Store visit time guidance system and program

Abstract

To provide a store visit time guidance system and program capable of notifying a customer of an appropriate store visit time according to commodities to be purchased.SOLUTION: A store visit time guidance system includes a customer terminal (terminal device) and a store server (server device). The customer terminal includes: a store visit information output unit which outputs, to the store server, information specifying the name of a store to be visited, the time at which a customer desires to visit the store, and a commodity to be purchased; and a store visit recommended date acquisition unit which acquires a store visit recommended date, from the store server. The store server includes: a store visit information acquisition unit which acquires, from the customer terminal, information specifying the name of the store, the date at which the customer desires to visit the store, and the commodity to be purchased; a sold-out time estimation unit which calculates estimated sold-out times based on estimated trends of the quantity of stock of the commodity to be purchased; a store visit recommended date calculation unit which calculates a store visit recommended date, based on the desired visit date and the earliest estimated sold-out time of the estimated sold-out times of the commodity to be purchased; and a store visit recommended date output unit which outputs the store visit recommended date to the customer terminal.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] An embodiment of the present invention relates to a store visit time information system and program. [Background technology]

[0002] In some retail stores and other stores, special sale periods are set for limited dates and times during which special sales are conducted. In order to ensure that customers purchase desired sale items during such sale periods, a system is known that provides guidance on appropriate times to visit the store based on the time periods when the customer visited the store in the past (for example, Patent Document 1).

[0003] The system of Patent Document 1 does not necessarily guide customers to the time to visit the store before the sale item runs out. Therefore, customers who visit the store at the time suggested may not be able to purchase the sale item. Summary of the Invention [Problem to be solved by the invention]

[0004] The problem to be solved by the present invention is to provide a store visit time guidance system and program that can guide customers to an appropriate store visit time according to the products they plan to purchase. [Means for solving the problem]

[0005] A store visit time guidance system according to an embodiment includes a terminal device used by a customer and a server device. The terminal device includes a store visit information output unit and a recommended store visit date and time acquisition unit. The store visit information output unit outputs to the server device information identifying the name of the store the customer plans to visit, the desired store visit date and time, and at least one sale item the customer plans to purchase. The recommended store visit date and time acquisition unit acquires the recommended store visit date and time from the server device. The server device includes a store visit information acquisition unit, a stockout time prediction unit, a recommended store visit date and time calculation unit, and a recommended store visit date and time output unit. The store visit information acquisition unit acquires the store name, the desired store visit date and time, and information identifying the sale item from the terminal device. The stockout time prediction unit calculates the expected stockout time of the sale item based on the predicted change in the inventory of the sale item. The recommended store visit date and time calculation unit calculates the recommended store visit date and time based on the desired store visit date and time and the earliest expected stockout time of the sale item. The recommended visit date and time output unit outputs the recommended visit date and time to the terminal device. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a block diagram illustrating an example of a schematic configuration of a store arrival time information system according to an embodiment. [Figure 2] FIG. 2 is a hardware block diagram showing an example of the hardware configuration of a store server included in the store visit time information system. [Figure 3] FIG. 3 is a diagram illustrating an example of a data structure of the product master. [Figure 4] FIG. 4 is a diagram illustrating an example of the data structure of the sales history file. [Figure 5] FIG. 5 is a diagram illustrating an example of a method for generating a learning model that predicts when a product will run out of stock. [Figure 6] FIG. 6 is a diagram illustrating a method for predicting the time when a product will run out of stock using the generated learning model. [Figure 7] FIG. 7 is a hardware block diagram showing an example of the hardware configuration of a customer terminal included in the store arrival time information system. [Figure 8] FIG. 8 is a diagram for explaining a method by which a customer selects a product he or she wishes to purchase from an electronic advertisement. [Figure 9] FIG. 9 is a diagram illustrating a method for a customer to select a product he or she wishes to purchase from a paper advertisement. [Figure 10] FIG. 10 is a diagram showing an example of a desired store visit date and time input screen displayed on the customer terminal. [Figure 11] FIG. 11 is a diagram showing an example of a screen displayed on a customer terminal, showing the recommended store visit date and time and the predicted store congestion. [Figure 12] FIG. 12 is a functional block diagram illustrating an example of the functional configuration of the store visiting time information system. [Figure 13] FIG. 13 is a flowchart illustrating an example of a flow of processing performed by the store arrival time information system according to the embodiment. [Figure 14] FIG. 14 is a flowchart showing an example of the process flow in which the store server calculates the estimated time when the product desired to be purchased will run out of stock when a special sale is being held at the time when the store visit information is acquired. [Figure 15] FIG. 15 is a flowchart showing an example of the process flow in which the store server calculates the estimated time when the product desired to be purchased will run out of stock if the special sale has not started at the time when the store visit information is acquired. DETAILED DESCRIPTION OF THE INVENTION

[0007] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will now be described with reference to the accompanying drawings. In the following embodiment, an example in which the present invention is applied to a store arrival time information system 10 will be described.

[0008] (Overview of the store visit time information system) A store arrival time information system 10 according to an embodiment of the present invention will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of a schematic configuration of the store arrival time information system according to the embodiment.

[0009] The store visit time guidance system 10 acquires, via a customer terminal 50, the name of the store the customer will visit, the desired date and time of the visit, and information on the sale item the customer wishes to purchase before visiting the store. The system estimates the expected time when the selected sale item will be out of stock, and notifies the customer of a recommended date and time to visit the store before the item runs out. The store visit time guidance system 10 has a configuration in which a store server 20 and a customer terminal 50 are connected via a network Nt. The store server 20 is also connected to multiple surveillance cameras 28 that monitor the inside of the store. The network Nt is, for example, the Internet. The store server 20 and the network Nt, and the customer terminal 50 and the network Nt are connected via a wireless LAN, a public line, or the like.

[0010] The store server 20 acquires from the customer terminal 50 the name of the store the customer plans to visit, the desired date and time of the visit, and information specifying the sale item the customer wishes to purchase. The store server 20 also predicts the date and time when the specified sale item will be out of stock and the degree of congestion at the store on the customer's desired date and time of visit. The store server 20 also notifies the customer terminal 50 of the date and time before the specified sale item is sold out as a recommended date and time to visit the store. The store server 20 is installed, for example, in each store or on the cloud. The store server 20 is an example of a server device in the present disclosure.

[0011] Surveillance camera 28 is installed in a store and monitors the product sales floor, for example, the condition of product shelves and the surrounding conditions of the sales floor. Surveillance camera 28 also calculates the number of products to be displayed as instructed by store server 20 and outputs this to store server 20. Surveillance camera 28 also takes images of the surrounding area of ​​the product sales floor as instructed by store server 20 and outputs the taken images to store server 20. Store server 20 calculates the degree of congestion around the sales floor based on the images acquired from surveillance camera 28. Note that the surveillance camera 28 may be configured to calculate the degree of congestion itself and output the calculated degree of congestion to store server 20.

[0012] The customer terminal 50, in response to the customer's operation, sets the name of the store they plan to visit, the planned date and time of the visit, and the product they wish to purchase. The customer terminal 50 then outputs the set information to the store server 20. The customer terminal 50 also acquires from the store server 20 the date and time before the specified sale product is sold out as the recommended date and time of the visit. The customer terminal 50 is, for example, a mobile terminal such as a smartphone or tablet terminal, or a terminal device such as a personal computer.

[0013] (Store server hardware configuration) The hardware configuration of the store server 20 will be described with reference to Fig. 2. Fig. 2 is a hardware block diagram showing an example of the hardware configuration of the store server included in the store visit time guidance system.

[0014] The store server 20 has a configuration in which a control unit 21, a storage unit 22, a peripheral device controller 24, and a communication controller 25 are interconnected via an internal bus 23.

[0015] The control unit 21 controls the overall operation of the store server 20. The control unit 21 includes a CPU (Central Processing Unit) 211, a ROM (Read Only Memory) 212, and a RAM (Random Access Memory) 213. The CPU 211 is connected to the ROM 212 and the RAM 213 via internal buses such as an address bus and a data bus. The CPU 211 loads various programs stored in the ROM 212 and the storage unit 22 into the RAM 213. The CPU 211 controls the operation of the store server 20 by operating in accordance with the various programs loaded into the RAM 213. In other words, the control unit 21 has the configuration of a typical computer.

[0016] The storage unit 22 is a storage device such as an HDD or SSD. Alternatively, the storage unit 22 may be a non-volatile memory such as a flash memory that retains stored information even when the power is turned off. The storage unit 22 stores a control program 221, a product master 222, an inventory master 223, and a sales history file 224.

[0017] The control program 221 is a program that controls the overall operation of the store server 20. The control program 221 may be provided in a state stored in the storage unit 22, or may be provided by being recorded in an installable or executable file on a computer-readable non-transitory recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD. The control program 221 may also be stored on a computer connected to a network and provided by being downloaded via the network. Furthermore, the control program 221 may be provided or distributed via a network such as the Internet.

[0018] The product master 222 is a master file that stores product information such as product names and prices of products for sale. The product master 222 stores various types of product information in association with product codes. Since the contents of the product master are updated as needed, the store server 20 keeps the contents of the product master 222 up to date by, for example, acquiring the latest product master from a higher-level server (not shown) via the communication controller 25. The data structure of the product master 222 will be described in detail later (see FIG. 3).

[0019] The inventory master 223 is a master file that stores the number of products in stock at the store. The inventory master 223 stores the warehouse inventory number and the store inventory number of the product in association with the product code. Each time a product is paid for, the store inventory number of the corresponding product is decremented. Furthermore, each time a product is replenished from the warehouse, the upper part of the inventory master 223 is updated.

[0020] The sales history file 224 is a file that stores the sales figures for each time period when products were on sale in the past. The sales history file 224 stores sales information for the products in association with the product code. The data structure of the sales history file 224 will be described in detail later (see FIG. 4).

[0021] The control unit 21 is connected to the surveillance camera 28 via the peripheral device controller 24. As described above, the surveillance camera 28 calculates the number of products displayed in the sales floor. The surveillance camera 28 also outputs captured images of the surrounding area of ​​the sales floor to the store server 20.

[0022] The control unit 21 also performs various communications with the customer terminal 50 via the communication controller 25. The contents of the information received by the store server 20 and the customer terminal 50 are as described above.

[0023] (Product master data structure) The data structure of the product master 222 will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the data structure of the product master.

[0024] The product master 222 is a master file that stores various product information in association with a product code that uniquely identifies the product. The product information stored in the product master 222 includes, for example, the product name, regular price, sale price, sale date, additional information, etc.

[0025] The product name is the name of the product.

[0026] The regular price is the normal selling price of the product.

[0027] The sale price is the sale price of the product on the sale day.

[0028] The sale date is information indicating the period during which the sale is being held, and includes the start date and end date of the sale.

[0029] The additional information is other information related to the product, such as information indicating that the product has an age restriction for purchase, information related to the consumption tax rate, etc.

[0030] The information stored in the product master 222 is not limited to the above, and other information may be stored.

[0031] (Sales history file data structure) The data structure of the sales history file 224 will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the data structure of the sales history file.

[0032] The sales history file 224 is a file that stores sales information for each product on a sale date in association with the product code. The sales information stored in the sales history file 224 includes, for example, the sale price, the time period, and the number of sales.

[0033] The sale price is the selling price of the product corresponding to the product code during the sale period.

[0034] The time period is a time period obtained by dividing the store's business hours into one-hour or 30-minute increments.

[0035] The sales number is the number of sales of the product corresponding to the product code for each time period.

[0036] The information stored in the sales history file 224 is not limited to the above, and other information may be stored. For example, the time when the product corresponding to the product code was out of stock may be stored.

[0037] (Method for predicting when a product will be out of stock) A method by which the store server 20 predicts when a product will be out of stock will be described using Figures 5 and 6. Figure 5 is a diagram showing an example of a method for generating a learning model that predicts when a product will be out of stock. Figure 6 is a diagram explaining a method for predicting when a product will be out of stock using the generated learning model.

[0038] The control unit 21 of the store server 20 predicts the time when the product will run out based on past sales information of the sale product and current inventory information of the sale product.

[0039] Although various prediction methods can be applied to predict the stock-out time, in this embodiment, a method using a learning model 44 is used.

[0040] The learning model 44 is a machine learning model that learns the relationship between the sales quantity 41 of the corresponding product X at the elapsed time t from the start of the sale in the past sale period, the warehouse inventory quantity 42 of the product X at the elapsed time t from the start of the sale in the past sale period, and the display quantity 43 of the product X at the elapsed time t, and the stock-out time 45 of the product X. The learning model 44 is described, for example, by a known neural network or the like.

[0041] The sales number 41 is the sales number of the corresponding product X, which is acquired from the sales history file 224 (FIG. 4).

[0042] The warehouse stock quantity 42 is the warehouse stock quantity of the relevant product X, which is acquired from the stock master 223.

[0043] The number of displays 43 is the number of displays of the product X calculated by the surveillance camera 28 from an image taken by the surveillance camera 28 of the display shelf on which the target product is displayed.

[0044] The out-of-stock time 45 is the time when the corresponding product X was out of stock during a past sale period, which is obtained from sales data of the store (not shown).

[0045] The store server 20 trains the learning model 44 so that when the sales volume 41, warehouse inventory volume 42, and display volume 43 of the relevant product during a past sale period are input to the learning model 44, the learning model 44 outputs a time close to the out-of-stock time 45 of the relevant product.

[0046] More specifically, by inputting the sales quantity 41, warehouse inventory quantity 42, display quantity 43, and out-of-stock time 45 into the learning model 44, the weighting coefficients assigned to the links between different layers in the neural network that constitutes the learning model 44 are adjusted. The store server 20 generates a different learning model 44 for each product that is the subject of a special sale. The learning model 44 generated in this way is also stored in the storage unit 22 (see FIG. 2).

[0047] The store server 20 uses the generated learning model 44 to calculate a predicted time 46 when a specific product will run out of stock, as shown in FIG.

[0048] Specifically, the store server 20 obtains the number of items sold 41 at the time t elapsed since the start of the sale, the number of items in stock 42 at the time t elapsed since the start of the sale, and the number of items on display 43 at the time t elapsed since the start of the sale, for the items for which the time of stockout is predicted.

[0049] The store server 20 then inputs the sales quantity 41, warehouse inventory quantity 42, and display quantity 43 into a learning model 44. Based on the learning results, the learning model 44 predicts the expected time 46 when the product will run out of stock, and outputs the prediction result.

[0050] Note that the learning model 44 described here was generated to predict the expected out-of-stock time 46 from the sales quantity 41, warehouse inventory quantity 42, and display quantity 43, but the expected out-of-stock time 46 may also be predicted from only the warehouse inventory quantity 42 and display quantity 43. The reason for taking the sales quantity 41 into account is that there will be a certain number of customers who continue shopping with the relevant product in their shopping cart, so even if the warehouse inventory quantity 42 and display quantity 43 decrease, this result will not be immediately reflected in the sales quantity 41. In this way, by taking the sales quantity 41 into account, it is possible to make a more reliable prediction of the expected out-of-stock time 46.

[0051] (Customer terminal hardware configuration) The hardware configuration of the customer terminal 50 will be described with reference to Fig. 7. Fig. 7 is a hardware block diagram showing an example of the hardware configuration of the customer terminal provided in the store arrival time information system.

[0052] The customer terminal 50 has a configuration in which a control unit 51, a storage unit 52, a peripheral device controller 54, and a communication controller 55 are interconnected by an internal bus 53.

[0053] The control unit 51 controls the overall operation of the customer terminal 50. The control unit 51 includes a CPU 511, a ROM 512, and a RAM 513. The CPU 511 is connected to the ROM 512 and the RAM 513 via internal buses such as an address bus and a data bus. The CPU 511 loads various programs stored in the ROM 512 and the storage unit 52 into the RAM 513. The CPU 511 controls the operation of the customer terminal 50 by operating in accordance with the various programs loaded into the RAM 513. In other words, the control unit 51 has the configuration of a typical computer.

[0054] The storage unit 52 is a storage device such as an HDD or SSD. Alternatively, the storage unit 52 may be a non-volatile memory such as a flash memory that retains stored information even when the power is turned off. The storage unit 52 stores a control program 521.

[0055] The control program 521 is a program that controls the overall operation of the customer terminal 50. The control program 521 may be provided in a state stored in the storage unit 52, or may be provided by being recorded in an installable or executable file on a computer-readable non-transitory recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD. The control program 521 may also be provided by being stored on a computer connected to a network and downloaded via the network. Furthermore, the control program 521 may be provided or distributed via a network such as the Internet.

[0056] The control unit 51 is connected to a display device 541, an operation device 542, and a camera 543 via a peripheral device controller .

[0057] The display device 541 outputs to the customer various information related to the store arrival time information system 10. The display device 541 is, for example, a liquid crystal monitor or an organic EL monitor.

[0058] The operation device 542 acquires various operation instructions from the customer for the store time information system 10. The operation device 542 is, for example, a touch panel stacked on the display device 541.

[0059] The control unit 51 also performs various communications with the store server 20 via the communication controller 55. The contents of the information received by the customer terminal 50 and the store server 20 are as described above.

[0060] (How to select the product you want to purchase (1)) A method for a customer to select a desired product from an electronic advertisement will be described with reference to Figure 8. Figure 8 is a diagram for explaining a method for a customer to select a desired product from an electronic advertisement.

[0061] The customer selects the product they wish to purchase by having the customer terminal 50 display an electronic advertisement acquired, for example, via the Internet, on the display device 541. Fig. 8 shows an example of an electronic advertisement 60 displayed on the display device 541 of the customer terminal 50.

[0062] The electronic advertisement 60 includes a store name 61, a sale period 62, a sale product list 63, a send button 65, and a back button 66. A customer can reach the screen of the electronic advertisement 60 shown in Fig. 8 by selecting the name of the store they plan to visit from the main menu screen of the electronic advertisement (not shown).

[0063] The store name 61 is the store name selected by the customer.

[0064] The sale period 62 is information indicating the start date and end date of the sale.

[0065] The sale item list 63 includes the name of the item being sold, the regular price, and the sale price. A check box 64 is placed at the top of the sale item list 63. A customer registers a sale item they wish to purchase (hereinafter referred to as a "purchase-intended item") as a purchase-intended item by tapping the check box 64 at the top of the sale item. A check mark is displayed in the tapped check box 64. FIG. 8 shows a state in which items B and C have been registered as purchase-intended items. If a check mark is placed on the wrong item, the check mark can be removed by tapping the check box 64 again. When a check mark is placed on the check box 64, the customer terminal 50 may display a pull-down menu (not shown) to allow the customer to set the number of items they wish to purchase.

[0066] The customer can scroll the sale item list 63 up and down by swiping up and down on the sale item list 63 (sliding up and down while touching the touch panel, which is the operating device).

[0067] The send button 65 is an operator for sending the registered details of the products to be purchased to the store server 20. The store server 20 acquires the contents of the check boxes 64 to identify the products that the customer wishes to purchase.

[0068] The back button 66 transitions the screen displayed on the display device 541 from the display of the electronic advertisement 60 to, for example, the main menu screen of the electronic advertisement.

[0069] (How to select the product you want to purchase (2)) A method for a customer to select a product he or she wishes to purchase from a paper advertisement is explained using Fig. 9. Fig. 9 is a diagram for explaining a method for a customer to select a product he or she wishes to purchase from a paper advertisement.

[0070] A customer can also select a product he or she wishes to purchase from a paper advertisement such as a newspaper advertisement or a magazine advertisement, and transmit the selected product to the store server 20.

[0071] Fig. 9 is an example of a paper advertisement 67. Although not shown in Fig. 9, the paper advertisement 67 displays the sale period and the name of the store where the sale is being held.

[0072] The customer handwrites a check mark 68 on the product they wish to purchase. The check mark 68 can take any form. Figure 8 shows an example in which check marks 68 have been added to product I, product M, and product N. If the customer wishes to purchase multiple units of the same product, they may handwrite the number of units they wish to purchase near the check mark 68.

[0073] Thereafter, the customer uses the camera 543 of the customer terminal 50 to take an image showing the check mark 68 that the customer has filled out on the paper advertisement 67. At that time, it is desirable to take the image so that the store name and the sale period displayed on the paper advertisement 67 are also visible in the same image. For example, it is desirable to place on the paper advertisement 67 a code symbol (such as a barcode or two-dimensional code) in which information identifying the paper advertisement 67 or information identifying the store name and sale period is registered, and when taking an image of the paper advertisement 67, to have the code symbol appear in the same image.

[0074] Thereafter, the customer selects, for example, a menu item "Send image of paper advertisement" from a main menu (not shown) on the customer terminal 50, and attaches the photographed image of the paper advertisement 67. Then, the customer causes the customer terminal 50 to send the attached image of the paper advertisement 67 to the store server 20.

[0075] When the store server 20 acquires an image of the paper advertisement 67 from the customer terminal 50, it performs image analysis on the acquired image to identify the product and quantity the customer wishes to purchase. The specific image analysis method is not critical. For example, the image of the paper advertisement acquired from the customer terminal 50 includes information indicating the name of the store to which the advertisement applies and the sale period. Therefore, the store server 20 adjusts the size, position, and orientation of the original image information of the paper advertisement 67 and the image of the paper advertisement 67 acquired from the customer terminal 50 so that they overlap, then performs a difference calculation between the images. By extracting the area of ​​the difference, i.e., the information written by the customer, the store server 20 identifies the product the customer wishes to purchase.

[0076] (How to set your desired visit date and time) A method for a customer to set a desired time to visit a specific store on a sale day will be described with reference to Fig. 10. Fig. 10 is a diagram showing an example of a desired store visit date and time input screen displayed on the customer terminal.

[0077] When a customer selects the name of the store they plan to visit on the main menu screen of the electronic advertisement displayed on the customer terminal 50, the customer terminal 50 displays the desired visit date and time input screen 70 shown in Figure 10 on its display device 541.

[0078] The desired visit date and time input screen 70 includes a store name 71 , a desired visit date 72 , a desired visit time zone 73 , setting information 74 , a confirm button 75 , a cancel button 76 , and a back button 77 .

[0079] The store name 71 is the store name selected by the customer.

[0080] The desired visit date 72 is the desired visit date selected by the customer. When the customer taps the desired visit date 72 window, the customer terminal 50 displays a pop-up window (not shown) listing the visit dates. The customer can set the desired visit date by tapping the date they wish to visit from the pop-up window. Figure 10 shows an example in which February 23, 2024 is set as the desired visit date.

[0081] Desired visit time slot 73 is an option for the time slot during which the customer would like to visit the store. The customer can set the desired visit time slot by tapping one of the options displayed in desired visit time slot 73. Figure 10 shows an example in which the desired visit time slot is set to 10:30 to 11:00.

[0082] The setting information 74 is information indicating the desired visit date and time set in the desired visit date 72 and desired visit time zone 73. By looking over the contents of the setting information 74, the customer can confirm whether the desired visit date and time that he or she has set has been set correctly.

[0083] The decision button 75 is an operator for transmitting the contents of the setting information 74 to the store server 20. That is, when a customer taps the decision button 75, the customer terminal 50 outputs the contents of the setting information 74 to the store server 20.

[0084] The cancel button 76 is an operator that cancels the contents of the setting information 74 and enables the customer to reset the desired visit date and time. That is, when the customer taps the cancel button 76, the customer terminal 50 deletes the setting information 74 and sets the desired visit date 72 and desired visit time zone 73 to an unselected state.

[0085] The back button 77 is an operator that cancels the setting of the desired store visit date and time and transitions the desired store visit date and time input screen 70 to the previous screen, for example, the main menu screen of the electronic advertisement, etc. When the back button 77 is tapped, the setting information 74 is deleted.

[0086] (Example of recommended visit date and time display) A method for a customer to set a desired time to visit a specific store on a sale day will be described using Fig. 11. Fig. 11 is a diagram showing an example of a screen displayed on a customer terminal that shows the recommended date and time to visit the store and the predicted congestion at the store.

[0087] The store server 20 calculates a recommended store visit date and time 82 based on the product desired by the customer, the name of the store to be visited, and the desired store visit date and time, all of which are acquired from the customer terminal 50. The recommended store visit date and time 82 is a store visit date and time at which the customer is unlikely to miss out on the desired product. It is desirable that the recommended store visit date and time coincide with the customer's desired store visit time zone, but it is also possible to recommend a less crowded time zone taking into account the store's congestion level. The store server 20 then outputs the recommended store visit date and time 82 to the customer terminal 50. The customer terminal 50 acquires information such as the recommended store visit date and time 82 from the store server 20, and displays a recommended store visit date and time display screen 80, shown in FIG. 11, on its own display device 541.

[0088] The recommended visit date and time display screen 80 includes a store name 81 , a recommended visit date and time 82 , a recommendation basis 83 , an estimated in-store congestion 84 , and a back button 85 .

[0089] Store name 81 is the name of the store that the customer wishes to visit.

[0090] The recommended store visit date and time 82 is a recommended store visit date and time calculated by the store server 20. "Recommended" means a date and time when the customer is unlikely to miss out on the desired product and when the store is not too crowded. If a customer selects multiple desired products, the store server 20 calculates the recommended store visit date and time 82 so that the customer does not miss out on the product with the earliest expected out-of-stock time 46.

[0091] The recommendation basis 83 is information indicating the basis on which the store server 20 calculated the recommended store visit date and time 82. Fig. 11 shows an example in which the customer is informed that, since product W is most likely to sell out the earliest among the products selected by the customer, it is desirable to visit the store before product W sells out, and that, based on the predicted in-store congestion 84 described below, it is desirable to visit the store between 11:30 and 12:00 when it is less crowded.

[0092] The in-store congestion forecast 84 is the degree of congestion in the store during the time period before and after the recommended visit date and time 82, as predicted by the store server 20. The in-store congestion forecast 84 may be the degree of congestion in the sales area for the product the customer wishes to purchase, or the degree of congestion in the store itself. In particular, it is desirable to display the in-store congestion forecast 84 in the form of a graph so that the customer can intuitively recognize the degree of congestion. In this embodiment, since the customer originally wanted to visit the store between 10:30 and 11:00 (see FIG. 10), the customer may check the in-store congestion forecast 84 for that time period and decide to visit the store between 10:30 and 11:00 based on their own judgment.

[0093] The back button 85 is an operator that stops the display of the recommended store visit date and time display screen 80 and transitions to the previous screen, for example, the main menu screen of the electronic advertisement.

[0094] (Functional configuration of the store visit time information system) The functional configuration of the store arrival time information system 10 will be described with reference to Fig. 12. Fig. 12 is a functional block diagram showing an example of the functional configuration of the store arrival time information system.

[0095] First, the functional configuration of the store server 20 will be described. The control unit 21 of the store server 20 loads and runs a control program 221 in the RAM 213, thereby realizing a store visit information acquisition unit 101, an out-of-stock time prediction unit 102, a congestion degree calculation unit 103, a recommended visit date and time calculation unit 104, and a recommended visit date and time output unit 105, all of which are shown in Fig. 12. Note that all or part of these functional units may be realized by dedicated hardware.

[0096] The store visit information acquisition unit 101 acquires, from the customer terminal 50 (terminal device), information specifying the name of the store the customer plans to visit, the customer's desired date and time of visit, and the product (sale product) the customer wishes to purchase. The store visit information acquisition unit 101 also acquires information specifying the customer terminal 50, such as an email address associated with the customer terminal 50 and a customer ID associated with the customer terminal 50.

[0097] The out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 of the desired product based on the predicted change in the stock quantity of the desired product.

[0098] More specifically, when the store visit information acquisition unit 101 acquires from the customer terminal 50 the name of the store the customer plans to visit, the customer's desired date and time of visit, and information identifying the product the customer wishes to purchase (sale product) at the time when the sale product is in sale, the out-of-stock time prediction unit 102 calculates the estimated time 46 when the sale product will run out based on the past sales figures for each time period of the sale product, the current inventory figures for each time period of the sale product in the warehouse, and the current number of sale products displayed on the shelves.

[0099] In addition, when the store visit information acquisition unit 101 acquires from the customer terminal 50 the name of the store the customer plans to visit, the customer's desired date and time of visit, and information identifying the product the customer wishes to purchase (sale product), the out-of-stock time prediction unit 102 calculates the predicted out-of-stock time 46 of the sale product based on the past sales volume of the sale product for each time period.

[0100] The congestion degree calculation unit 103 calculates the congestion degree of the sale item sales area for each time period during past sales periods based on images captured by the surveillance camera 28. More specifically, the congestion degree calculation unit 103 calculates the approximate number of people from images of the sale item sales area using a known person detection process. For example, the congestion degree calculation unit 103 calculates the approximate number of people per unit area to determine the congestion degree of the sale item sales area at that time or time period. The calculated congestion degree is associated with identification information identifying the sale item sales area and stored, for example, in the memory unit 22 of the store server 20. The stored congestion degree is updated whenever a sale is held. Specifically, the congestion degree calculation unit 103 updates the congestion degree stored in the memory unit 22 by averaging the congestion degrees for the same time or time period. The congestion degree calculation unit 103 may calculate the congestion degree of the entire store, rather than the congestion degree of a specific sale item sales area.

[0101] The recommended visit date and time calculation unit 104 calculates the recommended visit date and time 82 based on the desired visit date and time and the earliest expected out-of-stock time 46 of the sale items. Note that the recommended visit date and time calculation unit 104 may take into account the congestion degree calculated by the congestion degree calculation unit 103 when calculating the recommended visit date and time 82.

[0102] The recommended visit date and time output unit 105 outputs the recommended visit date and time 82 to the customer terminal 50 (terminal device) from which the visit information acquisition unit 101 has acquired various information.

[0103] Next, the functional configuration of the customer terminal 50 will be described. The control unit 51 of the customer terminal 50 deploys and runs a control program 521 in RAM 513, thereby realizing an electronic advertisement acquisition unit 91, a proposed purchase product acquisition unit 92, a paper advertisement photographing unit 93, a desired store visit date and time acquisition unit 94, a store visit information output unit 95, and a recommended store visit date and time acquisition unit 96, all of which are shown in Fig. 12. Note that all or part of these functional units may be realized by dedicated hardware.

[0104] The electronic advertisement acquisition unit 91 acquires, via the Internet or the like, an electronic advertisement 60 for a store that the user plans to visit.

[0105] The purchase intended product acquisition unit 92 acquires, based on the customer's operation information, information specifying the sale product that the customer intends to purchase, that is, the purchase intended product, from the sale product list 63 included in the electronic advertisement 60.

[0106] The paper advertisement photographing unit 93 photographs an image of the paper advertisement 67 that clearly states information specifying the product to be purchased.

[0107] The desired visit date and time acquisition unit 94 acquires the name of the store that the customer wishes to visit and the desired visit date and time based on the customer's operation information.

[0108] The store visit information output unit 95 outputs information identifying the name of the store to be visited, the desired date and time of the visit, and at least one sale item to be purchased to the store server 20 (server device). The store visit information output unit 95 also outputs information identifying the customer terminal 50, such as an email address associated with the customer terminal 50 and a customer ID associated with the customer terminal 50.

[0109] The recommended visit date and time acquisition unit 96 acquires the recommended visit date and time 82 from the store server 20.

[0110] (Processing flow of the store visit time information system) The flow of processing performed by the store arrival time information system 10 will be described with reference to Fig. 13. Fig. 13 is a flowchart showing an example of the flow of processing performed by the store arrival time information system of the embodiment.

[0111] First, we will explain the flow of processing performed by the customer terminal 50. It is assumed that the customer terminal 50 acquires, as a product to be purchased, a sale product according to the customer's operation from the sale product list 63 of the electronic advertisement 60 displayed on its own display device 541.

[0112] Based on the customer's operation information, the intended purchase product acquisition unit 92 acquires information identifying the sale products that the customer intends to purchase, i.e., the intended purchase products, from the sale product list 63 included in the electronic advertisement 60 (see Figure 8) (step S11).

[0113] The desired visit date and time acquisition unit 94 acquires the name of the store that the customer wishes to visit and the desired visit date and time based on the customer's operation information on the desired visit date and time input screen 70 (see FIG. 10) (step S12).

[0114] The store visit information output unit 95 outputs to the store server 20 the name of the store the customer plans to visit, the desired date and time of the store visit, and information specifying at least one sale item the customer plans to purchase (step S13).

[0115] The recommended visit date and time acquisition unit 96 acquires the recommended visit date and time 82 from the store server 20 (step S14). The customer terminal 50 displays the acquired recommended visit date and time 82 on the recommended visit date and time display screen 80 (see FIG. 11). Then, the customer terminal 50 ends the process.

[0116] If the customer writes the product they intend to purchase in the paper advertisement 67, instead of step S11, the customer terminal 50 acquires an image of the paper advertisement 67 taken by the customer's own camera 543. Then, instead of step S13, the store visit information output unit 95 outputs the name of the store they intend to visit, the desired date and time of the visit, and the image of the paper advertisement 67 to the store server 20.

[0117] Next, the flow of processing performed by the store server 20 will be described.

[0118] The store visit information acquisition unit 101 acquires, from the customer terminal 50, the name of the store the customer plans to visit, the desired date and time of the visit, and information identifying at least one sale item the customer plans to purchase (step S21).

[0119] The out-of-stock time prediction unit 102 determines whether the current date and time is within the sale period (step S22). If it is determined that the current date and time is within the sale period (step S22: Yes), the process proceeds to step S23. On the other hand, if it is not determined that the current date and time is within the sale period (step S22: No), the process proceeds to step S24. Although not shown in FIG. 13, if the sale period has ended at the current date and time, for example, if the store server 20 acquires an image of an old paper advertisement 67 in step S21, the store server 20 will notify the customer terminal 50 that the sale period has ended.

[0120] If it is determined in step S22 that the current date and time is during the sale period, the out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 of the desired product (step S23). The detailed flow of the process performed in step S23 will be described later (see FIG. 14). Then, the process proceeds to step S25.

[0121] On the other hand, if it is determined in step S22 that the current date and time is not within the sale period, the out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 of the desired product (step S24). The detailed flow of the process performed in step S24 will be described later (see FIG. 15). Then, the process proceeds to step S25.

[0122] Following step S23 or step S24, the congestion degree calculation unit 103 calculates the past congestion degree for each time period in the sales area for sale items based on images acquired from the monitoring camera 28 (step S25).

[0123] The recommended visit date and time calculation unit 104 calculates the recommended visit date and time 82 (step S26).

[0124] The recommended visit date and time output unit 105 outputs the recommended visit date and time 82 to the customer terminal 50 (step S27). Then, the store server 20 ends the process.

[0125] Next, the flow of processing by the store server 20 to calculate the estimated out-of-stock time 46 of the desired product when the current date and time is during a sale will be described using Figure 14. Figure 14 is a flowchart showing an example of the flow of processing by the store server to calculate the estimated out-of-stock time of the desired product when a sale is being held at the time the store visit information is acquired.

[0126] The out-of-stock time prediction unit 102 reads out the sales history during the past sale period for the same product as the product selected by the customer from the sales history file 224 (step S31).

[0127] The out-of-stock time prediction unit 102 acquires the warehouse stock quantity 42 at the current time of the product selected by the customer and intended to be purchased (step S32).

[0128] The out-of-stock time prediction unit 102 acquires the number 43 of items on display at the current time that are selected by the customer and intended to be purchased (step S33).

[0129] The out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 of the product to be purchased (step S34).

[0130] The out-of-stock time prediction unit 102 determines whether the estimated out-of-stock time 46 has been calculated for all the desired purchase items acquired by the store visit information acquisition unit 101 (step S35). If it is determined that the estimated out-of-stock time 46 has been calculated for all the desired purchase items (step S35: Yes), the process proceeds to step S25 in Fig. 13. On the other hand, if it is not determined that the estimated out-of-stock time 46 has been calculated for all the desired purchase items (step S35: No), the process returns to step S31.

[0131] Next, the flow of processing by the store server 20 to calculate the estimated out-of-stock time 46 of the desired product when a special sale has not started on the current date and time will be described using Figure 15. Figure 15 is a flowchart showing an example of the flow of processing by the store server to calculate the estimated out-of-stock time of the desired product when a special sale has not started at the time the store visit information is acquired.

[0132] The out-of-stock time prediction unit 102 reads out the sales history during the past sale period for the same product as the product selected by the customer from the sales history file 224 (step S41).

[0133] The out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 of the product to be purchased based on the sales history during the past sale period (step S42).

[0134] The out-of-stock time prediction unit 102 determines whether the estimated out-of-stock time 46 has been calculated for all the desired purchase items acquired by the store visit information acquisition unit 101 (step S43). If it is determined that the estimated out-of-stock time 46 has been calculated for all the desired purchase items (step S43: Yes), the process proceeds to step S25 in Fig. 13. On the other hand, if it is not determined that the estimated out-of-stock time 46 has been calculated for all the desired purchase items (step S43: No), the process returns to step S41.

[0135] As described above, the store visit time guidance system 10 of this embodiment comprises a customer terminal 50 (terminal device) used by a customer and a store server 20 (server device). The customer terminal 50 comprises a store visit information output unit 95 that outputs to the store server 20 information identifying the name of the store the customer plans to visit, the desired date and time of visit, and at least one sale item the customer plans to purchase, and a recommended store visit date and time acquisition unit 96 that acquires a recommended store visit date and time from the store server 20. The store server 20 comprises a store visit information acquisition unit 101 that acquires from the customer terminal 50 the store name, the desired date and time of visit, and information identifying the sale item, a stock-out time prediction unit 102 that calculates an estimated stock-out time 46 of the sale item based on the expected trend in inventory of the sale item, a recommended store visit date and time calculation unit 104 that calculates a recommended store visit date and time 82 based on the desired date and time of visit and the earliest estimated stock-out time among the estimated stock-out times 46 of the sale items, and a recommended store visit date and time output unit 105 that outputs the recommended store visit date and time 82 to the customer terminal 50. Therefore, the customer can be advised of the most appropriate time to visit the store depending on the product he or she plans to purchase.

[0136] Furthermore, in the store visit time guidance system 10 of the embodiment, when the time when the store visit information acquisition unit 101 acquires the store name, the desired visit date and time, and the information identifying the sale item from the customer terminal 50 is during a sale period for the sale item, the out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 for the sale item based on the past sales volume of the sale item for each time period, the current warehouse inventory volume 42 of the sale item for each time period, and the current display volume 43 of the sale item on the shelves. Therefore, when store visit information is acquired from a customer during a sale period, the store visit time guidance system 10 can predict the estimated out-of-stock time 46 with high reliability based on the inventory trends during the current sale period and the inventory trends during past sale periods.

[0137] Furthermore, in the store visit time information system 10 of the embodiment, if the store visit information acquisition unit 101 acquires the store name, the desired store visit date and time, and the information identifying the sale item from the customer terminal 50 before the start of the sale period for the sale item, the out-of-stock time prediction unit 102 calculates the estimated out-of-stock time 46 for the sale item based on the past sales figures for each time period for the sale item. Therefore, if store visit information is acquired from a customer before the start of the sale period, the store visit time information system 10 can predict the estimated out-of-stock time 46 with high reliability based on the inventory trends during the past sale period.

[0138] The store visit time guidance system 10 of the embodiment further includes a congestion degree calculation unit 103 that calculates the congestion degree for each time period of the sales floor for sale items during past sales periods based on images captured by a surveillance camera 28 installed in the store and monitoring the sales floor, and the recommended visit date and time output unit 105 further outputs the congestion degree to the customer terminal 50. Therefore, by taking the congestion degree of the sales floor into account in the recommended visit date and time 82, it is possible to recommend the least crowded time possible for the customer to purchase the intended item. Furthermore, providing the congestion degree can provide useful information for the customer when deciding on their own time to visit the store.

[0139] Furthermore, in the store visit time guidance system 10 of the embodiment, the store visit information output unit 95 checks the sale items in the electronic advertisement 60 delivered to the customer terminal 50 and outputs them, or outputs an image of a paper advertisement 67 with a marker attached to the sale items. Therefore, even customers who are unable to receive the electronic advertisement 60 can be informed of an appropriate store visit time according to the items they plan to purchase.

[0140] Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as set forth in the claims. [Explanation of symbols]

[0141] 10. Visit time information system 20 Store server (server device) 28 Surveillance Cameras 41 sales 42 warehouse inventory 43 Number of displays 44 Learning Model 45 Out of stock time 46 Estimated time of stockout 50 Customer terminal (terminal device) 60 Electronic Advertising 61 Store Name 62 Special Sale Period 63 Special Sale Items List 64 checkboxes 65 Send button 66 Back button 67 Paper Advertisements 68 check mark 70 Desired visit date and time input screen 71 Store Name 72 Desired visit date 73 Preferred time of visit 74 Setting Information 75 Decision button 76 Cancel button 77 Back button 80 Recommended visit date and time display screen 81 Store Name 82 Recommended visit date and time 83 Recommendation Basis 84 Store congestion forecast 85 Back button 91 Electronic Advertising Acquisition Department 92 Purchase Intent Acquisition Department 93 Paper Advertising Photography Department 94 Desired visit date and time acquisition section 95 Visit information output section 96 Recommended visit date and time acquisition section 101 Visitor Information Acquisition Department 102 Out-of-stock time prediction section 103 Congestion degree calculation unit 104 Recommended visit date and time calculation unit 105 Recommended visit date and time output section Nt Network [Prior art documents] [Patent documents]

[0142] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-78471

Claims

1. A store arrival time information system including a terminal device used by a customer and a server device, The terminal device a store visit information output unit that outputs to the server device the name of the store the user plans to visit, the desired date and time of the store visit, and information that identifies at least one sale item the user plans to purchase; a recommended visit date and time acquisition unit that acquires a recommended visit date and time from the server device, The server device a store visit information acquisition unit that acquires, from the terminal device, information specifying the store name, the desired store visit date and time, and the sale item; an out-of-stock time prediction unit that calculates an expected out-of-stock time for the sale item based on the predicted change in the stock quantity of the sale item; a recommended store visit date and time calculation unit that calculates the recommended store visit date and time based on the desired store visit date and time and the earliest expected out-of-stock time of the sale item; a recommended visit date and time output unit that outputs the recommended visit date and time to the terminal device, Visit time information system.

2. When the time when the store visit information acquisition unit acquires the store name, the desired store visit date and time, and the information specifying the sale item from the terminal device is during a sale period for the sale item, The out-of-stock time prediction unit The number of sales of the special sale items per time period in the past; The current inventory quantity of the special sale items in the warehouse for each time period; The number of the sale items currently displayed on the shelves; Calculating the expected time when the sale item will run out based on the above. The store arrival time information system according to claim 1.

3. When the time when the store visit information acquisition unit acquires the store name, the desired store visit date and time, and the information specifying the sale item from the terminal device is before the start of the sale period of the sale item, The out-of-stock time prediction unit calculating an expected time when the sale item will run out based on the past sales figures for each time period of the sale item; The store arrival time information system according to claim 1.

4. The store further includes a congestion degree calculation unit that calculates the congestion degree of the sales floor for the special sale items for each time period during a past special sale period based on images taken by a surveillance camera installed in the store and monitoring the sales floor for the items, The recommended visit date and time output unit further outputs the congestion degree to the terminal device.

4. The store arrival time information system according to claim 2 or 3.

5. The store visit information output unit The electronic advertisement delivered to the terminal device is output with a check mark next to the sale item, or an image of a paper advertisement with a marker next to the sale item is output. The store arrival time information system according to any one of claims 1 to 3.

6. A computer that controls a store arrival time information system that includes a terminal device used by a customer and a server device, The terminal device, a store visit information output unit that outputs to the server device the name of the store the user plans to visit, the desired date and time of the store visit, and information that identifies at least one sale item the user plans to purchase; a recommended visit date and time acquisition unit that acquires a recommended visit date and time from the server device; The server device, a store visit information acquisition unit that acquires, from the terminal device, information specifying the store name, the desired store visit date and time, and the sale item; an out-of-stock time prediction unit that calculates an expected out-of-stock time for the sale item based on the predicted change in the stock quantity of the sale item; a recommended store visit date and time calculation unit that calculates the recommended store visit date and time based on the desired store visit date and time and the earliest expected out-of-stock time of the sale item; causing the terminal device to function as a recommended store visit date and time output unit that outputs the recommended store visit date and time; program.

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