CN115907830A

CN115907830A - Index early warning-based strategy execution method, device, equipment and readable medium

Info

Publication number: CN115907830A
Application number: CN202211655764.5A
Authority: CN
Inventors: 文学超; 唐金志; 李阳; 付俊伟; 潘永辉; 伍四杰
Original assignee: Beijing Lingyan Technology Co ltd
Current assignee: Beijing Lingyan Technology Co ltd
Priority date: 2022-12-22
Filing date: 2022-12-22
Publication date: 2023-04-04
Anticipated expiration: 2042-12-22
Also published as: CN115907830B

Abstract

The disclosure provides a strategy execution method, a strategy execution device, equipment and a readable medium based on index early warning, and relates to the technical field of strategy management. The method comprises the following steps: acquiring indexes of a target guest group; carrying out insight analysis on indexes of the target customer group to generate an insight analysis result; monitoring indexes of the target customer group based on the insight analysis result; responding to the fact that the index of the target guest group exceeds a preset early warning range to carry out early warning, and binding and executing the strategy; and performing feedback adjustment on the strategy based on the strategy execution result. The method comprises the steps of constructing indexes by acquiring indexes in a model mode, deriving new indexes by combining the indexes, and defining and using the indexes in multiple directions, so that the circulation of the indexes in a service scene is achieved, and the indexes are bound with the strategy by means of a big data analysis technology, a model technology, an early warning recommendation technology, a scoring technology and the like, so that the service energization of data is realized, and an efficient and reasonable strategy execution method is provided.

Description

Index early warning-based strategy execution method, device, equipment and readable medium

Technical Field

The present disclosure relates to the field of policy management technologies, and in particular, to a method, an apparatus, a device, and a readable medium for policy execution based on index early warning.

Background

At present, in the guest group management, the application of index realization indexes can be established aiming at different service scenes. At present, most of index construction adopts a mode of customizing rule logic, the mode and the simplification are realized, the application scene is independent, the enabling of data services of corresponding indexes cannot be considered, and in this case, the indexes, the early warning and the strategy are used as independent modules for management and control, and the automatic flow transfer of the indexes and the automatic processing of the strategy cannot be realized.

Disclosure of Invention

In order to solve the above problems in the prior art, an object of the present disclosure is to provide an index-based early warning policy execution method, apparatus, device, and readable medium, which can quantize guest group data, and perform efficient and reasonable policy execution through accurate index monitoring and policy binding.

In order to achieve the purpose, the following technical scheme is adopted in the disclosure:

the disclosure provides a strategy execution method based on index early warning, which comprises the following steps:

acquiring indexes of a target customer group;

carrying out insight analysis on the indexes of the target customer group to generate an insight analysis result;

monitoring indexes of the target customer group based on the insight analysis result;

responding to the fact that the index of the target customer group exceeds a preset early warning range to carry out early warning, and binding and executing the strategy;

and performing feedback adjustment on the strategy based on the strategy execution result.

In some embodiments, before the obtaining the index of the target guest group, the method further includes:

constructing a guest group rule;

acquiring customer information according with the customer group rule based on the customer group rule;

and taking the guest group corresponding to the guest information as a target guest group and storing the target guest group.

In some embodiments, the target customer group metrics include a customer group metric and a life cycle metric.

In some embodiments, the method for obtaining the life cycle index includes:

dividing life cycle of the target passenger group by adopting a main and auxiliary stage method;

and analyzing the division rule of each stage of the life cycle to obtain at least one life cycle index.

In some embodiments, the performing insight analysis on the index of the target customer group to generate an insight analysis result specifically includes:

performing insight analysis on the customer group index or the life cycle index based on the target customer group to generate an insight analysis result;

responding to the insight analysis result that the customer group index or the life cycle index does not completely show the customers of the target customer group, and prompting error information;

and responding to the insight analysis result to show the customers of the target customer group completely for the customer group index or the life cycle index, and performing visual display.

In some embodiments, the responding that the index of the target guest group exceeds a preset early warning range to perform early warning and the binding and execution of the policy specifically include:

when the indexes of the target passenger group shake, performing early warning configuration and presetting an early warning range;

responding to the fact that the index of the target guest group exceeds a preset early warning range, carrying out early warning processing, and meanwhile, binding strategies;

and executing the policy based on the bound policy.

In some embodiments, the performing feedback adjustment on the policy based on the policy execution result specifically includes:

responding to the strategy to start execution, and monitoring the change range of the index of the target customer group;

verifying the integrity of the policy based on the transformation of the indicators before and after the policy is executed;

responding to the completion of the strategy execution and the completeness of the strategy, and acquiring a strategy execution result;

carrying out quantitative analysis on the strategy execution result to form a feedback adjustment suggestion;

and adjusting variables in the strategy based on the feedback adjustment suggestion.

The present disclosure also provides a policy enforcement device based on index early warning, which is characterized by comprising:

an acquisition unit configured to acquire an index of a target guest group;

the insight unit is configured to conduct insight analysis on the indexes of the target customer group and generate insight analysis results;

a monitoring unit configured to perform index monitoring on an index of the target customer base on the insight analysis result;

the early warning unit is configured to respond to the fact that the index of the target customer group exceeds a preset early warning range to carry out early warning, and bind and execute the strategy;

and the feedback unit is configured to perform feedback adjustment on the strategy based on the strategy execution result.

The present disclosure also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method described above are implemented.

The present disclosure also provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method as in any one of the above.

The beneficial effects of the above technical scheme that this disclosure provided include at least:

according to the strategy execution method, the strategy execution device, the strategy execution equipment and the readable medium based on the index early warning, when the customer group management is carried out, the indexes are used as carriers for monitoring and checking, the indexes are constructed in a model mode by obtaining the indexes, new indexes are derived through combination among the indexes, and the indexes are defined and used in multiple directions, so that the circulation of the indexes in a service scene is achieved, accurate indexes are bound with the strategies by means of a big data analysis technology, a model technology, an early warning recommendation technology, a grading technology and the like, so that the data are converted into the service value, the service enabling of the data is realized, the efficient and reasonable strategy execution method is provided, the service scene is rationalized by means of data quantification, the artificial interference in the service is reduced, and the efficient and reasonable effect is achieved.

Drawings

In order to more clearly explain the technical solutions in the embodiments of the present disclosure, the drawings that are needed to be used in the description of the embodiments will be briefly introduced below. Other features, objects, and advantages of the present disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.

Fig. 1 is a flowchart of a method for performing a strategy based on index pre-warning according to an embodiment of the present disclosure;

FIG. 2 is a flowchart illustration of an insight analysis provided by an embodiment of the present disclosure;

fig. 3 is a diagram illustrating a structure example of a policy execution device based on index early warning according to an embodiment of the present disclosure;

FIG. 4 is a schematic block diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

For a better understanding of the present disclosure, various aspects of the present disclosure will be described in more detail with reference to the accompanying drawings. It should be understood that the detailed description is merely illustrative of exemplary embodiments of the disclosure and is not intended to limit the scope of the disclosure in any way. Like reference numerals refer to like elements throughout the specification. The expression "and/or" includes any and all combinations of one or more of the associated listed items.

In the drawings, the size, dimension, and shape of elements have been slightly adjusted for convenience of explanation. The figures are purely diagrammatic and not drawn to scale. As used herein, the terms "approximately", "about" and the like are used as table-approximating terms and not as table-degree terms, and are intended to account for inherent deviations in measured or calculated values that would be recognized by one of ordinary skill in the art. In addition, in the present disclosure, the order in which the processes of the respective steps are described does not necessarily indicate an order in which the processes occur in actual operation, unless explicitly defined otherwise or can be inferred from the context.

It will be further understood that terms such as "comprising," "including," "having," "including," and/or "containing," when used in this specification, are open-ended and not closed-ended, and specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. Furthermore, when a statement such as "at least one of" appears after a list of listed features, it modifies that entire list of features rather than merely individual elements of the list. Furthermore, when describing embodiments of the present disclosure, the use of "may" mean "one or more embodiments of the present disclosure. Also, the term "exemplary" is intended to refer to examples or illustrations.

Unless otherwise defined, all terms (including engineering and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

As shown in fig. 1, the present disclosure provides a strategy execution method based on index early warning, including the following steps S100 to S500:

and step S100, acquiring indexes of the target passenger group.

In some embodiments, before the obtaining of the index of the target guest group, the policy execution method based on index early warning further includes the following steps S001 to S003:

and S001, constructing a guest group rule. Specifically, a guest group rule is constructed based on an actual service scene, and corresponding guest group screening conditions are provided for free drag combination, so that a target guest group conforming to the service scene is obtained through the combined guest group rule. Storing the guest group rule in the canvas into a database in a json data mode, when the json data is large, segmenting the json data, storing the json data into corresponding fields in the database, and storing the json data for multiple times in a data table according to an orderly adding method.

In step S002, the client information conforming to the guest group rule is acquired based on the guest group rule. Specifically, the customer group rules may be configured and combined in a canvas manner, an sql statement is generated after configuration is completed, and the customer information conforming to the customer group rules is acquired based on a result of query of the sql statement on a big data platform. As an example, a json data body based on the guest group rule performs data conversion, the conditions are spliced into sql statements according to different conditions represented by different nodes, the sql statements are sent to a big data platform query result, the customer information meeting the guest group rule is previewed, and the customer information is returned.

And step S003, the guest group corresponding to the guest information is taken as a target guest group and stored. Specifically, the cardholder information of the target guest group is stored in a database, so that query is facilitated. And for the created new target guest group, the approval is needed, after all the node approval passes, the current target guest group becomes in an effective state and can be used, and when running approval or previewing is carried out next time, the current target guest group can be inquired in the database. As an example, the database may be an oracle database.

In some embodiments, the target customer group metrics include a customer group metric and a life cycle metric. The customer group index refers to details of a target customer group and the target customer group displayed after the index is selected, the number of the selected target customer groups can be one or more, customer information of the target customer group can be screened according to a preset customer group index after the target customer group is selected, standard customer information is obtained, and the standard customer information is displayed in a chart mode.

Specifically, the target customer group index provides a screening basis for customer group insights, life cycle structure insights, custom insights and the like. Before defining indexes, a corresponding model is defined, after the indexes are selected and introduced, an sql statement is generated based on the model of the indexes, corresponding statistical results are obtained from a big data platform based on the sql statement, the statistical results are displayed in an icon mode, and each index represents statistical information. And acquiring the same part of each index based on the actual service scene and the implementation mode of each index, and performing abstract processing on all subsequent indexes according to the process to avoid repeated development processing. As an example, the same portion may be a summary portion and/or an aggregate portion, etc.

In some embodiments, the method for obtaining the life cycle index includes the following steps:

firstly, a main-auxiliary phase method is adopted for dividing a life cycle of the target guest group.

Specifically, the main stage rules and the auxiliary stage rules in the main and auxiliary stage methods are mainly combined by performing logical operation on preset separation rule fields through metadata-controlled fields, so as to generate corresponding main stage rules or auxiliary stage rules, wherein each main stage rule or auxiliary stage rule is displayed through the metadata-controlled fields.

Firstly, when the main and auxiliary stages are divided, the target guest group is operated in a canvas mode, the division rule of each stage is flexibly selected and configured based on the actual service scene to obtain a json data body, and the json data body is stored in a database.

And then, calculating the division rule of each stage by adopting a trial calculation function, acquiring migration data of the target passenger group, and displaying the migration data in a chart form. Specifically, json data bodies in a database are spliced together, converted into sql statements based on node relations, sent to a big data platform for calculation, client information is screened according to configured division rules of each stage, consumption rules of clients are calculated based on main and auxiliary relations, namely circulation conditions of the clients in a preset time period, migration data of each client in a target client group are obtained, and a chart is adopted for displaying.

And finally, acquiring a main and auxiliary stage list based on migration data of the target passenger group to realize the division of the life cycle. Meanwhile, the target guest group can be managed through the main and auxiliary phase name sheets, so that the guest group management of the life cycle is achieved, and the relationship between the life cycle and the guest group is opened.

And secondly, analyzing the division rule of each stage of the life cycle to obtain at least one life cycle index. Specifically, the division rule of each stage is the corresponding life cycle index, and the indexes of the life cycle can be combined, calculated and analyzed through the flexible configuration of the division rule of each stage of the life cycle to form a new life cycle index, and the new life cycle index is synchronized for use.

And step S200, performing insight analysis on the indexes of the target customer group to generate an insight analysis result.

In some embodiments, as shown in fig. 2, the performing an insight analysis on the index of the target customer group to generate an insight analysis result includes the following steps:

and firstly, performing insight analysis on the passenger group index or the life cycle index based on the target passenger group to generate an insight analysis result. Specifically, when the customer group is subjected to insight, after a target customer group and a corresponding index are selected, data verification is carried out, after the data verification, insight sql statements are formed by splicing in a preview mode and sent to a big data platform for inquiry, the showing condition of the index is obtained, and an insight analysis result is generated.

As an example, the customer information of all effective customer groups is stored in a customer group table in the big data platform according to the customer group numbers, and an insight sql statement is formed after a target customer group is selected, wherein in the insight sql statement, the table name is a customer group table, and if the condition is the customer group number, all customers in the target customer group can be queried; and then, assigning the insight sql statement, sending the assigned insight sql statement to a big data platform for query, comparing and analyzing a query result with all the clients in the target guest group queried in the client guest group table, acquiring the display condition of the index, and generating an insight analysis result.

And secondly, updating a client group table in response to the insight analysis result that the client group index or the life cycle index is a client who does not completely show the target client group.

And thirdly, responding to the insights and analysis result, namely completely displaying the customers of the target customer group for the customer group index or the life cycle index, and performing visual display. By way of example, the index observation of the created customer group can be realized by adopting an insight analysis result presentation through a histogram, a pie chart, a line chart and the like.

And step S300, monitoring the indexes of the target passenger group based on the insight analysis result.

In some embodiments, the index of the target customer group is monitored based on the visually displayed insight analysis result.

And S400, responding to the fact that the index of the target guest group exceeds a preset early warning range, carrying out early warning, and binding and executing the strategy.

In some embodiments, the responding to the fact that the index of the target guest group exceeds a preset early warning range to perform early warning and the binding and execution of the policy specifically include:

firstly, when the indexes of the target passenger group shake, early warning configuration is carried out, and an early warning range is preset. The early warning range comprises an early warning upper limit value, an early warning lower limit value and a numerical range between the early warning upper limit value and the early warning lower limit value.

And secondly, responding to the fact that the index of the target passenger group exceeds a preset early warning range, carrying out early warning processing, and meanwhile, binding strategies. Specifically, when the index is higher than the early warning upper limit value or lower than the early warning lower limit value, early warning processing is performed, and meanwhile, policy binding is performed based on the blood relationship between the index and the policy, that is, different policies are recommended correspondingly when different indexes perform early warning. For example, the blood relationship between the index and the strategy is accumulated based on machine learning, and mining and learning are performed step by step, and meanwhile, certain manual judgment can be assisted.

And thirdly, executing the strategy based on the bound strategy. Specifically, when the index exceeds the early warning range, the strategy is automatically executed after the strategy is bound.

Step S500, performing feedback adjustment on the policy based on the policy execution result.

In some embodiments, the performing feedback adjustment on the policy based on the policy execution result specifically includes the following steps:

and the first step, responding to the strategy to start executing, and monitoring the change range of the index of the target customer group.

And secondly, verifying the integrity of the strategy based on the transformation conditions of the indexes before and after the strategy is executed.

And thirdly, responding to the completion of the strategy execution and the completeness of the strategy, and acquiring a strategy execution result.

And fourthly, carrying out quantitative analysis on the strategy execution result to form a feedback adjustment suggestion. By way of example, staff scoring can be added to evaluate the strategy in addition to data quantization when performing quantitative analysis.

And fifthly, adjusting variables in the strategy based on the feedback adjustment suggestion. Specifically, the adjusted strategy is absorbed to a strategy library, and the strategy is awakened when the follow-up indexes exceed the early warning range, so that the intelligent automatic strategy execution is realized.

As shown in fig. 3, the present disclosure further provides a policy enforcement device based on indicator early warning, which is characterized by including:

an acquisition unit 101 configured to acquire an index of a target guest group;

an insight unit 102 configured to perform insight analysis on the index of the target customer group to generate an insight analysis result;

a monitoring unit 103 configured to perform index monitoring on an index of the target customer group based on the insight analysis result;

the early warning unit 104 is configured to perform early warning in response to the index of the target guest group exceeding a preset early warning range, and perform binding and execution of a policy;

and a feedback unit 105 configured to perform feedback adjustment on the policy based on the policy execution result.

In a possible implementation manner of some embodiments, before the obtaining unit 101, the policy execution device based on index early warning further includes: constructing a guest group rule; acquiring customer information according with the customer group rule based on the customer group rule; and taking the guest group corresponding to the guest information as a target guest group and storing the target guest group.

In a possible implementation manner of some embodiments, the index of the target guest group includes a guest group index and a life cycle index.

In a possible implementation manner of some embodiments, the method for obtaining the life cycle index includes: dividing life cycle of the target customer group by adopting a main and auxiliary stage method; and analyzing the division rule of each stage of the life cycle to obtain at least one life cycle index.

In a possible implementation manner of some embodiments, the insight unit 102 of the index-based warning policy execution apparatus is further configured to: performing insight analysis on the customer group index or the life cycle index based on the target customer group to generate an insight analysis result; responding to the insight analysis result that the customer group index or the life cycle index does not completely show the customers of the target customer group, and prompting error information; and responding to the insights and analysis result to the client who completely displays the target client group for the client group index or the life cycle index, and performing visual display.

In a possible implementation manner of some embodiments, the warning unit 104 of the index-based warning policy execution apparatus is further configured to: when the indexes of the target customer group shake, performing early warning configuration and presetting an early warning range; responding to the fact that the index of the target customer group exceeds a preset early warning range, carrying out early warning processing, and meanwhile, binding strategies; and executing the policy based on the bound policy.

In a possible implementation manner of some embodiments, the feedback unit 105 of the index-based warning policy enforcement device is further configured to: responding to the strategy to start execution, and monitoring the change range of the index of the target passenger group; verifying the integrity of the strategy based on the transformation conditions of the indexes before and after the strategy is executed; responding to the completion of the strategy execution and the completeness of the strategy, and acquiring a strategy execution result; carrying out quantitative analysis on the strategy execution result to form a feedback adjustment suggestion; and adjusting variables in the strategy based on the feedback adjustment suggestion.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not constitute any limitation to the implementation process of the embodiments of the present disclosure.

Referring now to fig. 4, a block diagram of an electronic device 400 suitable for use in implementing some embodiments of the present disclosure is shown. The server shown in fig. 4 is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present disclosure.

As shown in fig. 4, electronic device 400 may include a processing device (e.g., central processing unit, graphics processor, etc.) 401 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage device 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the electronic apparatus 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

Generally, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate wirelessly or by wire with other devices to exchange data. While fig. 4 illustrates an electronic device 400 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be alternatively implemented or provided. Each block shown in fig. 4 may represent one device or may represent multiple devices as desired.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 409, or from the storage device 408, or from the ROM 402. The computer program, when executed by the processing apparatus 401, performs the above-described functions defined in the methods of some embodiments of the present disclosure.

It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.

The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring indexes of a target guest group; performing insight analysis on the indexes of the target customer group to generate an insight analysis result; monitoring the indexes of the target customer base on the insights and analysis results; responding to the fact that the index of the target customer group exceeds a preset early warning range to carry out early warning, and binding and executing the strategy; and performing feedback adjustment on the strategy based on the strategy execution result.

Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, which may be described as: a processor comprises an acquisition unit, an insight unit, a monitoring unit, an early warning unit and a feedback unit. Here, the names of these units do not constitute a limitation to the unit itself in some cases, and for example, the acquisition unit may also be described as "a unit that acquires an index of a target guest group".

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.

Claims

1. A strategy execution method based on index early warning is characterized by comprising the following steps:

acquiring indexes of a target guest group;

carrying out index monitoring on indexes of the target customer group based on the insight analysis result;

responding to the fact that the index of the target guest group exceeds a preset early warning range to carry out early warning, and binding and executing the strategy;

2. The index-based early warning policy enforcement method of claim 1, wherein prior to the obtaining the index of the target customer group, the method further comprises:

constructing a guest group rule;

acquiring customer information conforming to the customer group rule based on the customer group rule;

3. The index-based early warning policy enforcement method of claim 1, wherein the target customer group index comprises a customer group index and a life cycle index.

4. The index early warning-based strategy execution method according to claim 3, wherein the life cycle index acquisition method comprises the following steps:

dividing the life cycle of the target guest group by adopting a main and auxiliary phase method;

5. The index early warning-based strategy execution method of claim 3, wherein the performing insight analysis on the indexes of the target customer group to generate an insight analysis result specifically comprises:

performing insight analysis on the passenger group index or the life cycle index based on the target passenger group to generate an insight analysis result;

prompting error information in response to an insight analysis result that the customer group index or the life cycle index does not fully show the customers of the target customer group;

and responding to the insight analysis result to completely display the customers of the target customer group for the customer group index or the life cycle index, and performing visual display.

6. The index-based early warning policy execution method according to claim 1, wherein the early warning is performed in response to the fact that the index of the target guest group exceeds a preset early warning range, and the binding and execution of the policy are performed, specifically comprising:

when the indexes of the target guest group shake, performing early warning configuration and presetting an early warning range; responding to the fact that the index of the target guest group exceeds a preset early warning range, carrying out early warning processing, and meanwhile, binding strategies;

and executing the policy based on the bound policy.

7. The index early warning-based policy execution method according to claim 1, wherein the feedback adjustment of the policy is performed based on the policy execution result, and specifically comprises: responding to the strategy to start execution, and monitoring the change range of the index of the target guest group; verifying the integrity of the policy based on the transformation of the indicators before and after the policy is executed;

adjusting variables in the policy based on the feedback adjustment suggestion.

8. A strategy execution device based on index early warning is characterized by comprising: an acquisition unit configured to acquire an index of a target guest group;

the early warning unit is configured to perform early warning in response to the index of the target guest group exceeding a preset early warning range, and perform binding and execution of a strategy;

a feedback unit configured to perform feedback adjustment on the policy based on a policy execution result.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.