CN113888229A - Store data processing and order processing method and device - Google Patents

Store data processing and order processing method and device Download PDF

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Publication number
CN113888229A
CN113888229A CN202111217933.2A CN202111217933A CN113888229A CN 113888229 A CN113888229 A CN 113888229A CN 202111217933 A CN202111217933 A CN 202111217933A CN 113888229 A CN113888229 A CN 113888229A
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store
stores
real
information
aggregation
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刘宏宇
刘越
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Rajax Network Technology Co Ltd
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Rajax Network Technology Co Ltd
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Priority to CN202111217933.2A priority Critical patent/CN113888229A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24553—Query execution of query operations
    • G06F16/24554—Unary operations; Data partitioning operations
    • G06F16/24556—Aggregation; Duplicate elimination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0203—Market surveys; Market polls
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders

Abstract

The application discloses a store data processing method and device and an order processing method and device. The store data processing method comprises the following steps: acquiring information of a real store matched with a target geographic area; aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information; displaying information of the aggregation store to a target user device; the geographical area of the target user equipment is matched with the target geographical area. The order processing method comprises the following steps: acquiring order information generated aiming at an object of an aggregation store; screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object. By adopting the method, the problem of high redundancy of display information caused by the fact that shops of the same brand cannot be uniformly displayed is solved.

Description

Store data processing and order processing method and device
Technical Field
The application relates to the technical field of electronic information, in particular to a store data processing method, device and equipment. The application also relates to an order processing method, an order processing device and order processing equipment.
Background
With the continuous development of electronic commerce, online shopping through stores displayed on an internet platform gradually becomes a common shopping mode. The user can access the platform through the terminal equipment, browse stores shown on the platform and object information provided by the stores, and accordingly make purchasing decisions. Therefore, how to show stores and the object information provided by the stores on the platform is particularly important.
Currently, the stores displayed on the service platform generally correspond to individual real stores, and information of each real store within a certain range from the current location of the user or within the distribution range of the user can be displayed. Therefore, redundant information is brought to the user, and the decision efficiency of the user is influenced. Particularly in the scenes of convenience stores and beverage stores, the distribution density of the convenience stores and beverage stores of the same brand is higher and the distribution time is close, so that the information which needs to be browsed by a user is more easily redundant. Moreover, the marketing of stores of the same brand is relatively independent, and the control of the whole brand is difficult.
Therefore, how to uniformly display stores of the same brand to reduce redundancy of display information is a problem to be solved.
Disclosure of Invention
The store data processing method provided by the embodiment of the application solves the problem that stores of the same brand cannot be uniformly displayed, so that the redundancy of displayed information is high.
The embodiment of the application provides a store data processing method, which comprises the following steps: acquiring information of a real store matched with a target geographic area; aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information; displaying information of the aggregation store to a target user device; the geographical area of the target user equipment is matched with the target geographical area.
Optionally, the method further includes: and determining a geographic area matched with the geographic area of the target user equipment as the target geographic area.
Optionally, the geographic area where the target user equipment is located is a dynamic scene area determined based on the current location of the target user equipment; the acquiring of the information of the real stores matched with the target geographic area comprises: selecting information of the real store according to the dynamic scene area; the aggregation store is a store group of real stores associated with the same brand information in the dynamic scene area.
Optionally, the target geographic area is a geographic area determined based on pre-divided geographic grids and/or business district information; the aggregation store is a pre-formed store group of real stores associated with the same brand information in a target geographic area; the displaying the information of the polymerization store to the target user equipment comprises: determining the geographical area of the target user equipment; and if the geographical area of the target user equipment and the geographical area of the target user equipment contain the same geographical identification, pushing the information of the aggregated store to the target user equipment and displaying the information.
Optionally, the target geographic area includes geographic identifiers of a plurality of geographic grids; the aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information includes: aggregating real stores within each geographic grid based on brand information associated with the real stores to form a store group corresponding to each geographic grid for the brand information; and combining to form an aggregate store aiming at the brand information and comprising a plurality of store groups according to the information of the store groups corresponding to each geographic grid in the target geographic area.
Optionally, the displaying the information of the aggregated store to the target user equipment includes: determining real stores meeting scheduling conditions in the aggregation stores or store groups contained in the aggregation stores; acquiring the object information of the real stores meeting the scheduling conditions as the object information of the aggregated stores; and displaying the object information of the aggregation store.
Optionally, the method further includes: acquiring a first expected delivery duration of each real store object meeting the scheduling condition; taking the average value of the first expected delivery duration as a second expected delivery duration of the object of the aggregation store; and displaying the second expected delivery time length.
Optionally, the method further includes: acquiring the distance between each real store meeting the scheduling condition and the target user equipment as a first delivery distance; taking an average of the first delivery distances as a second delivery distance between the aggregation store and the target user device; and displaying the second distribution distance.
Optionally, the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information includes: acquiring information of a first real store and information of a second real store which are related to the same brand information in the target area; generating identification information of the aggregation store according to the brand information; associating the same object of the first real store and the second real store with the aggregation store as a unified menu object of the aggregation store; associating different objects of the first real store and the second real store with the aggregate store as a designated menu object of the aggregate store.
Optionally, the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information includes: acquiring the estimated distribution time length of each real store with the same brand information in the target geographic area; and aggregating the real stores of which the difference value between the expected distribution time lengths is smaller than the distribution time difference threshold value to form an aggregated store corresponding to each brand information.
Optionally, the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information includes: acquiring at least one of the following information of the real store as an aggregation factor forming the aggregation store: order throughput, meal delivery duration, brand information, and geographic area of a real store; forming the polymerization store according to the polymerization factors.
Optionally, the brand information associated with the aggregated store is the same as the brand information of each real store in the aggregated store.
Optionally, the method further includes: and counting the marketing data of the aggregated store according to the order quantity and the consumption total of the real stores meeting the scheduling conditions of the aggregated store.
Optionally, the method further includes: configuring marketing activity data corresponding to the brand information according to the brand information associated with the aggregated store; and/or configuring marketing campaign data corresponding to the store group according to the store group information contained in the aggregated stores.
An embodiment of the present application further provides an order processing method, including: acquiring order information generated aiming at an object of an aggregation store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area; screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object.
Optionally, the screening out real stores that meet the scheduling condition and are associated with the aggregated store includes: acquiring information of real stores associated with the aggregated store; and screening out real stores of which the order backlog index data do not exceed the order backlog threshold value as the dispatchable stores.
Optionally, the screening out schedulable stores that satisfy the scheduling condition and are associated with the aggregation store includes: and determining the delivery time length and/or meal delivery time length of a real store of the aggregated store, and taking the real store as the dispatchable store if the delivery time length does not exceed the preset delivery time length in the dispatching condition and/or the meal delivery time length does not exceed the preset meal delivery time length in the dispatching condition.
Optionally, the method further includes: if order receiving information sent by a target store in the dispatchable stores is received within a preset time length, the order information is dispatched to the target store; otherwise, calculating the scheduling scores of the dispatchable stores according to the scheduling index data of the dispatchable stores and the index weights corresponding to the scheduling index data, selecting target stores from the dispatchable stores according to the scheduling scores, and dispatching the order information to the target stores.
The embodiment of the present application further provides a store data processing apparatus, including: the real store acquisition unit is used for acquiring the information of the real store matched with the target geographic area; the aggregation unit is used for aggregating the real stores based on the brand information associated with the real stores to form an aggregation store corresponding to the brand information; the system comprises a gathering store display unit, a target user device and a display unit, wherein the gathering store display unit is used for displaying information of the gathering store to the target user device; the geographical area of the target user equipment is matched with the target geographical area.
An embodiment of the present application further provides an order processing apparatus, including: the order receiving unit is used for acquiring order information generated aiming at the objects of the aggregated store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area; the order pushing unit is used for screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object.
An embodiment of the present application further provides an electronic device, including: a memory, and a processor; the memory is used for storing a computer program, and the computer program is executed by the processor to execute the method provided by the embodiment of the application.
The embodiment of the present application further provides a storage device, in which a computer program is stored, and the computer program is executed by the processor to perform the method provided in the embodiment of the present application.
Compared with the prior art, the method has the following advantages:
according to the store data processing method, device and equipment provided by the embodiment of the application, the information of the real store matched with the target geographic area is obtained; aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information; displaying information of the aggregation store to a target user device; the geographical area of the target user equipment is matched with the target geographical area. The information of real stores of the same brand can be uniformly displayed through the aggregation stores, the problem that the redundancy of displayed information is high due to the fact that stores of the same brand cannot be uniformly displayed is solved, and the shopping decision making efficiency of a user is improved.
According to the order processing method, the order processing device and the order processing equipment, order information generated by aiming at an object of a polymerization store is acquired; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area; screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object. The user places an order through the aggregation store, so that order information is generated for the object of the aggregation store. The order information is pushed to the dispatchable stores, the dispatchable stores can further rush orders, and the stores which successfully rush orders complete production tasks after receiving orders, so that a more reasonable order processing scheme of the convergent stores is provided.
Drawings
Fig. 1 is a process flow diagram of a store data processing method according to a first embodiment of the present application;
FIG. 2 is a schematic diagram of the aggregate store display effect provided by the first embodiment of the present application in comparison with the existing platform store display effect;
FIG. 3 is a push flow diagram of a concierge store according to a first embodiment of the present application;
FIG. 4 is a flowchart illustrating a method for processing an order according to a second embodiment of the present application;
FIG. 5 is a schematic diagram of a store data processing apparatus according to a third embodiment of the present application;
FIG. 6 is a schematic diagram of an order processing apparatus according to a fourth embodiment of the present application;
fig. 7 is a schematic diagram of an electronic device provided herein.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.
The embodiment of the application provides a store data processing method and device, electronic equipment and storage equipment. The embodiment of the application also provides an order processing method and device, electronic equipment and storage equipment. The following examples are individually set forth.
In order to uniformly display real stores (physical stores) of the same brand and facilitate marketing management based on the brand, an embodiment of the application provides a store data processing method, which aggregates different real stores of the same brand in a geographic area (or geographic grid) or a business district to form an abstract aggregated store and uniformly display information of the aggregated store. Thereby can solve the unable unified show of shop of the same brand and lead to the higher problem of show information redundancy to do not need every real shop under the brand all to stay the platform, can manage every real shop under this brand under the condition that the brand stays the platform, be convenient for carry out the marketing according to the brand.
A store data processing method according to a first embodiment of the present application is described below with reference to fig. 1 to 3. The store data processing method shown in fig. 1 includes: step S101 to step S103.
And step S101, acquiring information of the real store matched with the target geographic area.
The real store refers to a physical store or warehouse that actually provides an object to a user. The object means a commodity or a service provided to a user. In this embodiment, different real stores of the same brand in the target geographic area are aggregated to form an aggregated store of the brand, and information of the aggregated store is displayed in a unified manner. By a syndicated store is understood an abstract store formed by one or more real stores associated with the same brand information within a geographic area. In specific implementation, one or more real stores associated with the same brand information in a geographic grid can be aggregated into a store group, the store group can be identified by the identification of the store group, each real store in the store group can also form a store group identification of the real store by the identification based on the store group, and the store group identification of the real store can uniquely identify the real store in the store group; and combining one or more store groups into an abstract store. Of course, the brand identifier corresponding to the real store may also be formed by a brand-based identifier, and the brand identifier corresponding to the real store may uniquely identify the real store of the brand. The real stores of the same brand may be brand chain stores, league stores, small store brand convenience stores, community stores, and the like.
The step is to acquire the information of the real stores which are matched with the target geographical area in the geographical area. For example, the information of the real stores in the target geographic area may be acquired, specifically, the point of interest data in the target geographic area may be acquired, and the information of the real stores may be extracted from the point of interest data. The target geographic area may be a geographic area where the user is located acquired under the permission of the user, or may be an area formed based on a pre-divided geographic area.
In one embodiment, the target geographic area matched with the user is determined according to the geographic area of the user. The geographical area where the user is located may be a geographical area designated by the user, or may be a geographical area where the user is located determined according to the current location of the user equipment when the user allows to acquire and use the geographical location. The method specifically comprises the following steps: and determining a geographic area matched with the geographic area of the target user equipment as the target geographic area. And if the geographical area of the user contains one or more geographical identifications, taking the geographical area containing any geographical identification of the geographical area of the user as a target geographical area. In practical applications, as the user equipment moves, the location of the user equipment changes, and thus the target geographic area changes dynamically, which can be understood as a dynamic scene area. Accordingly, the actual stores within the target geographic area may also be different. Specifically, the geographic area where the target user equipment is located is a dynamic scene area determined based on the current position of the target user equipment; the obtaining information of the real store matching the target geographic area includes: selecting information of the real store according to the dynamic scene area; the aggregation store is a store group of real stores associated with the same brand information in the dynamic scene area. Thus, as the location of the user device changes, information of real stores contained in the same brand of aggregated stores may also change. Of course, the delivery range corresponding to the delivery position matched with the geographic area where the user is located may also be used as the target geographic area, so as to form an aggregation store of each brand corresponding to the target geographic area, and the aggregation store is displayed to the user, thereby facilitating the user to purchase a deliverable object on line.
In one embodiment, the pre-divided geographic area, for example, the pre-divided geographic area is a geographic grid or a mall, and the target geographic area may comprise one or more pre-divided geographic areas. In this step, information of real stores in the one or more pre-divided geographic areas is acquired, and in the subsequent step, the information is aggregated into an aggregated store corresponding to the target geographic area. In practice, a group of stores corresponding to each of the pre-divided geographical areas may be formed for each of the pre-divided geographical areas based on the brand information, and after the target geographical area is determined, an aggregated store corresponding to the target geographical area may be formed for each brand using the group of stores corresponding to the pre-divided geographical areas included in the target geographical area. The target geographic area is a geographic area determined based on pre-divided geographic grids and/or business district information; the aggregation store is a pre-formed store group of real stores associated with the same brand information in the target geographic area. In practice the aggregated store may comprise one or more groups of stores. The method specifically comprises the following steps: the target geographic area comprises geographic identifications of a plurality of geographic grids; then: aggregating real stores within each geographic grid based on brand information associated with the real stores to form a store group corresponding to each geographic grid for the brand information; and combining to form an aggregate store aiming at the brand information and comprising a plurality of store groups according to the information of the store groups corresponding to each geographic grid in the target geographic area. In the subsequent step, the information of the aggregation store is shown on the target user equipment, and the method comprises the following steps: determining the geographical area of the target user equipment; and if the geographical area of the target user equipment and the geographical area of the target user equipment contain the same geographical identification, pushing the information of the aggregated store to the target user equipment and displaying the information.
And S102, aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information.
The steps are to aggregate the real stores in the target geographic area into aggregated stores respectively corresponding to each brand. The brand information associated with the aggregated store is the same as the brand information of each real store in the aggregated store. The polymerization may be carried out according to a certain polymerization condition and/or polymerization factor. In one embodiment, the real stores of the same brand, which are within the delivery range of the geographic area where the user is located and have the similar delivery duration, are aggregated into the aggregated store of the brand, which is displayed on the user equipment. Wherein the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information comprises: acquiring the estimated distribution time length of each real store with the same brand information in the target geographic area; and aggregating the real stores of which the difference value between the expected distribution time lengths is smaller than the distribution time difference threshold value to form an aggregated store corresponding to each brand information. In one embodiment, the aggregation store and/or the group of stores that the aggregation store comprises is calculated offline as a function of the aggregation factors. Wherein the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information comprises: acquiring at least one of the following information of the real store as an aggregation factor forming the aggregation store: order throughput, meal delivery duration, brand information, and geographic area of a real store; forming the polymerization store according to the polymerization factors. It is understood that the aggregation factors include, but are not limited to, the factors listed above, and may also include other factors, such as business hours, etc.
In this embodiment, the method further includes aggregating objects of real stores of the same brand into an object unified exhibition of the aggregated store. Wherein the aggregating the real stores based on the brand information associated with the real stores to form an aggregated store corresponding to the brand information comprises: acquiring information of a first real store and information of a second real store which are related to the same brand information in the target area; generating identification information of the aggregation store according to the brand information; associating the same object of the first real store and the second real store with the aggregation store as a unified menu object of the aggregation store; associating different objects of the first real store and the second real store with the aggregate store as a designated menu object of the aggregate store.
Step S103, displaying the information of the aggregation store on target user equipment; the geographical area of the target user equipment is matched with the target geographical area.
This step is to present the information of the aggregated store to the target user. The aggregate store may include one or more groups of stores, each group of stores including one or more real stores. And controlling and displaying real stores meeting scheduling conditions during information display. The real stores satisfying the scheduling condition may be understood as real stores having a capability of providing production to the orders of the target users. Wherein the displaying the information of the aggregated store to the target user equipment comprises: determining real stores meeting scheduling conditions in the aggregation stores or store groups contained in the aggregation stores; acquiring the object information of the real stores meeting the scheduling conditions as the object information of the aggregated stores; and displaying the object information of the aggregation store. I.e. information showing the aggregated store and information of the objects of the aggregated store.
In this embodiment, information such as delivery duration information and delivery distance of the aggregated store may also be displayed. Preferably, the method further comprises the following steps: acquiring a first expected delivery duration of each real store object meeting the scheduling condition; taking the average value of the first expected delivery duration as a second expected delivery duration of the object of the aggregation store; and displaying the second expected delivery time length. The second expected delivery duration may be understood as delivery duration information of the aggregated store. Preferably, the method further comprises the following steps: acquiring the distance between each real store meeting the scheduling condition and the target user equipment as a first delivery distance; taking an average of the first delivery distances as a second delivery distance between the aggregation store and the target user device; and displaying the second distribution distance. The second delivery distance may be understood as a delivery distance of a back office. In implementation, the average value of the estimated delivery durations of all real stores meeting the scheduling condition can be used as the estimated delivery duration of the aggregated store; and taking the average value of the distribution distances of all real stores meeting the scheduling condition as the distribution distance of the aggregation store.
Referring to FIG. 2, a comparison of an aggregate store display with an existing platform store display is shown, comprising: aggregate store display effects 201 and existing store display effects 202. The aggregate store exhibition effect comprises information of the aggregate store and object information available by the aggregate store, a brand corresponds to the aggregate store or real stores with the same production capacity are aggregated into the aggregate store, and the aggregate store is associated with a plurality of real stores of the brand or a plurality of real stores with the same production capacity. Therefore, the display of the user-side shop is clearer, and the redundant display of shops with the same brand or the same production capacity is eliminated. For example, in the figure: "brand a store" is a syndicated store name named under the brand name; "object B" is a good B that can be offered by at least one real store associated with at least the aggregate store; the distribution time length N minutes is the average value of the expected distribution time lengths of all real stores associated with the brand A store and the current position of the user. The existing store exhibition effect is the exhibition effect of the existing online stores of the platform, each online store corresponds to a real store, and the real stores of the same brand or the same production capacity are exhibited independently. For example, in the figure: "brand a store 1" and "brand a store 2" are a real store 1 and a real store 2 of brand a, respectively, and the respective distribution time periods of these two real stores are similar, i.e., 39 minutes and 42 minutes, respectively. For a user, shops with the same brand and similar distribution duration can provide similar objects, and the object quality and the time cost are close to each other, so that information browsed by the user during shopping decision is redundant, and decision efficiency is affected. It is to be understood that the layout and style and size of the elements in the figures are merely illustrative and are not meant as a style constraint for presenting aggregated store information.
In this embodiment, the real stores of the same brand that match with the target geographic area are aggregated into the aggregated store of the brand, so that the unified marketing is facilitated according to the brand. Compared with the existing marketing that different real stores of the same brand are relatively independent, the control capability of the brand on the marketing is enhanced, the effective range of the unified marketing campaign can be configured according to the aggregated store of the brand and/or the store group under the aggregated store, and the marketing fee can also be settled in a unified way. For example, a marketing campaign configured for the identity of a brand, which is effective to the extent of all real stores of the brand; the marketing campaign configured for the identity of the brand and the identity of the group of stores is effective to the extent of the real stores within the group of stores of the brand. And when a new real store is added under the brand, the new real store can be associated to the aggregation store of the brand under the condition of no exposure, so that the new real store has an opportunity to receive a user order, and the condition that the exposure effect of the 'cold start' of the new store is poor is improved. The method specifically comprises the following steps: configuring marketing activity data corresponding to the brand information according to the brand information associated with the aggregated store; and/or configuring marketing campaign data corresponding to the store group according to the store group information contained in the aggregated stores. The embodiment further includes a step of counting marketing data of the aggregated store, which specifically includes: and counting the marketing data of the aggregated store according to the order quantity and the consumption total of the real stores meeting the scheduling conditions of the aggregated store. That is, the sales data "order amount/consumption total" of the aggregated store is equal to "order amount/consumption total of users under all physical stores satisfying the scheduling policy".
Compared with the existing method that the user places an order to a real store through a platform, the method that the user places an order to a gathering store is implemented. In this embodiment, an order processing scheme of the aggregation store is further provided. After a user places an order for the aggregation store, the order pushing system pushes the order to the real store associated with the aggregation store, the real store associated with the aggregation store performs order grabbing, and after the order grabbing fails, the scheduling system assigns the order to the specific real store.
In this embodiment, the following processing is specifically included: acquiring order information generated aiming at an object of an aggregation store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area; screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object. In implementation, different screening methods can be adopted to screen out the real stores meeting the scheduling conditions associated with the aggregated store as schedulable stores of the aggregated store, and under the condition of no conflict, multiple screening methods can be combined at will. In one embodiment, the screening out schedulable stores associated with the aggregation store that satisfy a scheduling condition includes: acquiring information of real stores associated with the aggregated store; and screening out real stores of which the order backlog index data do not exceed the order backlog threshold value as the dispatchable stores. In one embodiment, the screening out schedulable stores associated with the aggregation store that satisfy a scheduling condition includes: and determining the delivery time length and/or meal delivery time length of a real store of the aggregated store, and taking the real store as the dispatchable store if the delivery time length does not exceed the preset delivery time length in the dispatching condition and/or the meal delivery time length does not exceed the preset meal delivery time length in the dispatching condition. For example, the meal delivery duration of the real store 1 of the aggregated store is prolonged due to the backlog of orders or other reasons, and exceeds the meal delivery duration in the scheduling policy corresponding to the aggregated store, the real store 1 is removed from the scheduling range, and cannot be used as a schedulable store. Further, still include: if order receiving information sent by a target store in the dispatchable stores is received within a preset time length, the order information is dispatched to the target store; otherwise, calculating the scheduling scores of the dispatchable stores according to the scheduling index data of the dispatchable stores and the index weights corresponding to the scheduling index data, selecting target stores from the dispatchable stores according to the scheduling scores, and dispatching the order information to the target stores. By order delivery is meant the assignment of an order to a store. For example, after the order grabbing failure, the scheduling system calculates scheduling scores of real stores according to various index data of the real stores and push monotonicity strategies of corresponding aggregated stores, selects the real store with the highest score to assign a push order, and completes production tasks by the store.
Wherein the scheduling score is calculated using the following formula:
Figure BDA0003311397890000111
wherein score is a scheduling score; n represents n index items; caseiIndex data corresponding to the ith index item; weightiIs the scheduling weight of the ith index item.
The scheduling score calculation is described by taking table 1 and table 2 as an example. Table 1 shows information and index data of each real store in a certain aggregated store of a certain brand. The store group identifier in the table is an identifier of each real store based on the store group, and the brand identifier is an identifier of each real store based on the brand. For example, if the brand is identified as 1 and the store group is identified as 2, then the store group of brand a store 1 is identified as "10001" and its brand is identified as "20001".
TABLE 1 information and index data of each real store in a certain aggregated store of a certain brand
Store group mark Real store Brand mark Throughput capacity Length of delivery time Backlog data
20001 Brand A store 1 10001 80 35 20
20002 Brand A store 2 10002 100 32 30
20003 Brand A store 3 10003 70 40 10
In table 1, the aggregate scheduling ranges of the indexes are as follows: the delivery time is (0-60), the throughput is (0-100) and the backlog data is (0-100), then the scheduling scores of each real store are shown in table 2.
TABLE 2 scheduling scores for respective real stores in a certain aggregated store of a certain brand
Store group mark Real store Brand mark Scheduling scoring
20001 Brand A store 1 10001 (0.5＊35/60+0.4＊80/100-0.1＊20/100)/2＝0.2958
20002 Brand A store 2 10002 (0.5＊32/60+0.4＊100/100-0.1＊30/100)/2＝0.3183
20003 Brand A store 3 10003 (0.5＊40/60+0.4＊70/100-0.1＊10/100)/2＝0.3016
Referring to fig. 3, a push flow for a concierge store is shown, comprising: s301, the user places an order in the brand A store, and an order containing the store group identification of the real store is generated. The brand a store is associated with a plurality of real stores, each real store has a corresponding store group identifier for identifying the brand a store in the store group, for example, the store group identifier of the brand a store 1 is 20001, and the store group identifier of the brand a store 2 is 20002. S302, the order receiving service receives the order. That is, an order for brand a store is received. And S303, executing a push task by the scheduling system on the received order. S303-1, pushing order information to schedulable real stores meeting the scheduling conditions, and finishing the production tasks corresponding to the orders by the order-receiving real stores. Namely, the scheduling system pushes order information to schedulable real stores meeting scheduling conditions, each schedulable real store can rob orders, and the real stores receiving orders complete production tasks corresponding to the orders. And if the shop order is received within the preset time, the order pushing task is completed. And if no store order is received within the preset time, the order grabbing fails. When the order is pushed, real stores which do not meet the scheduling conditions in the store group of the brand A store corresponding to the order are filtered out, so that the real stores which meet the scheduling conditions at present are screened out. For example, if the current production backlog of the store N is too much, and the meal delivery time is prolonged, the store N is a store that does not satisfy the scheduling condition and is not within the push-to-order range. Then pushing a bill to the real stores meeting the scheduling conditions. S303-2, if the order grabbing fails, calculating the scheduling score of each real store according to each index data of each real store and a brand store push monotonicity strategy, assigning the order to the real store meeting the scheduling score threshold value, and completing a push order task. For example, the information for brand a store 1 is: delivery time was 35, throughput 80, and backlog 20. The information for brand a store 2 is: delivery time is 32, throughput is 100, and backlog is 30. The information for brand a store 3 is: the delivery time was 40, the throughput was 70, and the backlog number was 10, and the scheduling score for each brand store was calculated according to the above equation (1). And S304, after the order pushing task is completed, carrying out logistics scheduling, namely distributing the order to the rider for distribution, thereby completing the order.
The store data processing method provided in the embodiment aggregates real stores of the same brand into aggregated stores, and can realize unified management of the real stores, chain stores and the like of the same brand of the platform. The display effect of the information of the aggregated store on the user equipment is clearer, the redundant display of real stores with the same brand/same production capacity is removed, and the decision efficiency of the user is improved. And the order of the user is received by the aggregation store, and the order pushing is carried out according to the order scheduling strategy of the aggregation store, so that the same brand has certain self-adaptive capacity to the user order, and the matching degree of the order quantity and the real store is improved. Meanwhile, the aggregate store can solve some abnormal conditions compared with the independent display of each real store: for example, when one store is in a pause business, other businesses are in normal business, and the user cannot see useless information; for another example, if one store has insufficient inventory or other abnormal conditions, the production task can be completed by transferring orders to other stores through the gathering store. Therefore, the brand competitiveness and management capacity can be improved through the aggregated store, and further the brand can accommodate more orders and realize unified marketing. For the newly-added shops of the brands, the cold start problem can be avoided for the brand-based aggregated store, the user places an order to the aggregated store, and the newly-added shop can receive the order in the follow-up pushing order. In addition, the order receiving logic of each real store is changed due to the fact that the users aggregate store ordering, so that the real stores are promoted to be optimized for receiving more orders, and therefore the opportunity is provided for real store promotion service.
It should be noted that, in the case of no conflict, the features given in this embodiment and other embodiments of the present application may be combined with each other, and the steps S101 and S102 or similar terms do not limit the steps to be executed sequentially.
So far, the method provided by the embodiment is explained, and the method acquires the information of the real store matched with the target geographic area; aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information; displaying information of the aggregation store to a target user device; the geographical area of the target user equipment is matched with the target geographical area. The information of real stores of the same brand can be uniformly displayed through the aggregation stores, the problem that the redundancy of displayed information is high due to the fact that stores of the same brand cannot be uniformly displayed is solved, and the shopping decision making efficiency of a user is improved.
Based on the foregoing embodiments, a second embodiment of the present application provides an order processing method. This will be described below with reference to fig. 4. For the related parts, refer to the description of the corresponding parts in the above method embodiments. The order processing method shown in fig. 4 includes: step S401 to step S402.
Step S401, obtaining order information generated aiming at an object of a polymerization store; the aggregation store is an abstract store corresponding to brand information, and is formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area.
Step S402, selecting schedulable stores meeting scheduling conditions from real stores associated with the aggregation store, and pushing order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object.
Wherein, the screening out real stores which are associated with the aggregated store and meet the scheduling condition comprises: acquiring information of real stores associated with the aggregated store; and screening out real stores of which the order backlog index data do not exceed the order backlog threshold value as the dispatchable stores.
Further, if order receiving information sent by a target store in the dispatchable stores is received within a preset time length, the order information is dispatched to the target store; otherwise, calculating the scheduling scores of the dispatchable stores according to the scheduling index data of the dispatchable stores and the index weights corresponding to the scheduling index data, selecting target stores from the dispatchable stores according to the scheduling scores, and dispatching the order information to the target stores.
Compared with the existing method that the user places an order to a real store through a platform, the method that the user places an order to a gathering store is implemented. In this embodiment, an order processing scheme of the aggregation store is further provided. After a user places an order for the aggregation store, the order pushing system pushes the order to the real store associated with the aggregation store, the real store associated with the aggregation store performs order grabbing, and after the order grabbing fails, the scheduling system assigns the order to the specific real store. For example, after the order grabbing failure, the scheduling system calculates scheduling scores of real stores according to various index data of the real stores and push monotonicity strategies of corresponding aggregated stores, selects the real store with the highest score to assign a push order, and completes production tasks by the store.
Wherein the scheduling score is calculated using the following formula:
Figure BDA0003311397890000141
wherein score is a scheduling score; n represents n index items; caseiIndex data corresponding to the ith index item; weightiIs the scheduling weight of the ith index item.
The order processing method provided in the embodiment can be used for order scheduling of aggregated stores aggregated based on the aggregation of real stores of the same brand, so that unified order management of the real stores, chain stores and the like of the same brand of the platform is realized. The order of the user is received by the aggregation store, and the order pushing is carried out according to the order scheduling strategy of the aggregation store, so that the same brand has certain self-adaptive capacity to the user order, and the matching degree of the order quantity and the real store is improved. Meanwhile, the aggregate store can solve some abnormal conditions compared with the independent display of each real store: for example, one store has insufficient stock or other abnormal conditions, and the production task can be completed by transferring orders to other stores through the gathering store. Order scheduling through the aggregation store may enable brands to accommodate more orders and unify marketing. For the newly-added shops of the brands, the cold start problem can be avoided based on the aggregated store of the brands, the user places an order to the aggregated store, and the newly-added shops in the push order can receive the order. In addition, the order receiving logic of each real store is changed due to the fact that the users aggregate store ordering, so that the real stores are promoted to be optimized for receiving more orders, and therefore the opportunity is provided for real store promotion service.
So far, the method provided by the present embodiment is explained, which is to obtain order information generated for an object of an aggregation store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area; screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object. The user places an order through the aggregation store, so that order information is generated for the object of the aggregation store. The order information is pushed to the dispatchable stores, the dispatchable stores can further rush orders, and the stores which successfully rush orders complete production tasks after receiving orders, so that a more reasonable order processing scheme of the convergent stores is provided.
A third embodiment of the present application provides a store data processing apparatus corresponding to the first embodiment. The device is described below with reference to fig. 5. The store data processing apparatus shown in fig. 5 includes:
a real store obtaining unit 501, configured to obtain information of a real store matching a target geographic area;
an aggregation unit 502, configured to aggregate the real stores based on brand information associated with the real stores to form an aggregation store corresponding to the brand information;
an aggregate store display unit 503, configured to display information of the aggregate store on a target user equipment; the geographical area of the target user equipment is matched with the target geographical area.
Optionally, the real store acquiring unit 501 is specifically configured to: and determining a geographic area matched with the geographic area of the target user equipment as the target geographic area.
Optionally, the geographic area where the target user equipment is located is a dynamic scene area determined based on the current location of the target user equipment; the real store acquiring unit 501 is specifically configured to: selecting information of the real store according to the dynamic scene area; the aggregation store is a store group of real stores associated with the same brand information in the dynamic scene area.
Optionally, the target geographic area is a geographic area determined based on pre-divided geographic grids and/or business district information; the aggregation store is a pre-formed store group of real stores associated with the same brand information in a target geographic area; the aggregation store display unit 503 is specifically configured to: determining the geographical area of the target user equipment; and if the geographical area of the target user equipment and the geographical area of the target user equipment contain the same geographical identification, pushing the information of the aggregated store to the target user equipment and displaying the information.
Optionally, the target geographic area includes geographic identifiers of a plurality of geographic grids; the aggregation unit 502 is specifically configured to: aggregating real stores within each geographic grid based on brand information associated with the real stores to form a store group corresponding to each geographic grid for the brand information; and combining to form an aggregate store aiming at the brand information and comprising a plurality of store groups according to the information of the store groups corresponding to each geographic grid in the target geographic area.
Optionally, the aggregation store display unit 503 is specifically configured to: determining real stores meeting scheduling conditions in the aggregation stores or store groups contained in the aggregation stores; acquiring the object information of the real stores meeting the scheduling conditions as the object information of the aggregated stores; and displaying the object information of the aggregation store.
Optionally, the aggregation store display unit 503 is specifically configured to: acquiring a first expected delivery duration of each real store object meeting the scheduling condition; taking the average value of the first expected delivery duration as a second expected delivery duration of the object of the aggregation store; and displaying the second expected delivery time length.
Optionally, the aggregation store display unit 503 is specifically configured to: acquiring the distance between each real store meeting the scheduling condition and the target user equipment as a first delivery distance; taking an average of the first delivery distances as a second delivery distance between the aggregation store and the target user device; and displaying the second distribution distance.
Optionally, the aggregation unit 502 is specifically configured to: acquiring information of a first real store and information of a second real store which are related to the same brand information in the target area; generating identification information of the aggregation store according to the brand information; associating the same object of the first real store and the second real store with the aggregation store as a unified menu object of the aggregation store; associating different objects of the first real store and the second real store with the aggregate store as a designated menu object of the aggregate store.
Optionally, the aggregation unit 502 is specifically configured to: acquiring the estimated distribution time length of each real store with the same brand information in the target geographic area; and aggregating the real stores of which the difference value between the expected distribution time lengths is smaller than the distribution time difference threshold value to form an aggregated store corresponding to each brand information.
Optionally, the aggregation unit 502 is specifically configured to: acquiring at least one of the following information of the real store as an aggregation factor forming the aggregation store: order throughput, meal delivery duration, brand information, and geographic area of a real store; forming the polymerization store according to the polymerization factors. It is understood that the aggregation factors include, but are not limited to, the factors listed above, and may also include other factors, such as business hours, etc.
Optionally, the brand information associated with the aggregated store is the same as the brand information of each real store in the aggregated store.
Optionally, the apparatus comprises a marketing unit, the marketing unit being configured to: and counting the marketing data of the aggregated store according to the order quantity and the consumption total of the real stores meeting the scheduling conditions of the aggregated store.
Optionally, the marketing unit is specifically configured to: configuring marketing activity data corresponding to the brand information according to the brand information associated with the aggregated store; and/or configuring marketing campaign data corresponding to the store group according to the store group information contained in the aggregated stores.
A fourth embodiment of the present application provides an order processing apparatus corresponding to the second embodiment. The device is described below with reference to fig. 6. The order processing apparatus shown in fig. 6 includes:
an order receiving unit 601 configured to acquire order information generated for an object of an aggregation store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area;
the order pushing unit 602 is configured to screen schedulable stores meeting scheduling conditions from real stores associated with the aggregation store, and push the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object.
Optionally, the pushing unit 602 is specifically configured to: acquiring information of real stores associated with the aggregated store; and screening out real stores of which the order backlog index data do not exceed the order backlog threshold value as the dispatchable stores.
Optionally, the pushing unit 602 is specifically configured to: and determining the delivery time length and/or meal delivery time length of a real store of the aggregated store, and taking the real store as the dispatchable store if the delivery time length does not exceed the preset delivery time length in the dispatching condition and/or the meal delivery time length does not exceed the preset meal delivery time length in the dispatching condition.
Optionally, the pushing unit 602 is specifically configured to: if order receiving information sent by a target store in the dispatchable stores is received within a preset time length, the order information is dispatched to the target store; otherwise, calculating the scheduling scores of the dispatchable stores according to the scheduling index data of the dispatchable stores and the index weights corresponding to the scheduling index data, selecting target stores from the dispatchable stores according to the scheduling scores, and dispatching the order information to the target stores.
Based on the above embodiments, a fifth embodiment of the present application provides an electronic device, and please refer to the corresponding description of the above embodiments for related parts. Referring to fig. 7, the electronic device shown in the figure includes: a memory 701, and a processor 702; the memory is used for storing a computer program, and the computer program is executed by the processor to execute the method provided by the embodiment of the application.
Based on the foregoing embodiments, a sixth embodiment of the present application provides a storage device, and please refer to the corresponding description of the foregoing embodiments for related parts. The schematic diagram of the storage device is similar to fig. 7. The storage device stores a computer program, and the computer program is executed by the processor to execute the method provided by the embodiment of the application.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
1. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
2. As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Although the present application has been described with reference to the preferred embodiments, it is not intended to limit the present application, and those skilled in the art can make variations and modifications without departing from the spirit and scope of the present application, therefore, the scope of the present application should be determined by the claims that follow.

Claims (10)

1. A store data processing method, comprising:
acquiring information of a real store matched with a target geographic area;
aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information;
displaying information of the aggregation store to a target user device; the geographical area of the target user equipment is matched with the target geographical area.
2. The method of claim 1, further comprising:
and determining a geographic area matched with the geographic area of the target user equipment as the target geographic area.
3. The method of claim 2, wherein the geographic area of the target ue is a dynamic scene area determined based on a current location of the target ue;
the acquiring of the information of the real stores matched with the target geographic area comprises:
selecting information of the real store according to the dynamic scene area;
the aggregation store is a store group of real stores associated with the same brand information in the dynamic scene area.
4. The method of claim 1, wherein the target geographic area is a geographic area determined based on pre-divided geographic grid and/or business turn information;
the aggregation store is a pre-formed store group of real stores associated with the same brand information in a target geographic area;
the displaying the information of the polymerization store to the target user equipment comprises:
determining the geographical area of the target user equipment;
and if the geographical area of the target user equipment and the geographical area of the target user equipment contain the same geographical identification, pushing the information of the aggregated store to the target user equipment and displaying the information.
5. The method of claim 4, wherein the target geographic area contains geographic identifiers for a plurality of geographic grids;
aggregating the real stores based on the brand information associated with the real stores to form aggregated stores corresponding to the brand information, including:
aggregating real stores within each geographic grid based on brand information associated with the real stores to form a store group corresponding to each geographic grid for the brand information;
and combining to form an aggregate store aiming at the brand information and comprising a plurality of store groups according to the information of the store groups corresponding to each geographic grid in the target geographic area.
6. The method of claim 1 or 5, wherein the presenting information of the aggregation store to a target user device comprises:
determining real stores meeting scheduling conditions in the aggregation stores or store groups contained in the aggregation stores;
acquiring the object information of the real stores meeting the scheduling conditions as the object information of the aggregated stores;
and displaying the object information of the aggregation store.
7. The method of claim 1 or 5, further comprising:
acquiring a first expected delivery duration of each real store object meeting the scheduling condition;
taking the average value of the first expected delivery duration as a second expected delivery duration of the object of the aggregation store;
and displaying the second expected delivery time length.
8. The method of claim 1 or 5, further comprising:
acquiring the distance between each real store meeting the scheduling condition and the target user equipment as a first delivery distance;
taking an average of the first delivery distances as a second delivery distance between the aggregation store and the target user device;
and displaying the second distribution distance.
9. The method of claim 1, wherein the aggregating the real stores based on brand information associated with the real stores to form aggregated stores corresponding to brand information comprises:
acquiring information of a first real store and information of a second real store which are related to the same brand information in the target area;
generating identification information of the aggregation store according to the brand information;
associating the same object of the first real store and the second real store with the aggregation store as a unified menu object of the aggregation store;
associating different objects of the first real store and the second real store with the aggregate store as a designated menu object of the aggregate store.
10. An order processing method, comprising:
acquiring order information generated aiming at an object of an aggregation store; the aggregation store is an abstract store corresponding to brand information and formed by aggregating real stores based on the brand information associated with the real stores in the target geographic area;
screening schedulable stores meeting scheduling conditions from real stores associated with the aggregation stores, and pushing the order information to the schedulable stores; the schedulable store is a candidate real store that can provide the object.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114463103A (en) * 2022-04-08 2022-05-10 浙江口碑网络技术有限公司 Data processing method and equipment
CN115018521A (en) * 2022-08-02 2022-09-06 浙江口碑网络技术有限公司 Medical and beauty data processing method, electronic equipment and storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114463103A (en) * 2022-04-08 2022-05-10 浙江口碑网络技术有限公司 Data processing method and equipment
CN114463103B (en) * 2022-04-08 2022-07-15 浙江口碑网络技术有限公司 Data processing method and equipment
CN115018521A (en) * 2022-08-02 2022-09-06 浙江口碑网络技术有限公司 Medical and beauty data processing method, electronic equipment and storage medium

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