WO2023074974A1 - 배송 관련 정보를 처리하는 전자 장치 및 그 방법 - Google Patents

배송 관련 정보를 처리하는 전자 장치 및 그 방법 Download PDF

Info

Publication number
WO2023074974A1
WO2023074974A1 PCT/KR2021/015545 KR2021015545W WO2023074974A1 WO 2023074974 A1 WO2023074974 A1 WO 2023074974A1 KR 2021015545 W KR2021015545 W KR 2021015545W WO 2023074974 A1 WO2023074974 A1 WO 2023074974A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
delivery
shopping cart
store
order
Prior art date
Application number
PCT/KR2021/015545
Other languages
English (en)
French (fr)
Korean (ko)
Inventor
손승표
이길호
Original Assignee
쿠팡 주식회사
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 쿠팡 주식회사 filed Critical 쿠팡 주식회사
Publication of WO2023074974A1 publication Critical patent/WO2023074974A1/ko

Links

Images

Classifications

    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • 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
    • 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
    • G06Q30/0204—Market segmentation
    • G06Q30/0205—Location or geographical consideration
    • 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
    • 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services

Definitions

  • the present disclosure relates to an electronic device and method for processing delivery-related information. More specifically, the present disclosure relates to a method of acquiring an input to a shopping cart, obtaining expected order information corresponding to the input of adding a shopping cart based on the input, and providing the same to one or more candidate delivery drivers, and an electronic device using the same.
  • the delivery person arrives at the store (e.g. restaurant) before completing the cooking of the ordered food, or arrives at the store as soon as possible after the cooking of the ordered food is completed, thereby quickly delivering the ordered food to the customer. Needs to be.
  • the store e.g. restaurant
  • the delivery person arrives at the store (e.g. restaurant) before completing the cooking of the ordered food, or arrives at the store as soon as possible after the cooking of the ordered food is completed, thereby quickly delivering the ordered food to the customer. Needs to be.
  • food delivery services tend to concentrate delivery work at specific times (e.g. common meal times) and specific locations (e.g. densely populated areas), so that when delivery work is crowded, enough deliveries are not available to the stores. If it is not located nearby, delivery efficiency may decrease and delivery delays may occur.
  • This problem may be the same for various items other than food that require prompt delivery (e.g. flowers, parcels ordered for express delivery, etc.).
  • the problem to be solved by the present embodiment is to obtain one or more shopping cart addition inputs each including store information and item information, and to at least one of one or more pieces of information included in the one or more shopping cart addition inputs, in order to solve the above-described problem. based on this, obtaining expected order information corresponding to the one or more add-to-cart inputs, determining one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more add-to-cart inputs, and determining one or more candidate deliveries. It is an object of the present invention to provide an electronic device and method for providing prospective order information to customers.
  • a method of processing information in an electronic device providing an item delivery service includes obtaining one or more inputs to add to a shopping cart, each of which includes store information and item information. obtaining expected order information corresponding to the one or more shopping cart addition inputs based on at least one of the one or more pieces of information included in the one or more shopping cart addition inputs; determining one or more candidate delivery sources based on the expected order information and one or more store information included in the one or more shopping cart addition inputs; and providing the prospective order information to the one or more candidate delivery carriers.
  • the obtaining of the expected order information may include obtaining probability information including a result of calculating a probability value that will be converted into an actual order for at least some of the one or more inputs to add to the shopping cart; and obtaining the expected order information based on the probability information.
  • the obtaining of probability information includes classifying at least some of the one or more shopping cart addition inputs into one or more groups based on one or more store information included in the one or more shopping cart addition inputs; and calculating probabilities of converting into actual orders for each of the one or more groups.
  • the one or more groups are set for each specific regional range, and the classifying into the one or more groups includes location information for each one or more stores included in the one or more store information and correspondence for each of the one or more groups. and classifying at least some of the one or more shopping cart addition inputs into the one or more groups based on a result of comparing the regional ranges.
  • the obtaining of the probability information may include determining an order history for each store corresponding to the one or more store information based on the one or more store information included in the one or more shopping cart addition inputs; and obtaining the probability information based on the order history.
  • the step of determining the order history for each store may include store information included in an item corresponding to item information included in a specific shopping cart input for at least some of the one or more shopping cart addition inputs. It may include the step of determining the order history in the store corresponding to.
  • the obtaining of the probability information may include determining one or more order histories for each user corresponding to the one or more shopping cart addition inputs; and obtaining the probability information based on the order history.
  • the obtaining of the expected order information based on the probability information includes, for each one or more probability values included in the probability information, the number of shopping cart addition inputs corresponding to the corresponding probability value and the corresponding probability value. multiplication operation; and generating the order expected value information based on a result of the multiplication operation.
  • the determining of the one or more candidate delivery sources includes determining one or more location information corresponding to the expected order information based on the one or more store information; and obtaining information on at least one delivery person located within a predetermined radius based on the at least one location information.
  • the determining of the one or more candidate delivery sources may include determining whether the one or more candidate delivery sources can be allocated the actual order when an actual order corresponding to the expected order information occurs; And based on a result of determining whether the actual order can be assigned, the method may further include determining the one or more candidate delivery crews from among the one or more delivery crews.
  • the step of determining whether the actual order can be allocated includes determining whether the one or more delivery agents are in a delivery available state; determining whether a movement path from the location of the at least one delivery person to at least one location corresponding to the expected order information satisfies a preset condition; determining information on means of transportation used by the at least one delivery person; and determining whether a time to allocate the actual order is included in a preset time interval when the actual order occurs.
  • the providing of the expected order information may include providing a page including a map displaying the expected order information to the one or more candidate delivery men.
  • the map displaying the expected order information may be displayed based on coordinate information generated based on a result of determining the density of expected orders for each specific regional range.
  • the providing of the expected order information may include suggesting movement to one or more locations corresponding to the expected order information to the one or more candidate deliverymen.
  • the information processing method may further include requesting preparation of an item from a store based on the expected order information.
  • An electronic device for processing information to provide an item delivery service includes a transceiver, a memory for storing commands, and a processor, and the processor is connected to the transceiver and the memory to input one or more shopping cart additions.
  • an electronic device and method for processing delivery-related information predict future order generation based on an input to a shopping cart and provide the predicted result to one or more candidate delivery agents, thereby providing demand for delivery services and delivery services. It is possible to reduce the gap between the supply of Through this, since the delivery man can move in advance to an area where delivery orders are expected to be high, speedy and timely delivery is performed by reducing the gap between the time the item is ready and the time the delivery man arrives at the store to pick up the item. You can do it, and you can handle more shipping tasks.
  • FIG. 1 is a schematic configuration diagram illustrating a system for processing delivery-related information according to an embodiment.
  • FIG. 2 is an operation flowchart of a delivery order processing method of an electronic device in a system for processing delivery-related information according to an embodiment.
  • 3 is a diagram for illustratively explaining an operation of classifying at least some of one or more shopping cart addition inputs into one or more groups according to an embodiment.
  • FIG. 4 is a diagram for illustratively explaining an operation of determining a candidate delivery person according to an embodiment.
  • FIG. 5 is a diagram for illustratively explaining a result of determining whether a delivery person can be assigned an actual order according to an embodiment.
  • FIG. 6 is a diagram for illustratively describing a map displaying expected order information according to an exemplary embodiment.
  • FIG 7 is an operation flowchart of an information processing method of an electronic device according to an embodiment.
  • FIG. 8 is an exemplary diagram of a configuration of an electronic device that processes delivery-related information according to an embodiment.
  • a “terminal” referred to below may be implemented as a computer or portable terminal capable of accessing a server or other terminals through a network.
  • the computer includes, for example, a laptop, desktop, laptop, etc. equipped with a web browser
  • the portable terminal is, for example, a wireless communication device that ensures portability and mobility.
  • IMT International Mobile Telecommunication
  • CDMA Code Division Multiple Access
  • W-CDMA Wide-Code Division Multiple Access
  • LTE Long Term Evolution
  • each block of the process flow chart diagrams and combinations of the flow chart diagrams can be performed by computer program instructions.
  • These computer program instructions may be embodied in a processor of a general purpose computer, special purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment are described in the flowchart block(s). It creates means to perform functions.
  • These computer program instructions may also be stored in a computer usable or computer readable memory that can be directed to a computer or other programmable data processing equipment to implement functionality in a particular way, such that the computer usable or computer readable memory
  • the instructions stored in are also capable of producing an article of manufacture containing instruction means that perform the functions described in the flowchart block(s).
  • the computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to generate computer or other programmable data processing equipment. Instructions for performing processing equipment may also provide steps for performing the functions described in the flowchart block(s).
  • each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical function(s). It should also be noted that in some alternative implementations it is possible for the functions mentioned in the blocks to occur out of order. For example, two blocks shown in succession may in fact be executed substantially concurrently, or the blocks may sometimes be executed in reverse order depending on their function.
  • FIG. 1 is a schematic configuration diagram illustrating a system for processing delivery-related information according to an embodiment.
  • the system 100 for processing delivery-related information includes an electronic device 110, a user device 120, and a deliveryman device 130, and further includes a store device 140 according to an embodiment.
  • the system 100 for processing delivery-related information is a network supporting information transmission and reception between at least some of the electronic device 110, the user device 120, the delivery person device 130, and the store device 140. More networks may be included.
  • Each of the electronic device 110 , user device 120 , carrier device 130 , and store device 140 may include a transceiver, a memory, and a processor.
  • each of the electronic device 110, the user device 120, the delivery company device 130, and the store device 140 means a unit that processes at least one function or operation, which is hardware, software, or hardware. And it can be implemented as a combination of software.
  • each of the electronic device 110, the user device 120, the delivery company device 130, and the store device 140 is referred to as a separate device or server, but it may be a logically divided structure, and these At least some of them may be implemented by separate functions in one device or server.
  • the user device 120, the deliveryman device 130, and the store device 140 are not limited to a single device, but may be a concept encompassing a plurality of devices.
  • the user device 120 may be a general concept of a device used to provide an item delivery service for each one or more users.
  • the deliveryman device 130 may be a concept collectively referring to devices used for each of one or more candidate deliverymen determined by the electronic device 110 .
  • the store device 140 may be a collective concept of devices used by one or more sellers who perform at least one of preparing items and selling items.
  • the electronic device 110, the user device 120, the deliveryman device 130, and the store device 140 may include a plurality of computer systems or computer software implemented as a network server.
  • the electronic device 110, the user device 120, the delivery company device 130, and the store device 140 may communicate with other network servers through a computer network such as an intranet or the Internet. It may refer to a computer system and computer software that is connected to a device to receive a request for performing a task, performs a task for the request, and provides a result of performing the task.
  • At least some of the electronic device 110, the user device 120, the deliveryman device 130, and the store device 140 are built in a series of applications that can operate on a network server and in other nodes connected or internally. It can be understood as a concept in a broad sense that includes various databases.
  • at least some of the electronic device 110, the user device 120, the delivery company device 130, and the store device 140 are DOS, Windows, Linux, UNIX, Alternatively, it may be implemented using a network server program provided in various ways according to an operating system such as MacOS.
  • the electronic device 110 is a device that configures and provides various types of information.
  • the electronic device 110 may provide the configured information as a web page or application screen.
  • the electronic device 110 may be a device that serves to transmit and receive various information including information related to delivery, such as an input to add to a shopping cart and expected order information, to a user, a delivery man, and a seller.
  • the electronic device 110 obtains one or more inputs for adding to a shopping cart.
  • One or more shopping cart addition inputs may be obtained from one or more users through the user device 120 .
  • the shopping cart corresponds to an interface that allows the user to place an item desired to purchase on the purchase candidate list
  • the input to add to the shopping cart may correspond to an operation of placing a specific item on the purchase candidate list.
  • Each of the one or more shopping cart add inputs includes store information and item information.
  • Item information may correspond to information on a specific item to be placed on the purchase candidate list.
  • the store information may correspond to information about a store operated by a seller who performs at least one of preparing items and selling items.
  • Store information according to an embodiment may include store location information.
  • the item added to the shopping cart is more likely to lead to purchase on average than items not added to the shopping cart.
  • One or more inputs for adding to a shopping cart obtained from the user may include an input for adding food to a shopping cart.
  • the food may include various types of food, such as solid food, liquid food (eg, beverage or sauce), and gel-type food.
  • the input to add to the shopping cart is related to a service in which the electronic device 110 assigns a delivery person to deliver items from another subject according to a user's request through relaying, as well as an input to add to a shopping cart for food.
  • the input to add to the shopping cart obtained from the user is not limited to the input to add to the shopping cart for food.
  • the input to add to the shopping cart obtained from the user may include an input to add to the shopping cart for items requiring rapid delivery, such as flowers, feed, and other organisms, in addition to food.
  • the input to add to the shopping cart obtained from the user is not limited to items requiring prompt delivery, and may include an input to add to the shopping cart for industrial products, etc.
  • a delivery order requesting quick delivery is obtained from the user. It may be, but is not limited thereto.
  • an embodiment in which an input for adding food to a shopping cart is obtained from a user is described for convenience of description, but descriptions related to "food" throughout the specification will be widely understood as descriptions of various items subject to delivery. can
  • the electronic device 110 obtains expected order information corresponding to one or more inputs for adding one or more shopping carts based on at least one of one or more pieces of information included in one or more inputs for adding one or more shopping carts.
  • the expected order information may be information including a result of predicting an actual order to occur in the future based on one or more inputs to add to the shopping cart.
  • the electronic device 110 determines one or more candidate delivery sources based on the obtained expected order information and one or more store information included in one or more shopping cart addition inputs.
  • One or more candidate delivery carriers may be determined based on a result of determining whether they can be allocated when an actual order occurs later.
  • the electronic device 110 provides prospective order information to one or more candidate delivery drivers.
  • the electronic device 110 may provide the delivery source device 130 with a page including a map displaying expected order information.
  • the user may correspond to a customer who orders delivery of food.
  • the user device 120 may be a concept encompassing devices operated and managed by one or more users.
  • the user device 120 may receive a user input from one or more users or the like or receive information from the electronic device 110 or the like and perform a corresponding operation.
  • the user device 120 may receive an input to add to the shopping cart from the user and transmit it to the electronic device 110 .
  • the user device 120 may acquire the order request and deliver a delivery order corresponding thereto to the electronic device 110 .
  • the user device 120 may receive an input from the user and transmit it to the electronic device 110 or provide information received from the electronic device 110 to the user.
  • the delivery person may include various entities that take over food from the seller and deliver the food from the seller to the user.
  • Delivery sources include various businesses that provide delivery services in a specific regional scope, and businesses may include companies and individuals.
  • the delivery source may include a delivery service provider regardless of region.
  • the delivery source may include various entities that provide delivery services within a range of specific delivery means, and the specific delivery means may include walking, two-wheeled vehicles, bicycles, and automobiles.
  • the specific delivery means may include various types of delivery means, such as drones and railroads.
  • the deliveryman device 130 may be a concept encompassing devices operated and managed by one or more deliverymen.
  • the delivery man device 130 may receive a user input from the delivery man or the like or receive information from the electronic device 110 or the like, and perform a corresponding operation.
  • the delivery man device 130 may receive expected order information from the electronic device 110 and provide a user interface including the received expected order information to the delivery man.
  • a seller is an entity that sells food and may correspond to an entity that operates a store or works in a store.
  • the store device 140 may be a concept encompassing devices operated and managed by one or more sellers.
  • the store device 140 may receive a user input from a seller or the like or receive information from the electronic device 110 or the like and perform a corresponding operation.
  • the store device 140 may receive expected order information from the electronic device 110 and provide a user interface for requesting item preparation to the seller in response thereto.
  • the store device 140 may receive an expected food cooking time from the seller and transmit it to the electronic device 110 .
  • the store device 140 of the embodiment may include a terminal used by a seller, and may be implemented in a form of installing an application on a smartphone or may be implemented in a form of installing an application on a POS machine.
  • the user device 120, the delivery person device 130, and the store device 140 include information received from the electronic device 110 or the like, or display a user interface generated based on the received information on a screen or the like. It can be converted into a form that can be output on a device and provided to users, delivery agents, sellers, etc. Alternatively, the user device 120, the delivery person device 130, and the store device 140 may provide the information received from the electronic device 110 or the like without conversion through an output device such as a screen.
  • the user device 120, the delivery person device 130, and the store device 140 may include a computer device, a mobile communication terminal, a server, and the like.
  • the user device 120 , the delivery person device 130 , and the store device 140 may include or be connected to input devices such as a touch pad, a mouse, and a keyboard for receiving user input.
  • the user device 120, the deliveryman device 130, and the store device 140 may include or be connected to output devices such as a screen, a speaker, or an interface device for providing information to the user.
  • the input device and the output device of the user device 120, the deliveryman device 130, or the store device 140 may be integrally configured or interrelated, and for example, the user device 120 or the deliveryman device 130 An interface for receiving user input may be displayed on .
  • Operations related to a series of information processing methods may be implemented by a single physical device or may be implemented by organically combining a plurality of physical devices.
  • some of the components included in the system 100 for processing delivery-related information may be implemented by one physical device, and the remaining components may be implemented by other physical devices.
  • one physical device may be implemented as part of the electronic device 110, and another physical device may be implemented as part of the user device 120 or other external devices.
  • each component included in the system 100 for processing delivery-related information is distributed and arranged in different physical devices, and the distributed components are organically combined to process delivery-related information. It may be implemented to perform the functions and operations of system 100.
  • the electronic device 110 of this specification includes at least one sub-device, and some operations described as being performed by the electronic device 110 are performed by a first sub-device, and some other operations are performed by a second sub-device. It may also be performed by the device.
  • FIG. 2 is an operation flowchart of a delivery order processing method of an electronic device in a system for processing delivery-related information according to an embodiment.
  • the electronic device 110 obtains one or more inputs for adding to a shopping cart from the user device 120 (201).
  • the item subject to the delivery order is food
  • the description related to “food” throughout the specification can be broadly understood as a description of various items subject to delivery.
  • Each of the one or more shopping cart add inputs includes store information and item information.
  • the electronic device 110 Based on at least one of the one or more pieces of information included in the one or more inputs to add to the shopping cart, the electronic device 110 obtains expected order information corresponding to the one or more inputs to add to the shopping cart (202). Specifically, the electronic device 110 obtains probability information including a result of calculating a probability value that will be converted into an actual order for at least some of one or more inputs to add to the shopping cart, and based on the probability information, the expected order information. can be obtained.
  • the electronic device 110 classifies at least some of the one or more shopping cart addition inputs into one or more groups based on the one or more store information included in the one or more shopping cart addition inputs, and converts the one or more groups into actual orders.
  • the probability of conversion can be calculated for each. For example, one or more groups are set for each specific regional range, and the electronic device 110 compares location information for each store included in one or more store information and corresponding regional ranges for each one or more groups. At least some of the add-to-cart inputs may be classified into one or more groups.
  • the electronic device 110 may classify one or more shopping cart addition inputs corresponding to one or more stores located within a certain geographical range into the same group based on the location information of stores corresponding to each shopping cart addition input. For example, further referring to FIG. 3 , 11 inputs for adding a shopping cart corresponding to the first store 301 and 3 inputs for adding a shopping cart corresponding to the second store 302 are classified into a first group 310, , Seven shopping cart addition inputs corresponding to the third store 303 and two shopping cart addition inputs corresponding to the fourth store 304 are classified into the second group 320, and corresponding to the fifth store 305 Four inputs for adding a shopping cart and four inputs for adding a shopping cart corresponding to the sixth store 306 may be classified as a third group 330 (300).
  • each add-to-cart input can be classified into one or more groups according to various methods.
  • the electronic device 110 may classify one or more inputs for adding to a shopping cart into one or more groups by further considering item information included in each input for adding to a shopping cart.
  • the first store 301 is a large store where a large number of orders are placed
  • an input for adding a shopping cart related to the first store 301 is a representative item sold in the first store 301 (eg, chicken rice bowl). etc.)
  • the electronic device 110 displays an input including a representative item among inputs related to the first store 301 to add to the shopping cart and the first store 301.
  • Inputs that do not include a representative item among inputs related to Add to Shopping Cart can be classified into different groups.
  • the electronic device 110 determines an order history for each store corresponding to the one or more store information based on one or more store information, and calculates a probability value for converting one or more shopping cart addition inputs into an actual order based on the order history for each store. Probability information including the calculated result may be obtained. For example, if there were 1500 addition inputs to the shopping cart corresponding to the first store 301 over the past month and 600 of them led to actual orders, one or more orders corresponding to the first store 301 were actually placed. The probability of conversion to a spell can be calculated as 0.4.
  • the demand for delivery work can be predicted in advance, thereby reducing the gap between the demand for delivery work and the supply of delivery services.
  • the electronic device 110 may determine one or more order histories for each user corresponding to one or more inputs for adding to a shopping cart, and obtain probability information based on the order histories. In this case, the electronic device 110 determines the probability considering the user's propensity (whether preference for a specific store and specific item is high, whether the rate of converting an input to a shopping cart into an actual order is relatively high or low compared to other customers, etc.) information can be obtained.
  • the above-described acquisition method of probability information is an example, and in addition to the above-described acquisition method, the electronic device 110 considers a specific ordered item or calculates the probability of conversion to an actual order for a plurality of chain stores having the same headquarters by integrating them. Alternatively, the probability of converting an input to a shopping cart into an actual order may be calculated based on various methods, such as separately calculating the probability of conversion into an actual order by time. For example, according to an embodiment, the electronic device 110 determines that, for at least some of one or more inputs for adding a shopping cart, an item corresponding to item information included in a specific shopping cart input corresponds to store information included in a specific shopping cart input. Probability information can be obtained by determining the order history in .
  • the electronic device 110 classifies and recognizes a history including a representative item and a history not including a representative item among shopping cart addition history or order history related to the first store 301, and each shopping cart based thereon.
  • a conversion probability to an actual order may be calculated by further considering whether the additional input includes an input to add to the shopping cart for the representative item.
  • the electronic device 110 may calculate a probability that an input to add to a shopping cart is converted into an actual order based on a calculation model based on a machine learning algorithm.
  • the calculation model may be in a pre-learned state.
  • the calculation model can be learned based on the past order history, and the learning parameters include the time when the past shopping cart addition input was input, the actual order input time, the store information and item information corresponding to the shopping cart addition input or order, and the store's
  • Various factors such as attributes and one or more order records for each user corresponding to one or more inputs to add to the shopping cart, may be considered.
  • the electronic device 110 determines one or more candidate delivery agents based on one or more store information included in the expected order information and one or more inputs for adding one or more shopping carts (203). Specifically, the electronic device 110 determines one or more location information corresponding to the expected order information based on one or more store information, and based on the one or more location information, the electronic device 110 determines information of one or more deliverymen located in a certain radius range based on the one or more location information. can be obtained In relation to this, one or more pieces of location information corresponding to the expected order information may include location information of a store. Alternatively, the one or more pieces of location information corresponding to the expected order information may include one or more address information of the user.
  • one or more location information corresponding to expected order information includes store location information
  • the electronic device 110 provides expected order information to the determined one or more candidate delivery agents (204).
  • the electronic device 110 may provide expected order information to one or more candidate delivery men by providing the expected order information to the delivery man device 130 .
  • the electronic device 110 according to an embodiment may provide the expected order information by providing the delivery source device 130 with a page including a map displaying the expected order information.
  • An example of a map displaying expected order information may be displayed based on coordinate information generated based on a result of determining the density of expected orders for each specific regional range.
  • An example of a map displayed based on coordinate information generated based on a result of determining the density of expected orders for each specific regional range may include, but is not limited to, a heat map.
  • the electronic device 110 divides the density of expected orders into four levels, and does not separately display a region corresponding to the lowest level of density, and the next three levels of density Coordinate information for displaying different shades in corresponding regions may be generated, and a map displayed based on the coordinate information may be provided to one or more candidate delivery agents (600).
  • the electronic device 110 may generate coordinate information for displaying different colors capable of distinguishing the density of expected orders instead of shading (in this case, , shades and different colors may be mixed).
  • the electronic device 110 divides the density step by step according to a certain condition and displays it in different colors, instead of displaying the density as the density changes. Coordinate information that continuously changes color may be generated, and in this case, there may be an advantage that a map displayed based on the coordinate information may more accurately reflect the expected order density.
  • the electronic device 110 providing the expected order information may suggest movement to one or more locations corresponding to the expected order information to one or more candidate delivery agents.
  • an interface suggesting movement to the delivery man may be displayed along with a map displaying expected order information.
  • the electronic device 110 determines the total number of expected delivery orders and how many people are in nearby locations of the stores at the time of the delivery order. It is possible to compare whether or not there will be a delivery man, calculate how many delivery people need to move to the nearby locations of the stores as a result of the comparison, and determine how many candidate delivery people to suggest moving to based on the calculated result. Furthermore, the electronic device 110 may specifically determine which of the one or more candidate delivery crews to propose the movement to based on the calculated result.
  • the electronic device 110 when movement to one or more locations corresponding to the expected order information is proposed, minimizes the total movement distance for the deliveryman who has been suggested to move to the store or moves to the vicinity of the store. In order to minimize the total travel time for the proposed delivery person to move to the store neighborhood, which delivery person should move to which location, and based on the calculated result, which of one or more candidate delivery people to propose the move to; and It is also possible to determine to which location to propose a movement to each delivery person who will propose a movement.
  • the electronic device 110 may request preparation of an item from one or more stores based on the expected order information.
  • the preparation of specific items requires more accurate prediction than the movement of the delivery man (when the delivery man moves to a nearby area, even if the predicted order does not occur, other orders related to other items or other stores) , whereas items such as food must be prepared in a specific time range for a specific item to be ordered by the user), the electronic device 110 has a smaller amount than the amount of food prepared based on the expected order information. of food can be requested to be prepared by the store.
  • the electronic device 110 displays 50 of the expected number of orders. You can ask the store to prepare only 4 A-items that are %. In this regard, the electronic device 110 may request the store to prepare an item by further considering a result of determining whether the corresponding item actually leads to an order for each item sold by the store.
  • the store is requested to prepare the item in this way, the time from when the user orders the item to the actual delivery of the item can be further reduced, which increases user satisfaction, and the store and the delivery person also prepare the item in advance or Delivery can start, so it can help increase work efficiency or reduce work intensity.
  • FIG. 4 is a diagram for illustratively explaining an operation of determining a candidate delivery person according to an embodiment.
  • the electronic device 110 determines one or more location information corresponding to expected order information based on one or more store information and is located within a certain radius range based on the one or more location information. It is possible to obtain information of one or more delivery people who do (400).
  • an example of one or more pieces of location information corresponding to the expected order information includes first location information including a first store 301 and a second store 302, a third store 303 and a fourth store ( 304) and third location information including the fifth store 305 and the sixth store 306.
  • a certain radius range based on the first location information is indicated by reference number 410
  • a certain radius range based on the second location information is indicated by reference number 420
  • a certain radius based on the third location information is indicated at reference numeral 430.
  • a certain radius range based on the first location information, a certain radius range based on the second location information, and a certain radius range based on the third location information all have the same radius range.
  • different radius ranges may be set according to various conditions such as order density, traffic congestion, and preference of a delivery person.
  • the radial range is longer than the first distance and shorter than the second distance (ie, in a donut-shaped range) because there is no need to provide expected order information to deliverymen located closer than a certain distance from the restaurant.
  • the radius range is not necessarily limited to this shape, and for example, the radius range may be set as a donut-shaped range including all ranges shorter than the third distance.
  • a delivery man located within the indicated radius range may be determined as a candidate delivery man.
  • the electronic device 110 predicts deliverymen corresponding to reference numbers 401, 402, 405, and 406 belonging to at least one radial range. You can provide ordering information.
  • the delivery man corresponding to reference number 403 and the delivery man corresponding to reference number 404 do not belong to any radial range, they may not be determined as candidate delivery men.
  • the electronic device 110 may provide predicted order information customized for each individual according to which radius range each candidate delivery person belongs to. For example, the electronic device 110 provides expected order information corresponding to the first location information and expected order information corresponding to the second location information to the delivery person corresponding to reference number 401 and the delivery person corresponding to reference number 402, , Expected order information corresponding to the first location information may be provided to a delivery man corresponding to reference number 405, and expected order information corresponding to the third location information may be provided to a delivery man corresponding to reference number 406.
  • the electronic device 110 determines whether or not one or more delivery agents can be assigned an actual order when an actual order corresponding to the expected order information occurs, and based on the determination result, one or more delivery sources.
  • One or more candidate delivery sources of the circle may be determined.
  • the electronic device 110 may determine whether a delivery man is in a delivery available state, and may prevent a delivery man not being in a delivery available state from being included in one or more candidate delivery crews.
  • whether or not the delivery is available may be determined in consideration of at least one of whether the deliveryman is in a state of attendance when hired by a service provider and whether the deliveryman expresses an intention to be assigned a delivery task when the deliveryman is a freelancer.
  • whether or not the deliverable state is determined in consideration of at least one of whether the delivery person is performing a delivery task and whether there is a task to be performed by the delivery person at the time when the shopping cart addition input is converted into an actual order.
  • the electronic device 110 determines whether a moving path from the location of one or more deliverymen to one or more location information satisfies a preset condition, and if the preset condition is satisfied, the corresponding deliveryman may not be included in one or more candidate delivery sources.
  • the preset condition may include a case in which there is an obstacle condition that makes movement difficult on a movement path, such as crossing a river or crossing a mountain.
  • the preset condition may include whether the time required for the deliveryman to move to one or more pieces of location information through the moving route exceeds the preset time.
  • the electronic device 110 may determine information on means of transportation used by one or more delivery crews and determine one or more candidate delivery crews based on the determination. For example, the electronic device 110 may determine a radius for allocating a delivery order for each means of transportation in consideration of the moving speed of a means of transportation used by one or more deliverymen, and assign the delivery order to deliverymen within the corresponding radius. can determine whether For example, the electronic device 110 determines whether a delivery order can be processed for a delivery man located within a radius of 1 km from one or more location information in relation to a delivery man who moves on foot, and a delivery man who moves by bicycle.
  • a delivery order can be processed for a delivery person located within a radius of 1.8 km from one or more location information, and in relation to a delivery person moving by car, a delivery person located within a radius of 4 km from one or more location information It is possible to determine whether a delivery order can be processed for
  • the electronic device 110 determines whether a delivery order can be processed for a delivery man within a fixed radius, but sets the probability of being selected as a candidate delivery man lower for a delivery man using a slower moving means, and the like. There may be various embodiments for determining one or more candidate deliverymen based on the means of transportation used by the deliveryman.
  • the electronic device 110 may determine whether or not a delivery time at which a candidate delivery man actually delivers is included in a preset time interval, and based on the determination, one or more candidate delivery men may be determined.
  • the preset time interval may include, for example, a rush hour interval such as a commute interval in which traffic is concentrated.
  • FIG. 5 is a case in which an actual order corresponding to expected order information is generated by one or more delivery agents of the electronic device 110 in relation to the first store 301 and the second store 302 in the embodiment shown in FIG. 4 .
  • An example of a result of determining whether or not an actual order can be allocated and determining one or more candidate delivery carriers from among one or more delivery carriers based on the result of the determination is shown (500). Specifically, referring to FIG.
  • the deliveryman corresponding to the drawing number 405 is performing delivery work and is not in a delivery available state, and the deliveryman corresponding to the drawing number 406 Since it is expected that it will be difficult to arrive at the first location information at the time when a bar order, which is a delivery man who moves on foot, is expected to occur, the delivery man corresponding to drawing number 405 and the delivery man corresponding to drawing number 406 are candidate delivery men. may not be determined.
  • FIG 7 is an operation flowchart of an information processing method of an electronic device according to an embodiment.
  • the electronic device 110 obtains one or more shopping cart addition inputs from one or more users (710).
  • Each of the one or more shopping cart add inputs includes store information and item information.
  • One or more shopping cart addition inputs may be obtained through the user device 120 .
  • the electronic device 110 Based on at least one of the one or more pieces of information included in the one or more inputs to add to the shopping cart, the electronic device 110 obtains expected order information corresponding to the one or more inputs to add to the shopping cart (720).
  • the electronic device 110 may obtain probability information including a result of calculating a probability value of converting into an actual order for at least some of one or more inputs to add to a shopping cart, and obtain expected order information based on the obtained probability information. there is.
  • the electronic device 110 determines one or more candidate delivery agents based on the expected order information and one or more store information included in one or more shopping cart addition inputs (730).
  • the electronic device 110 determines one or more location information corresponding to the expected order information based on one or more store information, and obtains information of one or more delivery agents located in a predetermined radius based on the one or more location information, thereby obtaining one or more information.
  • the above candidate delivery sources can be determined.
  • the electronic device 110 provides expected order information to the determined one or more candidate delivery carriers (740).
  • the electronic device 110 may provide a page including a map displaying expected order information to one or more candidate delivery men.
  • FIG. 8 is an exemplary diagram of a configuration of an electronic device that processes delivery-related information according to an embodiment.
  • the electronic device 110 includes a transceiver 810, a processor 820, and a memory 830.
  • the electronic device 110 may be connected to the user device 120, the delivery person device 130, and other external devices through the transceiver 810 and exchange data.
  • the processor 820 may include at least one device described above with reference to FIGS. 1 to 7 or may perform at least one method described above with reference to FIGS. 1 to 7 .
  • the memory 830 may store information for performing at least one method described above through FIGS. 1 to 7 .
  • Memory 830 may be volatile memory or non-volatile memory.
  • the processor 820 may execute a program and control the electronic device 110 to provide information.
  • Program codes executed by the processor 820 may be stored in the memory 830 .
  • the electronic device 110 may further include an interface capable of providing information to a user.
  • An electronic device or terminal includes a processor, a memory for storing and executing program data, a permanent storage unit such as a disk drive, a communication port for communicating with an external device, a touch panel, and a key ), user interface devices such as buttons, and the like.
  • Methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on the processor.
  • the computer-readable recording medium includes magnetic storage media (e.g., read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and optical reading media (e.g., CD-ROM) ), and DVD (Digital Versatile Disc).
  • a computer-readable recording medium may be distributed among computer systems connected through a network, and computer-readable codes may be stored and executed in a distributed manner.
  • the medium may be readable by a computer, stored in a memory, and executed by a processor.
  • an embodiment is an integrated circuit configuration such as memory, processing, logic, look-up table, etc., which can execute various functions by control of one or more microprocessors or other control devices. can employ them.
  • the present embodiments include data structures, processes, routines, or various algorithms implemented as combinations of other programming constructs, such as C, C++, Java ( It can be implemented in a programming or scripting language such as Java), assembler, Python, or the like. Functional aspects may be implemented in an algorithm running on one or more processors.
  • this embodiment may employ conventional techniques for electronic environment setting, signal processing, and/or data processing.
  • Terms such as “mechanism”, “element”, “means” and “composition” may be used broadly and are not limited to mechanical and physical components. The term may include a meaning of a series of software routines in association with a processor or the like.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Marketing (AREA)
  • Tourism & Hospitality (AREA)
  • Finance (AREA)
  • Accounting & Taxation (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Quality & Reliability (AREA)
  • Educational Administration (AREA)
  • Data Mining & Analysis (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • General Factory Administration (AREA)
PCT/KR2021/015545 2021-10-26 2021-11-01 배송 관련 정보를 처리하는 전자 장치 및 그 방법 WO2023074974A1 (ko)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR1020210143637A KR102448463B1 (ko) 2021-10-26 2021-10-26 배송 관련 정보를 처리하는 전자 장치 및 그 방법
KR10-2021-0143637 2021-10-26

Publications (1)

Publication Number Publication Date
WO2023074974A1 true WO2023074974A1 (ko) 2023-05-04

Family

ID=83451475

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2021/015545 WO2023074974A1 (ko) 2021-10-26 2021-11-01 배송 관련 정보를 처리하는 전자 장치 및 그 방법

Country Status (3)

Country Link
KR (2) KR102448463B1 (zh)
TW (1) TW202318317A (zh)
WO (1) WO2023074974A1 (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102653033B1 (ko) * 2023-04-27 2024-04-01 쿠팡 주식회사 전자 장치 및 그의 정보 제공 방법

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20070058859A (ko) * 2005-12-05 2007-06-11 엔에이치엔(주) 상품 광고에 대한 리포트 관리 방법 및 상품 광고 리포트관리 시스템
KR20180042598A (ko) * 2016-10-18 2018-04-26 주식회사 우아한형제들 배달주문 분배시스템 및 방법
KR20190007875A (ko) * 2017-07-14 2019-01-23 십일번가 주식회사 유통과 물류의 최적화를 위한 마케팅 관리 데이터 제공 방법 및 이를 위한 장치
KR20210075814A (ko) * 2019-12-13 2021-06-23 쿠팡 주식회사 자동화된 배달원 스케줄링을 위한 시스템 및 방법

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20070058859A (ko) * 2005-12-05 2007-06-11 엔에이치엔(주) 상품 광고에 대한 리포트 관리 방법 및 상품 광고 리포트관리 시스템
KR20180042598A (ko) * 2016-10-18 2018-04-26 주식회사 우아한형제들 배달주문 분배시스템 및 방법
KR20190007875A (ko) * 2017-07-14 2019-01-23 십일번가 주식회사 유통과 물류의 최적화를 위한 마케팅 관리 데이터 제공 방법 및 이를 위한 장치
KR20210075814A (ko) * 2019-12-13 2021-06-23 쿠팡 주식회사 자동화된 배달원 스케줄링을 위한 시스템 및 방법

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ANONYMOUS: "Boost sales by paying for abandoned carts", APPIER., 24 December 2018 (2018-12-24), XP093061189, Retrieved from the Internet <URL:https://www.appier.com/ko-kr/blog/ebb0a9ecb998eb909c-ec9ea5ebb094eab5aceb8b88-eab2b0eca09ceba19c-eba7a4ecb69c-ec8381ec8ab9-ec9ca0eb8f84ed9598eab8b0> [retrieved on 20230705] *

Also Published As

Publication number Publication date
TW202318317A (zh) 2023-05-01
KR20230059722A (ko) 2023-05-03
KR102448463B1 (ko) 2022-09-30

Similar Documents

Publication Publication Date Title
Fayyaz S et al. An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis
EP3622459A1 (en) Method and apparatus for generating workflow
WO2023074974A1 (ko) 배송 관련 정보를 처리하는 전자 장치 및 그 방법
WO2023008636A1 (ko) 정보 제공 방법 및 이를 이용한 전자 장치
WO2021192470A1 (ja) 情報処理装置及び情報処理システム
WO2023106500A1 (ko) 배송 업무를 위한 정보를 제공하는 전자 장치 및 그 방법
WO2022004935A1 (ko) 전자 장치 및 그의 동작 방법
WO2023008625A1 (ko) 배송 정보를 제공하는 전자 장치 및 그 방법
WO2023033216A1 (ko) 상품 판매 서비스에서 카트 페이지를 제공하는 방법 및 이를 위한 전자 장치
WO2023042949A1 (ko) 아이템의 정보를 제공하는 전자 장치 및 그 방법
WO2023167355A1 (ko) 업무 정보를 제공하는 방법 및 장치
WO2017090607A1 (ja) 予約処理装置、予約処理方法および予約処理プログラム
WO2017119210A1 (ja) 予約処理装置、ユーザ端末および予約処理方法
WO2022255556A1 (ko) 음식 배달을 위한 정보를 처리하는 전자 장치 및 그 방법
WO2018021790A1 (ko) 인스턴트 메신저를 활용한 전자상거래 서비스 제공 방법 및 이를 위한 장치
WO2023085486A1 (ko) 배송 업무를 할당하는 전자 장치 및 그 방법
WO2015099231A1 (ko) 맞춤형 샘플 제공 시스템, 장치 및 방법
WO2011014028A2 (ko) 상품 거래 중개 시스템 및 이를 이용한 상품 거래 중개 방법
WO2023048496A1 (ko) 광고 캠페인에 관한 정보를 제공하기 위한 방법, 시스템 및 비일시성의 컴퓨터 판독 가능한 기록 매체
WO2023074973A1 (ko) 배송 주문을 처리하는 전자 장치 및 그 방법
WO2017090610A1 (ja) 予約処理装置、予約処理方法および予約処理プログラム
WO2020230736A1 (ja) 需要分散装置
WO2023033220A1 (ko) 아이템 그룹의 정보를 제공하는 방법 및 이를 위한 장치
WO2023085487A1 (ko) 배송 업무를 위한 정보를 처리하는 전자 장치 및 그 방법
JP6321756B2 (ja) 予約管理装置、予約管理方法及び予約管理プログラム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21962598

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE