CN112508656A - Guest-obtaining information processing method and device - Google Patents
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Abstract
The method and the device for processing the customer information firstly obtain the customer information order distribution of the customer information to be optimized and each order event record, secondly determine the dynamic order group contained in the customer information to be optimized based on the customer information order distribution, and then realize the secondary distribution of the order event records based on the order event records placed in the dynamic order group and the static order group, thereby realizing the recombination of the dynamic order group and the static order group. By the design, order event analysis of the customer information to be optimized can be realized based on the order event records of the dynamic order grouping and the static order grouping which are completed through recombination, and the customer information is accurately classified to realize subsequent user positioning.
Description
Technical Field
The invention relates to the technical field of customer acquisition, in particular to a customer acquisition information processing method and device.
Background
With the rapid development of online business, more and more enterprises begin to adopt the novel business model, which not only can reduce the site cost, but also can improve the sales volume. In practical application, it is very critical to accurately classify the acquired information to realize subsequent user positioning, however, the prior art has difficulty in achieving the purpose.
Disclosure of Invention
In order to improve the above problem, the present invention provides a method and an apparatus for processing guest-obtaining information.
A first aspect of an embodiment of the present invention provides a method for processing guest-obtaining information, including:
acquiring customer acquisition information order distribution and each order event record of the customer acquisition information to be optimized;
under the condition that the to-be-optimized customer obtaining information contains dynamic order groups according to the customer obtaining information order distribution, determining matching coefficients between each order event record under the static order groups of the to-be-optimized customer obtaining information and each order event record under the dynamic order groups of the to-be-optimized customer obtaining information according to order event records under the dynamic order groups of the order interaction networks of a plurality of merchant platforms and order heat distribution of the order event records, and adjusting the order event records under the static order groups of the to-be-optimized customer obtaining information, which are matched with the order event records under the dynamic order groups, to be under the corresponding dynamic order groups;
under the condition that the current static order grouping of the customer information to be optimized contains a plurality of order event records, determining a matching coefficient among the order event records of the current static order grouping of the customer information to be optimized according to the order event records of the dynamic order grouping of the order interaction networks of a plurality of merchant platforms and the order heat distribution thereof, and marking the order event records of the current static order grouping according to the matching coefficient among the order event records;
and setting a dynamic order grouping priority for each type of order event record obtained by the mark according to the order event record and the order heat distribution thereof placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms, and adjusting each type of order event record to the dynamic order grouping placed represented by the dynamic order grouping priority.
Optionally, the determining, according to order event records placed in groups of dynamic orders of the order interaction networks of the multiple merchant platforms and order heat distribution thereof, a matching coefficient between each order event record placed in groups of static orders of the to-be-optimized customer information and each order event record placed in groups of dynamic orders of the to-be-optimized customer information, and adjusting the order event records placed in groups of static orders of the to-be-optimized customer information and matched with the order event records placed in groups of dynamic orders to corresponding dynamic order groups comprises:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the determining, according to the order event records grouped and placed by the dynamic orders of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof, a matching coefficient between the order event records grouped and placed by the current static order of the to-be-optimized customer information, and marking the order event records grouped and placed by the current static order according to the matching coefficient between the order event records includes:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the setting of the dynamic order grouping priority for each type of order event record obtained by the above marking according to the order event record placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms includes: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
A second aspect of an embodiment of the present invention provides a guest information processing apparatus, including:
the customer information acquisition module is used for acquiring the customer information order distribution of the customer information to be optimized and each order event record;
the customer information obtaining adjustment module is used for determining matching coefficients between each order event record under the static order grouping of the customer information obtaining information to be optimized and each order event record under the dynamic order grouping of the customer information obtaining platform according to the order event records under the dynamic order grouping and the order heat distribution of the order interaction network of the multiple merchant platforms under the condition that the customer information obtaining to be optimized contains the dynamic order grouping according to the customer information obtaining order distribution, and adjusting the order event records under the static order grouping of the customer information obtaining to be optimized and matched with the order event records under the dynamic order grouping to the corresponding dynamic order grouping;
the customer information obtaining marking module is used for determining a matching coefficient among the order event records under the current static order grouping of the customer information to be optimized according to the order event records under the dynamic order grouping of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof under the condition that the current static order grouping of the customer information to be optimized contains multiple order event records, and marking the order event records under the current static order grouping according to the matching coefficient among the order event records;
and the record grouping setting module is used for setting a dynamic order grouping priority for each type of order event record obtained by the mark according to the order event record and the order heat distribution thereof placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms, and adjusting each type of order event record to the dynamic order grouping represented by the dynamic order grouping priority.
Optionally, the customer information obtaining adjustment module determines a matching coefficient between each order event record in the static order group of the customer information to be optimized and each order event record in the dynamic order group of the customer information to be optimized according to the order event records in the dynamic order group of the order interaction network of the multiple merchant platforms and the order heat distribution thereof, and adjusts the order event record in the static order group of the customer information to be optimized, which matches with the order event record in the dynamic order group of the customer information to be optimized, to a corresponding dynamic order group, specifically includes:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the customer information obtaining marking module determines matching coefficients between the order event records grouped under the current static order of the customer information to be optimized according to the order event records grouped under the dynamic order of the order interaction network of the plurality of merchant platforms and the order heat distribution thereof, and marking the order event records grouped under the current static order according to the matching coefficients between the order event records specifically includes:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the setting, by the record grouping setting module, a dynamic order grouping priority for each type of order event record obtained by the marking according to order event records placed in dynamic order grouping of the order interaction networks of the multiple merchant platforms specifically includes: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
By applying the method and the device, the customer obtaining information order distribution and each order event record of the customer obtaining information to be optimized are firstly obtained, then the dynamic order group contained in the customer obtaining information to be optimized is determined based on the customer obtaining information order distribution, and then the order event records placed in the dynamic order group and the static order group are secondarily distributed to realize the recombination of the dynamic order group and the static order group. By the design, order event analysis of the customer information to be optimized can be realized based on the order event records of the dynamic order grouping and the static order grouping which are completed through recombination, and the customer information is accurately classified to realize subsequent user positioning.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed 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 invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a method for processing guest-obtaining information according to an embodiment of the present invention.
Fig. 2 is a functional block diagram of a guest information processing apparatus according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a hardware structure of a server according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
Referring to fig. 1, a guest information processing method applied to a server is shown, including the following steps S11-S14.
Step S11, obtaining the order distribution of the customer information to be optimized and the event records of each order.
Step S12, when it is determined that the to-be-optimized customer information includes a dynamic order group according to the customer information order distribution, determining a matching coefficient between each order event record in the static order group of the to-be-optimized customer information and each order event record in the dynamic order group of the to-be-optimized customer information according to the order event records in the dynamic order group of the order interaction network of the multiple merchant platforms and the order heat distribution thereof, and adjusting the order event records in the static order group of the to-be-optimized customer information that match the order event records in the dynamic order group to the corresponding dynamic order group.
Step S13, when the current static order grouping of the to-be-optimized customer information includes a plurality of order event records, determining a matching coefficient between the order event records of the current static order grouping of the to-be-optimized customer information according to the order event records of the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution thereof, and marking the order event records of the current static order grouping according to the matching coefficient between the order event records.
Step S14, setting a dynamic order grouping priority for each type of order event record obtained by the above-mentioned label according to the order event record placed by dynamic order grouping of the order interaction networks of multiple merchant platforms and the order heat distribution thereof, and adjusting each type of order event record to the dynamic order grouping represented by the dynamic order grouping priority.
It can be understood that, by executing the above steps S11-S14, first obtaining the order distribution of the customer information to be optimized and each order event record, then determining the dynamic order group included in the customer information to be optimized based on the order distribution of the customer information, and then implementing secondary allocation of the order event records based on the order event records placed in the dynamic order group and the static order group, thereby implementing reassembly of the dynamic order group and the static order group. By the design, order event analysis of the customer information to be optimized can be realized based on the order event records of the dynamic order grouping and the static order grouping which are completed through recombination, and the customer information is accurately classified to realize subsequent user positioning.
Optionally, the determining, according to order event records placed in groups of dynamic orders of the order interaction networks of the multiple merchant platforms and order heat distribution thereof, a matching coefficient between each order event record placed in groups of static orders of the to-be-optimized customer information and each order event record placed in groups of dynamic orders of the to-be-optimized customer information, and adjusting the order event records placed in groups of static orders of the to-be-optimized customer information and matched with the order event records placed in groups of dynamic orders to corresponding dynamic order groups comprises:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the determining, according to the order event records grouped and placed by the dynamic orders of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof, a matching coefficient between the order event records grouped and placed by the current static order of the to-be-optimized customer information, and marking the order event records grouped and placed by the current static order according to the matching coefficient between the order event records includes:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the setting of the dynamic order grouping priority for each type of order event record obtained by the above marking according to the order event record placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms includes: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
Referring to fig. 2, there is provided a guest information processing apparatus 200, including:
the customer information acquisition module 210 is configured to acquire customer information order distribution of the customer information to be optimized and each order event record;
the customer information obtaining adjustment module 220 is configured to, when it is determined that the customer information to be optimized includes a dynamic order group according to the customer information order distribution, determine a matching coefficient between each order event record in the static order group of the customer information to be optimized and each order event record in the dynamic order group of the customer information to be optimized according to the order event records in the dynamic order group of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof, and adjust the order event record in the static order group of the customer information to be optimized, which matches with the order event record in the dynamic order group, to a corresponding dynamic order group;
the customer information obtaining marking module 230 is configured to, when a current static order group of the customer information to be optimized includes a plurality of order event records, determine a matching coefficient between each order event record under the current static order group of the customer information to be optimized according to the order event records under the dynamic order group of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof, and mark each order event record under the current static order group according to the matching coefficient between each order event record;
and a record grouping setting module 240, configured to set a dynamic order grouping priority for each type of order event record obtained by the above flag according to the order event record placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof, and adjust each type of order event record to the dynamic order grouping represented by the dynamic order grouping priority.
Optionally, the customer information obtaining adjustment module 220 determines matching coefficients between each order event record in the static order group of the customer information to be optimized and each order event record in the dynamic order group of the customer information to be optimized according to the order event records in the dynamic order group of the order interaction network of the multiple merchant platforms and the order heat distribution thereof, and adjusting the order event record in the static order group of the customer information to be optimized, which matches with the order event record in the dynamic order group of the customer information to be optimized, to a corresponding dynamic order group, specifically includes:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the customer obtaining information marking module 230 determines matching coefficients between the order event records grouped under the current static order of the customer obtaining information to be optimized according to the order event records grouped under the dynamic order of the order interaction network of the multiple merchant platforms and the order heat distribution thereof, and marking each order event record grouped under the current static order according to the matching coefficients between each order event record specifically includes:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
Optionally, the setting, by the record grouping setting module 240, the dynamic order grouping priority for each type of order event record obtained by the above flag according to the order event record placed in the dynamic order grouping of the order interaction networks of multiple merchant platforms specifically includes: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
Referring to fig. 3, a hardware block diagram of the server 110 is provided.
Fig. 3 is a block diagram illustrating a server 110 according to an embodiment of the present invention. The server 110 in the embodiment of the present invention may be a server with data storage, transmission, and processing functions, as shown in fig. 3, the server 110 includes: memory 111, processor 112, network module 113, and guest information processing apparatus 200.
The memory 111, the processor 112, and the network module 113 are electrically connected directly or indirectly to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 111 stores the guest information processing apparatus 200, the guest information processing apparatus 200 includes at least one software function module which can be stored in the memory 111 in the form of software or firmware (firmware), and the processor 112 executes various function applications and data processing by running the software programs and modules stored in the memory 111, such as the guest information processing apparatus 200 in the embodiment of the present invention, so as to implement the guest information processing method in the embodiment of the present invention.
The Memory 111 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 111 is used for storing a program, and the processor 112 executes the program after receiving the execution instruction.
The processor 112 may be an integrated circuit chip having data processing capabilities. The Processor 112 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The network module 113 is used for establishing communication connection between the server 110 and other communication terminal devices through a network, and implementing transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and that server 110 may include more or fewer components than shown in fig. 3 or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
An embodiment of the present invention also provides a computer-readable storage medium, which includes a computer program. The computer program controls the server 110 on which the readable storage medium is executed to perform the above-mentioned method.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts 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 invention. 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, the functional modules in the embodiments of the present invention 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 invention or a part thereof, which essentially contributes to the prior art, can 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, an electronic device 10, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. 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 should be noted that, in this document, 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 are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (8)
1. A method for processing guest-obtaining information, comprising:
acquiring customer acquisition information order distribution and each order event record of the customer acquisition information to be optimized;
under the condition that the to-be-optimized customer obtaining information contains dynamic order groups according to the customer obtaining information order distribution, determining matching coefficients between each order event record under the static order groups of the to-be-optimized customer obtaining information and each order event record under the dynamic order groups of the to-be-optimized customer obtaining information according to order event records under the dynamic order groups of the order interaction networks of a plurality of merchant platforms and order heat distribution of the order event records, and adjusting the order event records under the static order groups of the to-be-optimized customer obtaining information, which are matched with the order event records under the dynamic order groups, to be under the corresponding dynamic order groups;
under the condition that the current static order grouping of the customer information to be optimized contains a plurality of order event records, determining a matching coefficient among the order event records of the current static order grouping of the customer information to be optimized according to the order event records of the dynamic order grouping of the order interaction networks of a plurality of merchant platforms and the order heat distribution thereof, and marking the order event records of the current static order grouping according to the matching coefficient among the order event records;
and setting a dynamic order grouping priority for each type of order event record obtained by the mark according to the order event record and the order heat distribution thereof placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms, and adjusting each type of order event record to the dynamic order grouping placed represented by the dynamic order grouping priority.
2. The method of claim 1, wherein determining a matching coefficient between each order event record under the static order grouping of the customer information to be optimized and each order event record under the dynamic order grouping of the customer information to be optimized according to the order event records under the dynamic order grouping of the order interaction network of the plurality of merchant platforms and the order heat distribution thereof, and adjusting the order event records under the static order grouping of the customer information to be optimized that match the order event records under the dynamic order grouping to the corresponding dynamic order grouping comprises:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
3. The method of claim 1, wherein determining matching coefficients between the order event records grouped under the current static order of the to-be-optimized customer information according to the order event records grouped under the dynamic order of the order interaction network of the plurality of merchant platforms and the order heat distribution thereof, and marking the order event records grouped under the current static order according to the matching coefficients between the order event records comprises:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
4. The method of claim 1, 2 or 3, wherein setting a dynamic order grouping priority for each type of order event record obtained by the tag based on order event records placed by dynamic order grouping of order interaction networks of multiple merchant platforms comprises: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
5. A guest information processing apparatus, comprising:
the customer information acquisition module is used for acquiring the customer information order distribution of the customer information to be optimized and each order event record;
the customer information obtaining adjustment module is used for determining matching coefficients between each order event record under the static order grouping of the customer information obtaining information to be optimized and each order event record under the dynamic order grouping of the customer information obtaining platform according to the order event records under the dynamic order grouping and the order heat distribution of the order interaction network of the multiple merchant platforms under the condition that the customer information obtaining to be optimized contains the dynamic order grouping according to the customer information obtaining order distribution, and adjusting the order event records under the static order grouping of the customer information obtaining to be optimized and matched with the order event records under the dynamic order grouping to the corresponding dynamic order grouping;
the customer information obtaining marking module is used for determining a matching coefficient among the order event records under the current static order grouping of the customer information to be optimized according to the order event records under the dynamic order grouping of the order interaction networks of the multiple merchant platforms and the order heat distribution thereof under the condition that the current static order grouping of the customer information to be optimized contains multiple order event records, and marking the order event records under the current static order grouping according to the matching coefficient among the order event records;
and the record grouping setting module is used for setting a dynamic order grouping priority for each type of order event record obtained by the mark according to the order event record and the order heat distribution thereof placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms, and adjusting each type of order event record to the dynamic order grouping represented by the dynamic order grouping priority.
6. The apparatus according to claim 5, wherein the customer information obtaining adjustment module determines a matching coefficient between each order event record in the static order group of the customer information to be optimized and each order event record in the dynamic order group of the customer information to be optimized according to the order event records in the dynamic order group of the order interaction network of the plurality of merchant platforms and the order heat distribution thereof, and adjusts the order event records in the static order group of the customer information to be optimized that match the order event records in the dynamic order group to be optimized to be corresponding dynamic order group to be specified includes:
calculating attribute consistency weight between each order event record under the static order group of the customer information to be optimized and the record attribute information of each order event record under the dynamic order group of the customer information to be optimized;
respectively judging whether the attribute consistency weight reaches a first set threshold value, and adjusting the order event record under the static order grouping with the attribute consistency weight reaching the first set threshold value to the corresponding dynamic order grouping;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
7. The apparatus according to claim 5, wherein the customer information marking module determines a matching coefficient between each order event record grouped under a current static order of the customer information to be optimized according to the order event record grouped under the dynamic order of the order interaction network of the plurality of merchant platforms and the order heat distribution thereof, and marking each order event record grouped under the current static order according to the matching coefficient between each order event record specifically comprises:
calculating the attribute consistency weight among the record attribute information of each order event record under the current static order group of the customer information to be optimized;
for an order event record which is grouped by the current static order of the customer information to be optimized, marking all order event records with the attribute consistency weight reaching a second set threshold value between the order event record and the record attribute information thereof as one class;
wherein the record attribute information of the order event record is as follows: and counting the distribution condition of the order event records belonging to the dynamic order grouping priority according to the order event records placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms and the order heat distribution of the order event records.
8. The apparatus according to claim 5, 6 or 7, wherein the setting module for setting the dynamic order grouping priority for each type of order event record obtained by the above flag according to the order event record placed by the dynamic order grouping of the order interaction networks of the plurality of merchant platforms specifically comprises: for the marked order event records of the same type, determining the distribution condition of the dynamic order grouping priority of each order event record in the type according to the order event records placed in the dynamic order grouping of the order interaction networks of the multiple merchant platforms, and setting the dynamic order grouping priority for the order event records of the type according to the distribution condition.
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