Method and device for providing product information, and recording medium

Abstract

A method by which an electronic device provides product information, according to one embodiment of the present disclosure, may comprise the steps of: determining, on the basis of a purchase history of a user, a repurchase candidate product set related to the user; identifying a user purchase pattern related to a plurality of products included in the repurchase candidate product set; determining the rankings of the plurality of products on the basis of the user purchase pattern; determining, on the basis of the rankings of the plurality of products, one or more products to be recommended to the user from among the plurality of products in the order of highest ranking; and providing information about the one or more products to the user.

Description

Method, device and recording medium for providing product information

[0001] The present disclosure relates to a technology for providing product information. More specifically, it relates to a technology for preferentially recommending products with a high likelihood of repurchase among products considered for repurchase.

[0002] With advancements in communications technology and societal changes, e-commerce services are providing a wide range of products and services to a large number of users through online platforms. These platforms allow users to find and purchase desired products without having to visit brick-and-mortar stores, and enjoy the convenience of having them delivered to their preferred location.

[0003] However, as e-commerce services expanded and a wider variety of products emerged, finding the product you want among the vast array of products required time and effort, leading to increased difficulty in selecting the product to purchase.

[0004] Accordingly, there is a need for technology that can identify products that users frequently purchase and, based on this, prioritize products that users are likely to purchase, thereby reducing user difficulties in the product selection process.

[0005] According to one embodiment of the present disclosure, the technical problem is to identify a product that a user is likely to repurchase.

[0006] According to one embodiment of the present disclosure, a technical problem is to recommend products in order of the likelihood that a user will repurchase them.

[0007] The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art of the present disclosure from the description below.

[0008] A method for providing product information performed by an electronic device according to one embodiment of the present disclosure may include the steps of: determining a set of repurchase candidate products related to a user based on a purchase history of the user; identifying a purchasing pattern of the user related to a plurality of products included in the set of repurchase candidate products; determining a ranking of the plurality of products based on the purchasing pattern of the user; determining one or more products to be recommended to the user from among the plurality of products in descending order of ranking based on the rankings of the plurality of products; and providing information on the one or more products to the user.

[0009] In one embodiment, the user's purchase history may include at least one of the product name, category, purchase date, purchase price, or number of purchases of products purchased by the user, and the user's purchase pattern may include at least one of the number of purchases, purchase frequency, or time elapsed since the last purchase of products included in the set of candidate products for repurchase.

[0010] In one embodiment, the step of determining the set of candidate products for repurchase may include the step of identifying whether the category of the product is a fresh product if the number of purchases of the product by the user within a predetermined period is less than or equal to a predetermined number; and the step of including the product in the set of candidate products for repurchase if the category of the product is a fresh product.

[0011] In one embodiment, the step of determining the set of candidate products for repurchase may include the step of identifying a repurchase rate associated with the product if the category of the product is not a fresh product; and the step of including the product in the set of candidate products for repurchase if the repurchase rate is greater than a predetermined value.

[0012] In one embodiment, the repurchase rate may be a ratio of the number of times multiple users have purchased the product and the number of times they have repurchased the product.

[0013] In one embodiment, the repurchase rate may be a ratio of the number of times multiple users have purchased products corresponding to the product category and the number of times they have repurchased the products.

[0014] In one embodiment, the step of determining the set of candidate products for repurchase may include the step of including the product in the set of candidate products for repurchase if the number of purchases of the product by the user within a predetermined period of time is greater than a predetermined number of purchases.

[0015] In one embodiment, the step of determining the set of candidate products for repurchase may include the step of removing products from the set of candidate products for repurchase that do not fall within a specific price range.

[0016] In one embodiment, the step of determining the set of candidate products for repurchase may include the step of removing seasonal products purchased at a specific point in time from the set of candidate products for repurchase.

[0017] In one embodiment, the step of ranking the plurality of products may include the step of ranking the plurality of products such that fresh products are ranked higher than products in other categories.

[0018] In one embodiment, the step of determining the ranking of the plurality of products may include the step of identifying the type of page requested by the user; and the step of determining the ranking of the plurality of products based on the purchasing pattern of the user and the type of the page.

[0019] In one embodiment, the step of determining the ranking of the plurality of products may include, when the type of the page is the first type, the step of identifying an expected repurchase time and a discount rate for each of the plurality of products; and the step of adjusting the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time and the higher the discount rate, the higher the ranking.

[0020] In one embodiment, the step of determining the rank of the plurality of products may include, when the type of the page is the second type, the step of identifying a discount rate for each of the plurality of products; and the step of adjusting the rank of the plurality of products so that a higher discount rate gives a higher rank.

[0021] In one embodiment, the step of determining the rank of the plurality of products may include, when the type of the page is a third type, the step of identifying the price of each of the plurality of products; and the step of adjusting the rank of the plurality of products so that the lower the price, the higher the rank.

[0022] In one embodiment, the step of determining the rank of the plurality of products may include, when the type of the page is a third type, the step of identifying the size of each of the plurality of products; and the step of adjusting the rank of the plurality of products so that a smaller size gives a higher rank.

[0023] In one embodiment, the step of determining the ranking of the plurality of products may include, when the type of the page is the fourth type, the step of identifying an expected repurchase time for each of the plurality of products; and the step of adjusting the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time, the higher the ranking.

[0024] In one embodiment, the method for providing product information may further include the steps of: removing a product from the one or more products that the user is determined not to repurchase; determining a product to replace the removed product from among the plurality of products based on a ranking of the plurality of products; and providing information about the determined product to the user.

[0025] In one embodiment, the method for providing product information may further include the step of receiving, from the user, a request to remove a specific product from the one or more products; and the step of removing the specific product from the one or more products in response to the request to remove the specific product.

[0026] An electronic device according to one embodiment of the present disclosure comprises one or more processors, one or more memories storing instructions to be executed by the one or more processors, and when the instructions are executed by the one or more processors, the one or more processors may be configured to execute a method according to the present disclosure.

[0027] In one embodiment of the present disclosure, a non-transitory computer-readable recording medium having recorded thereon instructions that, when executed by one or more processors, cause the one or more processors to perform an operation, the instructions may be configured to cause the one or more processors to perform a method according to the present disclosure.

[0028] According to one embodiment of the present disclosure, by identifying products that a user is likely to repurchase, products that a user is unlikely to repurchase can be prevented from being recommended.

[0029] According to one embodiment of the present disclosure, products are recommended in order of the likelihood that the user will repurchase, thereby enabling the user to easily find and purchase the products he or she needs.

[0030] The effects according to the technical idea of ​​the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the specification.

[0031] FIG. 1 is a diagram illustrating an environment in which an electronic device according to one embodiment of the present disclosure can be applied.

[0032] FIG. 2 is a block diagram of an electronic device according to one embodiment of the present disclosure.

[0033] FIG. 3 is a diagram illustrating an example of a page recommending products for repurchase according to one embodiment of the present disclosure.

[0034] FIG. 4 is a diagram illustrating an example of a user interface displaying repurchase candidate products according to one embodiment of the present disclosure.

[0035] FIG. 5 is a flowchart illustrating a method for providing product information according to one embodiment of the present disclosure.

[0036] FIG. 6 is a flowchart illustrating detailed operations for determining the ranking of products for repurchase in a product information provision method according to one embodiment of the present disclosure.

[0037] The embodiments of this disclosure are provided for the purpose of illustrating the technical concepts of this disclosure. The scope of rights under this disclosure is not limited to the embodiments presented below or the specific descriptions of these embodiments.

[0038] All technical and scientific terms used in this disclosure, unless otherwise defined, have the meanings commonly understood by those of ordinary skill in the art to which this disclosure pertains. All terms used in this disclosure have been selected for the purpose of more clearly explaining this disclosure and are not intended to limit the scope of rights under this disclosure.

[0039] Expressions such as “including,” “comprising,” “having,” and the like used in this disclosure should be understood as open-ended terms that imply the possibility of including other embodiments, unless otherwise stated in the phrase or sentence in which the expression is included.

[0040] The singular forms described in this disclosure may include plural meanings unless otherwise stated, and the same applies to the singular forms described in the claims.

[0041] The expressions “first,” “second,” etc. used in this disclosure are used to distinguish between multiple components, and do not limit the order or importance of the components.

[0042] The term "unit" as used herein refers to software or hardware components such as field-programmable gate arrays (FPGAs) and application specific integrated circuits (ASICs). However, "units" are not limited to hardware and software. "Units" may be configured to reside on an addressable storage medium, and may be configured to execute one or more processors. Thus, by way of example, "units" include components such as software components, object-oriented software components, class components, and task components, as well as processors, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided within a component and "unit" may be combined into a smaller number of components and "units" or further separated into additional components and "units."

[0043] The expression "based on" as used in this disclosure is used to describe one or more factors that influence the decision, act of judgment, or action described in the phrase or sentence containing the expression, and this expression does not exclude additional factors that influence the decision, act of judgment, or action.

[0044] In this disclosure, when a component is referred to as being "connected" or "connected" to another component, it should be understood that the component can be directly connected or connected to the other component, or can be connected or connected via a new other component.

[0045] Hereinafter, embodiments of the present disclosure will be described with reference to the attached drawings. In the attached drawings, identical or corresponding components are assigned the same reference numerals. Furthermore, in the description of the embodiments below, redundant descriptions of identical or corresponding components may be omitted. However, even if a description of a component is omitted, it is not intended that such component is not included in any embodiment.

[0046] FIG. 1 is a diagram illustrating an environment in which an electronic device (110) according to one embodiment of the present disclosure can be applied.

[0047] In one embodiment, an electronic device (110) and a user terminal (120, hereinafter referred to as a “terminal”) are connected through a network and can communicate with each other.

[0048] In one embodiment, the electronic device (110) may be a server or may be a different terminal than the terminal (120).

[0049] In one embodiment, the terminal (120) may be implemented as a terminal capable of transmitting and receiving various information with the electronic device (110) via a network. For example, the terminal (120) may be one of a computer, a laptop, a portable communication terminal (such as a smartphone), a portable multimedia device, a wearable device, or an HMD. However, the type of the terminal (120) is not limited thereto, and the terminal (120) may be any device that includes an input / output interface capable of receiving information from a user or outputting information to a user, and that can communicate with the electronic device (110) or other devices via a network. The terminal (120) may provide information received from the electronic device (110) to the user, and may receive input from the user and transmit it to the electronic device (110). The input obtained from the user may include various forms of input, such as a click using a mouse, a touch using a touchpad or a touch screen, voice recognition, or other electronic input.

[0050] In one embodiment, the network may serve to connect the electronic device (110) and the terminal (120) or other external device. For example, the network may provide a connection path so that the terminal (120) can be connected to the electronic device (110) and transmit and receive packet data with the electronic device (110). The network may be implemented as any type of wired or wireless network, such as a Local Area Network (LAN), a Wide Area Network (WAN), a Mobile Radio Communication Network, or Wibro (Wireless Broadband Internet).

[0051] FIG. 2 is a block diagram of an electronic device (200) according to one embodiment of the present disclosure.

[0052] In one embodiment, the electronic device (200) may be a server or a terminal.

[0053] In one embodiment, the electronic device (200) may include as components a communication circuit (210), one or more processors (220), and / or one or more memories (230).

[0054] In one embodiment, at least one of the components of the electronic device (200) may be omitted, or another component may be added to the electronic device (200).

[0055] In one embodiment, additionally or alternatively, some components may be implemented in an integrated manner, or implemented as a single or multiple entities. In the present disclosure, one or more processors (220) may be referred to as a processor (220). The expression “processor (220)” may mean a set of one or more processors, unless the context clearly indicates otherwise. In the present disclosure, one or more memories (230) may be referred to as a memory (230). The expression “memory (230)” may mean a set of one or more memories, unless the context clearly indicates otherwise.

[0056] In one embodiment, at least some of the components inside / outside the electronic device (200) are connected to each other through a bus, GPIO (General Purpose Input / Output), SPI (Serial Peripheral Interface), MIPI (Mobile Industry Processor Interface), etc., and can exchange information (data, signals, etc.).

[0057] In one embodiment, the communication circuit (210) can communicate with the user's terminal and an external device. The communication circuit (210) can perform wireless or wired communication between the electronic device (200) and the terminal. For example, the communication circuit (210) can perform wireless communication according to a method such as eMBB (enhanced Mobile Broadband), URLLC (Ultra Reliable Low-Latency Communications), MMTC (Massive Machine Type Communications), LTE (Long-Term Evolution), LTE-A (LTE Advance), NR (New Radio), UMTS (Universal Mobile Telecommunications System), GSM (Global System for Mobile communications), CDMA (Code Division Multiple Access), WCDMA (Wideband CDMA), WiBro (Wireless Broadband), WiFi (Wireless Fidelity), Bluetooth (Bluetooth), NFC (Near Field Communication), GPS (Global Positioning System), or GNSS (Global Navigation Satellite System). For example, the communication circuit (210) can perform wired communication according to a method such as USB (Universal Serial Bus), HDMI (High Definition Multimedia Interface), RS-232 (Recommended Standard-232), or POTS (Plain Old Telephone Service).

[0058] In one embodiment, the electronic device (200) may be implemented integrated with another device. In this case, the communication circuit (210) may function as a connection circuit or interface connecting the electronic device (200) and the other device.

[0059] In one embodiment, the processor (220) may control at least one component of an electronic device (200) connected to the processor (220) by executing software (e.g., commands, programs, etc.). In addition, the processor (220) may perform various operations related to the present disclosure, such as calculations, processing, data generation, and processing. In addition, the processor (220) may load data from or store data in the memory (230). Furthermore, the processor (220) may transmit and receive various information with a user's terminal and an external device through the communication circuit (210).

[0060] In one embodiment, the processor (220) controls the communication circuit (210) to transmit various information, such as information about various pages, to the user's terminal.

[0061] In one embodiment, the memory (230) can store various information (data). The information stored in the memory (230) is information acquired, processed, or used by at least one component of the electronic device (200), and may include software (e.g., commands, programs, etc.). The memory (230) may include volatile and / or non-volatile memory. In the present disclosure, the commands or programs are software stored in the memory (230), and may include an operating system for controlling the resources of the electronic device (200), an application, and / or middleware that provides various functions to the application so that the application can utilize the resources of the electronic device (200).

[0062] In one embodiment, the memory (230) may store instructions that, when executed by the processor (220), cause the processor (220) to perform operations. The memory (230) may store at least a portion of information received from the terminal via the communication circuit (210) and / or information transmitted to the terminal via the communication circuit (210). The processor (220) may store at least a portion of information received from the terminal via the communication circuit (210) and / or information transmitted to the terminal via the communication circuit (210) in the memory (230).

[0063] Hereinafter, the operations described as being performed by the electronic device in FIGS. 3 to 6 can be understood as being performed by the processor (220) of the electronic device (200) described in FIG. 2.

[0064] Although the process steps, method steps, algorithms, etc., are described in a sequential order in the schematics and flowcharts illustrated in FIGS. 3 and 6, such processes, methods, and algorithms may be configured to operate in any suitable order. In other words, the steps of the processes, methods, and algorithms described in various embodiments of the present disclosure need not be performed in the order described herein. Furthermore, even if some steps are described as being performed asynchronously, in other embodiments, such some steps may be performed concurrently. Furthermore, the illustration of a process by depiction in the drawings does not imply that the illustrated process excludes other variations and modifications thereof, nor does it imply that the illustrated process or any of its steps is essential to one or more of the various embodiments of the present disclosure, nor does it imply that the illustrated process is preferred.

[0065] FIG. 3 is a drawing illustrating an example of a page (300) recommending products for repurchase according to one embodiment of the present disclosure.

[0066] In one embodiment, the processor (220) may provide a page (300) displaying one or more products (310) to the user. Here, the one or more products (310) may be products recommended to the user.

[0067] In one embodiment, one or more products (310) may be N products (N is a natural number) in order from the highest rank in the user's repurchase candidate product set. For example, one or more products (310) may be displayed on the page (300) in descending order of rank. Referring to FIG. 3, since 'D Banana' has the highest rank, it may be displayed first on the page (300) (e.g., at the top left). Meanwhile, a detailed description of a method for determining a user's repurchase candidate product set and a method for determining the rank of products included in the repurchase candidate product set will be described later with reference to FIGS. 5 and 6.

[0068] In one embodiment, the page (300) may display information about each product (310). For example, the page (300) may display at least one of the name, capacity, unit quantity, or price of each product (310).

[0069] Meanwhile, page (300) of FIG. 3 is merely an example for explaining the present disclosure and is not limited thereto. Some of the configurations of page (300) of FIG. 3 may be omitted, and their forms may also be changed.

[0070] FIG. 4 is a diagram illustrating an example of a user interface (400) displaying a product as a candidate for repurchase according to one embodiment of the present disclosure.

[0071] In one embodiment, the processor (220) may provide a user interface (400) displaying one or more products (410) to the user. Here, the one or more products (410) may be products recommended to the user. For example, the user interface (400) may take the form of a widget. As another example, the user interface (400) may be displayed as a widget included in a specific page.

[0072] In one embodiment, one or more products (410) may be N products (N is a natural number) in order from the highest rank in the user's repurchase candidate product set. For example, one or more products (410) may be displayed on the user interface (400) in order of highest rank. Referring to FIG. 4, since "ABC Milk" has the highest rank, it may be displayed first (e.g., on the far left) on the user interface (400). Meanwhile, a detailed description of a method for determining a user's repurchase candidate product set and a method for determining the rank of products included in the repurchase candidate product set will be described later with reference to FIGS. 5 and 6.

[0073] In one embodiment, the user interface (400) may display information about each product (410). For example, the user interface (400) may display at least one of the name, capacity, unit quantity, or price of each product (410).

[0074] In one embodiment, the user interface (400) may display a request interface (420) for requesting a page listing products for repurchase. For example, if the user selects the request interface (420), the processor (220) may provide the user with a page listing products for repurchase. Here, the page listing products for repurchase may be page (300) of FIG. 3.

[0075] Meanwhile, the user interface (400) of FIG. 4 is merely an example for explaining the present disclosure and is not limited thereto. Some of the components of the user interface (400) of FIG. 4 may be omitted, and their forms may be changed.

[0076] FIG. 5 is a flowchart illustrating a method for providing product information according to one embodiment of the present disclosure.

[0077] In step (S510), the processor (220) can determine a set of repurchase candidate products related to the user based on the user's purchase history.

[0078] In one embodiment, the user's purchase history may include at least one of the product name, category, purchase date, purchase price, or number of purchases of products purchased by the user.

[0079] In one embodiment, the processor (220) may determine whether to include a product in the set of repurchase candidates based on the number of purchases of the product by the user. The number of purchases of the product by the user may be the number of purchases over a predetermined period of time (e.g., one year).

[0080] In one embodiment, if the number of times a user has purchased a product is greater than a predetermined number of times, the processor (220) may include the product in the set of products to be repurchased.

[0081] In one embodiment, if the number of times a user has purchased a product is less than or equal to a predetermined number of times, the processor (220) may identify whether the category of the product purchased by the user is a fresh product. Here, a fresh product may refer to a product for which freshness is an important characteristic, and may include, for example, groceries (e.g., fruits, vegetables, meat, seafood, etc.), food (e.g., bread, dairy products, etc.), and plants (e.g., flowers, etc.).

[0082] For example, if the category of the product purchased by the user is fresh, the processor (220) can include the purchased product in the set of products for repurchase. Fresh products are essential for daily life, making them highly likely to be repurchased even if the user has limited purchasing history. Therefore, by including these products in the set of products for repurchase, fresh products can be displayed to the user as recommended products for repurchase.

[0083] For example, if the category of the product purchased by the user is not fresh, the processor (220) can identify a repurchase rate associated with the product purchased by the user. If the repurchase rate is greater than a predetermined value (e.g., 5%), the processor (220) can include the product in the set of product candidates for repurchase. Alternatively, if the repurchase rate is less than or equal to the predetermined value, the processor (220) can determine not to include the product in the set of product candidates for repurchase. For example, the repurchase rate may be the ratio of the number of times multiple users, including the user, purchased the product and the number of times multiple users, including the user, repurchased the product. As a specific example, if the product purchased by the user is "golf balls," the repurchase rate may be the ratio of the number of times multiple users, including the user, purchased "golf balls" and the number of times multiple users, including the user, repurchased the product. As another example, the repurchase rate may be the ratio of the number of times multiple users, including the user, purchased products corresponding to the category of the product and the number of times multiple users, including the user, repurchased the product. A category refers to a classification group of products with specific common attributes. A category may include a parent category and its subcategories, and products in a parent category may be classified into subcategories based on their detailed properties. For example, if the product purchased by a user is a "golf glove," the repurchase rate may be the ratio of the total number of times that multiple users, including the user, purchased products (e.g., "golf balls," "golf clubs," "golf shoes," etc.) belonging to the "golf equipment" category to which the "golf glove" belongs, to the total number of times that the user repurchased the product. As another specific example, if the product purchased by a user is a "golf glove," the repurchase rate may be the ratio of the total number of times that multiple users, including the user, purchased products (e.g., "sporting equipment," which is the parent category of "golf equipment," to which the "golf glove" belongs, to the total number of times that the user repurchased the product.As another example, the repurchase rate can be the ratio of the number of times multiple users, including the user, purchased products of the same brand and the number of times they repurchased the product. For example, if the product purchased by the user is brand "A," the repurchase rate can be the ratio of the total number of times multiple users, including the user, purchased products of brand "A" and the total number of times they repurchased the product. While the above example was based on multiple users, the repurchase rate can also be calculated based on the current user.

[0084] In one embodiment, the processor (220) may remove products that do not fall within a specific price range from the set of repurchase candidate products. That is, the processor (220) may filter products that are unlikely to be repurchased by a user from the set of repurchase candidate products based on a set price range. As a specific example, if the set of repurchase candidate products includes "Product A" priced at "300,000 Won," "Product B" priced at "600,000 Won," and "Product C" priced at "1.2 million Won," and the standard price range is set to "1 million Won or less," the processor (220) may remove "Product C" from the set of repurchase candidate products.

[0085] In one embodiment, the processor (220) may remove seasonal products purchased at a specific point in time from the set of repurchase candidate products. "Seasonal products" here may refer to products that are primarily sold or popular during specific periods, seasons, anniversaries (holidays), etc. While seasonal products may be included in the set of repurchase candidate products due to their high purchase frequency during a specific period, the actual likelihood of repurchase may be low because they are not products that users purchase regularly. For this reason, seasonal products may be removed from the set of repurchase candidate products to prioritize products with a high repurchase probability for users. As a specific example, "electric fans," which are seasonal products for the summer season, may be included in the set of repurchase candidate products due to their high purchase frequency during the summer. However, considering that "electric fans" are not a product that is repurchased regularly, the processor (220) may determine that the likelihood of repurchase is low after the summer period and remove them from the set of repurchase candidate products.

[0086] In step (S520), the processor (220) can identify a user's purchasing pattern related to a plurality of products included in a set of repurchase candidate products.

[0087] In one embodiment, a user's purchasing pattern may include at least one of the following: the number of purchases of products included in the set of repurchase candidates, the frequency of purchases of those products, or the elapsed time since the last purchase of those products. In an additional embodiment, the user's purchasing pattern may further include the type of page the user requests to purchase products. In this way, a user's purchasing pattern, as a result of analyzing purchase history, may reflect characteristics, tendencies, or preferences that are evident in the user's purchasing behavior.

[0088] In step (S530), the processor (220) can determine the ranking of multiple products included in the set of repurchase candidate products based on the user's purchasing pattern.

[0089] In one embodiment, the processor (220) may rank multiple products so that products with a higher number of purchases are given a higher rank. For example, if a set of repurchase candidate products includes "A" with 25 purchases and "B" with 100 purchases, the processor (220) may assign a higher rank to "B" than to "A."

[0090] In one embodiment, the processor (220) may rank multiple products so that products with higher purchase frequency are ranked higher. For example, if a set of repurchase candidate products includes "A," which is "purchased twice a day," and "B," which is "purchased twice a week," the processor (220) may assign a higher rank to "A" than to "B."

[0091] In one embodiment, the processor (220) can identify the expected repurchase time for each of the multiple products and rank the multiple products so that products with a shorter time remaining until the expected repurchase time are given a higher rank. In other words, by assigning a higher rank to products with a short time remaining until the user's repurchase, such products can be recommended with priority.

[0092] For example, the processor (220) may generate profile information for a user based on the user's purchasing patterns. The profile information may include the user's gender, family composition, pet ownership, age group, or lifestyle patterns (e.g., eating habits). For example, if a user frequently purchases beauty products (e.g., cosmetics), the processor (220) may determine the user's gender as female. As another example, based on the user's purchases of products for different purposes, such as baby products and women's products, the processor (220) may identify the user's family composition. For example, based on the frequency with which the user purchases groceries (e.g., rice), the processor (220) may identify the user's family composition. For example, if the user frequently purchases pet supplies, the processor (220) may determine that the user owns a pet. For example, if the user frequently purchases a specific combination of groceries (e.g., rice and sauce products), the processor (220) may identify the user's eating habits.

[0093] For example, the processor (220) may identify an expected repurchase time for a product based on the user's profile information. The processor (220) may identify an expected repurchase time for a product based on the product purchase cycle of the age group to which the user belongs.

[0094] For example, the processor (220) may identify an expected repurchase time for a product based on the product's capacity information and the user's profile information. The processor (220) may identify an expected repurchase time when consumption of the product is complete based on the average per-person consumption of the product and the number of family members of the user.

[0095] In one embodiment, the processor (220) may determine the ranking of multiple products such that fresh products are ranked higher than products in other categories. For example, if a set of repurchase candidate products includes fresh products "A," sporting goods "B," and kitchenware "C," the processor (220) may determine the rankings among "A," "B," and "C" such that fresh products "A" are ranked higher than "B" and "C."

[0096] In one embodiment, the processor (220) may determine the ranking of multiple products so that out-of-stock products are ranked lower than other products. For example, if a set of repurchase candidate products includes "A," "B," and "C," and "C" is out of stock, the processor (220) may assign a lower ranking to the out-of-stock "C" than to "A" and "B." This prevents out-of-stock products from being recommended to users.

[0097] In one embodiment, the processor (220) may determine the ranking of multiple products such that a higher discount rate gives them a higher ranking. The discount rate may be expressed as a percentage, calculated by subtracting the price a user would actually pay when purchasing the product from the original price of the product and dividing the difference by the original price. As a specific example, if a set of repurchase candidate products includes "A" with a 20% discount rate and "B" with a 40% discount rate, the processor (220) may assign a higher ranking to "B" than to "A."

[0098] In one embodiment, the processor (220) may determine a ranking of multiple products based on the respective categories of the multiple products. For example, the processor (220) may identify two or more products belonging to the same category among the multiple products and determine a ranking of the multiple products so that only one of the products is recommended to the user. Here, the category may be a parent category or a subcategory thereof. As a specific example, if a set of repurchase candidate products includes "A" and "B" in the same category, "B" may be given a lower ranking so that only "A" is recommended to the user.

[0099] In one embodiment, the processor (220) may determine the ranking of multiple products based on the type of page requested by the user to purchase the product. A detailed description of the method for determining the ranking based on the page type is provided below with reference to FIG. 6.

[0100] In one embodiment, the processor (220) may determine a weight for each of one or more items for determining the ranking of multiple products. Here, the one or more items may include, as examples for determining the ranking, the number of purchases, the frequency of purchases, the expected timing of repurchases, the category, whether the product is out of stock, or the discount rate. The processor (220) may determine the ranking of multiple products based on the weight for each of these items. As a specific example, if the set of candidate products for repurchases includes 'A' with a number of purchases of '10 times' and a purchase frequency of '2 times a day' and 'B' with a number of purchases of '30 times' and a purchase frequency of '1 time a day', and the purchase frequency is weighted higher than the number of purchases, the processor (220) may assign a higher ranking to 'A' than to 'B'.

[0101] In one embodiment, the processor (220) may use an artificial neural network to rank multiple products. The artificial neural network may be trained to rank multiple products based on at least some of the examples described above. For example, the artificial neural network may be trained to rank multiple products based on the number of purchases and frequency of purchases. The processor (220) may use the trained artificial neural network to rank multiple products. Furthermore, the present disclosure is not limited to artificial neural networks, and various models, hyperparameters, learning methods, and the like suitable for ranking multiple products may be utilized.

[0102] In step (S540), the processor (220) may determine one or more products to recommend to the user from among the plurality of products in order of highest ranking based on the ranking of the plurality of products.

[0103] For example, the processor (220) may determine N products (e.g., 20 products) in order of highest rank among a plurality of products to be recommended to the user.

[0104] In step (S550), the processor (220) may provide information about one or more products to the user.

[0105] For example, the processor (220) may provide a user with a page displaying information about one or more products. Here, the page may be the page (300) described in FIG. 3.

[0106] As another example, the processor (220) may provide the user with a user interface displaying information about one or more products. Here, the processor may provide the user with a page including a widget displaying information about one or more products. Here, the user interface (widget) may be the user interface (400) described in FIG. 4.

[0107] Meanwhile, in step (S550), the page displaying information on one or more products is a page provided at the user's request, and may include, for example, at least one of a home page, a fresh product list page, a repurchase candidate product list page, or a shopping cart page.

[0108] In one embodiment, the processor (220) may remove a product from one or more recommended products that the user determines is unlikely to repurchase. For example, if the user did not select the product, scrolled the page so that the product was not visible, or did not scroll the page so that the product was visible, the processor (220) may determine that the user is unlikely to repurchase the product and remove the product from one or more recommended products. In this case, the processor (220) may determine a new product to replace the product determined to not be repurchased and removed based on the ranking of multiple products included in the set of candidate products for repurchase. The processor (220) may provide the user with information about the new product.

[0109] In one embodiment, the processor (220) may receive a request from a user to remove a specific product from one or more products recommended to the user. The removal request may include a request to delete or hide the specific product. In response to the removal request, the processor (220) may remove the specific product requested for removal from the one or more products recommended to the user. In an additional embodiment, the processor (220) may provide the user with information regarding the completion of the removal of the specific product.

[0110] FIG. 6 is a flowchart illustrating detailed operations for determining the ranking of products for repurchase in a product information provision method according to one embodiment of the present disclosure.

[0111] Step (S600) of FIG. 6 may be a detailed operation of step (S530) of determining the ranking of multiple products included in the set of repurchase candidate products described with reference to FIG. 5.

[0112] In one embodiment, step (S600) may be performed each time a user requests a page for purchasing a product. That is, each time a user requests a page for purchasing a product, the ranking of products to be repurchased may be determined anew, or the existing ranking may be adjusted.

[0113] In step S610, the processor (220) can identify the type of page requested by the user. Users may request various pages during the product purchase process. For example, users may request a home page displaying various products, promotions, events, etc., a fresh product list page displaying fresh products, a repurchase candidate product list page displaying recommended repurchase products, or a shopping cart page displaying products added to the shopping cart.

[0114] In step (S620), the processor (220) can determine the ranking of multiple products included in the set of repurchase candidate products based on the type of page requested by the user.

[0115] In one embodiment, if the type of page requested by the user is the first type, the processor (220) can identify the expected repurchase time and discount rate for each of the multiple products. The expected repurchase time and discount rate are described in FIG. 5 . The processor (220) can adjust the rankings of the multiple products so that products with a shorter time remaining until the expected repurchase time and a higher discount rate are ranked higher. For example, the first type of page may be a homepage. While the user does not request the homepage to purchase a product that is a candidate for repurchase, the user may be interested in products with a short expected repurchase time and a large discount rate. Therefore, when the user requests the homepage, the processor (220) can assign a high ranking to such products. This allows the product to be recommended to the user, thereby encouraging the user to purchase the product.

[0116] In one embodiment, if the page type requested by the user is the second type, the processor (220) can identify a discount rate for each of the multiple products. For details on the discount rate, see the description in FIG. 5. The processor (220) can adjust the ranking of the multiple products so that a higher discount rate gives a higher ranking. For example, the second type of page may be a fresh product list page. Since the user requests the fresh product list page to purchase fresh products, the higher the discount rate, the more likely the user is to purchase the product. Accordingly, when the user requests the fresh product list page, the processor (220) can assign a higher ranking to fresh products with higher discount rates in the set of repurchase candidate products. This can be used to recommend the product to the user, thereby encouraging the user to purchase the product.

[0117] In one embodiment, if the page type requested by the user is the third type, the processor (220) may identify the price of each of the multiple products. The processor (220) may then adjust the ranking of the multiple products so that lower prices are given a higher ranking. For example, the third type of page may be a shopping cart page. Since the user requests a shopping cart page to purchase products added to the shopping cart, products with a higher probability of being purchased along with products already added to the shopping cart may be lower priced products. Therefore, when the user requests a shopping cart page, the processor (220) may prioritize lower priced products in the set of repurchase candidate products. This may allow the product to be recommended to the user, thereby encouraging the user to purchase the product. In an additional or alternative embodiment, if the page type requested by the user is the third type, the processor (220) may identify the size of each of the multiple products. Since the user requests a shopping cart page to purchase products added to the shopping cart, products with a higher probability of being purchased along with products already added to the shopping cart may be smaller size products. Therefore, when a user requests a shopping cart page, the processor (220) can prioritize smaller products in the set of repurchase candidate products. This allows the product to be recommended to the user, thereby encouraging the user to purchase the product.

[0118] In one embodiment, if the page type requested by the user is the fourth type, the processor (220) can identify the expected repurchase time for each of the multiple products. The processor (220) can adjust the ranking of the multiple products so that products with a shorter time remaining until the expected repurchase time are ranked higher. For example, the fourth type of page may be a page listing products for potential repurchase candidates. Since users request the page listing products for potential repurchase candidates to purchase frequently purchased products, they are more likely to purchase products with a near expected repurchase time. Therefore, when a user requests the page listing products for potential repurchase candidates, the processor (220) can assign a higher priority to products with a near expected repurchase time in the set of potential repurchase products. This can be used to recommend these products to the user, thereby encouraging the user to purchase them.

[0119] While the method has been described through specific embodiments, the method can also be implemented as computer-readable code on a computer-readable recording medium. A computer-readable recording medium includes any type of recording device that stores data that can be read by a computer system. Examples of computer-readable recording media include ROMs, RAMs, CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, etc. Furthermore, the computer-readable recording medium can be distributed across network-connected computer systems, so that the computer-readable code can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the above embodiments can be readily inferred by programmers skilled in the art to which the present disclosure pertains.

Claims

1. In a method for providing product information performed by an electronic device, A step of determining a set of repurchase candidate products related to the user based on the user's purchase history; A step of identifying a purchasing pattern of the user related to a plurality of products included in the set of candidate products for repurchase; A step of determining the ranking of the plurality of products based on the purchasing pattern of the user; A step of determining one or more products to be recommended to the user from among the plurality of products in order of highest ranking based on the ranking of the plurality of products; and A method comprising the step of providing information about said one or more products to said user.

2. In paragraph 1, The purchase history of the user includes at least one of the product name, category, purchase date, purchase price, or number of purchases of the product purchased by the user. A method wherein the purchase pattern of the user includes at least one of the number of purchases, purchase frequency, or time elapsed since the last purchase of a product included in the set of candidate products for repurchase.

3. In paragraph 1, The step of determining the set of candidate products for repurchase is as follows: A step of identifying whether the category of the product is a fresh product when the number of purchases of the product purchased by the user within a given period of time is less than or equal to a predetermined number of purchases; and A method comprising the step of including the product in the set of candidate products for repurchase, if the category of the product is fresh product.

4. In paragraph 3, The step of determining the set of candidate products for repurchase is as follows: If the category of the above product is not a fresh product, a step of identifying the repurchase rate related to the above product; and A method comprising the step of including the product in the set of candidate products for repurchase when the repurchase rate is greater than a predetermined value.

5. In paragraph 4, The above repurchase rate is a method in which the ratio of the number of times multiple users have purchased the product and the number of times they have repurchased the product.

6. In paragraph 4, The above repurchase rate is a method in which the ratio of the number of times multiple users purchased products corresponding to the above product category and the number of times they repurchased the products.

7. In paragraph 1, The step of determining the set of candidate products for repurchase is as follows: A method comprising the step of including the product in the set of candidate products for repurchase when the number of purchases of the product by the user within a given period of time is greater than a predetermined number of purchases.

8. In paragraph 1, The step of determining the set of candidate products for repurchase is as follows: A method comprising the step of removing products that do not fall within a specific price range from the set of repurchase candidate products.

9. In paragraph 1, The step of determining the set of candidate products for repurchase is as follows: A method comprising the step of removing seasonal products purchased at a specific point in time from the set of repurchase candidate products.

10. In paragraph 1, The step of determining the ranking of the above multiple products is: A method comprising the step of determining a ranking of the plurality of products such that fresh products are ranked higher than products in other categories.

11. In paragraph 1, The step of determining the ranking of the above multiple products is: A step of identifying the type of page requested by the user; and A method comprising the step of determining a ranking of the plurality of products based on the purchasing pattern of the user and the type of the page.

12. In paragraph 11, The step of determining the ranking of the above multiple products is: If the type of the above page is the first type, a step of identifying the expected repurchase time and discount rate for each of the plurality of products; and A method comprising a step of adjusting the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time and the higher the discount rate, the higher the ranking.

13. In paragraph 11, The step of determining the ranking of the above multiple products is: If the type of the above page is the second type, a step of identifying a discount rate for each of the plurality of products; and A method comprising the step of adjusting the ranks of the plurality of products so that the higher the discount rate, the higher the rank.

14. In paragraph 11, The step of determining the ranking of the above multiple products is: If the type of the above page is the third type, a step of identifying the price for each of the plurality of products; and A method comprising the step of adjusting the ranks of the plurality of products so that the lower the price, the higher the rank.

15. In paragraph 11, The step of determining the ranking of the above multiple products is: If the type of the above page is the third type, a step of identifying the size of each of the plurality of products; and A method comprising the step of adjusting the ranks of the plurality of products so that the smaller the size, the higher the rank.

16. In paragraph 11, The step of determining the ranking of the above multiple products is: If the type of the above page is the fourth type, a step of identifying an expected repurchase time for each of the plurality of products; and A method comprising a step of adjusting the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time, the higher the ranking.

17. In paragraph 1, A step of removing a product from the above one or more products that the user is determined not to repurchase; A step of determining a product to replace the removed product among the plurality of products based on the ranking of the plurality of products; and A method further comprising the step of providing information about the determined product to the user.

18. In paragraph 1, A step of receiving a request for removal of a specific product from the one or more products from the user; and A method further comprising, in response to said removal request, removing said specific product from said one or more products.

19. In electronic devices, One or more processors, comprising one or more memories storing instructions executed by the one or more processors; An electronic device, wherein when the instructions are executed by the one or more processors, the one or more processors are configured to execute a method according to any one of claims 1 to 18.

20. In a non-transitory computer-readable recording medium having recorded thereon instructions that, when executed by one or more processors, cause the one or more processors to perform an operation, A non-transitory computer-readable recording medium, wherein the instructions are configured to cause the one or more processors to execute a method according to any one of claims 1 to 18.

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