KR20210131009A - Method and system for controlling order and delivery of order service provider - Google Patents

Abstract

Disclosed are a method and system for controlling an order and delivery of an order relay business. By providing an order relay service using a delivery app, exposure of a menu for a store on the delivery app can be controlled based on the in-store situation information. Therefore, the present invention is capable of allowing the data to be analyzed.

Description

METHOD AND SYSTEM FOR CONTROLLING ORDER AND DELIVERY OF ORDER SERVICE PROVIDER

The description below relates to a method and system for order and delivery control of an order relay operator.

Recently, the proportion of using signage-based digital menu boards or displays is increasing in stores, and a kiosk-based ordering system is being established.

For example, Korean Patent Application Laid-Open No. 10-2014-0119242 (published on October 10, 2014) discloses a technology for ordering a store menu by wirelessly connecting to a kiosk in a store through an orderer smartphone in contact with a tag. .

It provides methods and systems for analyzing data through in-store data collection.

It provides a method and system that can provide and manage a digital menu in a variable type based on a CMS (content management system) as well as a fixed type.

A method and system for improving delivery efficiency by controlling user exposure information on delivery apps are provided.

A method executed on a computer system, the computer system comprising at least one processor configured to execute computer readable instructions contained in a memory, the method comprising: providing an order relay service using a delivery app; receiving, by at least one processor, in-store context information; and, by the at least one processor, controlling exposure of the menu of the store on the delivery app based on the context information.

According to an aspect, the receiving may include receiving at least one of an order waiting time for each menu and stock on the day as the order processing related information of the store.

According to another aspect, the controlling may include adjusting the menu exposure priority on the delivery app according to the context information.

According to another aspect, the method may further include, by the at least one processor, first exposing a store in a neighboring area through the delivery app.

According to another aspect, the exposing may expose a store adjacent to the customer's location or another store adjacent to the store selected by the customer.

According to another aspect, the method may further include, by the at least one processor, first exposing, by the at least one processor, the same store among customers to generate a duplicate order.

According to another aspect, the exposing may expose the same store to customers within a predetermined radius for an order within a predetermined time.

According to another aspect, the method comprises: generating, by the at least one processor, a list of callable riders based on the location of the customer; performing, by the at least one processor, regional clustering based on customer order information; and allocating, by the at least one processor, to each cluster according to the regional clustering.

According to another aspect, the generating may generate the list of riders based on at least one of a delivery area available for each rider, a delivery item, and an option for charging a delivery cost.

According to another aspect, the performing may include performing the regional clustering based on the location of the customer.

According to another aspect, the performing may include performing additional clustering based on items of an order menu for the same cluster.

According to another aspect, the method may further include, by the at least one processor, generating a list of deliverable stores for the order information of the customer.

According to another aspect, the generating of the store list may include generating the store list based on a delivery area set in each store and a location of the customer.

It provides a computer-readable recording medium in which a computer program for executing the method in a computer device is recorded.

A computer system comprising at least one processor configured to execute computer readable instructions contained in a memory, wherein the at least one processor provides an order relay service using a delivery app, and receives in-store situation information It provides a computer system, characterized in that for controlling the menu exposure of the store on the delivery app based on the context information.

1 is a block diagram illustrating an example of an internal configuration of a computer system according to an embodiment of the present invention.
2 is a view showing the overall system configuration for store data analysis in an embodiment of the present invention.
3 is a diagram for explaining a process of controlling menu exposure according to a store situation according to an embodiment of the present invention.
4 is a flowchart illustrating an example of a store data analysis method that the central system can perform according to an embodiment of the present invention.
5 is a view showing the overall system configuration for order and delivery control in an embodiment of the present invention.
6 is a diagram for explaining a process of providing an order relay service according to an embodiment of the present invention.
7 is a flowchart illustrating an example of a delivery control method that can be performed by the order relay server according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention relate to a method and system for order and delivery control of an order relay operator.

Embodiments including those specifically disclosed herein may present a method for analyzing data through in-store data collection, and provide a digital menu in a variable form based on a CMS (content management system) as well as a fixed type and manage.

1 is a block diagram illustrating an example of an internal configuration of a computer system according to an embodiment of the present invention. For example, a store data analysis system according to embodiments of the present invention may be implemented through the computer system 100 of FIG. 1 . 1, the computer system 100 is a component for executing the store data analysis method, and includes a processor 110, a memory 120, a permanent storage device 130, a bus 140, an input/output interface ( 150 ) and a network interface 160 .

Processor 110 may include or be part of any device capable of processing a sequence of instructions as a component for store data collection and analysis. Processor 110 may include, for example, a computer processor, a processor in a mobile device, or other electronic device and/or a digital processor. The processor 110 may be included in, for example, a server computing device, a server computer, a set of server computers, a server farm, a cloud computer, a content platform, and the like. The processor 110 may be connected to the memory 120 through the bus 140 .

Memory 120 may include volatile memory, permanent, virtual, or other memory for storing information used by or output by computer system 100 . The memory 120 may include, for example, random access memory (RAM) and/or dynamic RAM (DRAM). Memory 120 may be used to store any information, such as state information of computer system 100 . Memory 120 may also be used to store instructions of computer system 100 including, for example, instructions for collecting and analyzing store data. Computer system 100 may include one or more processors 110 as needed or appropriate.

Bus 140 may include a communications infrastructure that enables interaction between various components of computer system 100 . Bus 140 may carry data between, for example, components of computer system 100 , such as between processor 110 and memory 120 . Bus 140 may include wireless and/or wired communication media between components of computer system 100 and may include parallel, serial, or other topological arrangements.

Persistent storage 130 is a component, such as memory or other persistent storage, as used by computer system 100 to store data for an extended period of time (eg, compared to memory 120 ). may include Persistent storage 130 may include non-volatile main memory as used by processor 110 in computer system 100 . Persistent storage 130 may include, for example, flash memory, a hard disk, an optical disk, or other computer readable medium.

The input/output interface 150 may include interfaces to a keyboard, mouse, voice command input, display, or other input or output device. Configuration commands and/or inputs for store data collection and analysis may be received via the input/output interface 150 .

Network interface 160 may include one or more interfaces to networks such as a local area network or the Internet. Network interface 160 may include interfaces for wired or wireless connections. Configuration commands and/or input for store data collection and analysis may be received via network interface 160 .

Also, in other embodiments, computer system 100 may include more components than those of FIG. 1 . However, there is no need to clearly show most of the prior art components. For example, the computer system 100 is implemented to include at least some of the input/output devices connected to the above-described input/output interface 150, or a transceiver, a global positioning system (GPS) module, a camera, various sensors, It may further include other components such as a database and the like.

Hereinafter, specific embodiments of a method and system for collecting and analyzing customer information in a store will be described.

Recently ^{, as securing 1st} party data has become more important, a method for directly collecting customer data from stores that have offline stores for each brand is needed. In addition, it is possible to build an environment that can collect information in the store through CCTV and various sensors.

The store data analysis system according to the present invention can provide and manage the digital menu of the store in a variable form based on CMS as well as in a fixed form.

The store data analysis system according to the present invention may analyze data through in-store data collection. A method for collecting data for target advertisement and change of order quantity according to advertisement exposure is needed by identifying the correlation between digital menus and orders exposed at a specific point in time. By controlling in-store orders, customers can effectively manage product delivery time reduction and stock exhaustion on the same day after placing an order.

2 is a view showing the overall system configuration for store data analysis in an embodiment of the present invention.

2 shows a central system 210 , a separate store system 220 , and a delivery server 230 . In this case, the central system 210 , the individual store system 220 , and the delivery server 230 may be implemented as the computer system 100 described with reference to FIG. 1 .

The central system 210 serves as a server for store data analysis, and includes a data aggregation module 211 , a menu and ad. control module 212 , and a data analysis module ( a data analysis module 213 , and a network module 214 .

The individual store system 220 serves as a client that provides store data to the central system 210 and variably provides a digital menu under the control of the central system 210, and includes a menu and advertisement control module 221, data collection and a data aggregation and delivery module 222 , an order processing module 223 , a digital menu board 224 , a POS module 225 , a kiosk POS module 226 , and a CCTV 227 . , and Wi-Fi 228 .

Referring to FIG. 3 , the data collection and delivery module 222 collects in-store data and delivers it to the central system 210 .

The digital menu board 224 serves to expose menu information under the control of the central system 210 .

The order processing module 223 serves to process orders of customers in the store and to process pickup information after ordering.

The POS module 225 serves to provide the customer's order time information and menu exposure information on the digital menu board 224 to the data collection and delivery module 222 .

The kiosk POS module 226 serves to provide the customer's order time information, menu exposure information on the digital menu board 224, menu navigation information using a shopping cart, etc. to the data collection and delivery module 222 .

CCTV 227 is a data collection and delivery module for customer visit time information, customer movement information, customer order waiting information (order, menu selection, etc.), customer profile information (eg, gender, age, etc.) (222) performs the role provided.

The Wi-Fi 228 includes the customer's terminal information, the customer's browser information (provides a method that can replace the company's cookies (eg, fingerprint, etc.) when using free WiFi), the customer's stay information (eg, the time spent in the store), etc. It serves to provide the data collection and delivery module 222 .

The individual store system 220 provides an in-store digital menu board linkage service, and in particular, may include a requirement to induce a customer's menu selection in consideration of store order waiting time and same-day inventory.

The individual store system 220 may adjust an exposure time, an exposure frequency, and an exposure position (exposure order, etc.) when the menu on the digital menu board 224 is exposed. Depending on the weight of the menu, the exposure time, exposure frequency, exposure position, etc. of the menu can be configured differently. In this case, the weight may be determined based on an order waiting time of each menu, stock on the day, etc. For example, the longer the waiting time for an order, the smaller the weight may be as the stock of the day decreases.

The individual store system 220 may assign a temporary code upon exposure of the menu on the digital menu board 224 . Temporarily assigned custom codes (eg, numbers, numbers, character strings, etc.) can be displayed for specific items instead of the existing menu numbers. For example, the number of a specific menu can be changed from '1' to '1-1' or to 'time deal 101'.

Customers can order by presenting the number of the menu they want to order at the POS, selecting or directly entering the menu number at the kiosk, entering it on a mobile device, or scanning a QR code or barcode.

The individual store system 220 may provide an additional service according to input of the corresponding number to the customer when ordering using the number of the menu, and may provide, for example, discounts, savings, various benefits, and the like.

The menu and advertisement control module 212 may generate a customized code according to the situation of the store, and in particular, a temporary code may be given to each menu in consideration of the stock quantity on the day, preparation time (order waiting time), store policy, etc. can

The order processing module 223 may provide a processing time for each menu (order), a total waiting time, a total same-day processing amount, etc. as order processing-related information.

The digital menu board 224 may expose the customized code generated by the menu and advertisement control module 212 in the form of an advertisement for inducing a customer's menu selection. The digital menu board 224 may expose specific code information in the menu.

The POS module 225 and the kiosk POS module 226 may proceed with inputting a specific code when ordering from a customer, and may provide various additional services such as benefits according to the progress of entering the code.

The individual store system 220 is controlled by the central system 210 according to a weight in consideration of the store order waiting time or stock on the day, for example, by inducing a selection to a menu that does not accumulate much order, so that a specific product at a specific time is provided. It is possible to effectively avoid the crowding of orders, shorten the overall order waiting time, and implement efficient sales control according to the stock situation on the day.

4 is a flowchart illustrating an example of a store data analysis method that the central system can perform according to an embodiment of the present invention.

The store data analysis method may operate based on menu information in the order information, and in this case, the in-store menu may consist of a single item or a set menu.

Referring to FIG. 4 , in step S41 , the central system 210 may collect or receive in-store order information from the individual store system 220 . In this case, the order information may include at least one menu ordered by the customer.

In step S42 , the central system 210 may calculate the order processing time through interworking with the individual store system 220 .

In step S43 , the central system 210 may update average information on the in-store order processing time through interworking with the individual store system 220 . The central system 210 may update the order waiting time for each menu.

In step S44, the central system 210 may set a processing threshold or policy value for each menu in the order. As a method of setting a threshold or policy value, as an example, a relative value based on the actual required time compared to the basic processing time value for each menu in the order may be used, and as another example, an order processing time based on an absolute value may be used.

In step S45 , the central system 210 may update the weight of each menu when the order processing time for each menu within the order exceeds a threshold value or a policy value. By updating the weight according to the processing time for each menu, the exposure location, exposure time, exposure frequency, discount policy, etc. of the menu may vary based on the weight. can For example, in the case of a menu whose weight is less than or equal to a certain level according to the accumulation of orders, guide information on the required time may be provided.

In step S46 , the central system 210 may check whether the store manager confirms the weight update of the in-store menu.

In step S47 , when the confirmation of the store manager is confirmed, the central system 210 may update and expose menu information based on the weight of each menu on the digital menu board 224 of the store.

In step S48 , the central system 210 may also update information on the POS module 225 and the kiosk POS module 226 as menu information on the digital menu board 224 is updated.

On the digital menu board 224 , the layout or menu arrangement of the menu structure may be changed after the store manager confirms under the control of the central system 210 , and code values of each menu may be exposed. When the menu information of the digital menu board 224 is updated, the POS module 225 and the kiosk POS module 226 may update related information for ordering each updated menu.

Depending on the store situation, menus with fewer orders and more stock can be exposed by raising priority, and benefits such as discounts can be provided to users who order the menu. A menu that takes a long time due to a large number of orders can be given a lower weight to provide fewer benefits, and a menu with fewer orders can be given a higher weight to provide many benefits.

Hereinafter, a specific embodiment of the order and delivery control method and system of the order relay server will be described.

5 is a view showing the overall system configuration for order and delivery control in an embodiment of the present invention.

Referring to FIG. 5 , the order relay server 510 is a business server that provides an order relay service, and may control customer exposure information on a delivery app through interworking with the delivery server 230 that provides a delivery relay service.

The order relay server 510 may be implemented as a server system included in the central system 210 or may be implemented as a separate server system capable of interworking with the central system 210 .

The order relay server 510 may provide an order relay service by interworking with the individual store system 220 , and in particular, may control an order in consideration of a store situation. The order relay server 510 may adjust menu exposure priority, etc. by using in-store information (store order waiting time, stock on the day, etc.) received from the individual store system 220 .

The order relay server 510 may control the exposed menu of the store on the delivery app installed on the customer device 501 according to the priority of menu exposure according to the store situation.

The order relay server 510 may support delivery relay for each neighboring area based on the location of the device 501 used by the customer in conjunction with the delivery server 230 .

In order to improve delivery efficiency, the order relay server 510 may preferentially expose a store in a corresponding area centered on an adjacent area, and may support creation of an additional order through priority exposure centered on an adjacent area. For example, the order relay server 510 may preferentially expose a store close to the customer's location or additionally expose another store adjacent to the store selected by the customer. Also, the order relay server 510 may support order creation of the corresponding store by first exposing the same store in order to generate duplicate orders. The order relay server 510 may preferentially expose the same store to customers within a predetermined radius for an order within a predetermined time. For example, with respect to the store I ordered by the user A, the store I may be first exposed to the user B adjacent to the user A.

As shown in FIG. 6 , the order relay server 510 may include an order linkage server 611 , a local service exposure control server 612 , and a delivery app 613 .

The order processing module 223 of the individual store system 220 may provide the processing time for each menu (order), the total waiting time, the total amount of processing on the day, etc. to the central system 210 as order processing related information of the corresponding store.

The menu and advertisement control module 212 of the central system 210 may generate a customized code according to the situation and provide it to the order link server 611, in particular, for each menu, the stock quantity on the day, the preparation time (order waiting time) ), a temporary code can be assigned in consideration of store policies, etc.

The order link server 611 may interwork with the menu and advertisement control module 212 to periodically update order delay time information based on the order waiting time of each store, and may update orderable menu information.

The local service exposure control server 612 may control the local service (eg, advertisement, etc.) exposure according to the order situation for each store and the request of the operator, and may control the menu exposure priority of each store, and thus the delivery app 613 ), a customer order may occur according to the exposure of the image.

The order relay server 510 can adjust the priority when exposing the menu of the delivery app based on the order processing information collected in the store, thereby avoiding the increase in order processing time due to the rush of orders for a specific menu at a specific time. This allows the store to increase the efficiency of menu processing.

7 is a flowchart illustrating an example of a delivery control method that can be performed by the order relay server according to an embodiment of the present invention.

Referring to FIG. 7 , in step S71 , the order relay server 510 may receive the customer's order information through the delivery app. The order information may include customer location information, menu information, and the like.

In step S72, the order relay server 510 may perform a delivery available store list-up for providing customer service with respect to the customer's order information. For example, the order relay server 510 may generate a store list based on a delivery area set in each store. As another example, the order relay server 510 may generate a list of stores based on the callable rider based on the customer location.

In step S73, the order relay server 510 may perform a list-up of the rider information that can be called based on the customer location. The order relay server 510 may generate a rider information list based on a delivery area for each rider, a delivery available item, a delivery charge option (orderer option, a seller option, etc.).

In step S74, the order relay server 510 may perform regional clustering based on the customer's order information. The order relay server 510 may group customers in the same region based on the customer location. In this case, the order relay server 510 may perform additional clustering based on item information of the order menu when there are orders for several items (eg, cold menu or warm menu) in the same cluster.

In step S75, the order relay server 510 may allocate riders to each cluster based on the rider information. The order relay server 510 may allocate delivery riders based on priority based on the number of delivery cases, delivery cost bidding, and the like.

In step S76, the order relay server 510 may complete the order information processing by transferring the order information of the customer assigned to the rider when the rider assignment is completed.

The order relay server 510 can adjust the menu exposure priority according to the situation in the store, so it is possible to avoid an increase in order processing time due to a rush of orders for a specific menu, and to relay delivery for each neighboring area or expose duplicate order companies first. This can improve delivery efficiency.

The device described above may be implemented as a hardware component, a software component, and/or a combination of the hardware component and the software component. For example, the devices and components described in the embodiments may include a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), and a programmable logic unit (PLU). It may be implemented using one or more general purpose or special purpose computers, such as a logic unit, microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be embodied in any type of machine, component, physical device, computer storage medium or device for interpretation by or providing instructions or data to the processing device. have. The software may be distributed over networked computer systems, and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. In this case, the medium may be to continuously store the program executable by the computer, or to temporarily store the program for execution or download. In addition, the medium may be a variety of recording means or storage means in the form of a single or several hardware combined, it is not limited to a medium directly connected to any computer system, and may exist distributed on a network. Examples of the medium include a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and those configured to store program instructions, including ROM, RAM, flash memory, and the like. In addition, examples of other media may include recording media or storage media managed by an app store for distributing applications, sites for supplying or distributing other various software, and servers.

As described above, although the embodiments have been described with reference to the limited embodiments and drawings, various modifications and variations are possible by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (15)

A method executed on a computer system, comprising:
the computer system comprising at least one processor configured to execute computer readable instructions contained in a memory;
The method is
By providing an order relay service using a delivery app,
receiving, by the at least one processor, in-store situation information; and
Controlling, by the at least one processor, the menu exposure of the store on the delivery app based on the context information
How to include. According to claim 1,
The receiving step is
Receiving at least one of an order waiting time for each menu and stock on the same day as the order processing related information of the store
How to include. According to claim 1,
The controlling step is
Adjusting the menu exposure priority on the delivery app according to the context information
How to include. According to claim 1,
The method is
By the at least one processor, the first step of exposing a store in a neighboring area through the delivery app
How to include more. 5. The method of claim 4,
The exposing step is
Exposing stores adjacent to a customer's location or other stores adjacent to the store selected by said customer;
How to characterize. According to claim 1,
The method is
First exposing, by the at least one processor, the same store among customers to create duplicate orders.
How to include more. 7. The method of claim 6,
The exposing step is
Exposing the same store to customers within a certain radius for orders within a certain time
How to characterize. According to claim 1,
The method is
generating, by the at least one processor, a list of callable riders based on the location of the customer;
performing, by the at least one processor, regional clustering based on customer order information; and
Allocating, by the at least one processor, a rider for each cluster according to the regional clustering
How to include more. 9. The method of claim 8,
The generating step is
generating the list of riders based on at least one of a delivery area for each rider, a deliverable item, and an option to charge a delivery fee.
How to characterize. 9. The method of claim 8,
The performing step is,
performing the regional clustering based on the location of the customer;
How to characterize. 9. The method of claim 8,
The performing step is,
Steps to perform additional clustering based on items in the order menu for the same cluster
How to include. 9. The method of claim 8,
The method is
generating, by the at least one processor, a list of deliverable stores for the customer's order information
How to include more. 13. The method of claim 12,
The step of generating the store list includes:
Generating the store list based on the delivery area set in each store and the location of the customer
How to characterize. A computer-readable recording medium in which a computer program for executing the method of any one of claims 1 to 13 in a computer device is recorded. In a computer system,
at least one processor configured to execute computer readable instructions contained in memory
including,
the at least one processor,
Provide order relay service using delivery app,
Receive in-store context information and control the menu exposure of the store on the delivery app based on the context information
A computer system characterized by a.

Images