the group is saved, the custom part will store the data.

[0073] Step S23: query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query conditions, and generate a corresponding data trend chart for data display based on the salesperson portrait label data through a preset data display page.

[0074] In this embodiment, Figure 2 As shown, after completing the strategy creation, the corresponding strategy batch running operation can be performed, wherein the strategy batch running is divided into a message sending module and an attention indicator module. Accordingly, when querying the salesperson portrait label data corresponding to the target salesperson in the group portrait, the preset message mode module can be used according to the preset dynamic structured query statement according to the preset data query condition to query the salesperson portrait label data corresponding to the target salesperson in the group portrait, and then the preset condition factor module is used to determine whether the salesperson portrait label data meets the preset data query condition, and when it meets the preset data query condition, the message template of the preset message template module is used to generate the corresponding message, and the message is sent to the target salesperson.

[0075] Specifically, the message sending module can use dynamic SQL to query the sales personnel and corresponding label data in the group, and then use the condition factors to cyclically compare whether they are consistent. If they are consistent, the labels in the message template are replaced with corresponding data to form the message content. Finally, the cycle and frequency are set through the strategy, and the message sending module is started by using Quartz timing to generate message content, and then connected with the downstream system to send the message content to the corresponding sales personnel.

[0076] When the corresponding data trend chart is generated according to the salesperson portrait label data for data display, the corresponding click event can be generated based on the label query strategy, and the preset data display page can be jumped through the click event, and then the corresponding data trend chart is generated through the preset message sending module and the preset attention indicator module, and the data trend chart is displayed on the preset data display page. In other words, the attention indicator module will use the dynamic sql design method to query the salesperson in the group and the corresponding label data, and then according to the grouping data range of the attention indicator module, a circular comparison is performed to count the number of people who meet each group, form the label result data, and finally display the data trend chart on the page for user analysis. And after the strategy batch is completed, the strategy can be encapsulated with a click event, so that the data display page can be directly jumped by clicking. Among them, the reach of the message sending module and the data trend chart generated by the operation of the attention indicator module are all data statistics and data echoes recorded by recording the corresponding personnel, date, organization, channel and other data. Users can filter out the reach and data trend chart that meet the business scenario according to the conditions of date, organization, channel, etc. for data analysis.

[0077] For a more specific processing procedure of the above step S21, reference may be made to the corresponding contents disclosed in the above embodiments, which will not be described in detail here.

[0078] Through the above technical scheme, in this embodiment, portrait labels can be designed from different angles of sales personnel, and sales personnel portrait label data can be generated through big data technology processing. Then, through label setting, the association relationship between label definition data and sales personnel portrait label data is established. According to the business process operation of users in different scenarios, the label definition data is encapsulated, and parsed into sales personnel portrait label data query and statistics according to system rules, and then based on the query results, it is encapsulated as statistical information based on label definition and displayed in the scene. In this way, the system connects different links such as grouping, policy implementation, execution, issuance, and tracking through strategies, and realizes the association, encapsulation and parsing of label definitions and portrait label data under some links, thereby realizing the closed-loop management of the PDCA full link of sales personnel driven by data based on portrait label data, and further realizing the flexibility and diversity of label setting and use. In many application scenarios such as grouping screening conditions, result columns, label analysis, policy action factors, template message variables, and attention labels of group portraits, users can choose any label by themselves, and the system code does not need to be maintained again; and users can flexibly set label calculation formulas based on existing labels according to analysis and application needs to realize the analysis and application of custom labels;

[0079] See also Figure 4 As shown, the embodiment of the present application also discloses a salesperson data display device, including:

[0080] The data collection module 11 is used to collect sales data information corresponding to each salesperson and generate corresponding salesperson portrait label data according to the sales data information;

[0081] The label generation module 12 is used to create corresponding label definition data based on the salesperson portrait label data according to preset label settings, and establish an association relationship between the label definition data and the salesperson portrait label data, and construct a salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship;

[0082] A portrait generation module 13 is used to determine the tag type corresponding to the salesperson portrait tag, generate a tag tree corresponding to the salesperson portrait tag according to the tag type, and generate a group portrait of the salesperson portrait tag data according to the tag tree;

[0083] The data display module 14 is used to query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query conditions, and generate a corresponding data trend chart according to the salesperson portrait label data for data display through a preset data display page.

[0084] In this embodiment, portrait labels can be designed from different perspectives of sales personnel, and sales personnel portrait label data can be generated through processing. Then, through label setting, the association relationship between label definition data and sales personnel portrait label data can be established. In this way, the label definition data can be encapsulated according to the business process operation of users in different scenarios, and query and statistics based on sales personnel portrait label data can be realized, and then displayed in the scene based on the query results. In this way, different links can be connected in series through strategies, and the association, encapsulation and analysis of label definitions and portrait label data under some links can be realized, thereby realizing the closed-loop management of the entire link of sales personnel driven by data based on portrait label data, which helps users to flexibly realize the application of labels according to different needs and scenarios.

[0085] In some specific embodiments, the label generation module 12 specifically includes:

[0086] A type determination unit, used to determine the data type of the salesperson portrait label data, and construct a label type corresponding to the salesperson portrait label and a data table field of a preset label data table according to the data type;

[0087] A label construction unit is used to construct a sales staff portrait label corresponding to the sales staff portrait label data according to the association relationship, the label type and the data table field.

[0088] In some specific embodiments, the portrait generation module 13 specifically includes:

[0089] A label tree construction submodule, used to cyclically store the salesperson portrait labels into corresponding preset label categories according to the label types, and to construct a corresponding label tree based on the preset label categories;

[0090] The tag tree construction submodule specifically includes:

[0091] A first label storage unit, used for cyclically storing the salesperson portrait labels of the label types of numerical type, enumeration type, date type and text type into the corresponding first preset label classification;

[0092] A second label storage unit, used for cyclically storing the salesperson portrait labels whose label types are numerical and enumerated in the corresponding second preset label classification;

[0093] The third label storage unit is used to cyclically store the salesperson portrait label whose label type is numerical into the corresponding third preset label category.

[0094] In some specific embodiments, the portrait generation module 13 specifically includes:

[0095] A fourth label storage unit, used to store the salesperson portrait label or the preset label condition into the preset label data table according to the preset group type based on the label tree; the group type includes a static group and a dynamic group;

[0096] A fifth label storage unit, used for storing the salesperson portrait label in the preset label data table based on the label tree and according to the field name of the data table field corresponding to the salesperson portrait label;

[0097] A sixth label storage unit, used for storing the salesperson portrait label in the preset label data table based on the label tree and according to the corresponding data table field, label grouping setting and label grouping data range of the salesperson portrait label;

[0098] a seventh label storage unit, for generating a new numerical sales staff portrait label or an enumerated sales staff portrait label based on the label tree and according to the sales staff portrait label whose label type is numerical, and then storing the new numerical sales staff portrait label or the enumerated sales staff portrait label in the preset label data table;

[0099] A portrait generation unit is used to generate the group portrait of the salesperson portrait label data according to the preset label data table.

[0100] In some specific embodiments, the salesperson data display device further includes:

[0101] A strategy creation module is used to create a tag query strategy corresponding to the group portrait based on the tag tree, so as to query the salesperson portrait tag data corresponding to the target salesperson in the group portrait according to the preset data query conditions through the tag query strategy.

[0102] In some specific embodiments, the data display module 14 specifically includes:

[0103] A data query unit, configured to query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to a preset dynamic structured query statement and the preset data query condition;

[0104] A message generating unit is used to determine whether the salesperson portrait tag data meets the preset data query conditions, and if it meets the preset data query conditions, to generate a corresponding message through a preset message template, and to send the message to the target salesperson.

[0105] In some specific embodiments, the data display module 14 specifically includes:

[0106] An event generating unit, configured to generate a corresponding click event based on the tag query strategy, and jump to the preset data display page through the click event;

[0107] A data display unit is used to generate the corresponding data trend chart according to the salesperson portrait label data, and display the data trend chart on the preset data display page.

[0108] Furthermore, the present application also discloses an electronic device. Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0109] Figure 5 A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the data display method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0110] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0111] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0112] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and may be Windows Server, Netware, Unix, Linux, etc. In addition to computer programs that can be used to complete the data display method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 may further include computer programs that can be used to complete other specific tasks.

[0113] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the aforementioned disclosed data display method. The specific steps of the method can refer to the corresponding contents disclosed in the aforementioned embodiments, and will not be repeated here.

[0114] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0115] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0116] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0117] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0118] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data display method, characterized in that: include: Collect sales data information corresponding to each salesperson, and generate corresponding salesperson portrait label data based on the sales data information; Based on the salesperson portrait label data, corresponding label definition data is created according to preset label settings, and an association relationship between the label definition data and the salesperson portrait label data is established, and a salesperson portrait label corresponding to the salesperson portrait label data is constructed based on the association relationship; Determine the tag type corresponding to the salesperson portrait tag, generate a tag tree corresponding to the salesperson portrait tag according to the tag type, and generate a group portrait of the salesperson portrait tag data according to the tag tree; The salesperson portrait label data corresponding to the target salesperson is queried in the group portrait according to preset data query conditions, and a corresponding data trend chart is generated according to the salesperson portrait label data for data display through a preset data display page.

2. The data display method according to claim 1, characterized in that: The step of constructing the salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship includes: Determine the data type of the salesperson portrait label data, and construct a label type corresponding to the salesperson portrait label and a data table field of a preset label data table according to the data type; A sales staff portrait label corresponding to the sales staff portrait label data is constructed according to the association relationship, the label type and the data table field.

3. The data display method according to claim 2, characterized in that: Generating a tag tree corresponding to the salesperson portrait tag according to the tag type includes: Circularly storing the salesperson portrait tags into corresponding preset tag categories according to the tag types, and constructing a corresponding tag tree based on the preset tag categories; The step of cyclically storing the salesperson portrait tags to corresponding preset tag categories according to the tag types includes: The salesperson portrait labels of the label types of numerical type, enumeration type, date type and text type are cyclically stored in the corresponding first preset label category; And / or, the salesperson portrait labels whose label types are numerical and enumeration types are cyclically stored in the corresponding second preset label classification; And / or, the salesperson portrait label whose label type is numerical is cyclically stored in the corresponding third preset label category.

4. The data display method according to claim 3, characterized in that: The step of generating a group portrait of the salesperson portrait label data according to the label tree includes: Based on the label tree, the salesperson portrait label or the preset label condition is stored in the preset label data table according to the preset group type; the group type includes a static group and a dynamic group; Or, based on the tag tree and according to the field name of the data table field corresponding to the salesperson portrait tag, the salesperson portrait tag is stored in the preset tag data table; Or, based on the tag tree and according to the data table fields, tag grouping settings and tag grouping data ranges corresponding to the salesperson portrait tags, the salesperson portrait tags are stored in the preset tag data table; Or, based on the label tree and according to the salesperson portrait label whose label type is a numerical type, a new numerical salesperson portrait label or an enumeration type salesperson portrait label is generated, and then the new numerical salesperson portrait label or the enumeration type salesperson portrait label is stored in the preset label data table; The group portrait of the salesperson portrait label data is generated according to the preset label data table.

5. The data display method according to any one of claims 2 to 4, characterized in that: Before searching the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query condition, the method further includes: A tag query strategy corresponding to the group portrait is created based on the tag tree, so that the salesperson portrait tag data corresponding to the target salesperson is queried in the group portrait according to the preset data query conditions through the tag query strategy.

6. The data display method according to claim 5, characterized in that: The step of searching the group portrait for the salesperson portrait label data corresponding to the target salesperson according to the preset data query condition includes: Querying the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset dynamic structured query statement and the preset data query condition; Determine whether the salesperson portrait label data meets the preset data query conditions, and if it meets the preset data query conditions, generate a corresponding message through a preset message template, and send the message to the target salesperson.

7. The data display method according to claim 6, characterized in that: The generating a corresponding data trend chart according to the salesperson portrait tag data through a preset data display page for data display includes: Generate a corresponding click event based on the tag query strategy, and jump to the preset data display page through the click event; Generate the corresponding data trend chart based on the sales personnel portrait label data, and display the data trend chart on the preset data display page.

8. A data display device, characterized in that: include: A data collection module is used to collect sales data information corresponding to each salesperson and generate corresponding salesperson portrait label data according to the sales data information; A label generation module, used to create corresponding label definition data based on the salesperson portrait label data according to preset label settings, and establish an association relationship between the label definition data and the salesperson portrait label data, and construct a salesperson portrait label corresponding to the salesperson portrait label data based on the association relationship; A portrait generation module, used to determine the tag type corresponding to the salesperson portrait tag, generate a tag tree corresponding to the salesperson portrait tag according to the tag type, and generate a group portrait of the salesperson portrait tag data according to the tag tree; The data display module is used to query the salesperson portrait label data corresponding to the target salesperson in the group portrait according to the preset data query conditions, and generate a corresponding data trend chart for data display based on the salesperson portrait label data through a preset data display page.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, and the computer program is loaded and executed by the processor to implement the data presentation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, implements the data presentation method according to any one of claims 1 to 7.

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