KR20250033131A - Method, device, and recording medium for providing product information - Google Patents

Abstract

A method for providing product information performed by an electronic device according to one embodiment of the present disclosure may include: a step of determining a set of repurchase candidate products related to a user based on a purchase history of the user; a step of identifying a purchase pattern of the user related to a plurality of products included in the set of repurchase candidate products; a step of determining a ranking of the plurality of products based on the purchase 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 high ranking based on the rankings of the plurality of products; and a step of providing information on the one or more products to the user.

Description

METHOD, DEVICE, AND RECORDING MEDIUM FOR PROVIDING PRODUCT INFORMATION

The present disclosure relates to a technology for providing product information. More specifically, the present disclosure relates to a technology for preferentially recommending products with a high probability of repurchase among products that are candidates for repurchase.

With the development of communication technology and changes in the social environment, e-commerce services are providing a variety of products and services to many users through online platforms. Users can enjoy the convenience of finding and purchasing desired products without having to visit offline stores in person, and having them delivered to their desired location.

However, as the scale of e-commerce services has expanded and various products have appeared, it has become difficult for users to find the product they want among the numerous products, which requires time and effort.

Accordingly, a technology is required that can identify products that users frequently purchase and, based on this, recommend products that users are likely to purchase first, thereby preventing users from experiencing difficulties in the product selection process.

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

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.

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 from the description below.

A method for providing product information performed by an electronic device according to one embodiment of the present disclosure may include: a step of determining a set of repurchase candidate products related to a user based on a purchase history of the user; a step of identifying a purchase pattern of the user related to a plurality of products included in the set of repurchase candidate products; a step of determining a ranking of the plurality of products based on the purchase 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 rankings of the plurality of products; and a step of providing information on the one or more products to the user.

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.

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 purchased by the user within a predetermined period is less than or equal to a predetermined number of times; 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.

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.

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

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

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.

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.

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.

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.

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

In one embodiment, the step of determining the rank 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 rank of the plurality of products so that the rank is higher as the time remaining until the expected repurchase time is shorter and the discount rate is higher.

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

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

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

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

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 the plurality of products based on the ranking of the plurality of products; and providing information on the determined product to the user.

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.

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

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 operations, the instructions may be configured to cause the one or more processors to perform a method according to the present disclosure.

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.

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

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.

FIG. 1 is a diagram illustrating an environment to which an electronic device according to one embodiment of the present disclosure can be applied.
FIG. 2 is a block diagram of an electronic device according to one embodiment of the present disclosure.
FIG. 3 is a diagram illustrating an example of a page recommending products for repurchase according to one embodiment of the present disclosure.
FIG. 4 is a diagram illustrating an example of a user interface displaying repurchase candidate products according to one embodiment of the present disclosure.
FIG. 5 is a flowchart illustrating a method for providing product information according to one embodiment of the present disclosure.
FIG. 6 is a flowchart illustrating detailed operations for determining the ranking of products for repurchase in a method for providing product information according to one embodiment of the present disclosure.

The embodiments of the present disclosure are provided for the purpose of explaining the technical idea of the present disclosure. The scope of rights according to the present disclosure is not limited to the embodiments presented below or the specific description of these embodiments.

All technical and scientific terms used in this disclosure, unless otherwise defined, have the meaning commonly understood by one of ordinary skill in the art to which this disclosure belongs. All terms used in this disclosure have been selected for the purpose of more clearly describing this disclosure and are not selected to limit the scope of rights under this disclosure.

The expressions “including,” “comprising,” “having,” and the like, as used in this disclosure, should be understood as open-ended terms implying the possibility of including other embodiments, unless otherwise stated in the phrase or sentence in which the expression is included.

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.

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.

The term "unit" as used in this disclosure means software or a hardware component such as a field-programmable gate array (FPGA) or an application specific integrated circuit (ASIC). However, the "unit" is not limited to hardware and software. The "unit" may be configured to be on an addressable storage medium, and may be configured to execute one or more processors. Thus, by way of example, the "unit" includes 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 a "unit" may be combined into a smaller number of components and "units" or further separated into additional components and "units."

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

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.

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

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

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.

In one embodiment, the electronic device (110) may be a server or may be another terminal distinct from the terminal (120).

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 capable of communicating 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 touch pad or a touch screen, voice recognition, or other electronic input.

In one embodiment, the network may serve to connect the electronic device (110) and the terminal (120) or other external devices. 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, for example, a Local Area Network (LAN), a Wide Area Network (WAN), a Mobile Radio Communication Network, or a Wireless Broadband Internet (Wibro).

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

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

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).

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).

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

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

In one embodiment, the communication circuit (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).

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.

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, etc. from the memory (230) or store data in the memory (230). Furthermore, the processor (220) may transmit and receive various information with the user's terminal and external devices through the communication circuit (210).

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.

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 nonvolatile memory. In the present disclosure, the commands or programs are software stored in the memory (230), and may include an operating system for controlling resources of the electronic device (200), an application, and/or middleware for providing various functions to applications so that the applications can utilize resources of the electronic device (200).

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).

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

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 in the present disclosure. 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 changes and modifications thereto, 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.

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

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

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 order of their rank. Referring to FIG. 3, since 'D Banana' has the highest rank, it may be displayed first (e.g., at the top left) on the page (300). Meanwhile, a specific 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.

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).

Meanwhile, page (300) of Fig. 3 is only 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 be changed.

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.

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

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 their 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 specific 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.

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).

In one embodiment, the user interface (400) may display a request interface (420) for requesting a repurchase candidate product list page. For example, when the user selects the request interface (420), the processor (220) may provide the repurchase candidate product list page to the user. Here, the repurchase candidate product list page may be page (300) of FIG. 3.

Meanwhile, the user interface (400) of Fig. 4 is only an example for explaining the present disclosure and is not limited thereto. Some of the configurations of the user interface (400) of Fig. 4 may be omitted and their forms may be changed.

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

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

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.

In one embodiment, the processor (220) may determine whether to include a product in a set of repurchase candidate products based on the number of purchases of the product purchased by the user. Here, the number of purchases of the product purchased by the user may be the number of purchases during a predetermined period (e.g., one year).

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 a set of products to be repurchased.

In one embodiment, if the number of purchases of a product purchased by the user is less than or equal to a predetermined number of times, the processor (220) can identify whether the category of the product purchased by the user is a fresh product. Here, a fresh product may mean a product with freshness as 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.).

For example, if the category of the product purchased by the user is fresh product, the processor (220) can include the product purchased by the user in the set of products for repurchase candidates. In the case of fresh products, even if the user does not have much purchase history, there is a high possibility of repurchasing them because they are necessary for daily life. Therefore, by including such products in the set of products for repurchase candidates, fresh products can be exposed to the user as recommended products for repurchase.

For example, if the category of the product purchased by the user is not fresh, the processor (220) can identify a repurchase rate related to 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 candidate products 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 candidate products for repurchase. For example, the repurchase rate can be a ratio of the number of times that multiple users, including the user, have purchased the product and the number of times that they have repurchased it. As a specific example, if the product purchased by the user is 'golf balls', the repurchase rate can be a ratio of the number of times that multiple users, including the user, have purchased 'golf balls' and the number of times that they have repurchased it. As another example, the repurchase rate can be a ratio of the number of times that multiple users, including the user, have purchased products corresponding to the category of the product and the number of times that they have repurchased them. A category refers to a classification group of products having specific common attributes. A category may include a parent category and subcategories thereof, and products in a parent category may be classified into subcategories according to their detailed properties. As a 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 belonging to the 'golf equipment' category to which the 'golf glove' belongs (e.g., 'golf balls', 'golf clubs', 'golf shoes', etc.) and the total number of repurchases. 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 belonging to the 'sporting equipment' category to which the 'golf glove' belongs (e.g., 'sneakers', 'towels', etc.) and the total number of repurchases. As another example, the repurchase rate may be the ratio of the number of times that multiple users, including the user, purchased products of the same brand as the product and the number of repurchases. As a specific example, if the brand of the product purchased by the user is 'A', the repurchase rate can be the ratio of the total number of times multiple users including the user purchased products of the 'A' brand and the total number of times they repurchased them. In the above example, the explanation was based on multiple users, but it is also possible to calculate the repurchase rate based on the current user.

In one embodiment, the processor (220) may remove products that do not fall within a specific price range from the set of candidate products for repurchase. That is, the processor (220) may filter products that are unlikely to be repurchased by a user from the set of candidate products for repurchase based on a set price range. As a specific example, if the set of candidate products for repurchase includes 'Product A' with a price of '300,000 won', 'Product B' with a price of '600,000 won', and 'Product C' with a price of '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 candidate products for repurchase.

In one embodiment, the processor (220) may remove seasonal products purchased at a specific time from the set of candidate products for repurchase. Here, a seasonal product may mean a product that is mainly sold or popular during a specific time, season, anniversary (holiday), etc. Seasonal products may be included in the set of candidate products for repurchase because they are purchased frequently during a specific time, but may have a low actual repurchase probability because they are not products that users purchase regularly. For this reason, seasonal products may be removed from the set of candidate products for repurchase in order to preferentially recommend products with a high repurchase probability to users. As a specific example, a 'fan', which is a seasonal product for the summer season, may be included in the set of candidate products for repurchase because the number of purchases is high during the summer period. However, considering that the 'fan' is not a product that is repurchased periodically, the processor (220) may determine that the repurchase probability is low after the summer period, and remove it from the set of candidate products for repurchase.

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

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

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.

In one embodiment, the processor (220) may determine the ranking of multiple products so that a higher number of purchases gives them a higher ranking. For example, if a set of candidate products for repurchase includes 'A' with '25 purchases' and 'B' with '100 purchases', the processor (220) may give 'B' a higher ranking than 'A'.

In one embodiment, the processor (220) may determine the ranking of multiple products so that a higher purchase frequency gives a higher ranking. For example, if the set of candidate products for repurchase includes 'A' that is 'purchased twice a day' and 'B' that is 'purchased twice a week', the processor (220) may give 'A' a higher ranking than 'B'.

In one embodiment, the processor (220) can identify the expected repurchase time for each of the plurality of products, and determine the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time, the higher the ranking. In other words, by giving a high ranking to a product that the user has little time left until the repurchase, the product can be recommended preferentially.

For example, the processor (220) may generate profile information of the user based on the user's purchasing pattern. Here, the profile information may include the user's gender, family composition, presence or absence of a pet, age group, or lifestyle pattern (e.g., eating habits). As a specific example, if the user frequently purchases beauty products (e.g., cosmetics, etc.), the processor (220) may determine the user's gender as female. As another specific example, based on the user's purchase of products for different purposes, such as baby products and women's products, the processor (220) may identify the user's family composition. As a specific example, based on the frequency with which the user purchases groceries (e.g., rice), the processor (220) may identify the user's family composition. As a specific example, if the user frequently purchases pet supplies, the processor (220) may determine that the user raises a pet. As a specific 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.

For example, the processor (220) can identify an expected repurchase time of a product based on the user's profile information. The processor (220) can identify an expected repurchase time of a product based on the cycle in which the age group to which the user belongs purchases the product.

For example, the processor (220) can identify the expected repurchase time of the product based on the product capacity information and the user's profile information. The processor (220) can identify the expected repurchase time when consumption of the product is completed based on the average consumption amount per person of the product and the number of family members of the user.

In one embodiment, the processor (220) can determine a ranking of a plurality of products such that fresh products are ranked higher than products in other categories. As a specific example, if a set of repurchase candidate products includes 'A', a fresh product, 'B', a sporting goods product, and 'C', a kitchenware product, the processor (220) can determine a ranking among 'A', 'B', and 'C' such that 'A', a fresh product, is ranked higher than 'B' and 'C'.

In one embodiment, the processor (220) may determine the ranking of multiple products so that an out-of-stock product is ranked lower than other products. As a specific 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 'A' and 'B'. This may prevent out-of-stock products from being recommended to users.

In one embodiment, the processor (220) may determine the ranking of multiple products so that a higher discount rate has a higher ranking. Here, the discount rate may be a percentage value obtained by dividing the difference between the original price of the product and the price that the user actually pays when purchasing the product by the original price. As a specific example, if the set of candidate products for repurchase includes 'A' with a discount rate of '20%' and 'B' with a discount rate of '40%', the processor (220) may assign a higher ranking to 'B' than to 'A'.

In one embodiment, the processor (220) may determine a ranking of the plurality of products based on the category of each of the plurality of products. For example, the processor (220) may identify two or more products belonging to the same category among the plurality of products, and determine a ranking of the plurality of 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 candidate products for repurchase includes 'A' and 'B' in the same category, a low ranking may be given to 'B' so that only 'A' among them is recommended to the user.

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 specific description of a method for determining the ranking based on the type of page is described below with reference to FIG. 6.

In one embodiment, the processor (220) may determine a weight for each of one or more items for determining the ranking of the plurality of 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 repurchase, the category, whether out of stock, or the discount rate. The processor (220) may determine the ranking of the plurality of products based on the weight for each of these items. As a specific example, if the set of candidate products for repurchase includes 'A' with the number of purchases of '10 times' and the purchase frequency of 'purchased twice a day' and 'B' with the number of purchases of '30 times' and the purchase frequency of 'purchased once a day', and the purchase frequency has a higher weight than the number of purchases, the processor (220) may assign a higher ranking to 'A' than to 'B'.

In one embodiment, the processor (220) may determine the ranking of the plurality of products using an artificial neural network. Here, the artificial neural network may be trained to determine the ranking of the plurality of products based on at least some of the examples described above. For example, the artificial neural network may be trained to determine the ranking of the plurality of products based on the number of purchases and the frequency of purchases. The processor (220) may determine the ranking of the plurality of products using the trained artificial neural network. Meanwhile, the present disclosure is not limited to an artificial neural network, and various types of models, hyperparameters, learning methods, etc. suitable for determining the ranking of the plurality of products may be utilized.

In step (S540), the processor (220) may determine one or more products to recommend to the user among the multiple products in order of high ranking based on the rankings of the multiple products.

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

In step (S550), the processor (220) may provide information on one or more products to the user.

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.

As another example, the processor (220) may provide a user interface to the user that displays information about one or more products. Here, a page including a widget that displays information about one or more products may be provided to the user. Here, the user interface (widget) may be the user interface (400) described in FIG. 4.

Meanwhile, in step (S550), a page displaying information about 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.

In one embodiment, the processor (220) may remove a product from one or more products recommended to the user that is determined not to be repurchased by the user. 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 will not repurchase the product, and remove the product determined not to be repurchased from one or more products recommended to the user. In this case, the processor (220) may determine a new product to replace the product determined not to 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 information about the new product to the user.

In one embodiment, the processor (220) may receive a request from a user to remove a specific product from among one or more products recommended to the user. Here, the removal request may include a request to delete or hide a specific product. In response to the removal request, the processor (220) may remove the specific product for which removal is requested from among one or more products recommended to the user. As an additional embodiment, the processor (220) may provide the user with information about the completion of removal of the specific product.

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

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.

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 newly determined or the existing ranking may be adjusted.

In step (S610), the processor (220) can identify the type of page requested by the user. The user can request various pages during the process of purchasing a product. For example, the user can request a home page where various products, promotions, events, etc. are displayed, a fresh product list page where fresh products are displayed, a repurchase candidate product list page where repurchase recommendation products are displayed, or a shopping cart page where products added to the shopping cart are displayed.

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.

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 plurality of products. For the expected repurchase time and discount rate, refer to the description of FIG. 5. The processor (220) can adjust the ranking of the plurality of products so that the shorter the remaining time until the expected repurchase time and the higher the discount rate, the higher the ranking. For example, the first type of page can be a home page. The user does not request the home page to purchase a candidate product for repurchase, but may be interested in a product with a short expected repurchase time and a large discount rate. Therefore, if the user requests the home page, the processor (220) can assign a high ranking to such a product. Through this, the product can be recommended to the user, thereby inducing the user to purchase the product.

In one embodiment, if the type of page requested by the user is the second type, the processor (220) can identify a discount rate for each of the plurality of products. For the discount rate, refer to the description of FIG. 5. The processor (220) can adjust the ranking of the plurality of products so that a higher discount rate has a higher ranking. For example, the second type of page can be a fresh product list page. Since the user requests the fresh product list page to purchase a fresh product, the higher the discount rate, the higher the possibility of purchasing the product. Accordingly, when the user requests the fresh product list page, the processor (220) can assign a high ranking to a fresh product with a high discount rate in the set of repurchase candidate products. Through this, the product can be recommended to the user, thereby inducing the user to purchase the product.

In one embodiment, if the type of page requested by the user is the third type, the processor (220) can identify the price of each of the plurality of products. The processor (220) can adjust the ranking of the plurality of products so that a lower price is given a higher ranking. For example, the third type of page may be a shopping cart page. Since the user requests the shopping cart page to purchase a product added to the shopping cart, a product likely to be purchased together with a product already added to the shopping cart may be a product with a lower price. Accordingly, when the user requests the shopping cart page, the processor (220) can give a higher priority to a product with a lower price in the set of repurchase candidate products. This allows the product to be recommended to the user, thereby inducing the user to purchase the product. In an additional or alternative embodiment, if the type of page requested by the user is the third type, the processor (220) can identify the size of each of the plurality of products. Since the user requests the shopping cart page to purchase a product added to the shopping cart, a product likely to be purchased together with a product already added to the shopping cart may be a product with a smaller size. Accordingly, when a user requests a shopping cart page, the processor (220) can give a high priority to a product with a small size in the set of repurchase candidate products. This can lead to the product being recommended to the user, thereby inducing the user to purchase the product.

In one embodiment, if the type of page requested by the user is the fourth type, the processor (220) can identify the expected repurchase time for each of the plurality of products. The processor (220) can adjust the ranking of the plurality of products so that the shorter the time remaining until the expected repurchase time, the higher the ranking. For example, the fourth type of page can be a repurchase candidate product list page. Since the user requests the repurchase candidate product list page to purchase frequently purchased products, there is a high possibility that the user will purchase products whose expected repurchase time is close. Therefore, when the user requests the repurchase candidate product list page, the processor (220) can give a high priority to products whose expected repurchase time is close in the repurchase candidate product set. Through this, the corresponding product can be recommended to the user, thereby inducing the user to purchase the corresponding product.

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. The computer-readable recording medium includes any type of recording device that stores data that can be read by a computer system. Examples of the computer-readable recording medium may include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc. In addition, the computer-readable recording medium can be distributed over 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 embodiments can be easily inferred by programmers in the technical field to which the present disclosure belongs.

Claims (16)

In a method performed by an electronic device,
A step of identifying a purchasing pattern of the user related to a plurality of products included in the set of product candidates for the user's repurchase;
A step of determining, for each of the plurality of products, second information for determining a ranking of the plurality of products based on the first information for each of the plurality of products and the purchase pattern of the user;
A step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products;
A step of determining one or more target products in order of highest ranking among the plurality of products based on the ranking of the plurality of products; and
A method comprising the step of providing third information about said one or more target products to said user.
In the first paragraph,
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 products included in the set of candidate products for repurchase.
In the first paragraph,
A method wherein the first information for each of the plurality of products includes at least one of a category, a stock quantity, a discount rate, or a price for each of the plurality of products.
In the first paragraph,
The step of determining the second information for determining the ranking of the plurality of products based on the first information for each of the plurality of products and the purchase pattern of the user, for each of the plurality of products, is:
A method comprising, for each of the plurality of products, determining at least one of the time remaining until an expected repurchase time, a category, a quantity in stock, a discount rate, or a price as the second information for determining the ranking of the plurality of products.
In paragraph 4,
The step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products is as follows:
A method comprising: a step of determining the ranking of the plurality of products so that a shorter time remaining until the expected repurchase time is given a higher ranking when the time remaining until the expected repurchase time is determined as the second information for each of the plurality of products.
In paragraph 4,
The step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products is as follows:
A method comprising the step of determining the ranking of the plurality of products so that products belonging to the predetermined category have a higher ranking than products not belonging to the predetermined category, when the category is determined as the second information for each of the plurality of products.
In paragraph 4,
The step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products is as follows:
A method comprising: a step of determining the ranking of the plurality of products so that an out-of-stock product has a lower ranking than a non-out-of-stock product when the stock quantity is determined as the second information for each of the plurality of products.
In paragraph 4,
The step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products is as follows:
A method comprising the step of determining the ranking of the plurality of products so that a higher discount rate has a higher ranking when the discount rate is determined as the second information for each of the plurality of products.
In paragraph 4,
The step of determining the ranking of the plurality of products based on the second information determined for each of the plurality of products is as follows:
A method comprising the step of determining the ranking of the plurality of products so that a lower price has a higher ranking when the price is determined as the second information for each of the plurality of products.
In the first paragraph,
A step of removing a product among one or more target products that is determined not to be repurchased by the user;
A step of determining a replacement 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 said alternative product to said user.
In the first paragraph,
Further comprising a step of determining a set of candidate products for the repurchase of the user based on the purchase history of the user;
A method wherein the purchase history of the user includes at least one of the product name, category, purchase date, purchase price, or purchase count of the product purchased by the user.
In Article 11,
Based on the purchase history of the user, the step of determining the set of candidate products for the repurchase of the user is as follows:
A step of identifying whether the product belongs to a predetermined category if the number of purchases of the product purchased by the user within a predetermined period is less than or equal to a predetermined number; and
A method comprising the step of including the product in the set of candidate products for repurchase if the product belongs to the predetermined category.
In Article 12,
Based on the purchase history of the user, the step of determining the set of candidate products for the repurchase of the user is as follows:
If the product does not fall into the predetermined category, identifying a repurchase rate associated with the product; and
A method comprising the step of including the product in the set of candidate products for repurchase if the repurchase rate is greater than a predetermined value.
In Article 11,
Based on the purchase history of the user, the step of determining the set of candidate products for the repurchase of the user is as follows:
A method comprising 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.
In electronic devices,
one or more processors,
comprising one or more memories storing instructions executed by said 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 14.
A non-transitory computer-readable recording medium having recorded thereon instructions that, when executed by one or more processors, cause said one or more processors to perform an operation,
A non-transitory computer-readable recording medium configured to cause the one or more processors to execute a method according to any one of claims 1 to 14.

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