WO2023234450A1 - 쿠폰 관련 정보 관리 방법 및 이를 위한 전자 장치 - Google Patents

쿠폰 관련 정보 관리 방법 및 이를 위한 전자 장치 Download PDF

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WO2023234450A1
WO2023234450A1 PCT/KR2022/007984 KR2022007984W WO2023234450A1 WO 2023234450 A1 WO2023234450 A1 WO 2023234450A1 KR 2022007984 W KR2022007984 W KR 2022007984W WO 2023234450 A1 WO2023234450 A1 WO 2023234450A1
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coupon
information
customer
price
related information
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PCT/KR2022/007984
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English (en)
French (fr)
Korean (ko)
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푸주유
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쿠팡 주식회사
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0211—Determining the effectiveness of discounts or incentives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • 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
    • 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
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0224—Discounts or incentives, e.g. coupons or rebates based on user history

Definitions

  • This disclosure relates to a coupon-related information management method for efficiently distributing coupons based on customer data and an electronic device for the same.
  • coupon marketing is very simple, but it is widely used as a marketing technique that can effectively lead to various results, such as strengthening customer loyalty, creating new customers, increasing awareness, and helping to gain an advantage over competitors. .
  • coupons are distributed indiscriminately to customers, sales may increase but net profit may decrease, so it is necessary to carefully decide on the distribution method.
  • the present disclosure is proposed to solve the above-described problems, and its purpose is to provide a method of managing coupon-related information that efficiently distributes coupons based on customer data and an electronic device for the same.
  • a coupon-related information management method includes distributing a test coupon to a group including at least one customer, first information about the customer's characteristics, and first information about the customer's use of the test coupon. 2. Obtaining information, based on the first information, setting a plurality of subgroups within the group, based on the first information and the second information, for at least some of the subgroups Obtaining third information about the purchase conversion probability according to the price of the test coupon, based on the third information, confirming fourth information about the coupon to be distributed and the characteristics of the target customer of the coupon, and It may include distributing the coupon to the target customer based on the fourth information.
  • the first information may include at least one of the following: elapsed time from the most recent order, order frequency, total purchase amount, order amount per time, and number of previous coupon uses.
  • Setting the subgroups within the group includes dividing at least one piece of information among the first information into two or more sections based on at least one numerical value, and corresponding the customer of the group to each of the sections. It may include the step of asking.
  • the at least one numerical value may be determined so that the intervals between the sections are constant.
  • the at least one numerical value may be determined so that the number of customers corresponding to each of the sections is constant.
  • the step of confirming the fourth information includes entering conditions regarding at least one of an available coupon budget, a sales target amount, and an ROI target value, and within the conditions, a correspondence between the characteristics of the target customer and the price of the coupon. It may include determining at least one of a relationship, a price of the coupon, a type of product to which the coupon applies, and an expiration date of the coupon.
  • the step of obtaining the third information includes obtaining the coupon sensitivity of each of the subgroups, and the step of obtaining the coupon sensitivity includes the step of obtaining the coupon sensitivity for the price of the test coupon using a linear regression analysis method. It includes expressing the purchase conversion probability as a linear function, and calculating a slope of the linear function, and the correspondence relationship may be determined such that the coupon sensitivity and the price of the coupon are proportional.
  • the correspondence relationship may be determined so that the total price of the coupon is minimized while satisfying the conditions regarding the sales target amount.
  • the correspondence relationship may be determined to maximize sales while satisfying the conditions regarding the coupon budget.
  • the correspondence relationship may be determined to maximize the number of orders while satisfying the conditions regarding the coupon budget.
  • the correspondence relationship may be determined such that the ROI value (i.e., total sales amount/price of the coupon) is maximized while satisfying at least one of the conditions regarding the sales target amount and the condition regarding the coupon budget.
  • the ROI value i.e., total sales amount/price of the coupon
  • the correspondence relationship may be determined so that the total price of the coupon is minimum or the sales amount is maximum while satisfying the conditions regarding the ROI target value.
  • test coupons at different prices may be randomly distributed to the customers in the group.
  • An electronic device for a coupon-related information management method includes a memory storing at least one command, and based on the at least one command, distributing a test coupon to a group including at least one customer; , Obtaining first information about the customer's characteristics and second information about the customer's use of the test coupon, setting a plurality of subgroups within the group based on the first information, and using the first information And based on the second information, obtain third information about the purchase conversion probability according to the price of the test coupon for at least some of the subgroups, and obtain a coupon to be distributed based on the third information and the coupon to be distributed. It may include a processor that verifies fourth information about the characteristics of the target customer and distributes the coupon to the target customer based on the fourth information.
  • coupons can be efficiently distributed based on customer data, and profits can be maximized while satisfying conditions related to budget and goals by optimizing the coupon distribution method.
  • FIG. 1 is a schematic block diagram showing internal components of an electronic device according to embodiments of the present disclosure.
  • FIGS. 2 and 3 are flowcharts for explaining a method of managing coupon-related information according to embodiments of the present disclosure.
  • 4 to 6 are graphs or tables for explaining the steps of setting a plurality of subgroups within a group according to an embodiment of the present disclosure.
  • Figure 7 is a graph showing the purchase conversion probability according to the price of a test coupon obtained for one of the subgroups according to an embodiment of the present disclosure.
  • FIG. 8 is an example diagram illustrating the step of setting a plurality of subgroups within a group according to an embodiment of the present disclosure.
  • the “terminal” mentioned below may be implemented as a computer or portable terminal that can connect to a server or other terminal 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 guarantees portability and mobility.
  • all types of communication-based terminals such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), and LTE (Long Term Evolution), smartphones, tablet PCs, etc. It may include a handheld-based wireless communication device.
  • each block of the processing flow diagrams and combinations of the flow diagram diagrams can be performed by computer program instructions.
  • These computer program instructions can be mounted on a processor of a general-purpose computer, special-purpose computer, or other programmable data processing equipment, so that the instructions performed through the processor of the computer or other programmable data processing equipment are described in the flowchart block(s). It creates the means to perform functions.
  • These computer program instructions may also be stored in computer-usable or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement a function in a particular manner, so that the computer-usable or computer-readable memory It is also possible to produce manufactured items containing instruction means to perform the functions described in the flowchart block(s).
  • Computer program instructions can also be mounted 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 generate a process that is executed by the computer and then processed by the computer or other programmable data processing equipment. Instructions for performing processing equipment may also provide steps for executing the functions described in the flowchart block(s).
  • each block may represent a module, segment, or portion of code containing one or more executable instructions for executing specified logical function(s).
  • each block may represent a module, segment, or portion of code containing one or more executable instructions for executing specified logical function(s).
  • FIG. 1 is a schematic block diagram showing internal components of an electronic device according to embodiments of the present disclosure.
  • the electronic device 100 may include a processor 110, a transceiver 120, and a memory 130.
  • the electronic device 100 may be a server that operates an Internet-based service for e-commerce.
  • the electronic device 100 can exchange data with a user terminal and other external devices through the transceiver 120.
  • the electronic device 100 may be connected to a user terminal and other external devices through a network.
  • the network may be, for example, a Local Area Network (LAN), a Wide Area Network (WAN), a Value Added Network (VAN), a mobile radio communication network, a satellite communication network, or these.
  • LAN Local Area Network
  • WAN Wide Area Network
  • VAN Value Added Network
  • a network is a comprehensive data communication network that allows constituents to communicate smoothly with each other, and can use wired Internet, wireless Internet, or mobile wireless communication networks.
  • Wireless communication networks include, for example, wireless LAN (Wi-Fi), Bluetooth, Bluetooth low energy, ZigBee, WFD (Wi-Fi Direct), UWB (ultra wideband), and infrared communication (IrDA, infrared data). Association), NFC (Near Field Communication), etc.
  • the processor 110 may perform at least one method described with reference to FIGS. 2 to 7 based on instructions stored in the memory 130.
  • the memory 130 may store at least one instruction for performing at least one method described with reference to FIGS. 2 to 7 .
  • Memory 130 may be volatile memory or non-volatile memory.
  • the processor 110 can control the electronic device 100 to execute programs and provide information.
  • the code of the program executed by the processor 110 may be stored in the memory 130.
  • the electronic device 100 may further include an interface that provides information to the user.
  • the processor 110 in the electronic device 100 can distribute coupons to customers, obtain information, set subgroups, and check information according to instructions stored in the memory 130. Customers can use coupons using the user terminal. Information obtained in the process of managing coupon-related information according to the present disclosure may be stored in the memory 130 through the transceiver 120.
  • FIG. 3 illustrates the step of confirming information about the coupon to be distributed and the characteristics of the target customer of the coupon among the coupon-related information management methods according to embodiments of the present disclosure.
  • a test coupon may be distributed to a group including at least one customer.
  • the group may be a large enough set randomly selected from among a plurality of customers using an Internet-based service for electronic commerce.
  • Test coupons can have various prices.
  • the price of the test coupon may be selected from the first price to the nth price (n is a natural number of 2 or more).
  • n is a natural number of 2 or more.
  • the first price may be '0 dollars (won)'.
  • Test coupons may not be distributed to some customers.
  • Test coupons can be randomly distributed to customers. For example, the number of customer groups that received test coupons at different prices may be different.
  • step S220 first information about the customer's characteristics and second information about the customer's use of the test coupon may be obtained.
  • First information about the customer's characteristics may include information known through order history.
  • the first information may include at least one of the following: elapsed time from the most recent order, order frequency, total purchase amount, order amount per time, and number of previous coupon uses.
  • the first information about the customer's characteristics may further include information unrelated to order history, such as age, gender, and address.
  • the second information may include information about customers who used the test coupon.
  • Customers who used the test coupon may be part of the group of customers who received the test coupon. More specifically, the second information may include a correspondence between the characteristics of the customer who used the test coupon and the price of the test coupon.
  • Step S230 a plurality of subgroups may be set within the group based on the first information.
  • Step S230 may include dividing at least one piece of first information into two or more sections based on at least one numerical value, and matching customers of the group to each section.
  • the first information subject to section division may be numerical data. If the first information subject to section division is categorical data (e.g., gender, address, etc.), step S230 is a step of converting at least one piece of first information into numeric data. More may be included. The step of converting information into numerical data can use data processing methods such as dummy variableization or category embedding.
  • At least one value that serves as a standard for dividing sections may be determined so that the intervals between sections are constant. According to another embodiment, at least one value that serves as a standard for dividing sections may be determined so that the number of customers corresponding to each section is constant. Step S230 will be described in detail with reference to FIGS. 4 to 6.
  • third information about the purchase conversion probability according to the price of the test coupon may be obtained for at least some of the subgroups based on the first information and the second information. More specifically, the third information may include a graph where the horizontal axis is the price of the test coupon and the vertical axis is the purchase conversion probability. Customers who used test coupons can be displayed as dots on the graph.
  • the purchase conversion probability refers to the ratio of the number of people who completed conversion (for example, purchasing a product) to the number of people who accessed the Internet-based service for e-commerce through a predetermined path. ; CVR) can be estimated. For example, the purchase conversion rate itself can be used as the purchase conversion probability.
  • Step S240 may include obtaining coupon sensitivity for each subgroup.
  • the step of obtaining coupon sensitivity may include expressing the purchase conversion probability for the price of the test coupon as a linear function using a linear regression analysis method, and calculating the slope of the linear function. there is.
  • the purchase conversion probability for the price of the test coupon can be expressed as a linear function using the linear least square method.
  • the slope of the linear function means the degree to which the probability of purchase conversion increases as the price of the test coupon increases in each subgroup of customers who used the test coupon, and this is defined as coupon sensitivity.
  • step S250 fourth information about the coupon to be re-distributed and the characteristics of the target customer of the coupon can be confirmed based on the third information.
  • step S250 is a step of entering conditions regarding at least one of an available coupon budget, a sales target amount, and an ROI target value (S310), and within the conditions, a correspondence between the characteristics of the target customer and the price of the coupon. It may include a step (S310) of determining at least one of the relationship, the price of the coupon, the type of product to which the coupon is applied, and the expiration date of the coupon.
  • the correspondence between the characteristics of the target customer and the price of the coupon may be determined such that the coupon sensitivity obtained in step S240 is proportional to the price of the coupon.
  • the target customer may correspond to one of the subgroups set in step S230 depending on its characteristics.
  • the coupon sensitivity of the target customer may be estimated to be equal to the coupon sensitivity obtained in step S240 for the corresponding subgroup.
  • the correspondence relationship between the characteristics of the target customer and the price of the coupon may be determined so that the total price (i.e., cost) of the coupon is minimized while satisfying the condition regarding the sales target amount. More specifically, the correspondence between the characteristics of the target customer and the price of the coupon can be determined by the solution ( ⁇ x ij ⁇ ) of the first resource allocation problem expressed as [Equation 1] below.
  • the subgroups set in step S230 include different first to mth subgroups (m is a natural number of 2 or more), and the prices of the distributed coupons are different from the first to nth prices (n is 2). It is assumed that it is selected from among natural numbers (or more).
  • i is a natural number between 1 and m
  • j is a natural number between 1 and n
  • N i is the number of customers belonging to the ith subgroup
  • C j is the jth price
  • p ij is the ith subgroup.
  • T is the sales target.
  • p ij may mean the difference between the purchase conversion probability when a coupon at the jth price is provided to the ith subgroup and the purchase conversion probability when the coupon at the jth price is not provided to the ith subgroup.
  • p ij may be calculated using the linear function obtained in step S240.
  • the coupon sensitivity obtained in step S240 can be used to solve the first resource allocation problem expressed by [Equation 1].
  • the correspondence relationship can be determined so that the sales amount or number of orders is maximized while satisfying the conditions regarding the coupon budget. More specifically, the correspondence between the characteristics of the target customer and the price of the coupon can be determined by the solution ( ⁇ x ij ⁇ ) of the second resource allocation problem expressed as [Equation 2] below.
  • V i ' is the weight for the ith subgroup
  • C is the available coupon budget. Descriptions of symbols that overlap with [Equation 1] above are omitted.
  • p ij may be calculated using the linear function obtained in step S240.
  • the coupon sensitivity obtained in step S240 can be used to solve the second resource allocation problem expressed by [Equation 2].
  • the weight (V i ') for the ith subgroup is the average purchase amount of the ith subgroup, the correspondence between the characteristics of the target customer and the price of the coupon is established so that sales are maximized while satisfying the conditions regarding the coupon budget. can be decided.
  • the weight (V i ') for the ith subgroup is 1, the correspondence between the characteristics of the target customer and the price of the coupon can be determined so that the number of orders is maximized while satisfying the conditions regarding the coupon budget.
  • the correspondence relationship between the characteristics of the target customer and the price of the coupon is determined by satisfying at least one of the conditions regarding the sales target and the coupon budget while satisfying the return over investment (ROI) value (i.e., sales/ cost) may be determined to be maximized.
  • ROI return over investment
  • the correspondence between the characteristics of the target customer and the price of the coupon may be determined to minimize cost or maximize sales (or number of orders) while satisfying conditions regarding the ROI value.
  • the condition regarding the ROI value can be expressed as [Equation 3] below.
  • R is the ROI target value. Descriptions of symbols that overlap with [Equation 1] above are omitted.
  • coupon may be distributed to target customers based on the fourth information. Coupons may be distributed according to the correspondence between the characteristics of the target customer determined in step S250 and the price of the coupon.
  • the coupon-related information management method may further include the step of modifying the fourth information based on information about products sold in real time.
  • the step of modifying the fourth information may be interposed between steps S250 and S260, and thus coupons can be distributed more efficiently.
  • the coupon-related information management method includes obtaining fifth information about the target customer's use of the coupon after step S260, and updating third information based on the fifth information. Additional steps may be included. Afterwards, steps S250 and S260 may proceed again, and thus coupons may be distributed more efficiently.
  • FIGS. 4 and 5 are graphs for explaining the steps of setting a plurality of subgroups within a group according to an embodiment of the present disclosure.
  • Each of FIGS. 4 and 5 is shown as a graph with continuous values, but this is only an example for convenience of explanation, and each of FIGS. 4 and 5 may be a graph with discrete values.
  • one piece of first information about customer characteristics may be, for example, order frequency (i.e., frequency).
  • order frequency i.e., frequency
  • one piece of first information may be divided into first to fifth sections 410, 420, 430, 440, and 450 based on numerical values.
  • the numerical values may be determined so that the intervals between the first to fifth sections 410, 420, 430, 440, and 450 are constant.
  • the first section 410 may be a section in which the order frequency is 0 or more times a month and less than 3 times a month
  • the second section 420 may be a section in which the order frequency is 3 or more times a month but less than 6 times a month
  • the third section 430 may be a section in which the order frequency is 6 or more times per month and less than 9 times per month
  • the fourth section 440 may be a section in which the order frequency is 9 or more times per month but less than 12 times per month
  • the fifth section ( 450) may be a section where the order frequency is 12 or more times per month but less than 15 times per month.
  • Customers may correspond to each of the first to fifth sections 410, 420, 430, 440, and 450 according to order frequency.
  • one piece of first information about the customer's characteristics may be, for example, the elapsed time from the most recent order (i.e., recency).
  • one piece of first information may be divided into first to fifth sections 510, 520, 530, 540, and 550 based on numerical values.
  • the numerical values may be determined so that the number of customers corresponding to each of the first to fifth sections 510, 520, 530, 540, and 550 is constant.
  • the first section 510 may be a section in which the elapsed time from the most recent order is 0 to 5 days
  • the second section 520 may be a section in which the elapsed time from the most recent order is 5 to 15 days.
  • the third section 530 may be a section in which the elapsed time from the most recent order is more than 15 days and less than 30 days
  • the fourth section 540 may be a section in which the elapsed time from the most recent order is more than 30 days.
  • the section may be less than 50 days
  • the fifth section 550 may be a section in which the elapsed time from the most recent order is more than 50 days and less than 75 days.
  • the number of customers corresponding to each of the first to fifth sections 510, 520, 530, 540, and 550 may be the same.
  • FIG. 6 is a table illustrating steps for setting a plurality of subgroups within a group according to an embodiment of the present disclosure.
  • first information about the customer's characteristics may include, for example, order frequency and time since the most recent order.
  • the order frequency among the first information may be divided into, for example, a 1-1 section 611, a 1-2 section 612, and a 1-3 section 613 based on numerical values.
  • the 1-1 section 611 may be a section (Low Frequency) in which the order frequency is 0 or more times a month and less than 5 times a month
  • the 1-2 section 612 may be a section (Low Frequency) in which the order frequency is 5 or more times a month. It may be a section (Mid Frequency) with an order frequency of less than 10 times (Mid Frequency)
  • the first to third section 613 may be a section (High Frequency) with an order frequency of 10 times or more per month.
  • the elapsed time from the most recent order among the first information may be divided into, for example, a 2-1 section 621, a 2-2 section 622, and a 2-3 section 623 based on the numerical values.
  • the 2-1 section 621 may be a section where the elapsed time from the most recent order is 30 days or more (Least Recent)
  • the 2-2 section 622 may be a section where the elapsed time from the most recent order is 30 days or more. It may be a section of 10 to 30 days (Moderate Recent)
  • the second to third section 623 may be a section of less than 10 days from the most recent order (Most Recent).
  • the sections may be determined to have constant intervals, or the number of customers corresponding to each section may be determined to be constant.
  • nine subgroups can be set based on first information about the customer's characteristics, such as order frequency and elapsed time from the most recent order. Thereafter, third information about the purchase conversion probability according to the price of the test coupon may be obtained for at least some of the nine subgroups.
  • Figure 7 is a graph showing the purchase conversion probability according to the price of a test coupon obtained for one of the subgroups according to an embodiment of the present disclosure.
  • the prices of test coupons distributed to customers are, for example, $0 (first price), $5 (second price), $10 (third price), and $15 (fourth price). ), $20 (fifth price), and $25 (sixth price).
  • $0 first price
  • $5 second price
  • $10 third price
  • $15 fourth price
  • $25 sixth price
  • Customers belonging to one subgroup may be displayed as dots as shown in FIG. 7 according to the price of the test coupon received and the purchase conversion probability.
  • the tendency of these points can be expressed as a linear function, for example, through a linear regression analysis method.
  • the first function 701 is a linear function representing the purchase conversion probability for the price of the test coupon of the subgroup corresponding to the 1-2 section 612 and the 2-2 section 622. It is a function.
  • the slope of the first function 701 means the coupon sensitivity of the corresponding subgroup.
  • FIG. 8 is an example diagram illustrating the step of setting a plurality of subgroups within a group according to an embodiment of the present disclosure.
  • first information about the customer's characteristics may include, for example, order frequency, elapsed time from the most recent order, and total purchase amount.
  • Order frequency, elapsed time since most recent order, and total purchase amount can each be divided into three intervals.
  • the sections may be determined to have constant intervals, and the number of customers corresponding to each section may be determined to be constant.
  • 27 subgroups can be established based on first information about the customer's characteristics, such as order frequency, elapsed time from the most recent order, and total purchase amount. Thereafter, third information about the purchase conversion probability according to the price of the test coupon may be obtained for at least some of the 27 subgroups.
  • the first information about the customer's characteristics may include two or more pieces of information different from that described with reference to FIG. 8, and each of these pieces of information may be divided into two or more sections. The number of subgroups may vary accordingly.
  • the electronic device or terminal includes a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a touch panel, and a key. , and may include user interface devices such as buttons.
  • 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.
  • computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disk, hard disk, etc.) and optical read media (e.g., CD-ROM). ), DVD (Digital Versatile Disc), etc.
  • the computer-readable recording medium is distributed among computer systems connected to a network, so that computer-readable code can be stored and executed in a distributed manner.
  • the media may be readable by a computer, stored in memory, and executed by a processor.
  • This embodiment can be represented by functional block configurations and various processing steps. These functional blocks may be implemented in various numbers of hardware or/and software configurations that execute specific functions. For example, embodiments include integrated circuit configurations such as memory, processing, logic, look-up tables, etc. that can execute various functions under the control of one or more microprocessors or other control devices. can be hired. Similar to how the components can be implemented as software programming or software elements, the present embodiments include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, such as C, C++, Java ( It can be implemented in a programming or scripting language such as Java, assembler, Python, etc. Functional aspects may be implemented as algorithms running on one or more processors.
  • this embodiment may employ conventional technologies for electronic environment settings, signal processing, and/or data processing.
  • Terms such as “mechanism,” “element,” “means,” and “composition” can be used broadly and are not limited to mechanical and physical components. The term may include the meaning of a series of software routines in connection with a processor, etc.

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PCT/KR2022/007984 2022-05-31 2022-06-07 쿠폰 관련 정보 관리 방법 및 이를 위한 전자 장치 WO2023234450A1 (ko)

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Publication number Priority date Publication date Assignee Title
KR20140109574A (ko) * 2013-03-05 2014-09-16 (주) 씨엠에스시스템 샘플 상품 배포 시스템
KR20170021171A (ko) * 2015-08-17 2017-02-27 주식회사 케이티 마케팅 서비스 제공 방법 및 장치
JP2017204117A (ja) * 2016-05-11 2017-11-16 大日本印刷株式会社 クーポン配信装置及びクーポン配信プログラム
US20180012246A1 (en) * 2016-07-08 2018-01-11 Ali Kamarei Method of Selectively Displaying Electronic Coupons In Real Time Depending On Market Conditions
JP2021515337A (ja) * 2018-04-20 2021-06-17 ベイジン ディディ インフィニティ テクノロジー アンド ディベロップメント カンパニー リミティッド クーポン発行のためのシステム及び方法

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20140109574A (ko) * 2013-03-05 2014-09-16 (주) 씨엠에스시스템 샘플 상품 배포 시스템
KR20170021171A (ko) * 2015-08-17 2017-02-27 주식회사 케이티 마케팅 서비스 제공 방법 및 장치
JP2017204117A (ja) * 2016-05-11 2017-11-16 大日本印刷株式会社 クーポン配信装置及びクーポン配信プログラム
US20180012246A1 (en) * 2016-07-08 2018-01-11 Ali Kamarei Method of Selectively Displaying Electronic Coupons In Real Time Depending On Market Conditions
JP2021515337A (ja) * 2018-04-20 2021-06-17 ベイジン ディディ インフィニティ テクノロジー アンド ディベロップメント カンパニー リミティッド クーポン発行のためのシステム及び方法

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