KR20240043028A - Method for use public big data to provide product recommendations for unmanned stores for companion animals - Google Patents

Abstract

A method of providing product recommendations for an unmanned pet product store using public big data according to an embodiment of the present invention, comprising: (A) receiving buyer information and pet information for each region from a public institution server; (B) considering the buyer information and pet information, recommending a plurality of products judged to be in high demand in the area where the store to recommend products is located to the manager terminal of the unmanned store; (C) after the recommended product is supplied to the unmanned store, collecting product sales status for a predetermined period from a manager terminal of the unmanned store; and (D) adjusting the type or number of the plurality of products determined to be in high demand by assigning weights according to the sales performance of each recommended product within the product sales status and re-recommending them to the manager terminal. ;, the pet information includes the total number of pets in each region, the number of each type of pet, the average age of the pet, gender, and statistics on the pet's disease, and the buyer information includes the buyer's age, Includes gender.

Description

How to provide product recommendations for unmanned pet supply stores using public big data {METHOD FOR USE PUBLIC BIG DATA TO PROVIDE PRODUCT RECOMMENDATIONS FOR UNMANNED STORES FOR COMPANION ANIMALS}

The present invention relates to a method of providing product recommendations for unmanned pet supply stores by utilizing public big data. More specifically, the present invention relates to a method of receiving buyer information and pet information by region from a public institution server, and actually providing unmanned pet product recommendations. This is about how to analyze products sold in stores and recommend products with high sales volume and preference in pet supply stores that match regional characteristics.

According to the Korea Rural Economic Institute, the size of the domestic pet market in 2020 has grown to around 3.4 trillion won. This is an increase of approximately 79% compared to 1.9 trillion won in 2015. The Korea Rural Economic Institute predicted that the market will expand to 6 trillion won in 2027. And according to the Korean Pet Report published by a management research institute, the domestic pet population in 2021 was calculated to be approximately 14.48 million (6.04 million households).

As the size of the pet market increases, the pet products market is also growing, and the number of sales stores is also increasing. However, because the fixed cost of operating a store is high through labor costs, there are many pet supply stores that operate unmanned. In the case of unmanned stores, since they do not handle product sales individually, the identification of products preferred by customers may be delayed or insufficient compared to manned stores. In addition, the age and gender of buyers are different depending on the region, and the type, age, gender, disease, and total number of pets are also different.

Accordingly, there is a need for a method of providing product recommendations that recommends products with high customer preference and sales rates according to regional characteristics based on buyer information and companion animal information.

The present invention is intended to solve the problems of the prior art described above, and its purpose is to recommend products with high demand from buyers among pet products by utilizing public big data.

As a technical means for achieving the above-described technical problem, in a method of providing product recommendations for an unmanned pet supply store using public big data according to an embodiment of the present invention, (A) buyer information for each region and Receiving companion animal information from a public institution server; (B) considering the buyer information and pet information, recommending a plurality of products judged to be in high demand in the area where the store to recommend products is located to the manager terminal of the unmanned store; (C) after the recommended product is supplied to the unmanned store, collecting product sales status for a predetermined period from a manager terminal of the unmanned store; and (D) adjusting the type or number of the plurality of products determined to be in high demand by assigning weights according to the sales performance of each recommended product within the product sales status and re-recommending them to the manager terminal. ;, the pet information includes the total number of pets in each region, the number of each type of pet, the average age of the pet, gender, and statistics on the pet's disease, and the buyer information includes the buyer's age, Includes gender.

In addition, step (B) recommends pet products for the most commonly occurring diseases based on pet disease statistics, recommends the most preferred products based on the pet's breed and age, or recommends to the buyer We recommend the most preferred products considering your age and gender.

In addition, in step (C), after the product (C-1) is received in the unmanned store, product identification information, price information, display location information, and expiration date information for the received product are received from the unmanned store manager terminal. steps; (c-2) receiving product identification information for sold products from the unmanned store manager terminal; and (C-3) comparing received product information and sold product information over a predetermined period of time, calculating inventory depletion speed information for each product, and storing the product sales status.

In addition, step (C-3) includes calculating inventory depletion speed information for each product; Calculating a net profit margin for each product during a predetermined period in consideration of the inventory depletion speed information; and listing the ranking of net profit margins for each product during a predetermined period.

In addition, the step (D) compares the ranking of the net profit margin for each product with the plurality of products recommended in the step (B), and applies weights to each recommended product differently for each product, thereby reorganizing the product. When recommending, the type or number of previously recommended products is changed or a new product is recommended.

In addition, for the unmanned store, store operation information including operating hours of the unmanned store, ranking of products with a high purchase rate, repeat visit rate by regular customers, and customer unit price for each product is collected.

In addition, based on the collected store operation information, products that are selling well in other stores are monitored, products that are selling well that are not in stock in a specific store are found, and the products are recommended to the manager terminal of the specific store.

In addition, based on statistics collected from the unmanned store, the time period with the highest sales is extracted and provided to the unmanned store manager terminal.

In addition, the step (D) provides additional feedback information to change the display location of the recommended product in consideration of the sales performance of the recommended product, and the display location is a plurality of locations located in the store. Among the display shelves, it includes identification information on the display shelf and the location of the floor in the display shelf consisting of multiple layers.

An apparatus for providing product recommendations for an unmanned pet product store using public big data, comprising: a memory for storing a program on a method for providing product recommendations for an unmanned pet product store; and a processor for executing the program, the method comprising: (A) receiving purchaser information and companion animal information for each region from a public institution server; (B) considering the buyer information and pet information, recommending a plurality of products judged to be in high demand in the area where the store to recommend products is located to the manager terminal of the unmanned store; (C) after the recommended product is supplied to the unmanned store, collecting product sales status for a predetermined period from a manager terminal of the unmanned store; and (D) adjusting the type or number of the plurality of products determined to be in high demand by assigning weights according to the sales performance of each recommended product within the product sales status and re-recommending them to the manager terminal. ;, the pet information includes the total number of pets in each region, the number of each type of pet, the average age of the pet, gender, and statistics on the pet's disease, and the buyer information includes the buyer's age, Includes gender.

The present invention is a method of receiving public big data about a region from a public institution server, analyzing information on products sold in stores, and recommending products with a high buyer preference and purchase rate by region among various pet products. It can be provided.

Figure 1 is a structural diagram of a method for providing product recommendations in an unmanned pet supply store using public big data according to an embodiment of the present invention.
Figure 2 is a structural diagram of a product recommendation system for providing product recommendations for an unmanned pet product store using public big data according to an embodiment of the present invention.
Figure 3 is a flowchart showing the entire process of a method for providing product recommendations for an unmanned pet supply store using public big data according to an embodiment of the present invention.
Figure 4 is a flowchart showing the process of collecting product sales status in a method of providing product recommendations at an unmanned pet product store using public big data according to an embodiment of the present invention.
Figure 5 is a structural diagram of a method for recommending product display locations in an unmanned store according to an additional embodiment of the present invention.
Figure 6 is a structural diagram of a server for a product display location recommendation method in an unmanned store according to an additional embodiment of the present invention.
Figure 7 is a flowchart showing the process of a product display location recommendation method in an unmanned store according to an additional embodiment of the present invention.
Figure 8 is an exemplary diagram showing a time barcode according to an additional embodiment of the present invention.
Figure 9 is a table for changing the display position of products in the product display position recommendation method of an unmanned store according to an additional embodiment of the present invention.
Figure 10 is an exemplary diagram showing the location of store shelves in the method of recommending product display positions in an unmanned store according to an additional embodiment of the present invention.
Figure 11 is an example diagram showing recommended product positions on a shelf in a method of recommending product display positions in an unmanned store according to an additional embodiment of the present invention.

Below, with reference to the attached drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts that are not related to the description are omitted, and similar parts are given similar reference numerals throughout the specification.

Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case where it is "directly connected," but also the case where it is "electrically connected" with another element in between. . Additionally, when a part "includes" a certain component, this means that it may further include other components rather than excluding other components, unless specifically stated to the contrary.

In this specification, 'part' includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Additionally, one unit may be realized using two or more pieces of hardware, and two or more units may be realized using one piece of hardware. Meanwhile, '~ part' is not limited to software or hardware, and '~ part' may be configured to reside in an addressable storage medium or may be configured to reproduce one or more processors. Therefore, as an example, '~ part' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and 'parts' may be combined into a smaller number of components and 'parts' or may be further separated into additional components and 'parts'. Additionally, components and 'parts' may be implemented to regenerate one or more CPUs within a device or a secure multimedia card.

The “user terminal” mentioned below may be implemented as a computer or portable terminal that can connect to a server or other terminal through a network. Here, the computer is, for example, a laptop equipped with a web browser, a desktop, a laptop, a VR HMD (e.g., HTC VIVE, Oculus Rift, GearVR, DayDream, PSVR, etc.), etc. may include. Here, VR HMD is for PC (e.g. HTC VIVE, Oculus Rift, FOVE, Deepon, etc.), mobile (e.g. GearVR, DayDream, Storm Magic, Google Cardboard, etc.), and console (PSVR). Includes independently implemented Stand Alone models (e.g. Deepon, PICO, etc.). Portable terminals are, for example, wireless communication devices that ensure portability and mobility, including smart phones, tablet PCs, and wearable devices, as well as Bluetooth (BLE, Bluetooth Low Energy), NFC, RFID, and ultrasonic devices. , may include various devices equipped with communication modules such as infrared, WiFi, and LiFi. In addition, “network” refers to a connection structure that allows information exchange between nodes such as terminals and servers, including a local area network (LAN), a wide area network (WAN), and the Internet. (WWW: World Wide Web), wired and wireless data communication network, telephone network, wired and wireless television communication network, etc. Examples of wireless data communication networks include 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), Wi-Fi, Bluetooth communication, infrared communication, and ultrasound. This includes, but is not limited to, communication, Visible Light Communication (VLC), LiFi, etc.

<Example of product recommendation using public institution big data>

First, with reference to Figure 1, the structure of a method for providing product recommendations in an unmanned pet supply store using public big data according to an embodiment of the present invention will be described.

Referring to Figure 1, a method of providing product recommendations for an unmanned pet product store using public big data may include a product recommendation system 100, a public institution server 200, and a manager terminal 300.

Hereinafter, the structure of a product recommendation system according to an embodiment of the present invention will be described with reference to FIG. 2.

Referring to FIG. 2, the product recommendation system 100 includes a memory 101, a processor 102, and a communication module 103.

The memory 101 stores at least one of information and data input to the communication module 103, information and data required for functions performed by the processor 102, and data generated according to execution of the processor 102. You can. Memory 101 should be interpreted as a general term for non-volatile storage devices that continue to retain stored information even when power is not supplied and volatile storage devices that require power to maintain stored information. Additionally, the memory 101 may perform the function of temporarily or permanently storing data processed by the processor 102. The memory 101 may include magnetic storage media or flash storage media in addition to volatile storage devices that require power to maintain stored information, but the scope of the present invention is not limited thereto. no.

The memory 101 stores the product recommendation program, and links buyer information and companion animal information for each region received from the public institution server 200 through the processor 102 to the program. The name of the program is set for convenience of explanation, and the name itself does not limit the function of the program.

The processor 102 is configured to execute a program stored in the memory 101. The processor 102 may include various types of devices that control and process data. The processor 102 may refer to a data processing device built into hardware that has a physically structured circuit to perform functions expressed by codes or instructions included in a program. In one example, the processor 102 may include a microprocessor, central processing unit (CPU), processor core, multiprocessor, application-specific integrated circuit (ASIC), or FPGA ( It may be implemented in the form of a field programmable gate array, etc., but the scope of the present invention is not limited thereto.

The processor 102 is configured to perform detailed processes of a method for providing product recommendations for an unmanned pet supply store using public big data, as described below.

The communication module 103 can transmit and receive information with an external database or external device. Here, the external device may be an administrator terminal 300 or a public institution server 200. The communication module 103 may include a device including hardware and software necessary to transmit and receive signals such as control signals or data signals through wired or wireless connections with other network devices.

The communication module 103 transmits the product recommendation program stored in the memory 101 provided by the processor 102 of the product recommendation system 100 to an external database or external device so that it can be linked.

The public institution server 200 is a server that stores buyer information and companion animal information for each region. Buyer information may include the buyer's age and gender, and pet information may include the total number of pets in each region, the number by type, the average age of the pet, gender, and the pet's disease.

The manager terminal 300 inputs product identification information, price information, display location information, and expiration date information of products displayed in the unmanned store and transmits them to the product recommendation system 100. Then, product identification information for sold products among the displayed products is transmitted to the product recommendation system 100.

Hereinafter, with reference to FIG. 3, the entire process of providing product recommendations for an unmanned pet supply store using public big data according to an embodiment of the present invention will be described in detail.

First, buyer information and companion animal information for each region are received from the public institution server (200) (S310). Purchaser information and companion animal information for each region held by the public institution server 200 shall be replaced with the description of the public institution server 200 in FIG. 1 above.

Next, considering buyer information and pet information, products judged to be in high demand in the area where the store is located are recommended to the manager terminal 300 (S320).

At this time, based on pet disease statistics, pet products for the most common diseases are recommended, the most preferred products are recommended based on the pet's breed and age, or the purchaser's age and gender are considered. This allows you to recommend the most preferred product.

For example, if the area where the store is located has a large number of dogs that are raised outside and engage in agility activities compared to other areas, products such as props for outdoor activities or pest repellent can be recommended. Alternatively, if there are many more dogs than cats in the area where the store is located, allergy food and skin disease care products can be recommended because inventory of allergy food and skin disease care products is sold out quickly due to the number of dog breeds that are relatively more prone to skin diseases than cats.

And after the recommended product is supplied to the unmanned store, product sales status for a predetermined period is collected from the manager terminal 300 (S330). The S330 process will be described with reference to FIG. 4 below.

Referring to FIG. 4 below, it is a flowchart showing the process of collecting product sales status in a method of providing product recommendations at an unmanned pet supply store using public big data according to an embodiment of the present invention.

First, after the product is stocked in the unmanned store, product identification information, price information, display location information, and expiration date information about the stocked product are received from the manager terminal 300 (S331). The manager terminal 300 receives the product when the product is stocked. Once done, the product name, product identification information including product size and inventory, product price, expiration date, and current display location information are entered and transmitted to the product recommendation system 100.

Next, product identification information for the sold product is received from the unmanned store manager terminal 300 (S332). When the product is sold, the product identification information for the sold product is transmitted. At this time, since the product identification information includes the product name, size, and inventory, and is also stored in matching price, expiration date, and current display location, only the product identification information of the sold product is transmitted and any changes to the product are recorded. Details can be updated.

Then, for a given period of time, the received product information and the sold product information are compared, the inventory depletion speed information for each product is calculated, and the product sales status is stored (S333) through the product identification information of the sold product transmitted in the S332 process. Compare product information received and product information sold during a given period to calculate inventory depletion speed information for each product. Considering the calculated inventory depletion speed information, calculate the net profit rate for each product during a predetermined period. Calculate the calculated predetermined period. You can store the sales status of individual products by listing the net profit margin rankings for each product.

Next, weights are assigned according to the sales performance of each product recommended within the product sales status (S340). Then, according to the weight, the types or number of products judged to be in high demand are adjusted and re-recommended to the manager terminal 300 (S350). By comparing the ranking of the net profit rate for each product calculated in the S330 process with the multiple products recommended in the S320 process, the weight for each recommended product is applied differently to each product, so that when re-recommending a product, the previously recommended product is changed. You can change the type or quantity or recommend new products. Additionally, in consideration of the sales performance of the recommended product, feedback information to change the display position of the recommended product can be additionally provided. At this time, the display location may include identification information of a display stand among a plurality of display shelves located in the store and a floor location on a display shelf composed of multiple layers.

The product recommendation system 100 according to an additional embodiment of the present invention can collect store operation information including the operating hours of the unmanned store, ranking of products with a high purchase rate, repeat visit rate of regular customers, and purchaser unit price for each product. .

Based on the store operation information collected according to an additional embodiment of the present invention, monitor products that are selling well in other stores, find products that are not in stock in a specific store among the products that are selling well, and use the manager terminal of the specific store ( 300), you can recommend a product.

Based on statistics collected from the unmanned store according to an additional embodiment of the present invention, the time period with the highest sales can be extracted and provided to the unmanned store manager terminal 300.

<Example of product display location recommendation in unmanned stores>

Hereinafter, with reference to FIG. 5, the structure of the method for recommending product display positions in an unmanned store according to an additional embodiment of the present invention will be described.

Referring to FIG. 5, the method of recommending product display locations in an unmanned store may include a barcode scanner 400 for managers, a server 500, a manager terminal 300, and a kiosk 600. Here, the server 500 may refer to the same configuration as the product recommendation system 100 of FIG. 1 described above.

The barcode scanner 400 for managers can extract product identification information, price information, and expiration date by recognizing barcodes and expiration date information identification stickers of products arriving at unmanned stores.

The manager terminal 300 can receive the product identification information, price information, and expiration date extracted by the manager barcode scanner 400 and transmit them to the server 500. Additionally, product display location information can be entered manually or images taken of displayed products can be transmitted to the server 500.

The kiosk 600 allows customers to directly check out the products on display. The kiosk 600 has a barcode scanner installed in one area of the kiosk 600, and when a customer scans the barcode of a product into the barcode scanner, the amount is calculated and payment can be made using the customer's payment method.

Hereinafter, the structure of a server according to an additional embodiment of the present invention will be described with reference to FIG. 6.

The processor 520 of the server 500 is configured to perform the detailed processes of the method for recommending product display locations in an unmanned store as described below.

The communication module 530 of the server 500 can transmit and receive information with an external database or external device. Here, the external device may be the manager terminal 300. The communication module 530 may include a device including hardware and software necessary to transmit and receive signals such as control signals or data signals through wired or wireless connections with other network devices.

The communication module 530 transmits the product display location recommendation program stored in the memory 510 provided by the processor 520 of the server 500 to an external database or external device so that it can be linked.

Hereinafter, with reference to FIG. 7, the process of the product display location recommendation method in an unmanned store according to an additional embodiment of the present invention will be described in detail.

First, product identification information, product price, and expiration date are received from the manager terminal 300 (S410).

The server 500 extracts product identification information and price information by having a barcode scanner recognize the barcode of the product from the in-store manager terminal 300, and recognizes the expiration date information identification sticker to extract the expiration date, product identification information, and price information. and expiration date.

A time barcode for product identification information, price information, and expiration date information identification sticker according to an additional embodiment of the present invention will be described below with reference to FIG. 8.

Referring to Figure 8, a time barcode is a barcode that additionally includes expiration date information to an existing barcode. Therefore, it can be configured by adding 5 digits of expiration date information to the existing barcode including the country of origin (country) code, manufacturer code, and product code.

Next, display location information about the location where the product is displayed is received from the manager terminal 300, and the product identification information and product inventory information are matched and stored (S420).

The server 500 receives display location information manually entered by the manager or images taken of displayed products from the in-store manager terminal 300, and provides identification information, size, and display location information of products included in the received images. can be extracted. At this time, the display location information may include display stand identification information, shelf layer information within the display stand, and display coordinate information within the shelf layer.

And for each product, the server 500 has a pre-built DB in which images taken in various directions of the product, the size of the product and product identification information are matched and stored, and after receiving the image from the manager terminal 300, After identifying the shelf identification information and the areas of a plurality of objects, comparing the images in the area of each object with the images in the DB, identify which product is located in the object area and what its size value is, and identify the product located in the object area and what the size value is. By matching the displayed display location information value with the identification information of the identified product, the display location information of each product can be stored.

Additionally, when the display location information has a value known in advance, the display location information is pre-stored in the server 500, and the store manager can display products according to the pre-stored display location information.

Next, sales performance for each product is received from the manager terminal 500 for a preset period (S430).

The sales performance for a preset period that the server 500 receives from the manager terminal 300 may include information on customers purchasing the product. At this time, the customer's information is based on customer information already entered by the customer purchasing the product by the manager terminal 300 or information extracted by the store's camera, such as the customer's gender, age, frequently purchased products, and customer's moving information. can be collected. For example, information on the gender and age of the purchasing customer for each product purchased is based on the customer information including the purchased product information, payment card information, and previously entered gender and age entered by the customer through the unmanned kiosk 600. Based on this, you can collect information about frequently purchased products. And through the store's camera, information on the customer's visit frequency, the gender of the main customer, and the time of the customer's visit to the kitchen can be collected.

Next, based on the sales performance and expiration date information for each product, the changed display location of the product is transmitted to the manager terminal 300 to recommend a change in display location (S440).

Hereinafter, with reference to FIGS. 9 to 11, the recommendation to change the display position of a product in the product display position recommendation method of an unmanned store according to an additional embodiment of the present invention will be described.

Figure 9 is a table listing information about sold products and their current locations and recommended locations, and Figure 10 is a plan view showing the locations of store shelves. Additionally, Figure 11 is an example diagram showing the recommended position of a product on a display shelf.

Referring to Figure 9, product information including sales performance collected in the S430 process and inventory and expiration date information of currently remaining products can be confirmed through a table.

For example, product A has ‘low’ brand awareness, has an expiration date of ‘more than a year’ left, and has ‘60 units’ in stock. Additionally, since the average monthly sales volume is ‘10 units’, it can be recommended from the current location ‘C-4’ to ‘C-1’. In addition, product B has 'high' brand awareness, has an expiration date of 'more than 1 year' left, has '25 units' in stock, and an average monthly sales volume of '15 units', so it moves from its current location 'C-1' to ' C-4' can be recommended. Product C has ‘low’ brand awareness, has an expiration date of ‘less than 6 months’, and has ‘80 units’ in stock. Since the average monthly sales volume is ‘10 units’, the location as ‘U-2’ can be recommended.

Referring to Figure 10 below, it can be seen that among the positions of the store's display shelves, 'Shelf U' is located closest to the entrance door. Therefore, it is recommended that Product C, which has the shortest expiration date remaining, be moved to the second tier of the shelf closest to the entrance so that it can be easily seen by customers, thereby improving sales performance.

Referring to FIG. 11 below, the structure of the display stand and product location can be confirmed. In Figure 11, to the left of C-4 and C-1 are the current positions of products A and B. In FIG. 9, the recommended positions of products A and B are C-1 and C-4, respectively, based on expiration date, inventory, and average monthly sales. Accordingly, the recommended positions are products B and A on the right of C-4 and C-1 in Figure 11.

At this time, the changed display location information can be set in consideration of at least one of the expiration date, gender of the main purchasing customer, product margin rate, product sales ranking, product size, and shelf location corresponding to the customer's eye level. Here, the shelf position corresponding to the customer's eye level has different values depending on the customer's gender. Additionally, if the expiration date for each product is shorter than the preset period, changing the display location of the product may be recommended as a top priority.

At this time, the shelf position where the product is actually placed on the shelf is one of the important factors in increasing sales rate. Among the shelf positions on the shelf, the shelf position that corresponds to the customer's eye level can be referred to as the “golden line,” and refers to the level with the highest sales rate among the shelf levels. Additionally, because there is a difference in the eye level of male and female customers, the “golden line” may vary depending on the gender of the main purchasing customer and the propensity to purchase the product. By understanding this and placing products preferred by major customers on the golden line, sales can be improved.

For example, if the gender of the main purchaser is female and the age group is in the 30s to 40s, products related to pet health food are placed in the “golden line,” and if the main purchasing customers are in their 20s to 30s, products related to pet snacks are placed in the “golden line.” It can be placed on the “golden line”. Additionally, if the product is large, it can be displayed on a lower level, and products that are nearing their expiration date can be placed on the “golden line” with the highest priority.

The embodiment of product display location recommendation in an unmanned store and the embodiment of product recommendation using public institution big data can be combined and implemented. For example, using big data from public institutions, the gender and age of the main purchasing customers in the area where the unmanned store is located, the visiting time of the main purchasing customers, and the types and frequencies of diseases that pets mainly suffer from in the area. Based on the number of pets in the area, we estimate the product expected to be in the highest demand at unmanned stores in the area, and if the product is in stock, we recommend placing the product in an appropriate location. can do.

One embodiment of the present invention may also be implemented in the form of a recording medium containing instructions executable by a computer, such as program modules executed by a computer. Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and non-volatile media, removable and non-removable media. Additionally, computer-readable media may include all computer storage media. Computer storage media includes both volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data.

Although the methods and systems of the present invention have been described with respect to specific embodiments, some or all of their components or operations may be implemented using a computer system having a general-purpose hardware architecture.

The description of the present invention described above is for illustrative purposes, and those skilled in the art will understand that the present invention can be easily modified into other specific forms without changing the technical idea or essential features of the present invention. will be. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. For example, each component described as single may be implemented in a distributed manner, and similarly, components described as distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. do.

100: Product recommendation system 101: Memory
102: processor 103: communication module
200: Public institution server 300: Administrator terminal
400: Barcode scanner for administrator 500: Server
600: Kiosk

Claims (10)

In a method of providing product recommendations for unmanned pet supply stores using public big data,
(A) Receiving buyer information and companion animal information for each region from a public institution server;
(B) considering the buyer information and pet information, recommending a plurality of products judged to be in high demand in the area where the store to recommend products is located to the manager terminal of the unmanned store;
(C) after the recommended product is supplied to the unmanned store, collecting product sales status for a predetermined period from a manager terminal of the unmanned store; and
(D) adjusting the types or numbers of a plurality of products determined to be in high demand by assigning weights according to the sales performance of each recommended product within the product sales status and re-recommending them to the manager terminal; Including,
The pet information includes the total number of pets in each region, the number of each type of pet, the average age of the pet, gender, and statistics on the pet's disease, and the buyer information includes the age and gender of the buyer. person,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 1,
In step (B),
Based on pet disease statistics, we recommend pet products for the most common diseases, recommend the most preferred products based on the pet's breed and age, or take into account the buyer's age and gender. To recommend products that work,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 1,
In step (C),
(C-1) After the product is received in the unmanned store, receiving product identification information, price information, display location information, and expiration date information for the received product from the unmanned store manager terminal;
(c-2) receiving product identification information for sold products from the unmanned store manager terminal; and
(C-3) Comparing received product information and sold product information over a predetermined period of time, calculating inventory depletion speed information for each product and storing the product sales status;
which includes,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 3,
In the step (C-3),
Calculating inventory depletion speed information for each product;
Calculating a net profit rate for each product during a predetermined period in consideration of the inventory depletion speed information; and
Listing the ranks of net profit margins for each product over a predetermined period of time;
which includes,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 4,
In step (D),
By comparing the ranking of the net profit rate for each product and the plurality of products recommended in step (B) above, and applying different weights to each recommended product for each product, the type of product previously recommended when re-recommending a product Changing the number or recommending a new product,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 1,
Regarding the above unmanned stores,
Collecting store operation information including operating hours of the unmanned store, ranking of products with high purchase rate, repeat visit rate of regular customers, and customer price for each product,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 6,
Based on the collected store operation information, monitor products that are selling well in other stores, find products that are not in stock at a specific store among the products that are selling well, and recommend products to the manager terminal of the specific store,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 6,
Based on the statistics collected from the unmanned store, the time period with the highest sales is extracted and provided to the unmanned store manager terminal,
A method of providing product recommendations for unmanned pet supply stores using public big data. According to claim 1,
In step (D),
Considering the sales performance of the recommended product, additional feedback information is provided to change the display position of the recommended product,
The display position includes identification information of a display stand among a plurality of display shelves located in the store and a floor position in a display shelf composed of a plurality of layers,
A method of providing product recommendations for unmanned pet supply stores using public big data. In a device that provides product recommendations for unmanned pet supply stores using public big data,
A memory for storing a program on a method of providing product recommendations in an unmanned pet supply store; and
Includes a processor for executing the program,
The above method is,
(A) Receiving buyer information and companion animal information for each region from a public institution server;
(B) considering the buyer information and pet information, recommending a plurality of products judged to be in high demand in the area where the store to recommend products is located to the manager terminal of the unmanned store;
(C) after the recommended product is supplied to the unmanned store, collecting product sales status for a predetermined period from a manager terminal of the unmanned store; and
(D) adjusting the types or numbers of a plurality of products determined to be in high demand by assigning weights according to the sales performance of each recommended product within the product sales status and re-recommending them to the manager terminal; Including,
The pet information includes the total number of pets in each region, the number of each type of pet, the average age of the pet, gender, and statistics on the pet's disease, and the buyer information includes the age and gender of the buyer. person,
A device that provides product recommendations for unmanned pet supply stores using public big data.

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