CN110706032A - Promotion strategy making method and device, data processing equipment and storage medium - Google Patents
Promotion strategy making method and device, data processing equipment and storage medium Download PDFInfo
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- CN110706032A CN110706032A CN201910935487.5A CN201910935487A CN110706032A CN 110706032 A CN110706032 A CN 110706032A CN 201910935487 A CN201910935487 A CN 201910935487A CN 110706032 A CN110706032 A CN 110706032A
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- G06Q30/00—Commerce
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q30/02—Marketing; Price estimation or determination; Fundraising
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Abstract
The popularization strategy making method and device, the data processing equipment and the storage medium are provided by the application. And formulating a promotion strategy for the target category commodity by acquiring a first score of each promotion node and a second score of the target category commodity at each promotion node and based on the first score and the second score. The first score is obtained by calculating the number of promoted persons of each promotion node, and the first score is positively correlated with the number of promoted persons; and the second score is obtained by calculation according to the operation times of the preset operation type executed on the target category commodity by the promoted personnel of each promotion node. Therefore, when the promotion strategy is formulated for the target category commodity based on the first score and the second score of the target category commodity at each promotion node, the operation behavior of promoted personnel of each promotion node on the target category commodity is considered, and then the promotion effect of the promotion strategy is improved.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and an apparatus for formulating a promotion policy, a data processing device, and a storage medium.
Background
Social e-commerce is an emerging e-commerce model intended to attract potential customers through social means. The promotion activity is published in a social e-commerce platform (for example, a WeChat e-commerce applet), and the promotion effect of the promotion activity on each promotion node needs to be statistically analyzed, so that data reference is provided for the next promotion activity. However, at present, the statistical analysis of the promotion effect of the promotion activity on each promotion node mainly refers to the number of promoted persons of each promotion node, so that the analysis result of the promotion effect has certain limitation.
Disclosure of Invention
The application aims to provide a popularization strategy making method, a popularization strategy making device, data processing equipment and a storage medium, and aims to enable analysis results of popularization activities to be more referential and then improve popularization effects of popularization strategies made based on the analysis results.
One of the objectives of the embodiments of the present application is to provide a method for formulating a promotion policy, which is applied to a data processing device, and the method includes:
aiming at each target promotion node in the promotion activity process, acquiring the number of promoted persons of the target promotion node, and calculating and acquiring a first score of the target promotion node according to the number of promoted persons, wherein the first score is positively correlated with the number of promoted persons;
aiming at each category of promoted commodities of the target promotion node, obtaining the operation times of a preset operation type executed by the promoted personnel on the category of commodities, and calculating according to the operation times to obtain a second score of the category of commodities;
and aiming at the target category commodities, establishing a promotion strategy for the target category commodities according to the first scores of the promotion nodes and the second scores of the target category commodities at the promotion nodes.
Optionally, the promotion activities include a preset number of historical promotion activities, and the step of calculating a first score of the target promotion node according to the number of promoted persons includes:
aiming at each target historical popularization activity in the historical popularization activities, acquiring the historical number of popularized personnel of the target popularization node in the target historical popularization activity;
calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the history number of the promoted personnel;
carrying out attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is in positive correlation with the time interval of the latest promotion activity;
and summing the attenuated first historical scores to obtain the first score.
Optionally, the decay function is:
y＝c*e-kx；
wherein k is a decay factor, c is the history score, and x is the time interval from the most recent promotional activity.
Optionally, the step of calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the historical number of promoted persons includes:
acquiring the historical total amount of promoted persons in the target historical promotion activities, and calculating the ratio of the historical number of the promoted persons to the historical total amount of the promoted persons;
and taking the ratio as a first history score of the target promotion node in the target history promotion activities.
Optionally, the step of formulating, for the target category commodity, a promotion policy for the target category commodity according to the first score of each promotion node and the second score of the target category commodity at each promotion node includes:
according to the preset weight of the first score and the preset weight of the second score, carrying out weighted summation on the first score of each promotion node and the second score of the target category commodity on each promotion node to obtain the weighted score of the target category commodity on each promotion node;
and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
A second object of the embodiments of the present application is to provide a promotion policy making device, which is applied to a data processing device, and the promotion policy making device includes a first score obtaining module, a second score obtaining module, and a policy making module;
the first score acquisition module is used for acquiring the number of promoted persons of each target promotion node in the promotion activity process, and calculating and acquiring a first score of the target promotion node according to the number of promoted persons, wherein the first score is positively correlated with the number of promoted persons;
the second score acquisition module is used for acquiring the operation times of the preset operation types executed by the promoted personnel on the commodities of the category aiming at each category promoted by the target promotion node, and calculating to acquire a second score of the commodity of the category according to the operation times;
the strategy making module is used for making a promotion strategy for the target category commodities according to the first scores of the promotion nodes and the second scores of the target category commodities at the promotion nodes.
Optionally, the promotion activities include a preset number of historical promotion activities, and the first score obtaining module obtains the first score of the target promotion node by:
aiming at each target historical popularization activity in the historical popularization activities, acquiring the historical number of popularized personnel of the target popularization node in the target historical popularization activity;
calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the history number of the promoted personnel;
carrying out attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is in positive correlation with the time interval of the latest promotion activity;
and summing the attenuated first historical scores to obtain the first score.
Optionally, the policy making module makes a promotion policy for the target category commodity by:
according to the preset weight of the first score and the preset weight of the second score, carrying out weighted summation on the first score of each promotion node and the second score of the target category commodity on each promotion node to obtain the weighted score of the target category commodity on each promotion node;
and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
It is a further object of embodiments of the present application to provide a data processing apparatus, including a processor and a memory, where the memory stores machine executable instructions executable by the processor, and the processor can execute the machine executable instructions to implement the promotion policy making method.
It is a fourth object of the embodiments of the present application to provide a storage medium having a computer program stored thereon, where the computer program is executed to implement the promotion policy making method.
Compared with the prior art, the method has the following beneficial effects:
the popularization strategy making method and device, the data processing equipment and the storage medium are provided by the embodiment of the application. And formulating a promotion strategy for the target category commodity by acquiring a first score of each promotion node and a second score of the target category commodity at each promotion node and based on the first score and the second score. The first score is obtained by calculating the number of promoted persons of each promotion node, and the first score is positively correlated with the number of promoted persons; and the second score is obtained by calculation according to the operation times of the preset operation type executed on the target category commodity by the promoted personnel of each promotion node. Therefore, when the promotion strategy is formulated for the target category commodity based on the first score and the second score of the target category commodity at each promotion node, the operation behavior of promoted personnel of each promotion node on the target category commodity is considered, and then the promotion effect of the promotion strategy is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a hardware configuration diagram of a data processing device according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a method for making a promotion policy according to an embodiment of the present application;
fig. 3 is a schematic diagram of a promotion activity process provided in an embodiment of the present application;
FIG. 4 is a table of operation times of various categories of commodities according to an embodiment of the present disclosure;
FIG. 5 is a table of preference scores for categories of merchandise provided by an embodiment of the present application;
FIG. 6 is a second scoring table for each category of merchandise provided in the embodiments of the present application;
fig. 7 is a schematic structural diagram of a popularization policy making device according to an embodiment of the present application.
Icon: 100-a data processing device; 110-a promotion strategy making device; 120-a memory; 130-a processor; 501-a first promotion node; 502-a fourth promotion node; 503-a third promotion node; 504-a second promotion node; 1101-a first score obtaining module; 1102-a second score acquisition module; 1103-policy making module.
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.
In the description of the present application, it is noted that the terms "first", "second", "third", and the like are used merely for distinguishing between descriptions and are not intended to indicate or imply relative importance.
The promotion activities are published in the social e-commerce platform, the promotion effects of the promotion activities on all promotion nodes need to be statistically analyzed, and data references are provided for the next promotion activities. However, at present, the statistical analysis of the promotion effect of the promotion activity on each promotion node mainly refers to the number of promoted persons of each promotion node, so that the analysis result of the promotion effect has certain limitation.
Based on this, the embodiment of the present application provides a method for formulating a promotion policy, which is applied to the data processing device 100. In this embodiment, the data processing device 100 may be, but is not limited to, a smart phone, a Personal Computer (PC), a tablet PC, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), and the like.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of the data processing apparatus 100 according to an embodiment of the present disclosure. The data processing apparatus 100 comprises promotion policy making means 110, a memory 120 and a processor 130.
The memory 120, the processor 130, and the various elements are electrically connected to each other, directly or indirectly, to enable data transfer or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The promotion policy making apparatus 110 includes at least one software function module which can be stored in the memory 120 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the data processing device 100. The processor 130 is configured to execute executable modules stored in the memory 120, such as software function modules and computer programs included in the promotion policy making apparatus 110.
The Memory 120 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction.
The processor 130 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 2, fig. 2 is a flowchart illustrating steps of a popularization policy making method applied to the data processing apparatus 100 shown in fig. 1, and the method including the steps will be described in detail below.
Step S100, aiming at each target promotion node in the promotion activity process, obtaining the number of promoted persons of the target promotion node, and calculating and obtaining a first score of the target promotion node according to the number of promoted persons, wherein the first score is positively correlated with the number of promoted persons.
Step S200, aiming at each category of promoted commodities of the target promotion node, obtaining the operation times of the preset operation types executed by the promoted personnel on the category of commodities, and calculating according to the operation times to obtain a second score of the category of commodities.
Step S300, aiming at the target category commodities, a promotion strategy is made for the target category commodities according to the first scores of the promotion nodes and the second scores of the target category commodities at the promotion nodes.
Therefore, a promotion strategy is formulated based on the first score and the second score by obtaining the first score of each promotion node and the second score of the target category commodity at each promotion node. When a promotion strategy is formulated based on the first score and the second score, the operation behaviors of promoted users of all promotion nodes on the target category commodities are considered, and then the promotion effect of the promotion strategy is improved.
In step S100, when the data processing apparatus 100 performs a promotion activity through a specific platform, there may be a plurality of promotion nodes. For each promotion node, according to the number of promoted persons of the promotion node, a promotion node whose number of promoted persons is greater than a preset person threshold value is called a KOC (Key Opinion Consumer). The KOC can be used as a positive effect of publicizing products in the promotion activities of brand parties, so as to improve the influence of the brand parties in a customer group.
Therefore, when a company operation department needs to perform new promotion activities, the KOCs suitable for the current promotion activities can be screened out according to the KOCs in the historical promotion activities and the specific promotion activity types.
For example, referring to fig. 3, fig. 3 is a schematic diagram illustrating a process of promoting activities. The promoted persons of the first promotion node 501 include a second promotion node 504, a third promotion node 503, and a fourth promotion node 502. The number of promoted persons of the second promotion node 504 is 3, the number of promoted persons of the third promotion node 503 is 2, and the number of promoted persons of the fourth promotion node 502 is 4.
If the preset personnel threshold is 2, the first promotion node 501, the second promotion node 504, and the third promotion node 503 are KOCs.
Optionally, for each target promotion node, the data processing device 100 obtains the number of promoted persons of the target promotion node and the total number of promoted persons of the promotion activity; and calculating the ratio of the number of the promoted persons to the total number of the promoted persons, and taking the ratio as the first score of the target promotion node.
Referring again to fig. 3, in a possible example, if the total number of promoted persons of the promotion activity is 13 persons, and the promoted persons of the first promotion node 501 are 3 persons, the first score of the first promotion node 501 is 3/13. Similarly, the other promotion nodes obtain the corresponding first scores in the above manner.
Optionally, the number of promoted persons of each promotion node can be changed in different promotion activities. For example, the number of promoted persons of the first promotion node 501 in the first promotion activity is 3; in the second promotion activity, the number of promoted persons can be 4; in the third promotion activity, the number of promoted people can be 4.
If the number of promoted people of each promotion node changes, the social relationship of the node user changes, and the influence of the corresponding node user also changes. It should be understood that the greater the number of promoted people for each node, the greater its corresponding impact.
Based on this, considering the change of the influence of each promotion node, aiming at each target historical promotion activity in the preset number of historical promotion activities, the data processing device 100 acquires the historical number of promoted persons of the target promotion node in the target historical promotion activities; and calculating and obtaining a first history score of the promotion node in the target history promotion activities according to the history number of the promoted persons.
The data processing equipment performs attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is positively correlated with the time interval of the latest promotion activity. Further, the data processing device sums each of the attenuated first history scores to obtain the first score.
The data processing equipment acquires the historical total amount of promoted personnel in the target historical promotion activities and calculates the ratio of the historical number of the promoted personnel to the historical total amount of the promoted personnel for each target historical promotion activity; and taking the ratio as a first history score of the target promotion node in the target history promotion activities.
Optionally, the decay function is:
y＝c*e-kx；
wherein k is a decay factor, c is the history score, and x is the time interval from the most recent promotional activity.
For example, taking the first four promotion activities of the first promotion node 501 as an example, if the first score of the first promotion activity is 5, the corresponding x is 3; the first score of the second promotional activity is 4, and the corresponding x is 2; the first score of the third promotion activity is 7 points, and the corresponding x is 1; the first score of the latest promotional activity was 9 points, with the corresponding x being 0. The data processing apparatus 100 adds the first scores of the 4 attenuated promotional activities as the final first score of the last promotional activity of the first promotional node 501.
In this way, the variation of the user social relationship of each promotion node is considered, so that the first score obtained by summing the decayed historical scores has a reference value.
It should be noted that the attenuation function is not limited to the attenuation function provided in the above example, and can be adaptively adjusted according to actual requirements.
Referring to fig. 3 again, step S200 is performed. Taking the second promotion node 504 as an example, the second promotion node 504 includes 3 promoted persons, which are user a, user B and user B, respectively. The data processing apparatus 100 counts the number of operations of the preset operation type operations of the user a, the user B, and the user B on each category of goods. The preset operation type can be purchasing a certain category of goods, clicking a link of a certain category of goods and forwarding a link of a certain category of goods.
Referring to fig. 4, in one promotion activity, the user a performs operation of setting the operation type for the category a commodity for 5 times; the operation frequency of the user B for executing the preset operation type on the type B commodity is 1 time, and the operation frequency for executing the preset operation type on the type C commodity is 2 times; the number of times of the user C performing the operation of the preset operation type on the category C commodity is 1, and the number of times of the user C performing the operation of the preset operation type on the category D commodity is 1.
Alternatively, the data processing apparatus 100 calculates the ratio of the number of times of operations of the same user to perform a preset operation type on different categories of commodities, and takes the ratio as the preference score of the user for each category of commodities. Further, for each category of the commodities, the data processing apparatus 100 counts the obtained sum of the preference scores of the commodities in the category, and calculates a ratio of the sum of the preference scores to the sum of the preference scores of the commodities in all the categories, the ratio being the second score of the commodity in the category.
Referring to fig. 4 again, taking the user B as an example, the number of operations of the preset operation type performed on the product of the category B by the user B is 1, and the number of operations of the preset operation type performed on the product of the category C is 2. Then user B would have a preference score of 1/3 for category B items and 2/3 for category C items. Similarly, the preference scores for the categories of merchandise are shown in FIG. 5.
Further, the category B commodity is taken as an example. The preference score of the user B obtained for the product in the B category is 0.33, and the second score of the product in the B category is 0.33/(0.33+0.66+0.5+0.5+1) ═ 0.11. Similarly, the second scores for the categories of items are shown in fig. 6.
For step S300, the data processing apparatus 100 performs weighted summation on the first score of each promotion node and the second score of the target category commodity at each promotion node according to the preset weight of the first score and the preset weight of the second score, so as to obtain a weighted score of the target category commodity at each promotion node; and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
Referring to fig. 4, the category a commodities promoted by the second promotion node 504 are taken as an example. Suppose the first score is S1The preset weight of the first score is a; the second fraction is S2And the preset weight of the second score is b. The weighted score SUM may be expressed as:
SUM＝a*S1+b*S2；
therefore, the user can adjust the preset weight of the first score and the preset weight of the second score according to actual requirements. For example, if only the first score of each promotion node is needed, b may be adjusted to 0.
Optionally, the data processing device 100 needs to promote the target category of goods, and the data processing device 100 obtains a first score of each promotion node and a second score of the target category of goods at each promotion node; and obtaining the weighted score of the target category commodity at each promotion node according to the preset weight of the first score and the preset weight of the second score.
Further, the data processing device 100 performs sorting according to the value of the weighted score, and selects a promotion node with a pre-set ranking as a main promotion node of the target category of the commodity.
Therefore, when the target category commodity is popularized, the social influence of each popularization node is considered, and the operation behavior of the promoted personnel of each popularization node on the target category commodity is also considered, so that the promotion strategy formulated for the target category commodity can obtain a good popularization effect.
Referring to fig. 7, the present embodiment further provides a promotion policy making apparatus 110, where the promotion policy making apparatus 110 includes at least one functional module that can be stored in the memory 120 in a software form. Functionally divided, the promotion policy making apparatus 110 may include a first score obtaining module 1101, a second score obtaining module 1102, and a policy making module 1103.
The first score obtaining module 1101 is configured to obtain, for each target popularization node in a popularization activity process, the number of promoted persons of the target popularization node, and calculate and obtain a first score of the target popularization node according to the number of promoted persons, where the first score is positively correlated with the number of promoted persons.
In the present embodiment, the first score obtaining module 1101 is configured to perform step S100 in fig. 2, and as to the detailed description of the first score obtaining module 1101, reference may be made to the detailed description of step S100.
The second score obtaining module 1102 obtains, for each category of promoted goods of the target promotion node, the operation times of the preset operation type executed by the promoted person on the category of goods, and calculates and obtains a second score of the category of goods according to the operation times.
In this embodiment, the second score obtaining module 1102 is configured to perform step S200 in fig. 2, and reference may be made to the detailed description of step S200 for a detailed description of the second score obtaining module 1102.
The policy making module 1103 is configured to make a promotion policy for the target category commodity according to the first score of each promotion node and the second score of the target category commodity in each promotion node.
In the present embodiment, the policy making module 1103 is configured to execute step S300 in fig. 2, and as to the detailed description of the policy making module 1103, reference may be made to the detailed description of step S300.
Optionally, the promotion activities include a preset number of historical promotion activities, and the first score obtaining module 1101 obtains the first score of the promotion node by:
aiming at each target historical popularization activity in the historical popularization activities, acquiring the historical number of popularized personnel of the target popularization node in the target historical popularization activity; calculating and obtaining a first history score of the promotion node in the target history promotion activity according to the history number of the promoted personnel; carrying out attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is in positive correlation with the time interval of the latest promotion activity; and summing the attenuated first historical scores to obtain the first score.
Optionally, the policy making module 1103 makes a promotion policy for the target category of goods by:
according to the preset weight of the first score and the preset weight of the second score, carrying out weighted summation on the first score of each promotion node and the second score of the target category commodity on each promotion node to obtain the weighted score of the target category commodity on each promotion node; and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
The embodiment of the present application further provides a data processing device 100, which includes a processor 130 and a memory 120, where the memory 120 stores machine executable instructions that can be executed by the processor 130, and the processor 130 can execute the machine executable instructions to implement the popularization policy making method.
The embodiment of the application also provides a storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed, the popularization strategy making method is realized.
In summary, the popularization policy making method and device, the data processing device, and the storage medium provided by the embodiment of the application are provided. And formulating a promotion strategy for the target category commodity by acquiring a first score of each promotion node and a second score of the target category commodity at each promotion node and based on the first score and the second score. The first score is obtained by calculating the number of promoted persons of each promotion node, and the first score is positively correlated with the number of promoted persons; and the second score is obtained by calculation according to the operation times of the preset operation type executed on the target category commodity by the promoted personnel of each promotion node. Therefore, when the promotion strategy is formulated for the target category commodity based on the first score and the second score of the target category commodity at each promotion node, the operation behavior of promoted personnel of each promotion node on the target category commodity is considered, and then the promotion effect of the promotion strategy is improved.
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 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 modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules 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 stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only for various embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and all such changes or substitutions are included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A promotion strategy making method is applied to a data processing device, and comprises the following steps:
aiming at each target promotion node in the promotion activity process, acquiring the number of promoted persons of the target promotion node, and calculating and acquiring a first score of the target promotion node according to the number of promoted persons, wherein the first score is positively correlated with the number of promoted persons;
aiming at each category of promoted commodities of the target promotion node, obtaining the operation times of a preset operation type executed by the promoted personnel on the category of commodities, and calculating according to the operation times to obtain a second score of the category of commodities;
and aiming at the target category commodities, establishing a promotion strategy for the target category commodities according to the first scores of the promotion nodes and the second scores of the target category commodities at the promotion nodes.
2. The promotion strategy making method according to claim 1, wherein the promotion activities include a preset number of historical promotion activities, and the step of calculating a first score of the target promotion node according to the number of promoted persons comprises:
aiming at each target historical popularization activity in the historical popularization activities, acquiring the historical number of popularized personnel of the target popularization node in the target historical popularization activity;
calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the history number of the promoted personnel;
carrying out attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is in positive correlation with the time interval of the latest promotion activity;
and summing the attenuated first historical scores to obtain the first score.
3. The promotional strategy according to claim 2 wherein said decay function is:
y＝c*e-kx；
wherein k is a decay factor, c is the history score, and x is the time interval from the most recent promotional activity.
4. The promotion strategy making method according to claim 2, wherein the step of calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the history number of promoted persons comprises:
acquiring the historical total amount of promoted persons in the target historical promotion activities, and calculating the ratio of the historical number of the promoted persons to the historical total amount of the promoted persons;
and taking the ratio as a first history score of the target promotion node in the target history promotion activities.
5. The method for formulating the promotion policy according to claim 1, wherein the step of formulating the promotion policy for the target category commodity according to the first score of each promotion node and the second score of the target category commodity at each promotion node comprises:
according to the preset weight of the first score and the preset weight of the second score, carrying out weighted summation on the first score of each promotion node and the second score of the target category commodity on each promotion node to obtain the weighted score of the target category commodity on each promotion node;
and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
6. The popularization strategy making device is applied to data processing equipment and comprises a first score acquisition module, a second score acquisition module and a strategy making module;
the first score acquisition module is used for acquiring the number of promoted persons of each target promotion node in the promotion activity process, and calculating and acquiring a first score of the target promotion node according to the number of promoted persons, wherein the first score is positively correlated with the number of promoted persons;
the second score acquisition module is used for acquiring the operation times of the preset operation types executed by the promoted personnel on the commodities of the category aiming at each category promoted by the target promotion node, and calculating to acquire a second score of the commodity of the category according to the operation times;
the strategy making module is used for making a promotion strategy for the target category commodities according to the first scores of the promotion nodes and the second scores of the target category commodities at the promotion nodes.
7. The promotion strategy formulation apparatus according to claim 6, wherein the promotion activities include a preset number of historical promotion activities, and the first score obtaining module obtains the first score of the target promotion node by:
aiming at each target historical popularization activity in the historical popularization activities, acquiring the historical number of popularized personnel of the target popularization node in the target historical popularization activity;
calculating and obtaining a first history score of the target promotion node in the target history promotion activities according to the history number of the promoted personnel;
carrying out attenuation processing on each first history score according to a preset attenuation function to obtain an attenuated first history score, wherein the attenuation degree of the first history score is in positive correlation with the time interval of the latest promotion activity;
and summing the attenuated first historical scores to obtain the first score.
8. The promotion strategy making device according to claim 6, wherein the strategy making module makes a promotion strategy for the target category commodity by:
according to the preset weight of the first score and the preset weight of the second score, carrying out weighted summation on the first score of each promotion node and the second score of the target category commodity on each promotion node to obtain the weighted score of the target category commodity on each promotion node;
and sequencing the weighted scores to obtain a sequencing result, and formulating a promotion strategy for the target category commodity according to the sequencing result.
9. A data processing apparatus comprising a processor and a memory, the memory storing machine executable instructions executable by the processor to implement the promotional policy making method of any of claims 1-5.
10. A storage medium having stored thereon a computer program which, when executed, implements the promotional strategy formulation method of any of claims 1-5.
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