Content distribution system

Abstract

To provide a content distribution system capable of distributing product information or store information related to customer purchase history information while increasing affinity with user preference.SOLUTION: A content distribution system 10, which distributes content tailored to user preference, includes: a user information acquisition unit 28 that acquires user attribute information including a group identifier; a history information storage unit 44 that records user purchase information in association with the group identifier; a user feature calculation unit 30 that calculates, on the basis of the user purchase information and the group identifier, the user feature of a user; and a content distribution unit 38 that stores content information including information on a product or a store recommended to the user, and distributes it to user terminals of each user. The content distribution unit 38 determines, on the basis of the user feature calculated by the user feature calculation unit 30, the content information that is expected to interest the user.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This application relates to a content delivery system.

Background Art

[0002] In recent years, with the development of information processing technology, businesses that provide products or services have widely conducted sales activities of proposing products or services to users via user terminals. For example, Patent Document 1 discloses a sales promotion support device used for such purposes. Specifically, the sales promotion support device includes a customer identification unit that identifies customers who have purchased a product when the product is sold, and a purchase history storage unit that stores the purchase history of the product for the customers identified by the customer identification unit. Further, the sales promotion support device includes a product setting unit that sets service target products based on the selection desires of customers, and a service provision determination unit that determines whether to provide a service associated with the service target products based on the purchase history of the service target products. Therefore, the sales promotion support device can provide services to customers via a service provision instruction unit.

[0003] However, in the provision of such products or services, since it is limited to the provision of products or services within the range related to the selection desires of customers, it is not always easy for businesses to widely make their own products or services recognized, and it may be difficult to lead to the discovery of potential needs of customers beyond the range related to the selection desires of customers. For this reason, it is preferable to provide products or services via a user terminal while enhancing the affinity between customers and businesses.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In view of the above problems, an object of the present invention is to provide a content distribution system that can distribute product information or store information related to customer purchase history information while enhancing the affinity with user preferences.

Means for Solving the Problems

[0006] One aspect of the present disclosure is a content distribution system that distributes content according to user preferences, including a user information acquisition unit that acquires user attribute information including a group identifier, a history information accumulation unit that records user purchase information in association with the group identifier, a user feature calculation unit that calculates user features based on the user's purchase information and the group identifier, and a content distribution unit that accumulates content information including information on products or stores recommended to the user and distributes it to the user terminals of each user. The content distribution unit is characterized in that it determines content information that is presumed to be of interest to the user based on the user features calculated by the user feature calculation unit.

[0007] Also, in one aspect of the present disclosure, the purchase information includes purchase history information of food and beverages, and the content distribution unit may distribute content information related to food and beverage stores based on the purchase history information.

[0008] Furthermore, in one aspect of the present disclosure, the purchase information includes store visit history information of food and beverage stores, and the content distribution unit may distribute content information related to food and beverages based on the store visit history information.

[0009] Also, in one aspect of the present disclosure, the user attribute information may include location information.

[0010] Furthermore, in one aspect of the present disclosure, the content information related to food and beverage stores may include information related to food and beverage stores that provide food and beverages having the same group identifier as the information related to the food and beverages included in the purchase history information of food and beverages.

[0011] In addition, in one aspect of the present disclosure, the content information regarding the food and beverage store may include privilege information regarding the food and beverage store.

[0012] Furthermore, in one aspect of the present disclosure, the content information regarding the food and beverage may include information regarding the food and beverage having the same group identifier as the information regarding the food and beverage provided in the food and beverage store included in the store visit history information of the food and beverage store.

[0013] In addition, in one aspect of the present disclosure, the content information regarding the food and beverage may include information regarding newly released food and beverage and / or information regarding the retail store that sells the food and beverage.

[0014] Furthermore, in one aspect of the present disclosure, there is provided a content distribution method for distributing content according to a user's preference, including obtaining user attribute information including a group identifier, recording the user's purchase information in association with the group identifier, calculating the user's user characteristics based on the user's purchase information and the group identifier, accumulating content information including information regarding products or stores recommended to the user, and distributing the content information to the user terminals of each user, and determining content information that is presumed to be of interest to the user based on the calculated user characteristics.

[0015] In addition, in one aspect of the present disclosure, the purchase information includes purchase history information of food and beverage, and accumulating content information including information regarding products or stores recommended to the user and distributing the content information to the user terminals of each user may include accumulating the purchase history information and distributing content information regarding the food and beverage store based on the accumulated purchase history information.

[0016] Furthermore, in one aspect of the present disclosure, the purchase information includes store visit history information of the food and beverage store, and accumulating content information including information regarding products or stores recommended to the user and distributing the content information to the user terminals of each user may include accumulating the store visit history information and distributing content information regarding the food and beverage based on the accumulated store visit history information.

Advantages of the Invention

[0017] According to one aspect of the present disclosure, a content delivery system can obtain user attribute information including a group identifier by a user information acquisition unit, and record the purchase information of a user in association with the group identifier by a history information storage unit. Further, according to the content delivery system, a user feature calculation unit can calculate the user features of a user based on the purchase information of the user and the group identifier. Furthermore, the content delivery unit can determine content information that is presumed to be of interest to the user from among content information including information on products or stores recommended for the user stored in the content delivery unit, based on the user features calculated by the user feature calculation unit, and deliver the content information to the user's user terminal. Therefore, it is possible to deliver content information while estimating the potential needs of the user not only within the range of the user's purchase information but also outside this range. Thereby, it is possible to deliver product information or store information related to the customer's purchase history information while enhancing the affinity with the user's preferences.

[0018] Also, according to one aspect of the present disclosure, the purchase information includes purchase history information of food and beverages, and the content delivery unit can deliver content information related to food and beverage stores based on the purchase history information. Therefore, for example, it is possible to deliver content information related to food and beverage stores while broadly estimating the potential needs of the user. Thereby, it is possible to deliver related product information or store information based on the customer's purchase history information while enhancing the affinity with the user's preferences.

[0019] Furthermore, according to one aspect of the present disclosure, the purchase information includes visit history information of food and beverage stores, and the content delivery unit can deliver content information related to food and beverages based on the visit history information. Therefore, for example, it is possible to deliver content information related to food and beverages while broadly estimating the potential needs of the user. Thereby, it is possible to deliver related product information or store information based on the customer's purchase history information while enhancing the affinity with the user's preferences.

[0020] Also, according to one aspect of the present disclosure, the user attribute information can include location information. Therefore, for example, not only within the activity range of the user's daily life, but also while broadly estimating the user's potential needs, content information regarding food and beverages and food and beverage stores at locations outside the activity range of the user's daily life can be distributed. Thereby, while enhancing the affinity with the user's preferences, relevant product information or store information based on the customer's purchase history information can be distributed.

[0021] Furthermore, according to one aspect of the present disclosure, the content information regarding a food and beverage store can include information regarding a food and beverage store that provides food and beverages having the same group identifier as the information regarding the food and beverages included in the purchase history information of the food and beverages. Therefore, content information including food and beverage stores that the user has never visited or food and beverages that the user has never purchased can be distributed to the user. Thereby, the user's potential needs can be discovered, and the affinity between the user and the merchant can be further enhanced.

[0022] Also, according to one aspect of the present disclosure, the content information regarding a food and beverage store can include privilege information regarding the food and beverage store. Therefore, the incentive for the user to visit the food and beverage store can be improved. Thereby, the opportunity to discover the user's potential needs can be increased, and the affinity between the user and the merchant can be further enhanced.

[0023] Furthermore, according to one aspect of the present disclosure, the content information regarding food and beverages can include information regarding food and beverages having the same group identifier as the information regarding the food and beverages provided at the food and beverage stores included in the store visit history information of the food and beverage stores. Therefore, content information including food and beverages that the user has never purchased can be distributed to the user. Thereby, the user's potential needs can be discovered, and the affinity between the user and the merchant can be further enhanced.

[0024] Further, according to one aspect of the present disclosure, it can include information on newly released food and beverages, and / or information on retail stores that sell food and beverages. Therefore, content information including newly released food and beverages that the user has never purchased and retail stores that the user has never visited can be distributed to the user. Thereby, potential needs of the user can be explored, and the affinity between the user and the merchant can be further enhanced.

[0025] Furthermore, according to one aspect of the present disclosure, the content distribution method can acquire user attribute information including a group identifier and record the purchase information of the user in association with the group identifier. Also, according to the content distribution method, the user characteristics of the user can be calculated based on the purchase information and group identifier of the user. Furthermore, according to the content distribution method, content information including information on products or stores recommended for the user is accumulated, and based on the calculated user characteristics, content information that is presumed to be of interest to the user is determined and distributed to the user's user terminal. Therefore, content information can be distributed while estimating the potential needs of the user not only within the range of the user's purchase information but also outside this range. Thereby, while enhancing the affinity with the user's preferences, product information or store information related to the customer's purchase history information can be distributed.

[0026] Also, according to one aspect of the present disclosure, the purchase information includes purchase history information of food and beverages, and according to the content distribution method, content information on food and beverage stores can be distributed based on the purchase history information. Therefore, for example, content information on food and beverage stores can be distributed while broadly estimating the potential needs of the user. Thereby, while enhancing the affinity with the user's preferences, relevant product information or store information based on the customer's purchase history information can be distributed.

[0027] Furthermore, according to one aspect of the present disclosure, the purchase information includes the visit history information of the food and beverage store, and according to the content distribution method, content information regarding food and beverages can be distributed based on the visit history information. Therefore, for example, it is possible to widely promote potential needs of users while distributing content information regarding food and beverages. As a result, it is possible to distribute relevant product information or store information based on the purchase history information of customers while enhancing the affinity with the preferences of users.

Brief Description of Drawings

[0028]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Mode for Carrying Out the Invention

[0029] Hereinafter, with reference to the accompanying drawings, a content distribution system according to an embodiment will be described. The same or corresponding elements are denoted by the same reference numerals, and redundant descriptions will be omitted. For ease of understanding, the scale of the drawings may be changed for the description.

[0030] FIG. 1 shows an exemplary conceptual diagram of a content distribution system 10 (hereinafter referred to as "system 10") according to an embodiment. The system 10 includes, for example, a server 12 installed by a merchant who provides goods and / or services or installed by a server operator entrusted by the merchant, a merchant terminal 14 installed and owned by the merchant, and a user terminal 16 owned by a user as a customer who receives the provision of goods and / or services.

[0031] The server 12, the merchant terminal 14, and the user terminal 16 are configured to be communicable via a network NW. The network NW can use, for example, the Internet, WiFi (registered trademark), Bluetooth (registered trademark), a wireless communication system based on a communication standard such as 3G or 5G (3rd, 5th Generation Mobile Communication System), or other communication methods, or any combination thereof, and can use wired or wireless or a combination thereof. Thereby, as will be described later, the system 10 can distribute content information including information regarding goods or stores recommended by the merchant based on the user attribute information and purchase information input by the user via the user terminal 16 from the server 12.

[0032] As shown in FIG. 2, the server 12 includes, for example, a communication unit 22, a processing unit 24, a storage unit 26, and an input unit (not shown), and these components are electrically connected to each other by, for example, a bus or the like. Note that the server 12 may include components other than the above-described components. Further, instead of using the server 12 to exhibit the functions as in the present embodiment, a computer, a tablet, a smartphone, or other devices having arithmetic processing functions and / or communication functions may be used.

[0033] The communication unit 22 includes a communication interface circuit for connecting the server 12 to the network NW and communicating with the merchant terminal 14 and the user terminal 16. The processing unit 24 is configured to be able to acquire user attribute information and determine content information including information on products or stores recommended to the user, and includes, for example, one or more CPUs (Central Processing Unit). Note that the processing unit 24 may alternatively or additionally include an independent integrated circuit, a microprocessor, and / or firmware.

[0034] The storage unit 26 is configured to store user attribute information and content information, and includes, for example, a storage device such as a ROM (READ ONLY MEMORY), a RAM (RANDOM ACCESS MEMORY), and a hard disk drive. The storage unit 26 is also configured to be able to store various programs executed by the processing unit 24. Note that the programs executed by the processing unit 24 are not limited to those stored in the storage device from the beginning, and may be stored in the storage unit using, for example, a known setup program or the like from a computer-readable portable recording medium such as a CD-ROM or a DVD-ROM.

[0035] As shown in FIG. 1, the merchant terminal 14 is configured to create content information to be distributed to the user or to receive it from outside the merchant terminal 14 and accumulate the content information. For example, it may be a computer, a server, a tablet, a smartphone, or other communicable device. In the following, the server 12 and the merchant terminal 14 will be described as being separately provided, but the present invention is not limited to this. For example, without providing a server, the merchant terminal may perform all processes from acquisition of user attribute information to distribution of content information in a unified manner.

[0036] The user terminal 16 is configured such that the user can input user attribute information and receive and confirm content information. For example, it may be a mobile phone such as a smartphone or a feature phone, a tablet, or a personal computer. Further, dedicated application software for inputting user attribute information and receiving and confirming content information may be installed in the user terminal 16. Furthermore, the user terminal 16 may include, for example, a CPU, a ROM, a RAM, a storage device such as a hard disk drive, and / or an input device and / or a display device such as a touch panel, a mouse, a keyboard, and a liquid crystal display.

[0037] The user attribute information input from the user terminal 16 includes, for example, information such as a user ID, the user's name, the user's gender, date of birth, and location information (address and postal code of the place of residence or workplace). These user attribute information are used in the processing unit 24 as so-called user identifier information for simply recognizing the user or as group identifier information used as an index when segmenting the user. Each user attribute information is defined as user identifier information or group identifier information according to the content of the content information to be distributed and the purpose of distributing the content information.

[0038] In addition, the purchase information of the user input from the user terminal 16 includes history information such as the purchase history including the user's product purchase date and the store visit history including the date of receiving the service, and not limited to the cost information, but also includes information related to the products purchased by the user and information related to the stores visited by the user. These product information and store information are also used as group identifier information when segmenting users according to the content of the content information to be distributed and the purpose of distributing the content information. The server 12 can identify and acquire the purchase information from the text information input by the user from the user terminal 16 and the image information transmitted from the user terminal 16. Specifically, the server 12 is configured to read information from image information such as the photo 18 of the store where the user visited and the products purchased and the photo 20 of the receipt for payment and product purchase at the store among the images transmitted from the user terminal 16, so as to identify the product information and the store information.

[0039] In FIG. 1, the photos 18 and 20 show, as an example of products and services, photos 18 of food and beverages and food and beverage stores and photos 18 of their receipts. Here, the food and beverages mentioned refer to all foods and beverages (excluding pharmaceuticals, quasi-drugs, and products such as regenerative medicine defined by laws regarding the quality, effectiveness, and safety of pharmaceuticals, medical devices, etc.), regardless of whether they are cooked or not. Also, the beverages mentioned here include both alcoholic beverages and non-alcoholic beverages. The alcoholic beverages include, for example, beer, alcoholic carbonated beverages other than beer, i.e., sparkling sake, sparkling alcoholic beverages with a beer flavor infused with another alcoholic beverage manufactured from raw materials other than malt (so-called third beer), chu-hai, cocktail sour, umeshu soda, spirit soda, sparkling sake, sparkling wine, or highballs and other various beverages. The non-alcoholic beverages include non-alcoholic carbonated beverages, i.e., non-alcoholic beer, non-alcoholic spirits, non-alcoholic wine, non-alcoholic sour, non-alcoholic cocktail, or carbonated juice and other various beverages. These beverages also include concentrated beverages (stock solutions).

[0040] As shown in FIG. 2, the processing unit 24 of the server 12 includes a user information acquisition unit 28, a user feature calculation unit 30, and a content distribution unit 38. The user information acquisition unit 28 is configured to acquire user attribute information input by the user on the user terminal 16 and record it in the storage unit 26. Further, the user feature calculation unit 30 is configured to determine content information to be distributed for each segment of the user based on the user attribute information. Furthermore, the content distribution unit 38 is configured to distribute the content information determined by the user feature calculation unit 30 to the user terminal 16 of the users belonging to the segment.

[0041] The storage unit 26 includes a user information storage unit 40, a content information storage unit 42, and a history information storage unit 44. The user information storage unit 40 is configured to record user attribute information input by the user on the user terminal 16. The content information storage unit 42 is configured to record product information and store information created by merchants for distribution to users. Further, the history information storage unit 44 is configured to record purchase information of the user input from the user terminal 16. Furthermore, the storage unit 26 includes a product information storage unit 46 and a store information storage unit 48. In the product information storage unit 46, information about products such as product images and JAN codes is stored so that products can be specified from the purchase information of the user input from the user terminal 16. In the store information storage unit 48, information about stores such as D codes is stored so that stores can be specified from the purchase information of the user input from the user terminal 16.

[0042] The user feature calculation unit 30 includes a score calculation unit 32, a content feature calculation unit 34, and a matching determination unit 36. The score calculation unit 32 defines one or more pieces of information to be used as group identifier information from the user attribute information and the user's purchase information according to the content of the content information to be distributed and the distribution purpose of the content information. The group identifier information defined in this way is weighted according to the relevance to the distribution purpose, that is, scored, and the score (the sum of scores when using a plurality of pieces of group identifier information), that is, the score as the user feature is calculated. A user whose score exceeds a predetermined value is determined as a user with a high relevance to the distribution purpose and is extracted as a matching target, that is, segmented (see step S40 in FIG. 3). Further, the content feature calculation unit 34 extracts features along the distribution purpose from the accumulated content information (see step S50 in FIG. 3) and quantifies these features, that is, calculates feature values. Here, the user features for calculating the feature values include, as specific examples, area information, category information, purchase segment information, and purchase brand information. The area information can include the location of the store where the user purchased the product and the store where the user visited (for example, Shibaura 3-chome, Minato-ku, Tokyo, etc.). The category information can include, for example, the category information of the product (beverage) purchased or consumed by the user from the pre-defined product category information such as alcoholic beverages or non-alcoholic beverages (for example, alcoholic beverages, etc.). Further, the purchase segment information can include, for example, the purchase segment information of the product (beverage) purchased or consumed by the user from the pre-defined purchase segment information such as beers / chu-hais / shochus / wines / sakes / health teas / (for example, high-quality beers among beers, etc.). The purchase brand information can include, for example, the purchase brand information of the product (beverage) purchased or consumed by the user from the pre-defined purchase brand information such as class S (ultra-high quality) / class A (high quality) / class B (superior quality) / class C (mass production quality) (for example, ultra-high quality beers among class S (ultra-high quality), etc.).

[0043] Furthermore, the matching determination unit 36 quantitatively determines whether the combination of the segmented user groups and the content information matches the distribution purpose by using the scores and feature values. Based on this, the content information to be distributed to the segmented user groups is determined (see step S60 in FIG. 3). The series of processes executed by the user feature calculation unit 30 in this way can be executed by any method of machine learning (AI), a program other than machine learning created in advance, or the manual calculation of a merchant. The content distribution unit 38 distributes the content information determined by the user feature calculation unit 30 to the segmented user groups (see step S70 in FIG. 3) and ends the process (see step S80 in FIG. 3).

[0044] The flow of distributing content information in the system 10 will be described while associating the flowchart of the content information processing in the server 12 shown in FIGS. 3, 7, and 10 with the display screen 50 of the user terminal 16 shown in FIGS. 4 to 14(b).

[0045] FIG. 4 shows the display screen 50 of the user terminal 16 on which the start screen of the application software related to the system 10 is displayed. When the user starts this application software, the processing flow of the server 12 shifts to step S10 shown in FIG. 3.

[0046] When the user inputs the user ID and logs in, the server 12 shifts to step S20 and acquires the attribute information of the user registered at the first startup of the application software (information such as the user's gender, date of birth, place of residence, or the address and postal code of the place of work, etc.).

[0047] The logged-in user can input purchase information and food and beverage consumption history via the display screen 50 (menu screen) shown in FIG. 5. In the example shown in FIG. 5, on the menu screen 50, there are a point display section D1 that displays points given by the merchant when the user inputs purchase information and the like, and input buttons B1 to B5 for inputting purchase information and the like. The input buttons B1 to B5 are configured such that when purchase information and the like are input via them, points are given to the user by the merchant. Therefore, the incentive for the user to input purchase information and food and beverage consumption history can be enhanced. Here, on the menu screen 50, there are an input button B1 for recording the purchase history of goods by utilizing the receipt image, and an input button B2 for recording the store visit history by inputting or selecting the store where food and beverage were consumed.

[0048] Furthermore, on the menu screen 50, there is an input button B3 for recording the participation history and participation registration in events planned and proposed by the merchant. Also, when the user achieves a target registered in advance and approved by the merchant or a target proposed by the merchant (for example, participating in a full marathon, climbing Mount Fuji, etc.), there is an input button B4 for recording the implementation history in order to receive points. Furthermore, on the menu screen 50, there is an input button B5 for recording the food and beverage consumption history.

[0049] FIG. 6(a) and FIG. 6(b) show a reception screen for purchase item records. When the user taps the input button B1 (see FIG. 5) for recording the purchase history of the items on the menu screen 50, the server 12 proceeds to step S30 (see FIG. 3) and displays an input screen for the purchased items on the user's display screen 50 as shown in FIG. 6(a). The user can select the type of beverage purchased from among the types of beverages (beverages) displayed under the display of "Input of Purchased Items". Also, on the input screen, items (beverages) for which the user has had a high chance of purchase based on the user's purchase history are displayed. Therefore, the user can easily select the type of purchased item (purchased beverage). When the type of purchased beverage is selected, a reception screen for an image of the receipt of the purchased beverage as shown in FIG. 6(b) is displayed on the user's display screen 50. The user can tap the user terminal 16 along with the display content of the display screen 50 to take a picture of the receipt of the purchased beverage (an example is shown in FIG. 6(c)).

[0050] FIG. 7 shows, as a flowchart, a specific example of the processing corresponding to steps S30 to S60 of the flowchart shown in FIG. 3 when processing purchase item records. FIGS. 8(a) to 8(c) show a confirmation screen for purchase item records and a registration screen for purchase item records. The reception of purchase item records is started in step S110, and in step S120, the server 12 receives an image (photo 20) of the receipt of the purchased items (FIG. 6(c)) taken by the user.

[0051] The user information acquisition unit 28 acquires an image and analyzes the receipt image (photo 20) using an image processing program other than AI or machine learning (for example, OCR reading), or visual inspection by a merchant, etc. As a result, from the purchase information such as product name, price, and purchase date and time displayed on the receipt, store / chain store name information, purchase / eating area information, product purchase date and time information, purchased product / brand information, etc. are identified, and it is confirmed whether it matches the product selected by the user. Further, after associating the identified information as group identifier information, it is recorded (stored) in the user information storage unit 40. At this time, on the user terminal 16, a screen notifying that the receipt is being confirmed as shown in FIG. 8(a) is displayed. The user information acquisition unit 28 also checks, in step S130, whether the acquired purchased product / brand information includes a product that is a target of content distribution, or whether the acquired store / chain store name information includes a store / chain store that is a target of content distribution. The user information acquisition unit 28 further associates (links) the purchased product / brand information or store / chain store name information that is a target of content distribution with the user identifier information in step S140. When these processes are completed, as shown in FIG. 8(b), it is displayed on the user's display screen 50 that the confirmation is completed, and subsequently, as shown in FIG. 8(c), it is displayed that the merchant has awarded points to the user along with the registration of the purchased product record.

[0052] System 10 proceeds to step S150 shown in FIG. 7, determines store information and product information related to the visited store (food and beverage store) and the products consumed, and provides (distributes) these to the user. For this purpose, System 10 proceeds to step S160 and step S70 of the flowchart of FIG. 3 corresponding thereto. Information distributed to the user includes, for example, as corresponding to area information, store information such as stores newly opened in the neighboring area, stores highly evaluated by the user, stores during a campaign, and the like. Also, as corresponding to category information and purchase segment information, information about stores that offer beverages belonging to the same category or purchase segment can be cited. Further, as corresponding to purchase brand information, information about high-class stores (expert stores) that offer beverages of the same brand can be cited. These stores include food and beverage stores that the user has never visited and stores other than food and beverage stores such as supermarkets. In the example shown in FIG. 8(c), on the registration screen of the purchase product record of the user terminal 16, in addition to the registration of the purchase product record, advertisements for new products (new beverages) combined with privilege information such as the present of a gift card and guidance on events held by merchants can be displayed. Thus, the information that guides, that is, recommends, the user is specified by the user feature calculation unit 30 based on the user's purchase information. Based on the analysis by the user feature calculation unit 30 (processing from step S40 to step S60 in FIG. 3), System 10 can recommend not only products with a purchase history of the user but also products without a purchase history (including new products) or non-product entities such as food and beverage stores (processing of step S70 and step S80 in FIG. 3). For this reason, System 10 can distribute product information or store information while widely promoting the potential needs of the user, and can enhance the affinity with the user's preferences.

[0053] Figs. 9(a) and 9(b) show the reception screen for the store visit record. When the user taps the input button B2 (see Fig. 5) for recording the store visit history on the menu screen 50, the server 12 proceeds to step S30 (see Fig. 3), and as shown in Fig. 9(a), displays an input screen for the image of the food and beverage store visited and the beverage consumed at the time of the visit on the user's display screen 50. The user can input the image of the beverage taken at the time of the visit during or after the store visit. Also, when the user taps "Select the store where I drank", the user proceeds to the input screen as shown in Fig. 9(b). If the user is currently at the store, the user can utilize the GPS function incorporated in the user terminal 16 to search for and identify the food and beverage store visited from the current location of the store visited, or if the user is during or after the store visit, from the keywords related to the food and beverage store, and input (transmit) it to the server 12. Also, on the input screen, based on the user's store visit history, food and beverage stores that the user has visited frequently are displayed. Therefore, the user can easily select the food and beverage store visited.

[0054] Fig. 10 shows, as a flowchart, a specific example of the processing corresponding to steps S30 to S60 of the flowchart shown in Fig. 3 when processing the store visit record. Also, Figs. 11(a) and 11(b) show the confirmation screen and the registration screen for the store visit record. In step S210, the reception of the store visit record is started, and in step S220, the server 12 receives the store visit information and the image of the beverage consumed (Fig. 11(a)) transmitted by the user.

[0055] The user information acquisition unit 28 acquires the visited store information and images, and analyzes the images of the beverages consumed during the visit using an image processing program other than AI and machine learning (for example, OCR reading), or visual inspection by a merchant, etc. Thereby, store / chain store name information, purchase / eating area information, product purchase date and time information, purchased product / brand information, etc. are identified, it is confirmed whether it matches the input food and beverage store, and after making an association as group identifier information, it is recorded (stored) in the user information storage unit 26. FIG. 12 shows an example of the visited store record stored in the user information storage unit 26. In this example, the visited store record is classified for each food and beverage store, for each visit history (visited store history), and for each retail store where products are purchased. The user information acquisition unit 28 also checks, in step S230, whether the products included in the acquired visited store record include products that are targets of content distribution, or whether the acquired store / chain store name information includes stores / chain stores that are targets of content distribution. The user information acquisition unit 28 further associates, in step S240, the purchased product / brand information that is the target of content distribution, or the store / chain store name information with the user identifier information. When these processes are completed, as shown in FIG. 11(b), it is displayed on the user's display screen 50 that the confirmation is completed and that the merchant has awarded points to the user with the registration of the visited store record.

[0056] System 10 proceeds to step S250 shown in FIG. 10, determines store information and product information related to the visited store (food and beverage store) and the products consumed, and can proceed to step S260 and step S70 of the flowchart of FIG. 3 to provide (distribute) this information to the user. The information distributed to the user includes, for example, information about beverages of the same brand as shown in the example of FIG. 13(a) as corresponding to the purchased brand information. Also, as corresponding to the category information and purchase segment information, information about products (such as new product information) that offer beverages belonging to the same category or purchase segment can be cited. For this reason, these products (beverages) also include products (beverages) that the user has not purchased and consumed. Further, as corresponding to the area information, store information such as stores newly opened in the neighboring area, stores highly evaluated by the user, and stores during a campaign as shown in the example of FIG. 13(b) can be cited. These stores also include food and beverage stores that the user has not visited and stores other than food and beverage stores such as supermarkets. Also, as shown in FIG. 13(b), the content information distributed to the user can include privilege information (such as "skewer cutlets for 100 yen" in the figure). Further, in the example shown in FIG. 11(b), on the registration screen of the visited store record, recommendations for products, food and beverage stores, and events can be displayed. Here, the information to guide, that is, recommend to the user, is specified by the user feature calculation unit 30 based on the user's purchase information. Based on the analysis by the user feature calculation unit 30 (processing from step S40 to step S60 in FIG. 3), System 10 can recommend not only food and beverage stores with the user's store visit history but also food and beverage stores without a store visit history and products (beverages) rather than food and beverage stores (processing in step S70 and step S80 of FIG. 3). For this reason, System 10 can distribute product information or store information while broadly promoting the user's potential needs, and can enhance the affinity with the user's preferences.

[0057] FIG. 14(a) shows a reception screen for event participation records or event participation registrations, and FIG. 14(b) shows a registration screen for event participation records and event participation wishes. When the user taps the input button B3 (see FIG. 5) for recording the participation history in the event on the menu screen 50, the server 12 proceeds to step S30 (see FIG. 3) and displays a selection screen for event information as shown in FIG. 14(a) on the user's display screen 50. The user can select the event information that the user has participated in or the event information that the user wishes to participate in from the events displayed on the display screen 50. Further, on the selection screen, based on the user's event participation history, events that are being held or are scheduled to be held and that the user is likely to be interested in can be displayed (recommended) (processing from step S40 to step S80 in FIG. 3).

[0058] As shown in FIG. 14(b), when the event that the user has participated in or the event that the user wishes to participate in is selected, it is displayed on the display screen 50 that the registration has been completed, and subsequently, it is displayed that the merchant has awarded points to the user along with the registration of the event. The system 10 analyzes in the user feature calculation unit 30 by including the location information included in the user attribute information in the group identifier (processing from step S40 to step S60 in FIG. 3), and for example, not only within the activity range of the user's daily life but also for content information related to food and beverages and food and beverage stores and event-related content information at locations outside the activity range of the user's daily life. The content information can be distributed (processing in steps S70 and S80 in FIG. 3). Therefore, the system 10 can distribute product information or store information while widely promoting the potential needs of the user, and can enhance the affinity with the user's preferences.

[0059] Subsequently, the operation and effects of the system 10 according to the present embodiment will be described.

[0060] According to the system 10 according to this embodiment, the system 10 can acquire user attribute information including a group identifier by the user information acquisition unit 28, and record the purchase information of the user in association with the group identifier by the history information storage unit 44. Further, the system 10 can calculate the user characteristics of the user based on the purchase information and group identifier of the user by the user characteristic calculation unit 30. Furthermore, the content distribution unit 38 can determine content information that is presumed to be of interest to the user from among the content information including information on products or stores recommended for the users accumulated here, based on the user characteristics calculated by the user characteristic calculation unit 30, and distribute it to the user's user terminal 16. Therefore, it is possible to distribute content information while estimating the potential needs of the user not only within the range of the user's purchase information but also outside this range. As a result, it is possible to distribute product information or store information related to the customer's purchase history information while enhancing the affinity with the user's preferences.

[0061] Furthermore, according to the system 10 according to this embodiment, the purchase information 18, 20 includes purchase history information of food and beverages and store visit history information of food and beverage stores, and the content distribution unit 38 can distribute content information related to food and beverage stores without store visit history information based on the purchase history information. Therefore, it is possible to distribute content information related to food and beverage stores without store visit history information while widely estimating the potential needs of the user not only within the range of the user's store visit history. As a result, it is possible to distribute related product information or store information based on the customer's purchase history information while enhancing the affinity with the user's preferences.

[0062] Moreover, according to the system 10 according to the present embodiment, the purchase information 18, 20 includes purchase history information of food and beverages and store visit history information of food and beverage stores, and the content distribution unit 38 can distribute content information regarding products without purchase history information based on the store visit history information. Therefore, it is possible to distribute content information regarding food and beverages without purchase history information while broadly inferring the potential needs of the user, not only within the range of the user's purchase history. As a result, it is possible to distribute relevant product information or store information based on the customer's purchase history information while enhancing the affinity with the user's preferences.

[0063] Furthermore, according to the system 10 according to the present embodiment, the user attribute information can include location information. Therefore, for example, it is possible to distribute content information regarding food and beverages in stores or food and beverage stores located in locations outside the user's daily life activity range while broadly inferring the potential needs of the user, not only within the user's daily life activity range. As a result, it is possible to distribute relevant product information or store information based on the customer's purchase history information while enhancing the affinity with the user's preferences.

[0064] Furthermore, according to the system 10 according to the present embodiment, the content information regarding food and beverage stores can include information regarding food and beverage stores that provide food and beverages having the same group identifier as the information regarding the food and beverages included in the purchase history information of the food and beverages. Therefore, it is possible to distribute content information including food and beverage stores that the user has never visited or food and beverages that the user has never purchased to the user. As a result, it is possible to discover the potential needs of the user and further enhance the affinity between the user and the merchant.

[0065] Moreover, according to the system 10 according to the present embodiment, the content information regarding food and beverage stores can include privilege information regarding the food and beverage stores. Therefore, it is possible to improve the incentive for the user to visit the food and beverage store. As a result, it is possible to increase the opportunity to discover the potential needs of the user and further enhance the affinity between the user and the merchant.

[0066] Furthermore, according to the system 10 according to the present embodiment, the content information regarding food and drink can include information regarding food and drink having the same group identifier as the information regarding food and drink provided in the food and drink store included in the store visit history information of the food and drink store. Therefore, content information including food and drink that the user has never purchased can be distributed to the user. As a result, potential needs of the user can be discovered, and the affinity between the user and the merchant can be further enhanced.

[0067] Also, according to the system 10 according to the present embodiment, it can include information regarding newly released food and drink and / or information regarding retail stores that sell food and drink. Therefore, content information including newly released food and drink that the user has never purchased and retail stores that the user has never visited can be distributed to the user. As a result, potential needs of the user can be discovered, and the affinity between the user and the merchant can be further enhanced.

[0068] As described above, the content distribution system 10 according to the present embodiment can distribute product information or store information related to the user's purchase history information while enhancing the affinity with the user's preferences.

[0069] Although the embodiments of the content distribution system 10 have been described above, the present invention is not limited to the above embodiments. It is considered that those skilled in the art can understand that various modifications of the above embodiments are possible.

Description of Reference Numerals

[0070] 10 Content distribution system (system) 16 User terminal 18 Photo (purchase information) 20 Photo (purchase information) 28 User information acquisition unit 30 User feature calculation unit 38 Content distribution unit 44 History information storage unit

Claims

1. A content delivery system for delivering content tailored to a user's preferences, comprising: a user information acquisition unit that acquires user attribute information including a group identifier; a history information storage unit that records the purchase information of the user in association with the group identifier; a user feature calculation unit that calculates user features of the user based on the purchase information of the user and the group identifier; a content delivery unit that stores content information including information on products or stores recommended for the user and delivers the content information to the user terminal of each user. The content delivery unit is characterized in that it determines the content information that is presumed to be of interest to the user based on the user features calculated by the user feature calculation unit. A content delivery system.

2. The purchase information includes purchase history information of food and beverages, The content delivery unit delivers content information regarding food and beverage stores based on the purchase history information. The content delivery system according to claim 1.

3. The purchase information includes store visit history information of food and beverage stores, The content delivery unit delivers content information regarding food and beverages based on the store visit history information. The content delivery system according to claim 1.

4. The user attribute information includes location information. The content delivery system according to claim 1.

5. The content information regarding the food and beverage store includes information regarding a food and beverage store that provides food and beverages having the same group identifier as the information regarding the food and beverages included in the purchase history information of the food and beverages. The content delivery system according to claim 2.

6. The content information regarding the food and beverage store includes privilege information regarding the food and beverage store. The content delivery system according to claim 5.

7. The content information regarding the food and drink includes information regarding food and drink having the same group identifier as the information regarding the food and drink provided at the food and drink store included in the store visit history information of the food and drink store. The content distribution system according to claim 3.

8. The content information regarding the food and drink includes information regarding newly released food and drink and / or information regarding retail stores that sell the food and drink. The content distribution system according to claim 7.

9. A content distribution method for distributing content according to a user's preference, comprising: obtaining user attribute information including a group identifier; recording the purchase information of the user in association with the group identifier; calculating user characteristics of the user based on the purchase information of the user and the group identifier; accumulating content information including information regarding products or stores recommended for the user, and distributing the content information to the user terminals of each user, determining the content information that is presumed to be of interest to the user based on the calculated user characteristics. A content distribution method characterized by this.

10. The purchase information includes purchase history information of food and drink, accumulating content information including information regarding products or stores recommended for the user, and distributing the content information to the user terminals of each user includes accumulating the purchase history information and distributing content information regarding food and drink stores based on the accumulated purchase history information. The content distribution method according to claim 9.

11. The purchase information includes store visit history information of food and drink stores, Storing content information including information on products or stores recommended to the user and distributing the content information to the user terminals of each user includes storing the store visit history information and distributing content information related to food and beverages based on the stored store visit history information. The content distribution method according to claim 9.

Images