CN112202575A - Charging data processing method and device for cloud computing resources - Google Patents
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- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
- H04L12/141—Indication of costs
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
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Abstract
The application provides a charging data processing method and device for cloud computing resources, relates to the technical field of cloud computing, and comprises the steps of determining an integral value of a registered user based on a preset positive action and a preset negative action generated by the user on a platform; receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference; determining a current integral value of the user, wherein the current integral value is determined based on a preset positive action and a preset negative action generated on a platform by the user; determining a current additional discount coefficient according to the current integral value; and determining the current preferential value of the cloud computing resource according to the current additional preferential coefficient and the initial preferential, so that the problem of unreasonable existing charging mode is solved.
Description
Technical Field
The application relates to the technical field of cloud computing, in particular to a charging data processing method and device for cloud computing resources.
Background
Cloud computing is an augmentation, usage, and interaction model for internet-based related services, typically involving the provision of dynamically scalable and often virtualized resources over the internet. While the payment function of the cloud computing manufacturer is opened towards the customer to meet the customer demand to the maximum extent, the cloud computing manufacturer generally guides the customer to order the cloud computing product in terms of product design, pricing, marketing and the like in a prepayment mode as much as possible, for example, the customer can enjoy a lower product price when ordering in the prepayment mode.
The discount preferential strategies adopted by the prepaid products (generally purchased in a month and year) of various cloud computing manufacturers when a user newly purchases and continues to purchase are generally as follows: presetting a fixed discount as a discount for the product, such as 8 discounts for new purchase of the cloud host product and 9 discounts for renewal of the charge; or, a discount strategy according to the purchase duration or the charge duration is preset for the product, such as 9 folds for a new purchase or charge duration of a cloud host product in 1 year, 7 folds for 2 years, 5 folds for 3 years, or 1 month cost for 1 year and 3 months cost for 2 years; or, according to the business contract signed by the manufacturer and the user, corresponding fixed discount is given or the full discount is given according to the new purchase/charge duration, for example, the A user signs the contract according to the discount of 9, and the B user signs the contract according to the discount of 8 in 1 year.
Under the former two strategies, the discount offers enjoyed by all users are completely the same under the condition of the same product and the same new purchase/charge duration, and no difference exists. The third strategy makes the discount offers of different users different to a certain extent, because generally, most users with high monthly consumption potential can obtain a relatively lower discount offer when business negotiations.
Disclosure of Invention
The application aims to provide a charging data processing method and device for cloud computing resources, so as to relieve the technical problem of unreasonable charging in the prior art.
In a first aspect, an embodiment of the present application provides a method for processing charging data of cloud computing resources, including:
determining an integral value of a registered user based on a preset positive action and a preset negative action generated by the user on a platform;
receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference;
determining a current integral value of the user, wherein the current integral value is determined based on a preset positive action and a preset negative action generated on a platform by the user;
determining a current additional discount coefficient according to the current integral value;
and determining a current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit.
In an alternative embodiment, the predetermined forward behavior comprises one or more of:
perfecting the registration information on the platform, consuming on the platform, and guiding the platform.
In an alternative embodiment, the preset negative-going behavior comprises one or more of:
an unsubscribe operation, a due/no-last operation, and a monthly decline operation.
In an optional embodiment, the determining a current extra-benefit coefficient according to the current integration value includes:
determining the consumption capacity level of the user according to the current integral value;
and determining the current additional discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resources.
In an optional embodiment, before the step of determining the current additional offer coefficient according to the consumption capability level to which the user belongs and pre-configured additional offer configuration data corresponding to the purchased cloud computing resource, the method further includes:
and presetting the corresponding relation among the user consumption potential grade, the product line identification and the additional discount preferential coefficient.
In an optional embodiment, the step of determining the current additional benefit coefficient according to the consumption capability level to which the user belongs and the product line identifier of the purchased cloud computing resource includes:
and matching in the preset corresponding relation among the user consumption potential grade, the product line identification and the extra discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resource, and determining the current extra discount coefficient.
In a second aspect, an embodiment of the present application provides a charging data processing apparatus for cloud computing resources, including:
the system comprises a first determination module, a second determination module and a third determination module, wherein the first determination module is used for determining an integral value of a registered user based on a preset positive action and a preset negative action generated by the registered user on a platform;
the receiving module is used for receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference;
the second determination module is used for determining a current integral value of the user, and the current integral value is determined based on a preset positive-going behavior and a preset negative-going behavior generated on a platform by the user;
a third determining module, configured to determine a current extra-offer coefficient according to the current integration value;
and the fourth determining module is used for determining the current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit.
In an alternative embodiment, the predetermined forward behavior comprises one or more of:
perfecting the registration information on the platform, consuming on the platform, and guiding the platform.
In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program executable on the processor, and the processor implements the steps of the method described in any one of the foregoing embodiments when executing the computer program.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon machine-executable instructions that, when invoked and executed by a processor, cause the processor to perform the method of any of the preceding embodiments.
The embodiment of the application provides a charging data processing method and device for cloud computing resources. Determining an integral value of a registered user by means of a preset positive-going behavior and a preset negative-going behavior generated on a platform based on the user; receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference; determining a current integral value of the user, wherein the current integral value is determined based on a preset positive action and a preset negative action generated on a platform by the user; determining a current additional discount coefficient according to the current integral value; and determining a current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit. Therefore, the user behaviors can be quantized, and the corresponding preferential mode is determined based on the quantized user behaviors, so that the user mode can better meet the user requirements, and the user experience is improved.
Drawings
In order to more clearly illustrate the detailed description of the present application or the technical solutions in the prior art, the drawings needed to be used in the detailed description of the present application or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flowchart of a charging data processing method for cloud computing resources according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another charging data processing method for cloud computing resources according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a charging data processing apparatus for cloud computing resources according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Fig. 1 is a schematic flowchart of a charging data processing method for cloud computing resources according to an embodiment of the present application. As shown in fig. 1, the method includes:
and S110, determining the integral value of the user based on the preset positive behavior and the preset negative behavior generated on the platform by the registered user.
Wherein the user may register on the platform. After a user registers with the platform, services provided by the platform may be used. The services provided by the platform can comprise various services such as purchasing cloud computing resources, paying for the purchased cloud computing resources, knowing about information related to the cloud computing resources and recommending new users. The actions of a user registering on the platform and using the services provided by the platform can be regarded as the actions generated by the user on the platform. The behavior of the user on the platform may be classified in advance, for example, into positive and negative categories.
When the user generates corresponding preset forward behavior on the platform, corresponding points can be issued to the user; when the user generates a corresponding preset negative action on the platform, the system automatically deducts a corresponding integral from the user. Therefore, the user behaviors are quantized, and the more the user points are, the more the forward behaviors of the user are considered, namely the better the user is; the less, or even negative, the user's score, the more negative behavior the user is considered, i.e., the worse the user is. Based on the quantified user behavior, each user can be evaluated so as to better provide services for the user.
As an example, the preset forward behavior includes one or more of: perfecting the registration information on the platform, consuming on the platform and guiding the platform.
For example, the preset forward behavior includes, but is not limited to, user perfecting real-name authentication information, ordering/renewing product resources, inviting other users to complete registration/authentication/ordering/renewing activities, monthly consumption increase of traffic/storage/API/peak bandwidth class products, and the like.
For each forward behavior, points allocated to the user may be preset, and point issuing policies corresponding to different behaviors may be the same or different, and may be specifically determined according to actual needs. Wherein the more the behavior meets the expectations of the platform for the user, the more points the corresponding user can get. For example, when a user completes business real-name authentication more points are issued than when the user completes personal real-name authentication, the points issued when the user orders high-viscosity high-gross profit products such as a cloud host may be more points than when the user orders low-viscosity low-gross profit products such as a CDN, cloud communication, and the like.
As another example, the predetermined negative-going behavior includes one or more of: an unsubscribe operation, a due/no-last operation, and a monthly decline operation.
For example, the preset negative behavior includes, but is not limited to, unsubscribing from the user for product resources, expiration of product resources for no-go, reduction in monthly consumption of traffic/storage/API/peak bandwidth class products, and the like.
For each negative-going behavior, the integral of the user can be preset and subtracted, and the integral subtraction strategies corresponding to different behaviors can be the same or different and can be determined according to actual needs. Wherein the more this behavior deviates from the platform's expectations for the user, the more points are deducted.
S120, receiving an order request of a user, wherein the order request is used for requesting to purchase cloud computing resources, and the cloud computing resources are provided with initial offers correspondingly.
The user can order the product through the cloud platform, the order can be that the product is mainly cloud computing resources, and after the cloud computing resources are purchased, a cloud computing product instance can be created, so that corresponding cloud services can be provided for the user who purchases the product.
The order request at the user may include, among other things, purchasing a new product or renewing a purchased product. The user may trigger the subscription request based on a user interface provided by the cloud platform through the client. For example, the client may display a product provided by the cloud platform, the user may trigger a purchase operation for the displayed product, and the client generates an order request and sends the order request to the cloud platform after receiving the purchase operation.
The order request may carry a product identification of the cloud computing product. Initial offers of various cloud computing products can be predefined, and the initial offers and product identifications are correspondingly stored in a database. After receiving the order request, the initial offer may be obtained in the database based on the product identifier carried by the order request.
And S130, determining a current integral value of the user, wherein the current integral value is determined based on the preset positive action and the preset negative action generated on the platform by the user.
The cloud platform can count the user behaviors in real time and determine the integral value of each user, and the integral value of each user can be stored in the database corresponding to the user identification. After receiving a subscription request of a user, the subscription request may include a user identification, and a corresponding credit value may be obtained in the database according to the user identification, wherein a current credit system of the user is the credit value determined based on user behavior before receiving the subscription request.
And S140, determining the current extra discount coefficient according to the current integral value.
The correspondence between the integrated value and the extra benefit coefficient may be defined in advance. The correspondence may be a correspondence of the range of the integration value and the additional coupon coefficient.
Based on the current integral value of the user, matching can be performed in the corresponding relation between the predetermined integral value and the extra benefit coefficient, and the corresponding current extra benefit coefficient is determined.
In addition, a conversion formula between the integral value and the extra benefit coefficient may be defined in advance, and the current extra benefit coefficient may be calculated based on the current integral value and the conversion formula.
And S150, determining a current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit.
And integrating the current additional benefit coefficient and the initial benefit to obtain a current benefit value corresponding to the current subscription request of the user, and generating a subscription bill corresponding to the subscription request based on the current benefit value so that the user can confirm and pay the bill and the like.
Because the consumption potentials of different users are different, and the platform promotion operation activities also have different bill-forming conversion effects on different users, the discount benefits of the platform can better obtain the benefits only when the platform is inclined towards the users with higher consumption potentials and higher bill-forming conversion possibilities.
According to the embodiment of the application, the user behaviors are quantized, and the corresponding preferential mode is determined based on the quantized user behaviors, so that the user mode can better meet the user requirements, and the user experience is improved.
In some embodiments, after the user behavior is quantified, the user consumption potential can be quantified through the user integral, and the mechanism of discount offer when the user newly purchases and renews the product is dynamically adjusted according to the user consumption potential level, so that the discount offer of the platform is really inclined to the high-potential customer as far as possible, the benefit maximization of the platform and the user is realized, and the win-win effect is realized. As an example, as shown in fig. 2, the step S140 may be specifically implemented by the following steps:
and S210, determining the consumption capacity level of the user according to the current integral value.
Wherein a correspondence between the integrated value and the consumption capability level, which indicates a range of the integrated value corresponding to each consumption capability level, may be defined in advance. Based on the current credit value, a consuming capacity level to which the current user belongs may be determined.
And calculating according to the current user point value and a preset consumption capacity grade calculation formula to obtain the consumption potential grade of the user, wherein the higher grade represents the greater consumption potential. For example, the predetermined calculation formula for calculating the consumption potential level of the user according to the accumulated points of the user includes, but is not limited to, falling in steps according to the size interval of the points, such as F (x) { Li | x ∈ (Ni, Nj ], 0 ≦ i < j ≦ p, 0 ≦ Ni < Nj ≦ 2^32 }.
And S220, determining the current additional discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resource.
Wherein, the corresponding relation of the user consumption potential grade, the product line identification and the additional discount preferential coefficient can be preset. And then, according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resource, matching is carried out in the corresponding relation of the preset user consumption potential grade, the product line identification and the extra discount coefficient, and the current extra discount coefficient is determined. The product line identifier may be carried in the order request, or the product line identifier corresponding to the product line identifier may be determined based on the product identifier carried in the user request.
As an example, extra offer configuration data may be preset, and the configuration data may be composed of a series of triple data of < user consumption potential level, product line identification, extra discount offer coefficient >. Based on the three groups of data, the additional discount coefficient used when the user newly purchases or renews the product example can be obtained according to the user consumption potential grade and the resource example product line identifier to be newly purchased or renewed.
And calculating to obtain the final discount offer of the user according to the additional discount offer coefficient and the effective official network discount offer of all users or the discount offer set when the user signs up. This makes it possible to achieve a finer granularity of the benefit to the user.
The final discount offer of the user can be equal to the official website discount offer which is effective for all users by the platform or the discount offer which is set when the user signs up.
It should be noted that, due to the high or low negotiation capacity of different businesses and the efficiency and cost of ordering, many times, users with low consumption potential can enjoy low discount even than high potential customers. In addition, in the business contract period, the discount offer of the user can be dynamically adjusted according to the actual consumption potential of the user, so that the user is encouraged to generate more consumption under the platform, unless the user signs the contract again, and as the user knows that most business contracts have a sign period (generally taking years as units), the contracts are generally difficult to be invalidated and re-signed before the contracts are not expired, and thus the platform is likely to waste some sales opportunities.
According to the embodiment of the application, the user behaviors are quantized, the user is classified based on the quantization result, and the corresponding preferential mode is determined based on the classified user, so that the user mode can better meet the user requirement, and the user experience is improved.
Fig. 3 is a schematic structural diagram of a charging data processing apparatus for cloud computing resources according to an embodiment of the present application. As shown in fig. 3, the apparatus includes:
a first determining module 301, configured to determine an integral value of a registered user based on a preset positive behavior and a preset negative behavior generated by the user on a platform;
a receiving module 302, configured to receive a subscription request of the user, where the subscription request is used to request to purchase a cloud computing resource, and the cloud computing resource has an initial offer;
a second determining module 303, configured to determine a current integration value of the user, where the current integration value is determined based on a preset positive-going behavior and a preset negative-going behavior generated by the user on a platform;
a third determining module 304, configured to determine a current extra-offer coefficient according to the current integration value;
a fourth determining module 305, configured to determine a current offer value of the cloud computing resource according to the current additional offer coefficient and the initial offer.
In some embodiments, the preset forward behavior comprises one or more of:
perfecting the registration information on the platform, consuming on the platform, and guiding the platform.
In some embodiments, the preset negative-going behavior comprises one or more of:
an unsubscribe operation, a due/no-last operation, and a monthly decline operation.
In some embodiments, the third determining module 304 is specifically configured to:
determining the consumption capacity level of the user according to the current integral value;
and determining the current additional discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resources.
In some embodiments, the third determining module 304 is specifically configured to:
and presetting the corresponding relation among the user consumption potential grade, the product line identification and the additional discount preferential coefficient.
In some embodiments, the third determining module 304 is specifically configured to:
and matching in the preset corresponding relation among the user consumption potential grade, the product line identification and the extra discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resource, and determining the current extra discount coefficient.
The charging data processing device for cloud computing resources provided by the embodiment of the application has the same technical characteristics as the charging data processing method for cloud computing resources provided by the embodiment of the application, so that the same technical problems can be solved, and the same technical effects can be achieved.
As shown in fig. 4, in a computer device 700 provided in an embodiment of the present application, the computer device 700 may be a platform in the foregoing embodiments, and the computer device 700 may specifically include: the charging data processing method comprises a processor 701, a memory 702 and a bus, wherein the memory 702 stores machine readable instructions executable by the processor 701, when a computer device runs, the processor 701 and the memory 702 are communicated through the bus, and the processor 701 executes the machine readable instructions to execute the steps of the charging data processing method of the cloud computing resource.
Specifically, the memory 702 and the processor 701 may be general-purpose memory and processor, which are not specifically limited herein, and when the processor 701 executes a computer program stored in the memory 702, the charging data processing method for cloud computing resources may be executed.
Corresponding to the charging data processing method for the cloud computing resources, an embodiment of the present application further provides a computer-readable storage medium, where a machine executable instruction is stored in the computer-readable storage medium, and when the computer executable instruction is called and executed by a processor, the computer executable instruction causes the processor to execute the steps of the charging data processing method for the cloud computing resources.
The charging data processing device for cloud computing resources provided by the embodiment of the application can be specific hardware on equipment, or software or firmware installed on the equipment, and the like. The device provided by the embodiment of the present application has the same implementation principle and technical effect as the foregoing method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiments where no part of the device embodiments is mentioned. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the foregoing systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. 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 which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes several instructions to enable a shunting device (which may be a personal computer, a server, or a computer device) to execute all or part of the steps of the mobile control method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the scope of the embodiments of the present application. Are intended to be covered by the scope of the present application.
Claims (10)
1. A charging data processing method of cloud computing resources is characterized by comprising the following steps:
determining an integral value of a registered user based on a preset positive action and a preset negative action generated by the user on a platform;
receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference;
determining a current integral value of the user, wherein the current integral value is determined based on a preset positive action and a preset negative action generated on a platform by the user;
determining a current additional discount coefficient according to the current integral value;
and determining a current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit.
2. The method of claim 1, wherein the pre-set forward behavior comprises one or more of:
perfecting the registration information on the platform, consuming on the platform, and guiding the platform.
3. The method of claim 1, wherein the predetermined negative-going behavior comprises one or more of:
an unsubscribe operation, a due/no-last operation, and a monthly decline operation.
4. The method of claim 1, wherein determining a current bonus coefficient based on the current integration value comprises:
determining the consumption capacity level of the user according to the current integral value;
and determining the current additional discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resources.
5. The method of claim 4, wherein before the step of determining the current additional offer coefficient according to the consumption capability level of the user and the pre-configured additional offer configuration data corresponding to the purchased cloud computing resource, the method further comprises:
and presetting the corresponding relation among the user consumption potential grade, the product line identification and the additional discount preferential coefficient.
6. The method of claim 5, wherein the step of determining the current additional benefit factor according to the consumption capability level of the user and the product line identifier of the purchased cloud computing resource comprises:
and matching in the preset corresponding relation among the user consumption potential grade, the product line identification and the extra discount coefficient according to the consumption capacity grade of the user and the product line identification of the purchased cloud computing resource, and determining the current extra discount coefficient.
7. A charging data processing device for cloud computing resources is characterized by comprising:
the system comprises a first determination module, a second determination module and a third determination module, wherein the first determination module is used for determining an integral value of a registered user based on a preset positive action and a preset negative action generated by the registered user on a platform;
the receiving module is used for receiving a subscription request of the user, wherein the subscription request is used for requesting to purchase cloud computing resources, and the cloud computing resources have initial preference;
the second determination module is used for determining a current integral value of the user, and the current integral value is determined based on a preset positive-going behavior and a preset negative-going behavior generated on a platform by the user;
a third determining module, configured to determine a current extra-offer coefficient according to the current integration value;
and the fourth determining module is used for determining the current benefit value of the cloud computing resource according to the current additional benefit coefficient and the initial benefit.
8. The apparatus of claim 7, wherein the preset forward behavior comprises one or more of:
perfecting the registration information on the platform, consuming on the platform, and guiding the platform.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer readable storage medium having stored thereon machine executable instructions which, when invoked and executed by a processor, cause the processor to execute the method of any of claims 1 to 6.
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| CN109741107A (en) * | 2018-12-30 | 2019-05-10 | 上海掌门科技有限公司 | Favor information determines method, apparatus, electronic equipment and medium |
| CN110135900A (en) * | 2019-05-09 | 2019-08-16 | 达疆网络科技(上海)有限公司 | A kind of real-time discount coupon distribution method based on user behavior |
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| CN109377286A (en) * | 2018-11-07 | 2019-02-22 | 中国平安财产保险股份有限公司 | The method, apparatus and computer equipment of insurance price are calculated based on prediction model |
| CN109741107A (en) * | 2018-12-30 | 2019-05-10 | 上海掌门科技有限公司 | Favor information determines method, apparatus, electronic equipment and medium |
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