TWI905553B - Method, device, and recording medium for providing product information - Google Patents

Abstract

An embodiment of the present invention, a method for providing product information via an electronic device, may include the following steps: determining a repurchase candidate product set associated with the user based on the user's purchase history; identifying the user's purchase patterns associated with a plurality of products included in the repurchase candidate product set; determining the order of the plurality of products based on the user's purchase patterns; determining one or more products to recommend to the user from the plurality of products in descending order of priority based on the order of priority; and providing the user with information on one or more products.

Description

Methods, devices and recording media for providing product information

This invention relates to a technique for providing product information. More specifically, it relates to a technique for prioritizing products with a higher probability of repurchase in a repurchase waiting list.

With the development of communication technology and changes in the social environment, e-commerce services are providing a wide range of goods and services to users through online platforms. Users can use these platforms to enjoy the convenience of finding and purchasing desired goods and receiving delivery to their desired locations without having to go to physical stores.

However, as e-commerce services continue to expand, products are becoming increasingly diverse. Among these numerous products, users need to spend time and effort to find the products they want, and as a result, users are encountering more and more difficulties in the process of choosing what to buy.

Therefore, the industry needs a technology that can identify the products users frequently purchase and, based on this, prioritize recommending products that users are more likely to buy, thereby avoiding difficulties for users in the process of choosing products.

[The problem that the invention aims to solve]

According to one embodiment of the present invention, the technical challenge is to identify products that users are more likely to repurchase.

According to one embodiment of the present invention, the technical challenge is to recommend products in descending order of user repurchase probability.

The technical problems of this invention are not limited to those mentioned above. Those skilled in the art can clearly understand other unmentioned technical problems based on the description in the patent application. [Technical Means for Solving the Problem]

An embodiment of the present invention, a method for providing product information via an electronic device, may include the following steps: determining a repurchase candidate product set associated with a user based on the user's purchase history; identifying the user's purchase pattern associated with a plurality of products included in the repurchase candidate product set; determining the order of the plurality of products based on the user's purchase pattern; determining one or more products recommended to the user from the plurality of products in descending order of priority based on the order of priority of the plurality of products; and providing the user with information on the one or more products.

In one embodiment, the user's purchase history may include at least one of the following: the name, category, purchase date, purchase price, or number of purchases of the goods purchased by the user; and the user's purchase pattern may include at least one of the following: the number of purchases, purchase frequency, or time elapsed since the last purchase of the goods included in the repurchase waiting list.

In one embodiment, the step of determining the above-mentioned repurchase candidate product set may include the following steps: when the number of times the above-mentioned user purchases the product within a specified time is less than or equal to a predetermined number, identifying whether the category of the above-mentioned product is fresh product; and when the category of the above-mentioned product is fresh product, including the above-mentioned product in the above-mentioned repurchase candidate product set.

In one embodiment, the step of determining the repurchase candidate product set may include the following steps: when the product category is not a new product, identifying the repurchase rate associated with the product; and when the repurchase rate is greater than a predetermined value, including the product in the repurchase candidate product set.

In one embodiment, the repurchase rate may be the ratio of the number of times a plurality of users purchase the aforementioned goods to the number of repurchases.

In one embodiment, the repurchase rate may be the ratio of the number of times a plurality of users purchase goods corresponding to the aforementioned product category to the number of repurchases.

In one embodiment, the step of determining the above-mentioned repurchase candidate product set may include the following steps: when the number of times the above-mentioned user purchases the product within a specified time is greater than the predetermined number of times, the above-mentioned product is included in the above-mentioned repurchase candidate product set.

In one embodiment, the step of determining the above-mentioned repurchase candidate product set may include the following steps: removing products that do not fall within a specific price range from the above-mentioned repurchase candidate product set.

In one embodiment, the step of determining the above-mentioned repurchase candidate product set may include the following steps: removing seasonal products purchased at a specific point in time from the above-mentioned repurchase candidate product set.

In one embodiment, the step of determining the order of the plurality of goods may include the following steps: determining the order of the plurality of goods so that fresh goods have a higher order than other categories of goods.

In one embodiment, the step of determining the order of the plurality of goods may include the following steps: identifying the type of page requested by the user; and determining the order of the plurality of goods based on the user's purchase pattern and the type of page.

In one embodiment, the steps for determining the order of the plurality of goods may include the following steps: when the type of the page is Type 1, identifying the expected repurchase time and discount rate of each of the plurality of goods; and adjusting the order of the plurality of goods in such a way that the shorter the remaining time until the expected repurchase time and the higher the discount rate, the higher the order.

In one embodiment, the step of determining the order of the plurality of goods may include the following steps: when the type of the page is type 2, identifying the discount rate of each of the plurality of goods; and adjusting the order of the plurality of goods so that the higher the discount rate, the higher the order.

In one embodiment, the steps of determining the order of the plurality of goods may include the following steps: when the type of the page is type 3, identifying the price of each of the plurality of goods; and adjusting the order of the plurality of goods so that the lower the price, the higher the order.

In one embodiment, the steps of determining the order of the plurality of goods may include the following steps: when the type of the page is type 3, identifying the size of each of the plurality of goods; and adjusting the order of the plurality of goods so that the smaller the size, the higher the order.

In one embodiment, the steps for determining the order of the plurality of goods may include the following steps: when the type of the page is Type 4, identifying the expected repurchase time of each of the plurality of goods; and adjusting the order of the plurality of goods so that the shorter the remaining time before the expected repurchase time, the higher the order.

In one embodiment, the product information provision method may further include the following steps: removing products determined that the user will not repurchase from the one or more products; determining, based on the order of the plurality of products, a product to replace the removed product; and providing the user with information about the determined product.

In one embodiment, the product information provision method may further include the steps of: receiving from the user a removal request for a specific product among the more than one products; and in response to the removal request, removing the specific product from the more than one products.

An electronic device according to one embodiment of the present invention may include: one or more processors; one or more memory stores commands executed by the one or more processors; when the commands are executed by the one or more processors, the one or more processors constitute a method for executing the present invention.

An embodiment of the present invention, a non-transitory computer-readable recording medium, records commands that, when executed by one or more processors, cause those processors to perform actions. These commands constitute a method for causing the one or more processors to execute the present invention. [Effects of the Invention]

According to one embodiment of the present invention, by identifying products that users are more likely to repurchase, it is possible to prevent the recommendation of products that users are less likely to repurchase.

According to one embodiment of the present invention, by recommending products in descending order of user repurchase probability, users can easily find and purchase the products they need.

The effects of this invention are not limited to those mentioned above. Those skilled in the art can clearly understand other technical issues not mentioned based on the description in the scope of the patent application.

The embodiments of this invention are provided for the purpose of illustrating the technical concept of this invention. The scope of this patent application is not limited to the embodiments presented below or the specific description of such embodiments.

Unless otherwise defined, all technical and scientific terms used in this invention shall have the meanings commonly understood by one of ordinary skill in the art to which this invention pertains. All terms used in this invention have been selected for the purpose of more clearly describing this invention and are not selected to limit the scope of this invention for patent application.

The terms “including,” “having,” and “possessing” used in this invention should be understood as open-ended terms that may include other embodiments, unless otherwise mentioned in the sentences or text containing the corresponding terms.

Unless otherwise stated, the singular expressions described in this invention may contain the meaning of the plural, and this also applies to the singular expressions recorded in the scope of the patent application.

The terms "first" and "second" used in this invention are used to distinguish multiple constituent elements from each other, and do not limit the order or importance of such constituent elements.

As used in this invention, the term "component" refers to software or hardware components such as FPGA (field-programmable gate array) and ASIC (application-specific integrated circuit). However, "component" is not limited to hardware and software. A "component" can be constructed in a manner located on addressable storage media, or it can be constructed by reproducing one or more processors. Thus, as an example, a "component" includes components such as software components, object-oriented software components, class components and task components, processors, functions, properties, programs, sub-constants, code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables. The functions provided by the constituent elements and the "parts" can be combined to form a smaller number of constituent elements and "parts", or they can be further separated into other constituent elements and "parts".

The term "based on" as used in this invention is used to describe one or more factors described in the statement or text containing the term that affect the determination or judgment of an act or action. The term does not exclude other factors that affect the determination or judgment of an act or action.

In this invention, when a constituent element is referred to as being "connected" or "linked" to another constituent element, it should be understood that the aforementioned constituent element can be directly connected or linked to the aforementioned other constituent element, or can be connected or linked to the aforementioned other constituent element through a new or other constituent element as a medium.

The embodiments of the present invention will now be described with reference to the accompanying drawings. In the drawings, identical or corresponding constituent elements are assigned the same reference numerals. Furthermore, in the following description of the embodiments, repeated descriptions of identical or corresponding constituent elements may be omitted. However, even if the description of a constituent element is omitted, it does not mean that such a constituent element is not included in a particular embodiment.

Figure 1 is a diagram showing the environment in which an electronic device 110, an embodiment of the present invention, can be applied.

In one embodiment, electronic device 110 can communicate with a user terminal (120, hereinafter referred to as "terminal") via a network.

In one embodiment, the electronic device 110 may be a server or a different terminal from the terminal 120.

In one embodiment, terminal 120 may be implemented as a terminal capable of sending and receiving various information with electronic device 110 via a network. For example, terminal 120 may be one of a computer, laptop, portable communication terminal (smartphone, etc.), portable multimedia device, wearable device, or HMD (Head Mounted Display). However, the type of terminal 120 is not limited to these, and terminal 120 may be any device including an input/output interface that allows a user to input or output information, and capable of communicating with electronic device 110 or other devices via a network. Terminal 120 can provide users with information received from electronic device 110, and can receive input from users and transmit it to electronic device 110. Input obtained from users can include various forms of input such as mouse clicks, touch controls using a touchpad or touchscreen, voice recognition, and other electronic inputs.

In one embodiment, the network can serve to connect electronic device 110 to terminal 120 or other external devices. For example, the network can provide a connection path that allows terminal 120 to connect to electronic device 110 and send and receive packet data with electronic device 110. The network can 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).

Figure 2 is a block diagram of an electronic device 200 according to one embodiment of the present invention.

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

In one embodiment, the electronic device 200 may include a communication circuit 210, one or more processors 220 and/or one or more memory 230 as constituent elements.

In one embodiment, at least one of the constituent elements of the electronic device 200 may be omitted, or other constituent elements may be added to the electronic device 200.

In one embodiment, some of the constituent elements may be additionally or alternatively integrated to implement, or implemented as a single or multiple entities. In this invention, one or more processors 220 may be referred to as processor 220. Unless otherwise expressly stated herein, the term processor 220 may refer to a collection of one or more processors. In this invention, one or more memory units 230 may be referred to as memory 230. Unless otherwise expressly stated herein, the term memory unit 230 may refer to a collection of one or more memory units.

In one embodiment, at least some of the internal/external components of the electronic device 200 are interconnected via buses, GPIO (General Purpose Input/Output), SPI (Serial Peripheral Interface), or MIPI (Mobile Industry Processor Interface) to transmit and receive information (data, signals, etc.).

In one embodiment, the communication circuit 210 can communicate with a user's terminal and external devices. The communication circuit 210 can enable wireless or wired communication between the electronic device 200 and the terminal. For example, communication circuit 210 can implement 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, NFC (Near Field Communication), and GPS (Global System for Mobile Communications). Wireless communication via methods such as Positioning System (GPS) or GNSS (Global Navigation Satellite System). For example, communication circuit 210 can implement wired communication via methods 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 can also be integrated with other devices. In this case, the communication circuit 210 can function as a connection circuit or interface connecting the electronic device 200 with the corresponding other devices.

In one embodiment, processor 220 can drive software (e.g., commands, programs, etc.) to control at least one component of electronic device 200 connected to processor 220. Furthermore, processor 220 can perform various operations related to the present invention, such as calculations, processing, data generation, and manipulation. Also, processor 220 can load data from memory 230 or store it in memory 230. Moreover, processor 220 can send and receive various information from user terminals and external devices via communication circuit 210.

In one embodiment, processor 220 can control communication circuit 210 to send various information, such as information on various pages, to the user's terminal.

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

In one embodiment, memory 230 may store commands that cause processor 220 to perform calculations during execution by processor 220. Memory 230 may store at least a portion of information received from the user terminal via communication circuit 210 and/or information sent to the user terminal via communication circuit 210. Processor 220 may store at least a portion of information received from the user terminal via communication circuit 210 and/or information sent to the user terminal via communication circuit 210 in memory 230.

The actions performed by the electronic device as described in Figures 3 to 6 below can be understood as being performed by the processor 220 of the electronic device 200 described in Figure 2.

In the configuration diagrams and flowcharts shown in Figures 3 and 6, although the process steps, method steps, and algorithms are described sequentially, these processes, methods, and algorithms can be configured to run in any suitable order. The steps of the processes, methods, and algorithms described in the various embodiments of the present invention do not need to be performed in the order described in the present invention. Furthermore, even if some steps are described as not being performed simultaneously, such some steps can be performed simultaneously in other embodiments. Moreover, the examples of processes described in the figures do not imply the exclusion of other variations and modifications to the illustrated processes, nor do they imply that the illustrated processes or any of their steps are necessary in at least one of the various embodiments of the present invention, nor do they imply that the illustrated processes are superior.

Figure 3 is a diagram illustrating an example of page 300, which shows a recommended buyback waiting list item, according to one embodiment of the present invention.

In one embodiment, 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 items 310 may be N items (N being a natural number) arranged sequentially from the highest order in the user's repurchase candidate item set. For example, one or more items 310 may be displayed on page 300 in descending order. Referring to Figure 3, since "D Banana" has the highest order, it can be displayed first (e.g., at the top left) on page 300. On the other hand, the following describes in detail the method for determining the user's repurchase candidate item set and the method for determining the order of the items included in the repurchase candidate item set, referring to Figures 5 and 6.

In one embodiment, page 300 may display information about each product 310. For example, page 300 may display at least one of the following: name, capacity, quantity per unit, or price of each product 310.

On the other hand, page 300 of Figure 3 is merely an example for illustrating the present invention and is not limited thereto. A portion of the structure of page 300 of Figure 3 may be omitted, or the form of such portion may be changed.

Figure 4 is a diagram illustrating an example of a user interface 400 for displaying buyback waiting list items according to one embodiment of the present invention.

In one embodiment, processor 220 may provide a user interface 400 that displays one or more products 410. Here, the one or more products 410 may be products recommended to the user. For example, user interface 400 may be in the form of an interface toolset. Or, for example, user interface 400 may be displayed as an interface toolset included in a particular page.

In one embodiment, one or more items 410 may be N items (N being a natural number) arranged sequentially from the highest order in the user's repurchase candidate item set. For example, one or more items 410 may be displayed on the user interface 400 in descending order. Referring to Figure 4, since "ABC Milk" has the highest order, it can be displayed first (e.g., on the far left) on the user interface 400. On the other hand, the method for determining the user's repurchase candidate item set and the method for determining the order of the items included in the repurchase candidate item set will be explained below with reference to Figures 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 following: name, capacity, quantity per unit, or price of each product 410.

In one embodiment, user interface 400 may display request interface 420 for requesting a repurchase waitlist page. For example, if the user selects request interface 420, processor 220 may provide the user with a repurchase waitlist page. Here, the repurchase waitlist page may be page 300 of Figure 3.

On the other hand, the user interface 400 in Figure 4 is merely an example to illustrate the present invention and is not limited thereto. A portion of the configuration of the user interface 400 in Figure 4 may be omitted, or the form of such portion may be changed.

Figure 5 is a flowchart illustrating the operation of a product information provision method according to one embodiment of the present invention.

In step S510, processor 220 can determine the repurchase candidate set related to the user based on the user's purchase history.

In one embodiment, a user’s purchase history may include at least one of the following: the name of the goods purchased, the category, the date of purchase, the price of purchase, or the number of purchases.

In one embodiment, processor 220 may determine whether a product is included in the repurchase candidate product set based on the number of times the user has purchased the product. Here, the number of times the user has purchased the product may be the number of purchases within a predetermined period (e.g., 1 year).

In one embodiment, when a user purchases a product more times than a predetermined number of times, the processor 220 may include the product in a buyback candidate product set.

In one embodiment, when the number of times a user purchases a product is less than or equal to a predetermined number, the processor 220 can identify whether the product category purchased by the user is a fresh product. Here, fresh products can refer to products with freshness as an important characteristic, such as food (e.g., fruits, vegetables, meat, seafood, etc.), food products (e.g., bread, dairy products, etc.), and plants (e.g., fresh flowers, etc.).

For example, when the product purchased by the user is a new product, the processor 220 can include the purchased product in the repurchase waiting list. Even if a user has a short history of purchasing new products, there is a high probability that they will repurchase them due to daily needs. Therefore, by including such products in the repurchase waiting list, new products can be displayed to the user as recommended repurchase items.

For example, when the product purchased by a user is not a new product, processor 220 can identify the repurchase rate associated with the product. If the repurchase rate is greater than a predetermined value (e.g., 5%), processor 220 can include the product in the repurchase candidate set. Alternatively, if the repurchase rate is less than or equal to a predetermined value, processor 220 can determine not to include the product in the repurchase candidate set. For example, the repurchase rate could be the ratio of the number of times a plurality of users, including the user, purchase the product to the total number of repurchases. As a concrete example, when a user purchases a "golf ball," the repurchase rate could be the ratio of the number of times a user, including that user, purchases a "golf ball" to the number of repurchases. Alternatively, the repurchase rate could be the ratio of the number of times a user, including that user, purchases a product corresponding to that product category to the number of repurchases. A category refers to a group of products that share specific common attributes. A category can include a superordinate category and subordinate categories belonging to that superordinate category. Products in a superordinate category can be further classified into subordinate categories based on their detailed attributes. As a specific example, when the product purchased by a user is "golf gloves", the repurchase rate can be the ratio of the total number of times that multiple users, including that user, purchase products belonging to "golf supplies" (such as "golf balls", "golf clubs", "golf shoes", etc.) to the total number of repurchases. "Golf supplies" is the category to which "golf gloves" belong. As another concrete example, when a user purchases "golf gloves," the repurchase rate can be the ratio of the total number of times multiple users, including that user, purchase items belonging to the "sports goods" category (e.g., "sports shoes," "towels," etc.) to the total number of repurchases. "Sports goods" is the superior category of "golf goods" to which "golf gloves" belong. Alternatively, the repurchase rate can be the ratio of the number of times multiple users, including that user, purchase items of the same brand as the purchased item to the number of repurchases. As a concrete example, when the brand of the product purchased by a user is "A", the repurchase rate can be the ratio of the total number of times multiple users, including the user, purchase products of brand "A" to the total number of repurchases. In the example above, although multiple users are used as the basis for explanation, the repurchase rate can also be calculated using the current user as the basis.

In one embodiment, processor 220 can remove products that do not fall within a specific price range from the repurchase candidate set. That is, processor 220 can use a set price range as a benchmark to filter out products from the repurchase candidate set that are less likely to be repurchased by the user. As a specific example, the repurchase candidate set includes "Product A" priced at "300,000 KRW", "Product B" priced at "600,000 KRW", and "Product C" priced at "1,200,000 KRW". When the benchmark price range is set to "below 1,000,000 KRW", processor 220 can remove "Product C" from the repurchase candidate set.

In one embodiment, processor 220 may remove seasonal products purchased at a specific point in time from the repurchase waiting list. Here, seasonal products may refer to products that are primarily sold or are popular during specific periods, seasons, anniversaries (programs), etc. Although seasonal products are purchased more frequently during a specific period and are included in the repurchase waiting list, they are not products that users regularly purchase, and therefore the actual likelihood of repurchase may be lower. For this reason, seasonal products may be removed from the repurchase waiting list to prioritize recommending products with a higher likelihood of repurchase to users. As a specific example, the seasonal product "electric fan" is purchased more frequently during the summer and can be included in the repurchase waiting list. However, the processor 220 can consider that the "electric fan" is not a product that is regularly repurchased, determine that the possibility of repurchasing it after the summer is low, and remove it from the repurchase waiting list.

In step S520, processor 220 can identify the purchase patterns of users associated with multiple products included in the buyback waitlist.

In one embodiment, a user's purchase pattern may include at least one of the following: the number of times a product in a buyback waiting list has been purchased, the purchase frequency of that product, or the time elapsed since the last purchase of that product. As an additional embodiment, a user's purchase pattern may further include the type of page requested by the user in order to purchase the product. As described above, a user's purchase pattern is the result of analyzing purchase history and may reflect characteristics, tendencies, or preferences exhibited in the user's purchasing behavior.

In step S530, the processor 220 can determine the order of multiple items included in the repurchase waiting list based on the user's purchase pattern.

In one embodiment, processor 220 can determine the order of multiple items so that the more times they are purchased, the higher their order. For example, in a repurchase candidate set that includes "A" purchased "25 times" and "B" purchased "100 times", processor 220 can assign "B" a higher order than "A".

In one embodiment, processor 220 can determine the order of multiple items so that a higher purchase frequency results in a higher order. For example, in a repurchase waiting list that includes "A" which is "purchased twice a day" and "B" which is "purchased twice a week", processor 220 can assign a higher order to "A" than to "B".

In one embodiment, processor 220 can identify the expected repurchase time of each of a plurality of products and determine the order of the plurality of products so that the shorter the time remaining before the expected repurchase time, the higher the order. That is, products with shorter time remaining before the user repurchases can be given a higher order, thereby prioritizing the recommendation of those products.

For example, processor 220 can generate user profile information based on the user's purchasing patterns. This profile information may include the user's gender, family structure, whether they have pets, age group, or lifestyle (e.g., eating habits). As a specific example, if a user frequently purchases beauty products (e.g., cosmetics), processor 220 can determine that the user's gender is female. As yet another specific example, based on whether the user purchases baby products, women's products, or other products targeting different demographics, processor 220 can identify the user's family structure. As a specific example, based on the frequency of the user's food purchases (e.g., rice), processor 220 can identify the user's family structure. As a specific example, when a user frequently purchases pet supplies, the processor 220 can determine that the user keeps pets. As a specific example, when a user frequently purchases a particular combination of food (e.g., rice and sauces), the processor 220 can identify the user's eating habits.

For example, processor 220 can identify the expected repurchase time of a product based on the user's configuration profile information. Processor 220 can also identify the expected repurchase time of a product based on the purchase cycle of products belonging to the user's age group.

For example, processor 220 can identify the expected repurchase time of the product based on the product's capacity information and the user's configuration file information. Processor 220 can identify the expected repurchase time when the product is consumed based on the average consumption per person and the number of family members of the user.

In one embodiment, processor 220 can determine the order of a plurality of goods so that fresh goods have a higher order than other categories of goods. As a specific example, when the buyback candidate goods set includes fresh goods "A", sporting goods "B", and kitchenware "C", processor 220 can determine the order among "A", "B", and "C" so that fresh goods "A" has a higher order than "B" and "C".

In one embodiment, processor 220 can determine the order of a plurality of items so that sold-out items have a lower order than other items. As a concrete example, when the repurchase waiting list includes "A", "B", and "C", and "C" is sold out, processor 220 can assign the sold-out "C" a lower order than "A" and "B". This avoids recommending sold-out items to the user.

In one embodiment, processor 220 can determine the order of a plurality of items so that higher discount rates have higher order. Here, the discount rate can be expressed as a percentage, which is obtained by subtracting the price actually paid by the user from the original price of the item and then dividing the difference by the original price. As a concrete example, when the buyback waiting list includes "A" with a discount rate of "20%" and "B" with a discount rate of "40%", processor 220 can assign "B" a higher order than "A".

In one embodiment, processor 220 may determine the order of a plurality of products based on their respective categories. For example, processor 220 may identify two or more products belonging to the same category among the plurality of products and determine the order of the plurality of products so that only one of the products is recommended to the user. Here, the category may be a higher-level category or a lower-level category belonging to that higher-level category. As a concrete example, when the buyback candidate set includes "A" and "B" of the same category, "B" may be assigned a lower order so that only "A" is recommended to the user.

In one embodiment, processor 220 may determine the order of multiple items based on the type of page requested by the user to purchase the items. Hereinafter, with reference to FIG6, the method of determining the order based on the type of page will be specifically explained.

In one embodiment, processor 220 may determine the weighting values of one or more items used to determine the order of a plurality of items. Here, the one or more items may include examples described above for determining the order, such as purchase frequency, purchase frequency, expected repurchase time, category, whether sold out, or discount rate. Processor 220 may determine the order of the plurality of items based on the weighting values of these items. As a specific example, the buyback candidate set includes "A" which has been purchased 10 times and has a purchase frequency of 2 times per day, and "B" which has been purchased 30 times and has a purchase frequency of 1 time per day. If the weighted value of the purchase frequency is higher than the purchase frequency, the processor 220 can assign "A" a higher order than "B".

In one embodiment, processor 220 may use an artificial neural network to determine the order of a plurality of items. Here, the artificial neural network may be learned to determine the order of the plurality of items based on at least a portion of the examples described above. For example, the artificial neural network may be learned to determine the order of the plurality of items based on the number of purchases and the purchase frequency. Processor 220 may use the learned artificial neural network to determine the order of the plurality of items. On the other hand, the invention is not limited to artificial neural networks; various types of models, hyperparameters, learning methods, etc., suitable for determining the order of a plurality of items may also be used.

In step S540, the processor 220 can determine one or more products to recommend to the user from among the multiple products in descending order of their order.

For example, processor 220 can determine N (e.g., 20) products to recommend to the user from among a plurality of products, arranged in order from the highest order.

In step S550, processor 220 can provide the user with information on more than one product.

For example, processor 220 may provide a user with a page displaying information about one or more products. Here, the page may be page 300 as illustrated in Figure 3.

For example, processor 220 may provide a user interface that displays information about one or more products. Here, a page may be provided to the user that includes an interface toolset that displays information about one or more products. Here, the user interface (interface toolset) may be the user interface 400 illustrated in Figure 4.

On the other hand, in step S550, the page displaying information on more than one product is provided at the user's request, and may include at least one of the following: home page, fresh product list page, repurchase waiting list page, or shopping cart page.

In one embodiment, processor 220 can remove products determined that the user will not repurchase from one or more products recommended to the user. For example, if the user does not select the product, scrolls the page to hide the product, or does not scroll the page to display the product, processor 220 can determine that the user will not repurchase the product and remove the product determined not to repurchase from one or more products recommended to the user. In this case, processor 220 can determine new products based on the order of multiple products included in the repurchase candidate set, which replace the products determined not to be repurchased and removed. Processor 220 can provide the user with information about the new products.

In one embodiment, processor 220 may receive from a user a removal request for a specific item from one or more products recommended to the user. Here, the removal request may include a request to delete or hide the specific item. In response to the removal request, processor 220 may remove the requested specific item from one or more products recommended to the user. As an additional embodiment, processor 220 may provide the user with information indicating that the removal of the specific item has been completed.

Figure 6 is a flowchart illustrating the detailed actions of determining the order of repurchase of candidate products in the product information provision method of one embodiment of the present invention.

Step S600 in Figure 6 is a detailed action of step S530 described in Figure 5, which determines the order of the multiple items included in the repurchase candidate product set.

In one embodiment, step S600 can be performed when a user requests a page for purchasing goods. That is, when a user requests a page for purchasing goods, the order of repurchased standby goods can be redefined or the existing order can be adjusted.

In step S610, the processor 220 can identify the type of page requested by the user. Users can request various pages during the purchase process. For example, a user can request: a homepage displaying various products, promotions, events, etc.; a new product list page displaying new products; a repurchase waiting list page displaying recommended repurchase items; or a shopping cart page displaying items added to the shopping cart, etc.

In step S620, the processor 220 can determine the order of multiple items included in the repurchase candidate set based on the type of page requested by the user.

In one embodiment, when the user requests a page of type 1, the processor 220 can identify the expected repurchase time and discount rate for each of several products. See Figure 5 for an explanation of the expected repurchase time and discount rate. The processor 220 can adjust the order of the several products as follows: the shorter the time remaining until the expected repurchase time and the higher the discount rate, the higher the order. For example, a type 1 page could be the homepage. Although the user would not request the homepage to purchase repurchase waiting list items, they might be interested in products that are close to their expected repurchase time and have a larger discount rate. Therefore, when the user requests the homepage, the processor 220 can assign a higher order to such products. This allows you to recommend the product to users and guide them to purchase it.

In one embodiment, when the user requests a page of type 2, the processor 220 can identify the discount rates of multiple products. An explanation of the discount rates can be found in Figure 5. The processor 220 can adjust the order of the multiple products so that higher discount rates are assigned a higher order. For example, a type 2 page could be a fresh produce list page. Since the user requests the fresh produce list page to purchase fresh produce, a higher discount rate increases the likelihood of purchasing that product. Therefore, when a user requests a fresh produce list page, the processor 220 can assign a higher order to fresh produce with higher discount rates from the buyback waiting list. This allows you to recommend the product to users and guide them to purchase it.

In one embodiment, when the user requests a page of type 3, the processor 220 can identify the prices of multiple items. The processor 220 can adjust the order of the multiple items so that lower-priced items have a higher priority. For example, a type 3 page could be a shopping cart page. Since the user requests the shopping cart page to purchase items added to the shopping cart, items with a higher probability of being purchased together with items already added to the cart can be lower-priced items. Therefore, when the user requests the shopping cart page, the processor 220 can assign a higher priority to lower-priced items in the repurchase waiting list. This allows the processor to recommend the product to the user, thereby guiding them to purchase it. As an additional or alternative implementation, when the user requests a type 3 page, the processor 220 can identify the size of each of the multiple products. Since the user requests the shopping cart page to purchase items added to their cart, smaller items are more likely to be purchased along with items already added to the cart. Therefore, when the user requests the shopping cart page, the processor 220 can prioritize smaller items in the repurchase waiting list. This allows the processor to recommend the product to the user, thereby guiding them to purchase it.

In one embodiment, when the user requests a page of type 4, the processor 220 can identify the estimated repurchase time for each of a plurality of products. The processor 220 can adjust the order of the plurality of products so that the shorter the time remaining before the estimated repurchase time, the higher the order. For example, a type 4 page could be a repurchase waiting list page. Since the user requests a repurchase waiting list page to purchase frequently purchased products, there is a higher probability that the user will purchase products closer to the estimated repurchase time. Therefore, when a user requests a repurchase waitlist page, the processor 220 can prioritize items closer to their expected repurchase date within the waitlist. This allows the processor to recommend the item to the user and guide them to purchase it.

Although the above method has been described with reference to specific embodiments, it can also be implemented in the form of computer-readable code on a computer-readable recording medium. A computer-readable recording medium can include all types of recording devices storing data that can be read by a computer system. Examples of computer-readable recording media include ROM (Read-only memory), RAM (Random-access memory), CD-ROM (Compact Disc Read-Only Memory), magnetic tape, floppy disks, optical information storage devices, etc. Furthermore, the computer-readable recording medium is distributed across a computer system connected to a network, thereby enabling distributed storage and execution of computer-readable recording code. Furthermore, programmers in the technical field to which this invention pertains can easily deduce the functional programs, code, and code segments used to implement the above embodiments.

110: Electronic Device 120: User Terminal 200: Electronic Device 210: Communication Circuit 220: Processor 230: Memory 300: Page 310: Product 400: User Interface 410: Product 420: Request Interface S510: Steps S520: Steps S530: Steps S540: Steps S550: Steps S600: Steps S610: Steps S620: Steps

Figure 1 is a diagram illustrating the environment of an electronic device to which one embodiment of the present invention can be applied. Figure 2 is a block diagram of the electronic device according to one embodiment of the present invention. Figure 3 is a diagram illustrating an example of a page recommending repurchase waiting list items according to one embodiment of the present invention. Figure 4 is a diagram illustrating an example of a user interface displaying repurchase waiting list items according to one embodiment of the present invention. Figure 5 is a flowchart illustrating the operation of a product information provision method according to one embodiment of the present invention. Figure 6 is a flowchart illustrating the detailed operations of determining the order of repurchase waiting list items in the product information provision method according to one embodiment of the present invention.

110: Electronic Devices

120: User Terminal

Claims (19)

A method for providing product information, implemented via an electronic device, includes the following steps: determining a repurchase waiting list of products associated with a user based on the user's purchase history; identifying the user's purchase patterns associated with a plurality of products included in the repurchase waiting list; determining the order of the plurality of products based on the user's purchase patterns; determining one or more products to recommend to the user from the plurality of products in descending order of preference based on the order of preference; and providing the user with first information about the one or more products; wherein the step of determining the order of the plurality of products includes : Identify the type of the product list page requested by the user, wherein the type of the product list page indicates the product list to be displayed among the plurality of different product lists on the product list page; based on the user's purchasing pattern and the identified type of the product list page, identify at least one of the remaining time, discount rate, price, or size of each of the plurality of products included in the repurchase waitlist as second information for adjusting the order of the plurality of products; and adjust the order of the plurality of products based on the second information identified for each of the plurality of products. As in the product information provision method of Request Item 1, the user's purchase history includes at least one of the following: product name, category, purchase date, purchase price, or number of purchases of the products purchased by the user; and the user's purchase pattern includes at least one of the following: number of purchases, purchase frequency, or time elapsed since the last purchase of the products included in the repurchase waiting list. As in the product information provision method of claim 1, the step of determining the above-mentioned repurchase candidate product set includes the following steps: when the number of times the above-mentioned user purchases the product within a specified time is less than or equal to a predetermined number, identify whether the category of the above-mentioned product is a new product; and when the category of the above-mentioned product is a new product, include the above-mentioned product in the above-mentioned repurchase candidate product set. As in the product information provision method of claim 3, the step of determining the above-mentioned repurchase candidate product set includes the following steps: when the above-mentioned product category is not a new product, identifying the repurchase rate associated with the above-mentioned product; and when the above-mentioned repurchase rate is greater than a predetermined value, including the above-mentioned product in the above-mentioned repurchase candidate product set. As in the product information provision method of Request 4, the repurchase rate mentioned above is the ratio of the number of times a plurality of users purchase the above product to the number of repurchases. As in the product information provision method of Request 4, the repurchase rate is the ratio of the number of times a plurality of users purchase products corresponding to the above product category to the number of repurchases. As in the product information provision method of Request 1, the step of determining the above-mentioned repurchase candidate product set includes the following steps: when the number of times the above-mentioned user purchases the product within a specified time is greater than the pre-determined number of times, the above-mentioned product is included in the above-mentioned repurchase candidate product set. As in the product information provision method of Request 1, the step of determining the above-mentioned repurchase candidate product set includes the following steps: removing products that do not fall within a specific price range from the above-mentioned repurchase candidate product set. As in the product information provision method of Request 1, the step of determining the above-mentioned repurchase candidate product set includes the following steps: removing seasonal products purchased at a specific point in time from the above-mentioned repurchase candidate product set. As in the product information provision method of claim 1, the step of determining the order of the plurality of products includes the following steps: determining the order of the plurality of products so that fresh products have a higher order than other categories of products. As in the product information provision method of claim 1, the step of identifying at least one of the following for each of the plurality of products included in the repurchase waitlist—the remaining time before the expected repurchase time, the discount rate, the price, or the size—as the second information for adjusting the order of the plurality of products, based on the user's purchase pattern and the type of the identified product list page, includes the following steps: based on the user's purchase pattern and the type of the identified product list page... The first type of the first product list, which displays one or more products displayed together with promotions or events, identifies the expected repurchase time and the discount rate for each of the plurality of products; and the step of adjusting the order of the plurality of products based on the second information identified for each of the plurality of products includes adjusting the order of the plurality of products in such a way that the shorter the remaining time before the expected repurchase time and the higher the discount rate, the higher the order. As in the product information provision method of claim 1, the step of identifying at least one of the following for each of the plurality of products included in the repurchase waitlist—the remaining time before the expected repurchase time, the discount rate, the price, or the size—as the second information for adjusting the order of the plurality of products, based on the user's purchase pattern and the type of the identified product list page, includes the following steps: The user's purchase pattern and the type of the product list page are a second type that displays a second product list including one or more fresh products, and identify the discount rate of each of the plurality of products; and the step of adjusting the order of the plurality of products based on the second information identified for each of the plurality of products includes: adjusting the order of the plurality of products so that the higher the discount rate, the higher the order. As in the product information provision method of claim 1, the step of identifying at least one of the following for each of the plurality of products included in the repurchase waitlist—the remaining time before the expected repurchase time, the discount rate, the price, or the size—as the second information for adjusting the order of the plurality of products, based on the user's purchase pattern and the type of the identified product list page, includes the following steps: The user's purchase pattern and the type of the aforementioned product list page are a third type that displays a third product list including one or more items added to the user's shopping cart, and identifies the aforementioned prices of each of the aforementioned plurality of products; and the step of adjusting the order of the aforementioned plurality of products based on the aforementioned second information identified for each of the aforementioned plurality of products includes: adjusting the order of the aforementioned plurality of products so that the lower the price, the higher the order. As in the product information provision method of claim 1, the step of identifying at least one of the following for each of the plurality of products included in the repurchase waitlist—the remaining time before the expected repurchase time, the discount rate, the price, or the size—as the second information for adjusting the order of the plurality of products, based on the user's purchase pattern and the type of the identified product list page, includes the following steps: The user's purchase pattern and the type of the aforementioned product list page are a third type that displays a third product list including one or more items added to the user's shopping cart, and identify the aforementioned size of each of the aforementioned plurality of products; and the step of adjusting the order of the aforementioned plurality of products based on the aforementioned second information identified for each of the aforementioned plurality of products includes: adjusting the order of the aforementioned plurality of products so that the smaller the size, the higher the order. As in the product information provision method of claim 1, the step of identifying at least one of the following for each of the plurality of products included in the repurchase waitlist, based on the user's purchase pattern and the type of the identified product list page, as the second information for adjusting the order of the plurality of products, includes the following steps: based on the user's purchase pattern and the type of the identified product list page, the remaining time before the expected repurchase time, the discount rate, the price, or the size. The single-page type is a fourth type that displays a fourth product list including at least one of the aforementioned plurality of products contained in the aforementioned repurchase candidate product set, identifies the aforementioned expected repurchase time for each of the plurality of products; and the step of adjusting the order of the plurality of products based on the aforementioned second information identified for each of the plurality of products includes: adjusting the order of the plurality of products such that the shorter the remaining time before the aforementioned expected repurchase time, the higher the order. The product information provision method of claim 1 further includes the following steps: removing products determined that the user will not repurchase from the above one or more products; determining, based on the order of the above plurality of products, a product to replace the removed product; and providing the user with information on the determined product. The product information provision method of claim 1 further includes the following steps: receiving a removal request from the user for a specific product among the one or more products; and in response to the removal request, removing the specific product from the one or more products. An electronic device includes: one or more processors; one or more memory stores commands executed by the one or more processors; and when the commands are executed by the one or more processors, the one or more processors are configured to perform a method as described in any one of claims 1 to 17. A non-transitory computer-readable recording medium that records commands that, when executed by one or more processors, cause the one or more processors to perform actions, the commands constituting a method for causing the one or more processors to perform any of the claims 1 to 17.