Product ordering device and product ordering program

Abstract

We will further improve personalized recommendations and aim to increase average customer spending. [Solution] A product ordering device for a regular home delivery service has a storage means for storing products to be ordered, a user-selected product setting means for storing products selected by a user from among the home delivery products in the storage means, a recommended product acquisition means for acquiring recommended products for the user from among the home delivery products, a recommended product setting means for storing the recommended products in the storage means, and an order processing means for executing order processing for the products stored in the storage means.

Description

[Technical Field]

[0001] The present invention relates to a product ordering device and a product ordering program. [Background technology]

[0002] One of the recommendation technologies used in online shopping and e-commerce (EC) sites is personalized recommendation, which uses an algorithm to analyze a user's past purchase history and browsing history to recommend products that the user is likely to purchase, with the aim of improving customer convenience and increasing customer unit prices (see, for example, Patent Documents 1 and 2).

[0003] Non-Patent Document 1 also describes multiple recommendation engines each with their own characteristics. For example, in the case of an e-commerce site that provides a regular home delivery service for organic vegetables, a novelty engine recommends new products based on the customer's preferences, and then a repetition engine recommends repurchases. If a purchase is made at this time, the purchase interval is determined, and a periodicity engine recommends the product at the time that is considered optimal for each customer, thereby leading to regular product purchases. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2018-181135 [Patent Document 2] Japanese Patent Application Publication No. 2024-137518 [Non-patent literature]

[0005] [Non-Patent Document 1] "Nikkei Computer" Nikkei BP, November 12, 2015 issue, pp. 58-61 Summary of the Invention [Problem to be solved by the invention]

[0006] Personalized recommendations are a technology that predicts demand for each individual customer, based on "who is likely to buy what, when," and recommends products to that customer at a time when they are most effective, thereby increasing the average customer spending.

[0007] However, while recommended products have traditionally been displayed in areas such as the recommended product display area on e-commerce sites, even for recommended products that users are highly likely to purchase, there is still a step or process required for users to discover the product from the countless products on the e-commerce site and select it (move it to the cart) before they can place an order (purchase it).In addition, in recent years, it has been said that the usability of e-commerce sites (for example, simplification and simplification of the process leading up to the completion of a purchase) has an impact on sales, and this is particularly noticeable for smartphone users.

[0008] The present invention has been proposed in view of the above points, and in one aspect, aims to further improve personalized recommendations and increase the average customer spending, etc. [Means for solving the problem]

[0009] In order to solve the above problems, a product ordering device according to the present invention comprises: A fixed-term order period for delivery items A product ordering device for a regular home delivery service, In the product storage area for order processing a storage means for storing the After the order start date and time of the order period and before the order deadline date and time, Items selected by the user from among the delivery items Order processing product storage area a user-selected product setting means for storing the selected product in the Determined by the product recommendation system a recommended product acquisition means for acquiring recommended products for the user; The user-selected product setting means excludes products that overlap with products already stored in the product storage area for order processing at a time point after the order start date and time of the order period and before the order deadline date and time by a predetermined time. The recommended products The order processing target product storage area a recommended product setting means for storing the recommended product in the The order processing target product storage area an order processing means for executing order processing for the merchandise stored in the The recommended products are products that the user has previously purchased based on the user's past purchase history of home delivery products and for which the current term falls within the purchase cycle for the user. [Effects of the Invention]

[0010] According to an embodiment of the present invention, in one aspect, personalized recommendations can be further improved, and the average customer spending can be increased. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of the configuration of a regular home delivery product recommendation system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating an example of a functional configuration of a recommendation machine according to the present embodiment. [Figure 3] FIG. 1 is a diagram (part 1) illustrating a recommendation engine according to the present embodiment. [Figure 4] FIG. 2 is a diagram (part 2) illustrating a recommendation engine according to the present embodiment. [Figure 5] FIG. 10 is a diagram (part 3) for explaining the recommendation engine according to the present embodiment. [Figure 6] FIG. 2 is a diagram illustrating a top screen of an EC site according to the present embodiment. [Figure 7] FIG. 1 is a diagram illustrating a cart screen 1 of an EC site according to the present embodiment. [Figure 8] FIG. 2 is a diagram illustrating a cart screen 2 of an EC site according to the present embodiment. [Figure 9] FIG. 2 is a diagram illustrating a cart screen 3 of an EC site according to the present embodiment. [Figure 10] FIG. 4 is a diagram illustrating a cart screen 4 of an EC site according to the present embodiment. [Figure 11] FIG. 10 is a diagram illustrating a cart screen 5 of an EC site according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail with reference to the drawings. [Embodiment 1] <System configuration> Fig. 1 is a diagram showing an example of the configuration of a regular delivery product recommendation system according to this embodiment. The regular delivery product recommendation system 100 in Fig. 1 includes an online delivery shopping server 10, a recommendation machine 20, various DBs (databases) 30, and a user terminal 40, all of which are connected via a network 50.

[0013] The home delivery online shopping server (product ordering device) 10 is a web server that provides an e-commerce site for a business that operates a regular home delivery service for products such as groceries and daily necessities. Users (members) of the regular home delivery service access and log in to the e-commerce site using a user terminal 40, and select and order products for delivery. On the e-commerce site, the products for delivery are displayed categorized in a predetermined product display column, and a recommended product display area is provided in which recommended products (recommended products) determined by a recommendation machine 20 are displayed.

[0014] The recommendation machine 20 has multiple recommendation engines (described later) and is a product recommendation device that analyzes and calculates the past purchase history (purchase history) of each user, and determines (decides) products that the user is likely to purchase from among home delivery products. The recommended products are output and displayed to the user on the EC site.

[0015] The user terminal 40 is, for example, a PC (personal computer), smartphone, tablet terminal, or the like, and is the terminal of a user who uses the regular home delivery service. A predetermined application program and a general-purpose web browser for accessing and logging in to the EC site of the online home delivery shopping server 10 are pre-installed on the user terminal 40. The user accesses and logs in to the EC site using the user terminal 40, selects and orders (purchases) items for delivery. The ordered items are delivered to a destination such as a home according to a delivery schedule. In general, with regular home delivery services, there is a set period during which orders can be placed, and orders are placed within a set period each week, with the items being delivered on a set day of the week after the order deadline.

[0016] (Functional configuration) 2 is a diagram showing an example of the functional configuration of the online home delivery shopping server according to this embodiment. The online home delivery shopping server 10 according to this embodiment has, as its main functional units, a cart storage unit 101, a user-selected product setting unit 102, a recommended product acquisition unit 103, a recommended product setting unit 104, a cart product display unit 105, and an order processing unit 106.

[0017] The cart storage unit 101 has a function of storing products to be processed in the cart (storage area for products to be processed in the order).

[0018] The user-selected product setting unit 102 has a function of storing the product selected by the user from among the home delivery products (product A to be processed for order processing) in the cart (storage area for products to be processed for order).

[0019] The recommended product acquisition unit 103 has a function of acquiring recommended products for the user from among home delivery products, from the recommendation machine 20 (product recommendation unit 201).

[0020] The recommended product setting unit 104 has a function of storing the recommended product (product B to be processed for order) recommended and acquired from home delivery products by the recommendation machine 20 in the cart (storage area for products to be processed for order).

[0021] The cart product display unit 105 has a function of displaying to the user the products (product A and product B to be processed for order processing) stored in the cart (storage area for products to be processed for order processing).

[0022] The order processing unit 106 has a function of executing order processing for products (product A and product B to be processed for order processing) stored in the cart (storage area for products to be processed for order processing). Product order processing is processing that occurs after an order is placed, and more specifically, includes processing for settling the product price, shipping the ordered products, etc.

[0023] The delivery online shopping server 10 can be implemented using a general-purpose computer. Specifically, the delivery online shopping server 10 includes hardware such as a processing unit (e.g., a CPU), memory, an input / output interface, and a communication interface. The functions of the delivery online shopping server 10 are realized by the processing unit executing processes in accordance with a computer program stored in memory. That is, each functional unit is implemented by a computer program executed on the hardware resources, such as the processing unit and memory, of the computer that constitutes the delivery online shopping server 10. These functional units may also be referred to as "means," "module," "unit," or "circuit." Some of the functional units may be located in the memory of the delivery online shopping server 10 or in an external storage device on a network. Each functional unit of the delivery online shopping server 10 may not only be implemented by a single server device, but may also be implemented as a system consisting of multiple devices with distributed functions. The computer program may also be stored on a computer-readable storage medium.

[0024] (Database) The DB 30 according to this embodiment includes a user DB, a product DB, a product purchase history DB, and order delivery schedule information. The user DB is a DB in which user information of members who use the regular home delivery service is registered, such as the user's membership ID, name, age, address, family, preferences, membership enrollment date, and membership duration, as well as login information for logging in to the EC site of the online home delivery shopping server 10, such as a login ID and login password.

[0025] The product DB is a DB (product master) in which products sold as home delivery products are registered. Product information includes, for example, product code, product name, JAN code, product category, price, content volume, stock quantity, manufacturer, etc. Products to be recommended are selected from the products registered in the product DB.

[0026] The product purchase history DB is a DB that records the purchase history (purchase history) of products purchased by users in the past. It includes at least product purchase history information for each user, such as the purchase date and time, product code, product name, purchase price, purchase quantity, and purchase count.

[0027] The order delivery schedule information is information regarding the period during which products can be ordered and the delivery date. Generally, in the case of a regular delivery service, the period during which orders can be placed is set, and orders are placed during a fixed period each week, with the products being delivered on a fixed day of the week. For example, in the case of a weekly regular delivery service, users can order products during the order period from 12:00 AM on Tuesday (order start date and time) to 12:00 PM on Sunday (order deadline date and time). Orders for the current week are closed at the order deadline date and time, and the ordered products are delivered, for example, on Wednesday of the following week. Note that the order delivery schedule information may be set individually for each region based on the user's address. It may also be set for two or more terms each week.

[0028] (Recommendation engine) 3 is a diagram (part 1) illustrating a recommendation engine according to this embodiment. As shown in FIG. 3, the recommendation machine 20 according to this embodiment has a recommendation engine (recommendation engine program) with a plurality of different algorithms, including, for example, a novelty engine, a repetition engine, a periodicity engine, and a preference engine.

[0029] The novelty engine is a recommendation engine that encourages first-time purchases. The novelty engine has the function of recommending new products that the user has not purchased before, such as new products and promotional products, and contributes to expanding the range of items purchased.

[0030] The repeatability engine is a recommendation engine that encourages repeat purchases. The repeatability engine has the function of recommending products that the user has purchased once in the past, contributing to increasing purchasing frequency.

[0031] The periodicity engine is a recommendation engine that encourages third or more purchases. The periodicity engine has the function of recommending products that the user has purchased more than twice in the past, contributing to increasing purchasing frequency. The periodicity engine identifies the purchase periodicity (interval between purchases) of a product based on the purchase history of products that have been purchased repeatedly in the past, and encourages repurchase (repeat purchase) by recommending that product when the purchase period (for example, periodic week) arrives. Product recommendations by the periodicity engine can also be seen as a function to prevent users from forgetting to buy periodic products, which are experience products.

[0032] A preference engine is a recommendation engine that encourages the purchase of products that match the preferences of the user. In the case of a preference engine, products that can be recommended include new products and experience products. For example, based on information in user information such as preferences, age, family, and / or preference information based on the user's purchasing history, it can recommend new products (for situations where you want to encourage a first-time purchase) and experience products (for situations where you want to encourage multiple purchases or more), either alone or in combination with other novelty engines or periodicity engines.

[0033] FIG. 4 is a diagram (part 2) illustrating a recommendation engine according to this embodiment. Products recommended by a novelty engine are new products, while products recommended by a repetitive engine and a periodic engine are experienced products. The recommendation machine 20 calculates a score representing the user's likelihood of purchasing a product and a priority order based on the score for each product from among the multiple or numerous recommended products for each engine, and recommends products with higher priority based on the calculation results (recommendation priority lists for each recommendation engine) shown in FIG. 4 . The score for each engine can be calculated comprehensively by incorporating various parameters, such as the user's preferences (preference engine) in addition to the recommendation algorithm for each engine, as well as the product's market sales (popularity), the time since release, whether it is a standard product, seasonality, inventory volume, and sales promotion level (a weighted value indicating the degree to which the delivery service provider particularly wants to prioritize sales).

[0034] 5 is a diagram (part 3) for explaining the recommendation engine according to this embodiment. The recommendation process of the recommendation engine 20 will be explained using the following model case. Step S1: The recommendation engine 20 recommends a new product, product A, based on the novelty engine (or preference engine). At this time, it is assumed that the user has not purchased the new product (nth week).

[0035] Step S2: The recommendation engine 20 again recommends product A based on the novelty engine (or preference engine). At this time, it is assumed that the user has purchased the new product (week n+1). Information about the purchased product A is recorded as the first purchase history in the product purchase history DB together with the purchase date and time.

[0036] Step S3: The recommendation engine 20 recommends product A from among experienced products (purchased only once in the past) based on the repetition engine. At this time, it is assumed that the user has not purchased the new product (week n+2).

[0037] Step S4: Based on the repeatability engine, the recommendation engine 20 recommends product A from among experienced products (purchased only once in the past). At this time, it is assumed that the user has purchased the new product (week n+3). Information about the purchased product A is recorded as the second purchase together with the purchase date and time in the product purchase history DB. Furthermore, based on the product purchase history DB of the first purchase date and time (week n+1) and the second purchase date and time (week n+3), the recommendation engine 20 determines that the purchase interval (purchase cycle) for the user is two weeks, and stores information about the user, product A, and purchase cycle in association with each other.

[0038] Step S5: Based on the cycle engine, the recommendation engine 20 recommends product A, whose purchase cycle falls within the current week (this week), from among experienced products (purchased at least twice in the past) (week n+5). Note that the recommendation engine 20 does not recommend product A, which does not fall within the purchase cycle, in week n+4. In week n+4, the recommendation engine 20 may recommend some other product, such as another product whose purchase cycle falls within that week.

[0039] Step S6: Based on the periodicity engine, the recommendation engine 20 recommends product A (week n+7) from among experienced products (purchased at least twice in the past) whose purchase cycle falls within the current week (this week). In this way, the periodicity engine recommends product A at a periodic timing when the user is likely to purchase product A, thereby linking product A to regular purchases.

[0040] <Online shopping e-commerce site with home delivery> The EC site screen according to this embodiment is generated by the online home delivery shopping server 10 and displayed on the screen of the user terminal 40. A user accesses the EC site using the user terminal 40, enters the user's login ID and login password, and logs in to the EC site. A detailed explanation will be given below with reference to an example of the EC site screen.

[0041] (EC site screen) Fig. 6 is a diagram illustrating the top screen of the e-commerce site according to this embodiment. The top screen of the e-commerce site for user A shown in Fig. 6 includes, for example, a current logged-in user 401 as of October 1, 2024, a current date and time 402, an order delivery schedule for the current term 403, a cart item count display area 404, a recommended item display area 405, a content area 406, and the like.

[0042] In this embodiment, when a user "adds an item to a cart," it refers to selecting an item that the user wants to order or purchase from among the delivery options available on the e-commerce site and adding it to the shopping cart when purchasing an item on an e-commerce site. The action of adding an item to the cart is a step before finally ordering or purchasing the item. By adding an item to the cart, the user temporarily saves one or more items that the user wants to order or purchase. The user can, for example, select multiple items, check the total price all at once, and then perform the final purchase procedure for the items in the cart, without having to purchase each item individually. A cart may also be called, for example, an order cart, shopping cart, shopping basket, shopping bag, cash register, checkout cart, virtual order cart, virtual shopping cart, virtual shopping basket, virtual shopping bag, virtual cash register, or virtual checkout cart.

[0043] The recommended product display area 405 shown in Figure 6 includes a first recommended product display area 405a, a second recommended product display area 405b, and a third recommended product display area 405c. For example, the first recommended product display area 405a displays new products recommended by the novelty engine, the second recommended product display area 405b displays experience products recommended by the repetition engine and periodicity engine, and the third recommended product display area 405c displays new products or experience products recommended by the preference engine. The novelty engine encourages suggestions for new products and an expansion of purchased product items. The repetition engine and periodicity engine encourage repurchases (repeat purchases) by recommending experience products.

[0044] From the perspective of improving purchase frequency and unit price, each recommended product display area may be displayed not only on the top screen but also on other screens, taking into consideration the overall display balance of the recommended product display areas by each engine.

[0045] The number of items in the cart at the current time is displayed in the cart item count display area 404. While the number of items in the cart is usually 0 immediately after a user logs in to an EC site, in this embodiment the number of items in the cart is, for example, 5. That is, for example, 5 recommended items have already been added to the cart (storage area for items to be ordered). When the user presses the cart image, the screen transitions to the cart screen shown in FIG. 7.

[0046] Fig. 7 is a diagram illustrating a cart screen 1 of an e-commerce site according to this embodiment. The cart screen of the e-commerce site shown in Fig. 7 is a screen that displays the products in the user's cart. Specifically, the cart 411 according to this embodiment shown in Fig. 7 contains recommended products (e.g., experience products recommended by a periodicity engine) such as "eggs," "mayonnaise," "soy sauce," "rice," and "bread" as initial cart products immediately after login.

[0047] The home delivery online shopping server 10 (recommended product acquisition unit 103) acquires a predetermined number (e.g., five) of high-priority products or products with a predetermined score or higher from the recommendation machine 20, for example, based on the calculation results by the recommendation engine (each recommendation priority list for each recommendation engine in FIG. 4).Then, the home delivery online shopping server 10 (recommended product setting unit 104) sets the acquired products in advance in the user's cart (storage area for products to be ordered).

[0048] When the user wishes to order (purchase) the products in the initial cart that are marked with "Recommended" 415, indicating that they are recommended products, the user presses "Order (Purchase)" 412. The home delivery online shopping server 10 (order processing unit 106) executes the order process for the recommended products stored in the initial cart.

[0049] On the other hand, if there are any unnecessary products in the cart that the user does not want to order, the user presses "Delete" 414 for the unnecessary products (deletion operation means). The operated products are deleted from the cart. If the user wants to continue shopping for other items, the user presses "Continue Shopping" 413. When "Continue Shopping" 413 is pressed, the screen transitions to, for example, the top screen of the EC site again. The user selects the products they want to purchase and adds them to the cart.

[0050] 8 is a diagram illustrating a cart screen 2 of an e-commerce site according to this embodiment. Compared to the cart 411 shown in FIG. 7, the cart 411 shown in FIG. 8 has "rice" deleted by the user, and the products selected by the user, "canned beer" and "bananas," have been added to the cart (storage area for products to be ordered) with "add" 416 displayed to indicate that they are user-selected products. When the user finally orders (purchases) the products in the cart, by pressing "Order (Purchase)" 412, the home delivery online shopping server 10 (order processing unit 106) executes order processing for the products stored in the cart, including recommended products and user-selected products.

[0051] In this embodiment, products (especially recommended products) that a user has deleted from the cart are not completely erased from the cart display, but rather the deleted state is indicated by, for example, striking through the product name or making the text of the product name lighter, while the deleted product remains visible to the user on the cart display (deleted product display means).

[0052] Furthermore, even after a product has been deleted, the user can easily return the deleted product to the cart by pressing "Return" 417 for that product (for example, "rice") (means for canceling the deletion operation). In particular, if the product that the user has deleted is an experience product (periodic product) recommended by a periodicity engine intended to prevent the user from forgetting to buy periodic products, the possibility of the product being ordered can be increased at the stage when the user finally orders (purchases) the product in the cart.

[0053] In this way, the home delivery online shopping server 10 according to this embodiment sets recommended products suited to the user in the user's cart as products in the initial cart immediately after logging in. This allows the user to order (purchase) recommended products in the cart with simple operation steps, i.e., without having to select products (cart movement operation) by themselves.

[0054] Furthermore, since the products set in the initial setting cart are recommended products tailored to the user, they are products that the user has a particularly high likelihood of purchasing and expectation of purchasing. Therefore, the periodic home delivery product recommendation system 100 according to this embodiment utilizes personalized recommendation technology on e-commerce sites to increase the likelihood of users purchasing recommended products and their expectation of purchasing, thereby enabling further improvement in the average customer spending, etc.

[0055] In this regard, recommended products have traditionally been displayed in a recommended product display area on e-commerce sites, but no matter how likely or expected a user is to purchase a recommended product, in order to actually place an order (purchase), the user must first discover the product from the countless products available on the e-commerce site and then select the product (move it to the cart).In recent years, it has been said that usability on e-commerce sites (for example, simplification and simplification of the process leading up to the completion of a purchase) has an impact on sales, and this is particularly noticeable for smartphone users.

[0056] The following points are also mentioned: The recommended products may be set in the cart 411 as products in the initial cart immediately after the user logs in. Therefore, even before the user logs in for the first time, for example, between the end of the previous week's term and the start of the current week's term, the products in the initial cart may be set according to the user.

[0057] The products in the initial cart are particularly suitable for experience products recommended by a periodicity engine. The periodicity engine encourages repeat purchases by recommending products that have reached a purchase cycle (e.g., a periodic week) for the user, and experience products in the cart during that period have a high likelihood of being purchased by the user and a high expected purchase value. Product recommendations by the periodicity engine can also be seen as a function to prevent users from forgetting to buy periodic products.

[0058] On the other hand, the products in the default cart may be recommended products that are highly likely to be purchased by the user who has logged in as an e-commerce site, and therefore the recommended products may not only be experience products based on a periodicity engine, but also other products such as new products based on a novelty engine, or new or experience products based on a preference engine.

[0059] Items in the initial cart are different from items (user-selected items) that are added to the cart by the user themselves through product selection (cart movement operation). User-selected items include regular purchase items that have been registered (set) in advance by the user, and items that were selected by the user in the previous term and added to the cart but remain in the cart without being ordered (purchased).

[0060] The calculation process of recommended products by the recommendation machine 20 (for example, the process of creating and updating the recommendation priority list in FIG. 4) is performed before the recommended products are set as products in the initial cart, but the calculation process does not have to be performed in real time and may be performed, for example, once a week or once per term, from the viewpoint of reducing the load cost associated with an increase in calculation frequency. The home delivery online shopping server 10 can obtain information on recommended products in order of priority from the recommendation priority list at that time before the recommended products are set.

[0061] [Embodiment 2] For example, as shown in Figure 7 of the first embodiment, recommended products were set in the cart 411 as products in the initial cart immediately after the user logged in, but in this embodiment, the timing for setting recommended products in the initial cart is set just before the order deadline for that term. As described above, for example, in the case of a weekly regular home delivery service, users can order products during the order period from 12:00 AM every Tuesday (order start date and time) to 12:00 PM every Sunday (order deadline date and time).

[0062] FIG. 9 is a diagram illustrating a cart screen 3 of an EC site according to this embodiment. The cart screen of the EC site shown in FIG. 9 is a screen showing the products in the user's cart immediately after the order start date. The cart 411 according to this embodiment shown in FIG. 9 is empty as of 14:00 on 10 / 1 / 2024 immediately after the order start date, and no products have been added to the initial cart. The user is taken to the top screen of the EC site, where they can select the products they want to purchase, add them to their cart, and order (purchase) the products.

[0063] FIG. 10 is a diagram illustrating a cart screen 4 of an e-commerce site according to this embodiment. The cart screen of the e-commerce site shown in FIG. 10 is a screen showing the items in the user's cart immediately before the order deadline. Specifically, the cart 411 according to this embodiment shown in FIG. 10 contains recommended items (e.g., experience items recommended by a periodicity engine) such as "eggs," "mayonnaise," "soy sauce," "rice," and "bread" as initial cart items as of 9:00 AM on October 6, 2024, immediately before the order deadline.

[0064] That is, just before the order deadline, the home delivery online shopping server 10 (recommended product acquisition unit 103) acquires a predetermined number (for example, five) of high-priority products or products with a predetermined score or higher from the recommendation machine 20, for example, based on the calculation results by the recommendation engine (each recommendation priority list for each recommendation engine in FIG. 4).Then, the home delivery online shopping server 10 (recommended product setting unit 104) sets the acquired products in advance in the user's cart (storage area for products to be ordered).

[0065] The point immediately before the order deadline is a point after the order start date and time and a specified time before the order deadline. Specifically, this may be the day of the order deadline, one day before (24 hours before), or three days before (72 hours before).

[0066] In the cart screen 3 of the e-commerce site shown in Figure 9, the order start date and time for the term is immediately after the order start date and time, and there is still plenty of time until the order deadline. On the other hand, in the cart screen 3 of the e-commerce site shown in Figure 10, the order start date and time for the term is immediately after the order start date and time, and there is not much time until the order deadline. The home delivery online shopping server 10 according to this embodiment allows the user to order by selecting products themselves (moving the cart) when there is time until the order deadline, but when there is not much time left until the order deadline, it sets recommended products tailored to the user as products in the initial cart in the user's cart.

[0067] Furthermore, periodic products recommended by a periodicity engine are particularly suitable for the products set in the initial cart. The periodicity engine encourages repurchases (repeat purchases) by recommending products that are in the user's purchase cycle (e.g., periodic week) from the aspect of preventing the user from forgetting to buy products that are in their prime purchase period. Therefore, at the time of the order deadline when there is little time to spare, periodic products that are not yet in the order cart and that the user is likely to forget to buy can be recommended in the cart at the last moment, thereby further increasing purchase frequency and unit price.

[0068] 11 is a diagram illustrating a cart screen 5 of an e-commerce site according to this embodiment. In this case, the user first logs in to the e-commerce site immediately after the order start date, and from the empty cart, the user selects items they want to purchase, such as "soy sauce," "rice," "bread," "canned beer," and "banana," and adds them to the cart. The user then logs out, and then logs in again to the e-commerce site at 9:00 AM on October 6, 2024, the day of the order deadline, i.e., just before the order deadline.

[0069] The cart screen of the e-commerce site shown in Fig. 11 is a screen that shows the products in the user's cart in this case. Specifically, in addition to the user-selected products "soy sauce," "rice," "bread," "canned beer," and "banana," the cart 411 according to this embodiment shown in Fig. 11 also contains recommended products (e.g., experience products recommended by a periodicity engine) such as "eggs" and "mayonnaise" as initial cart products immediately before the order deadline.

[0070] Note that "soy sauce," "rice," and "bread," which have already been added to the cart by the user, overlap with the recommended products and are therefore excluded from the products in the initial cart. The home delivery online shopping server 10 (recommended product setting unit 104) compares the products acquired from the recommendation machine 20 with the products already added to the cart by the user, excludes the overlapping products, and sets the remaining acquired products in the user's cart (storage area for products to be ordered).

[0071] [Embodiment 3] For example, as shown in Figure 7 of the first embodiment, if a user does not order (purchase) an item in the initial cart, the user can delete the item in the initial cart and mark it as not being purchased. Here, the home delivery online shopping server 10 sends feedback to the recommendation machine 20, for each item in the initial cart set in the cart, whether it was ordered (purchased) by the user or deleted by the user and not ordered (purchased), i.e., information on the purchase result.

[0072] As described above, the score for each engine can be calculated comprehensively by incorporating various parameters in addition to the recommendation algorithm for each engine. From the next time onwards, when calculating the score representing the user's purchase possibility and expected purchase value for each product and the priority order based on the score, the recommendation machine 20 will also reflect information on the purchase results of the products in the initial cart (recommended products).

[0073] More specifically, in the cart 411 according to this embodiment shown in FIG. 7, recommended products (e.g., experience products recommended by a periodicity engine) such as "eggs," "mayonnaise," "soy sauce," "rice," and "bread" are included as products in the initial cart immediately after login. If the recommended "rice" among these is deleted by the user and not ordered (purchased), the recommendation machine 20 reflects the purchase result indicating the non-purchase of "rice" in parameters, etc., and recalculates the score for "rice," which represents the user's purchase possibility and expected purchase value, to be lower. As a result, from the next week term onwards, "rice" will be less likely to be included in the user's initial cart compared to other products, and other products will be more likely to be included instead.

[0074] On the other hand, if the user orders (purchases) "eggs," "mayonnaise," "soy sauce," and "bread" other than the recommended "rice," the recommendation machine 20 reflects the purchase results indicating the purchase of "eggs," "mayonnaise," "soy sauce," and "bread" in the parameters, etc., and recalculates the scores representing the user's purchase possibility and expected purchase value for "eggs," "mayonnaise," "soy sauce," and "bread" to be higher. As a result, from the next week term onwards, "eggs," "mayonnaise," "soy sauce," and "bread" are more likely to be included in the user's initial cart relative to other products.

[0075] While the present invention has been described with reference to specific examples in accordance with preferred embodiments thereof, it will be apparent that various modifications and changes can be made to these examples without departing from the broader spirit and scope of the present invention as defined in the appended claims. In other words, the details of the examples and the accompanying drawings should not be construed as limiting the present invention. [Explanation of symbols]

[0076] 10. Online delivery shopping server 20 Recommendation Machine 30 DB 40 User terminals 50 Network 100 Delivery product recommendation system 101 Cart memory section 102 User-selected product setting section 103 Recommendation Product Acquisition Department 104 Recommendation Product Setting Department 105 Cart product display section 106 Order Processing Unit 201 Product Recommendation Department

Claims

1. A product ordering device for a fixed-term regular home delivery service in which a period during which home delivery products can be ordered is set, a storage means for storing products to be processed in a storage area for products to be processed; a user-selected product setting means for storing a product selected by a user from among home delivery products in an order processing target product storage area after the order start date and time of the order period and before the order cut-off date and time; a recommended product acquisition means for acquiring recommended products for the user determined by the product recommendation device from among home delivery products; a recommended product setting means for storing the recommended products, excluding products that overlap with products already stored in the order processing target product storage area by the user-selected product setting means, in the order processing target product storage area at a time point after the order start date and time of the order period and before the order cut-off date and time by a predetermined time; an order processing means for executing order processing for the products stored in the order processing target product storage area; and The recommended product is Based on the user's past purchase history of home delivery products, the product is one that the user has purchased in the past and the current term corresponds to a purchase cycle for the user; A product ordering device comprising:

2. A computer that is a product ordering device for a fixed-term regular home delivery service in which a delivery product can be ordered during a specified period, a storage means for storing products to be processed in a storage area for products to be processed; a user-selected product setting means for storing a product selected by a user from among home delivery products in an order processing target product storage area after the order start date and time of the order period and before the order cut-off date and time; a recommended product acquisition means for acquiring recommended products for the user determined by the product recommendation device from among home delivery products; a recommended product setting means for storing the recommended products, excluding products that overlap with products already stored in the order processing target product storage area by the user-selected product setting means, in the order processing target product storage area at a time point after the order start date and time of the order period and before the order cut-off date and time by a predetermined time; an order processing means for executing order processing for the products stored in the order processing target product storage area; and make it work, The recommended product is Based on the user's past purchase history of home delivery products, the product is a product that the user has previously purchased and for which the current term falls within the purchase cycle of the user. Product ordering program.

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