Information processing device, information processing method, and information processing program

Abstract

To provide a new kind of enjoyment related to purchasing products. [Solution] The information processing device comprises an acquisition unit, an extraction unit, a correction unit, and a presentation unit. The acquisition unit acquires first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object. When a user purchases a product, the extraction unit extracts target correction information corresponding to the purchased product from the correction information. The correction unit corrects the first state information using the target correction information. The presentation unit presents the corrected first state information and the second state information to the user in a state where they can be compared.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Conventionally, technologies for supporting users' purchasing behaviors have been provided. As an example of such a technology, a technology has been proposed that identifies a transaction target according to the tendency of a user's purchasing behavior and provides the user with information on a store that handles the identified transaction target.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the above conventional technologies may not always be able to provide new enjoyment related to product purchase.

[0005] For example, in the above conventional technologies, since a transaction target handled in a physical store within the area where the user is located is identified according to the tendency of the user's purchasing behavior or the browsing history of the user's coordination, etc., the convenience of product purchase is considered to be improved. On the other hand, it is difficult to say that new enjoyment is generated regarding product purchase in such above conventional technologies.

[0006] The present invention has been made in view of the above, and an object thereof is to provide new enjoyment related to product purchase.

Means for Solving the Problems

[0007] To solve the above problems, one embodiment of the information processing device according to the present invention includes: an acquisition unit that acquires first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object; an extraction unit that, when a user purchases a product, extracts target correction information from the correction information corresponding to the purchased product; a correction unit that corrects the first state information using the target correction information; and a presentation unit that presents the corrected first state information and the second state information to the user in a state where they can be compared. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide a new kind of enjoyment related to purchasing products. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 is a diagram illustrating the background of the present invention. [Figure 2] Figure 2 shows a specific example of persona diagnosis. [Figure 3] Figure 3 shows an example of the configuration of an information processing system according to the embodiment. [Figure 4] Figure 4 is a diagram illustrating the outline of the proposed technology provided by the server device. [Figure 5] Figure 5 shows an example of the configuration of a server device according to this embodiment. [Figure 6] Figure 6 shows an example of a hierarchical structure according to the present invention. [Figure 7] Figure 7 shows an example of a reward data storage unit according to the embodiment. [Figure 8] Figure 8 is a flowchart showing the procedure for the correction process according to this embodiment. [Figure 9] Figure 9 shows an example of a correction method used in the correction process according to this embodiment. [Figure 10] Figure 10 is a flowchart showing the steps for the point awarding process and the reset process according to the embodiment. [Figure 11]FIG. 11 is a diagram illustrating an example of correction information adjustment processing according to an embodiment. [Figure 12] FIG. 12 is a flowchart showing the procedure of promotion processing according to an embodiment. [Figure 13] FIG. 13 is a flowchart showing hint presentation processing according to an embodiment. [Figure 14] FIG. 14 is a hardware configuration diagram showing an example of a computer according to an embodiment.

Mode for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the present specification and drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant descriptions are omitted.

[0011] One or more of the embodiments (including examples, modified examples, and application examples) described below can be implemented independently. On the other hand, at least some of the plurality of embodiments described below may be implemented in appropriate combination with at least some of other embodiments. These plurality of embodiments may include different novel features. Therefore, these plurality of embodiments can contribute to solving different purposes or problems and can exhibit different effects.

[0012] (Embodiment) [1. Introduction] First, the background of the present invention will be described. FIG. 1 is a diagram for explaining the background of the present invention. For example, a person may imagine an ideal image of a person different from the real self as an ideal form (ideal image). The real self is the superficial self that actually appears as the characteristics of the person in social life and the like, while the ideal image of the person is the potential self that is not manifested.

[0013] As shown in FIG. 1, based on past experiences, people come to know what suits them in various fields (e.g., fashion). For example, through experience, people may come to know that "〇〇 fashion suits me" or "△△ situations suit me". Thus, what is discovered through such experiences forms the characteristics of that person.

[0014] On the other hand, people may envision an image of "the person they want to be", for example, imagining an ideal persona such as "wanting to experience △△ situations in the appearance like 〇〇".

[0015] Therefore, there is a method called persona diagnosis for determining the characteristics of user U in a specific field and the persona that user U desires in that specific field.

[0016] For example, in persona diagnosis, user U is asked to answer a questionnaire regarding a specific field, and based on the answers input by user U, the characteristics that user U actually has for the specific field (the superficial self formed by accumulating experiences in the specific field) and the ideal persona (the potential self) that user U has for the specific field may be determined.

[0017] As an example, in persona diagnosis, for each of the six items such as "honesty", "extroversion", "neurotic tendency", "openness", and "cooperativeness", an item index (hereinafter, may simply be referred to as "index") indicating the degree to which user U fits is calculated based on the answers of user U. Then, in persona diagnosis, user U is classified into one of multiple types based on the result of combining the indexes of each item.

[0018] More specifically, in persona diagnosis, user U is classified into types for both the real persona, which is the current state (also considered the characteristics of user U), and the ideal persona, which is the ideal state (also considered the ideal image of user U).

[0019] Figure 2 shows an example where User U, whose specific field is fashion, undergoes a persona assessment, and whose usual clothing style is A fashion. In this example, the persona assessment provides User U with the diagnosis results of their actual persona type and the fashion style corresponding to that type, as well as their ideal persona type and the fashion style corresponding to that type.

[0020] Furthermore, in the persona diagnosis, a radar chart RCx may be generated by combining the indices that formed the basis of the type classification, and this may be presented to user U along with the diagnosis result. Figure 2 shows an example in which radar chart RC1 is generated from a set of indices calculated based on user U's answers to a questionnaire for determining the real persona, and that the diagnosis result of the real persona being "open type" is obtained based on radar chart RCx. From this diagnosis result, user U can learn that they are an open type because "fashion B suits them."

[0021] Furthermore, Figure 2 shows a radar chart RC2 generated from a set of indices calculated based on user U's responses to a questionnaire used to determine the ideal persona, and an example where the diagnostic result for the ideal persona "Honesty Type" is obtained based on the radar chart RC2. From this diagnostic result, user U can learn that, although they idealize the Honest Type, they actually "aspire to C Fashion."

[0022] It should be noted that User U's real persona is just one example of a real state. The real state does not necessarily have to be determined by persona diagnosis. For example, the real state may be determined by User U based on their past experiences, or it may be dynamically determined based on User U's various histories (e.g., purchase history). The real state corresponds to the first state. For this reason, the radar chart RC1 corresponds to real state information, or first state information, that shows the real state.

[0023] Furthermore, User U's ideal persona is an example of an ideal state. The ideal state does not necessarily have to be determined by persona diagnosis. For example, the ideal state may be determined by User U themselves based on their past experiences, or it may be dynamically determined based on User U's various histories (e.g., purchase history). The ideal state corresponds to the second state. For these reasons, the radar chart RC2 corresponds to ideal state information, or second state information, that shows the ideal state.

[0024] Furthermore, in the following embodiment, the persona diagnosis is assumed to generate a radar chart RCx from indices corresponding to each of the six items: "conscientiousness," "extroversion," "neuroticism," "openness," and "agreeableness." However, the number and content of items are not limited to the example in Figure 2 and can be freely changed according to the implementer's needs. For example, items such as "softness" and "hardness" may be added, resulting in around 20 items.

[0025] Here, the results of the persona assessment are not immutable; they may change over time as User U gains more experience, and depending on various conditions such as User U's mood and physical condition at the time of the persona assessment. In other words, the indices used in the persona assessment are not fixed and may fluctuate depending on the factors surrounding User U.

[0026] Therefore, the inventors of this invention focused on the fact that, in line with the recent spread of persona assessments, the number of users U who are interested in persona assessments has been increasing, and that the results of persona assessments are inherently variable. They believed that by utilizing these assessment results, it would be possible to provide a new kind of enjoyment related to product purchases.

[0027] Based on the above, the proposed technology of the present invention changes real-world state information (for example, one of the indices constituting the radar chart RC1) in response to a product purchase by user U, and presents the user with the result of how close or farther the changed real-world state information is from the ideal state information (radar chart RC2), thereby providing user U with a kind of game experience (for example, a lottery-based item purchase game). By providing a new kind of enjoyment related to product purchases according to the proposed technology of the present invention, it becomes possible to realize a purchase promotion system that evaluates user U's shopping (purchase history, purchase performance).

[0028] In the following, the information processing related to the proposed technology of the present invention will be described as information processing according to an embodiment. In the information processing according to the embodiment, the first state will be the actual state (type as an actual persona) based on persona diagnosis, and the second state will be the ideal state (type as an ideal persona) based on persona diagnosis, as an example. However, the first and second states may be the states of user U determined by some method other than persona diagnosis.

[0029] [2. System Configuration] Figure 3 is a diagram showing an example configuration of an information processing system according to the embodiment. Figure 3 shows information processing system 1 as an example of an information processing system according to the embodiment. The information processing according to the embodiment (i.e., the proposed technology of the present invention) is realized in information processing system 1. In information processing system 1, a game GA, which is a lottery-type item purchase game, is realized.

[0030] As shown in Figure 3, the information processing system 1 includes a user device 10, a store device 20, a business device 30, and a server device 100. The information processing system 1 may also include multiple user devices 10, multiple store devices 20, multiple business devices 30, and multiple server devices 100.

[0031] User device 10 is an example of an information processing terminal used by user U. User device 10 may be a smartphone, a wearable device, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. For example, user device 10 is equipped with an application for sending and receiving information with server device 100. Such an application may be a general-purpose application such as a web browser, or it may be a dedicated application newly implemented in accordance with the present invention.

[0032] The store device 20 is an information processing device belonging to store SHx. The store device 20 may be either a payment information processing terminal (e.g., a POS terminal) installed at the front of store SH that enables payment using a predetermined payment method, or a store-side server device connected to such information processing terminal. Store SHx is, for example, a member store that agrees to provide a game experience using correction information and is a member of the information processing system 1. The predetermined payment method may be, for example, a payment application installed on the user device 10 (e.g., an application that displays payment code information corresponding to one transaction). Depending on the payment method, a reader R that reads code information (e.g., barcodes or QR codes (registered trademarks)) may be connected to the store device 20.

[0033] The store SHx may be either a physical store or an online virtual store. However, when purchasing goods using an online virtual store, payment methods other than reading code information via a payment application (e.g., credit card payment, points payment, bank transfer, convenience store payment, etc.) may be used.

[0034] The business operator device 30 is an information processing device belonging to business operator T, which provides a platform related to the proposed technology of the present invention. The business operator device 30 may be either an information processing terminal used by business operator T, or a server device on the business operator's side connected to such information processing terminal. For example, if the business operator device 30 is an information processing terminal, it may be a smartphone, a wearable device, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, etc. An application for sending and receiving information with the server device 100 may also be installed in the business operator device 30.

[0035] The server device 100 is the central device for performing information processing according to the embodiment, and may be implemented as a cloud server device. The following describes an overview of the information processing performed by the server device 100.

[0036] [3. Overview of the Server Equipment] Figure 4 illustrates the outline of the proposed technology provided by the server device 100. Figure 4 shows a scene in which user U, who has learned that they aspire to C fashion after reviewing the results of a persona diagnosis, tries out the game GA.

[0037] As shown in the example in Figure 4, user U compares radar chart RC1 (actual state information) and radar chart RC2 (ideal state information) included in the diagnostic results and notices that the index for the honesty item in radar chart RC1 is several points lower than the index for the honesty item in radar chart RC2. User U then hopes that if they purchase some fashion item to get closer to fashion C, their index for the honesty item will also increase.

[0038] To participate in the game GA, it is necessary to purchase an item, so in the example in Figure 4, user U visits a nearby store SH1 to purchase a fashion item. For example, user U decides to purchase a dress PD as a fashion item. The payment process for purchasing the dress PD takes place between the user device 10 and the store device 20. For example, user U presents code information corresponding to one transaction of purchasing a dress PD to store clerk SF1 at store SH1, and clerk SF1 has reader R read the code information.

[0039] The store device 20 transmits the product information PDN read by the reader R from the code information to the server device 100. In the example in Figure 4, the product information PDN transmitted by the store device 20 may include the store code of store SH1, the product code of the dress PD, the payment amount, the payment date and time, etc. Based on the product code, the server device 100 may identify attribute information such as the product category, brand, and product name of the dress PD and include it in the product information PDN.

[0040] Furthermore, the server device 100 stores product master data, and a simple example of product master data is shown in Figure 4. The product master data includes correction information for adjusting the index for each product category. More specifically, the product master data includes correction information for adjusting the index for each combination of a "store code" that identifies the store SHx and a "product category" (for example, food or fashion). The correction information defines a "correction value" that indicates how much to increase or decrease the index of each of the six items, such as "conscientiousness," "extraversion," "neuroticism," "openness," and "agreeableness."

[0041] Therefore, the server device 100 compares the product information PDN with the product master data and extracts the combination of "store code" and "product category" that corresponds to the product information PDN. In the example in Figure 4, the server device 100 can extract the combination of store code "SH1" and product category "fashion".

[0042] Furthermore, the server device 100 extracts "correction information" that corresponds to the combination of store code "SH1" and product category "fashion" from the "correction information". In the example in Figure 4, the server device 100 extracts the item "integrity" and correction value "+2", and the item "cooperativeness" and correction value "-3" as "correction information".

[0043] The server device 100 then performs a correction that increases the index of the integrity item in the radar chart RC1 by "2" according to the item "integrity" and the correction value "+2". The server device 100 also performs a correction that decreases the index of the cooperation item in the radar chart RC1 by "3" according to the item "cooperativeness" and the correction value "-3".

[0044] The server device 100 generates a screen G in which radar chart RC1' and radar chart RC2, composed of the corrected indices, are displayed in a comparable state, and presents the generated screen G to user U. Specifically, the server device 100 displays screen G by transmitting it to user device 10. The comparison result of comparing radar chart RC1' and radar chart RC2 corresponds to the result of user U's challenge in the game GA, allowing them to understand whether or not they succeeded in the challenge.

[0045] For example, in the example shown in Figure 4, by purchasing One Piece PD, User U was able to increase the index for the conscientiousness item as intended, but the index for the cooperativeness item unexpectedly decreased, allowing User U to experience a sense of gamification, such as "That's a shame, I'll try again." Thus, according to the information processing of this embodiment, User U is not made to deeply accept the outcome of the challenge, but rather can experience a sense of gamification, enjoying the purchase while anticipating whether the result will be as expected.

[0046] [4. Server Equipment Configuration] The server device 100 according to the embodiment will be described using Figure 5. Figure 5 is a diagram showing an example of the configuration of the server device 100 according to the embodiment. As shown in Figure 5, the server device 100 has a communication unit 110, a storage unit 120, and a control unit 130.

[0047] (Communications Department 110) The communication unit 110 is implemented, for example, by a NIC (Network Interface Card). For example, the communication unit 110 transmits and receives information between the user device 10, the store device 20, and the business device 30.

[0048] (Storage unit 120) The storage unit 120 is implemented by, for example, a semiconductor memory element such as RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or optical disc. The storage unit 120 may store, for example, data and programs related to information processing according to the embodiment. Also, as shown in Figure 5, the storage unit 120 may have a customer data storage unit 121, a product master data storage unit 122, and a reward data storage unit 123.

[0049] (Customer data storage unit 121) The customer data storage unit 121 stores the following information as part of the persona diagnosis results: the index for each item constituting radar chart RC1, the index for each item constituting radar chart RC2, the type as a real persona, and the type as an ideal persona. The customer data storage unit 121 may also store the corrected index for each item constituting radar chart RC1. The customer data storage unit 121 may also store purchase history, including product information PDN.

[0050] (Product master data storage unit 122) The product master data storage unit 122 stores product master data. The product master data has a hierarchical structure H composed of predetermined classification units. That is, the product master data storage unit 122 stores the hierarchical structure H as product master data. Figure 6 shows an example of the hierarchical structure H according to the embodiment.

[0051] A classification unit is a single unit included in the hierarchical structure H, and is information used to classify a specific object into one or a group. Figure 6 shows an example in which the hierarchical structure H is composed of classification units in a five-level relationship: the first, second, third, fourth, and fifth levels, but the number of levels is not limited. Also, Figure 6 shows an example where the first level is "store code," the second level is "product category (major)," the third level is "product category (minor)," the fourth level is "brand," and the fifth level is "product code," but the content of the classification units is not limited to this example.

[0052] The first-level classification unit may be a "store code." A "store code" is identification information that classifies a store as a unique store. Alternatively, the store name may be used as the first-level classification unit instead of a store code.

[0053] The second-level classification unit may be "product category (broad)." A "product category (broad)" is information used to classify the products handled by the store indicated by the "store code" into specific, broad categories. Examples include "fashion," "furniture and storage," and "food."

[0054] The third level of classification may be "product category (small)". A "product category (small)" is a category under "product category (large)" and is information used to classify products into specific categories with a small level of granularity. For example, "product category (small)" under the product category (large) "fashion" could include "dresses," "jackets," and "pants."

[0055] The fourth level of classification can be "brand." A "brand" is a category under a "product category (minor)" and is information used to classify products into a specific brand. For example, under the product category (minor) "dress," brands such as "brand A" and "brand B" could be listed.

[0056] The fifth level classification unit may be a "product code." A "product code" is identification information that classifies products handled at a store indicated by a "store code" as a single, unified product. Instead of a product code, a product name may also be used as the fifth level classification unit.

[0057] Furthermore, as shown in the example in Figure 6, correction information is set for each classification unit to adjust the index. Specifically, for each classification unit, a "correction value" is set as correction information, indicating how much to increase or decrease the index of one of the six items, such as "conscientiousness," "extraversion," "neuroticism," "openness," and "agreeableness." Thus, the correction information may be defined as a pair of an item and a correction value.

[0058] Figure 6 shows an example in which, for a specific classification content "SH1" within a single classification unit "store code," the "correction information" includes a pair of the item "openness" and a correction value "+1," and a pair of the item "extroversion" and a correction value "-3."

[0059] Furthermore, there is no limit to the number of correction information sets for each classification unit. For example, for the specific classification item "One Piece" within another classification unit "Product Category (Small)", the following "correction information" sets may be applied: the item "Neuroticism" and correction value "+5", the item "Openness" and correction value "+4", and the item "Honesty" and correction value "-3".

[0060] The correction information may be set by the store indicated by the "store code," for example, or by business operator T.

[0061] (Reward data storage unit 123) The information processing related to the implemented liquid includes a reset process that returns the current real-world state information to the uncorrected real-world state information, instead of rewarding the user U based on the degree of approximation, which indicates how closely the current real-world state information approximates the ideal state information. The reward data storage unit 123 stores various condition information used in this reset process.

[0062] Here, Figure 7 shows an example of the reward data storage unit 123 according to the embodiment. In the example in Figure 7, the reward data storage unit 123 has items such as "point service", "reset conditions", "approximation degree", and "points awarded".

[0063] There are multiple point services that offer points as rewards, and "point service" is an identifier that distinguishes each of these different point services. "Point service" may use the service name or identifier of the point service.

[0064] The reset process does not completely revert the current real-world state information back to the pre-correction real-world state information; rather, it may revert to a state similar to the pre-correction real-world state information. The conditional information that determines what state similar to the pre-correction real-world state information should be is called the "reset condition." For example, a "reset condition" might be to maintain the current index for the cooperativeness item (not revert to the pre-correction cooperativeness item index), while resetting the indices for other items to their previous state (reverting to the pre-correction indices for each item). The "reset condition" may be set by the point service provider or by the service provider T.

[0065] The "degree of approximation" indicates how closely the real-world state information approximates the ideal state information, and may include concepts of identical or similar. For example, the server device 100 may calculate the degree of approximation as the degree of difference in shape when comparing the shape of radar chart RC1 with the shape of radar chart RC2.

[0066] Furthermore, the "degree of similarity" referred to here is a condition for determining how many points to award based on that value, and as shown in Figure 7, it may be classified in stages within a predetermined range. For example, Figure 7 shows an example where a degree of similarity of "81% or more" is associated with the awarded points of "100pt". This example corresponds to defining a condition that if the calculated degree of similarity is "81% or more", then "100pt" will be awarded to user U. The relationship between the "degree of similarity" and the "awarded points" may be set by the point service provider or by the business operator T. As another example, this relationship may be determined by surveys or votes from various users.

[0067] (Control unit 130) Returning to Figure 5, the control unit 130 is implemented by a CPU (Central Processing Unit) or MPU (Micro Processing Unit), etc., which executes various programs (for example, the information processing program according to this embodiment) stored in the storage device inside the server device 100 using RAM as the working area. Alternatively, the control unit 130 can be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0068] As shown in Figure 5, the control unit 130 includes a reception unit 131, an acquisition unit 132, an extraction unit 133, a correction unit 134, a presentation unit 135, an execution unit 136, an adjustment unit 137, and a promotion unit 138, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Figure 5, and other configurations are also possible as long as they perform the information processing described later. Also, the connection relationships of the various processing units in the control unit 130 are not limited to the connection relationships shown in Figure 5, and other connection relationships are also possible.

[0069] (Reception desk 131) The reception unit 131 receives various types of information related to requests, inputs, and inquiries. For example, the reception unit 131 receives various types of information related to requests, inputs, and inquiries from the user device 10, the store device 20, and the business device 30. The reception unit 131 may also store the received information in the storage unit 120 and update the stored contents.

[0070] (Acquisition part 132) The acquisition unit 132 acquires first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object. For example, the acquisition unit 132 acquires real state information (indices for each item constituting the radar chart RC1) that indicates the real state of user U (type as a real persona). The acquisition unit 132 also acquires ideal state information (indices for each item constituting the radar chart RC2) that indicates the real state of user U (type as an ideal persona).

[0071] Furthermore, the acquisition unit 132 may acquire other information necessary for the information processing according to the embodiment while executing the information processing according to the embodiment. The destination of the information acquired by the acquisition unit 132 may be the storage unit 120 or an external device other than the server device 100. In addition, the acquisition unit 132 may acquire information received by the reception unit 131.

[0072] (Extraction part 133) The extraction unit 133 extracts target correction information corresponding to the purchased product from the correction information when user U purchases a product. For example, the extraction unit 133 extracts target correction information corresponding to the purchased product from the correction information set for each predetermined unit. The correction information set for each predetermined unit is the correction information (a pair of items and correction values) set for each classification unit in the hierarchical structure H as product master data. More specifically, it is the correction information (a pair of items and correction values) set for each specific classification content of the classification unit (for example, store code "SH1", product category (major) "fashion", etc.). Thus, the correction information is candidate correction information to be extracted as target correction information.

[0073] In this state, the extraction unit 133 extracts combinations of a first unit (e.g., store code) and a second unit (e.g., brand) that are linked to information about purchased products (product information PDN including product code, payment amount, payment date and time, category, brand, product name, etc.), and extracts the correction information set for the first unit (e.g., store code "SH1") and the second unit (e.g., brand "Brand A") included in the extracted combination as target correction information.

[0074] (Correction section 134) The correction unit 134 corrects the first state information (actual state information) using the target correction information. Specifically, the correction unit 134 corrects the first state information using a plurality of target correction information extracted according to the combination extracted by the extraction unit 133.

[0075] The term "correction" here refers to the use of correction information (a pair of an item and a correction value) to control the index of a corresponding item among the indices that make up the radar chart RC1, such as raising or lowering it, as explained in Figure 4. The specific correction method is explained in Figure 9.

[0076] (Presentation part 135) The presentation unit 135 presents the corrected first state information and the second state information to the user U in a comparable state. In the example shown in Figure 4, the presentation unit 135 generates a screen G in which the radar chart RC1' and radar chart RC2, composed of the corrected indices, are displayed in a comparable state, and presents the generated screen G to the user U.

[0077] Here, we will explain the operation procedure of the server device 100 involved in the correction process using Figure 8. Figure 8 is a flowchart showing the procedure of the correction process according to the embodiment.

[0078] In the example shown in Figure 8, the reception unit 131 determines whether it has received product information PDNs related to the purchased products from the store device 20 when user U purchases a product (step S801). The product information PDNs may be information for products purchased in a single transaction. For example, if multiple products are purchased at the same time, the reception unit 131 receives the product information PDNs corresponding to each product as information for products purchased in a single transaction.

[0079] The reception unit 131 waits until it receives a product information PDN (step S801; No) while it has not received a product information PDN.

[0080] On the other hand, if product information PDN is received (step S801; Yes), the extraction unit 133 compares the product information PDN with the product master data (hierarchical structure H) and extracts the combination of classification units in a hierarchical relationship that corresponds to the product information PDN (step S802).

[0081] Furthermore, the extraction unit 133 extracts the correction information set for each classification unit included in the combination extracted in step S802 as target correction information (step S803).

[0082] For example, suppose the product information PDN contains product code "SH1", product category (major) "Fashion", product category (minor) "Dress", brand "Brand A", and product code "A11". In this example, in step S802, the extraction unit 133 extracts the combination of product code "SH1", product category (major) "Fashion", product category (minor) "Dress", brand "Brand A", and product code "A11" from among the combinations of classification units included in the hierarchical structure H, as the combination corresponding to the product information PDN.

[0083] Furthermore, using the above example, in step S803, the extraction unit 133 performs the following extraction. The extraction unit 133 extracts correction information #1 as correction information to be set for product code "SH1". According to the example in Figure 6, correction information #1 includes a pair of item "openness" and correction value "+1", and a pair of item "extroversion" and correction value "-3".

[0084] The extraction unit 133 extracts correction information #2 as correction information to be set for the product category (large) "Fashion". In the example in Figure 6, correction information #2 includes a pair of the item "Honesty" and a correction value "-2", and a pair of the item "Cooperativeness" and a correction value "+5".

[0085] The extraction unit 133 extracts correction information #3 as correction information to be set for the product category (small) "One Piece". According to the example in Figure 6, correction information #3 includes the pair of item "Neuroticism" and correction value "+5", the pair of item "Openness" and correction value "+4", and the pair of item "Honesty" and correction value "-3".

[0086] The extraction unit 133 extracts correction information #4 as correction information to be set for brand "Brand A". In the example in Figure 6, correction information #4 includes a pair of item "Extroversion" and correction value "+4", and a pair of item "Agreeableness" and correction value "+2".

[0087] The extraction unit 133 extracts correction information #5 as correction information to be set for product code "A11". In the example in Figure 6, correction information #5 includes the item "cooperativeness" and the correction value "-2".

[0088] Furthermore, the acquisition unit 132 acquires the actual state information and ideal state information of user U (step S804). Specifically, the acquisition unit 132 acquires the actual state information (indices for each item constituting the radar chart RC1) and ideal state information (indices for each item constituting the radar chart RC2) of user U who has made a payment corresponding to the product information PDN.

[0089] Next, the correction unit 134 corrects the real-world state information using the correction information (step S805). For example, the correction unit 134 controls the system by raising or lowering the index of the corresponding item among the items in the radar chart RC1, according to the set of items and correction values ​​included in the correction information extracted in step S803.

[0090] Here, we will explain a specific correction method using Figure 9. Figure 9 is a diagram showing an example of a correction method adopted in the correction process according to the embodiment. Figure 9 shows the correction method when correction information #1, correction information #2, correction information #3, correction information #4, and correction information #5 are extracted as target correction information.

[0091] For example, the correction unit 134 calculates a total correction value for each item based on correction information #1 to #5. For example, correction information #1 includes the item "Openness" and the correction value "+1". Correction information #3 includes the item "Openness" and the correction value "+4". Therefore, the correction unit 134 adds the correction value "+1" and the correction value "+4" to calculate a total value of "+5" corresponding to the item "Openness". Correction information #1 also includes the item "Extroversion" and the correction value "-3". Correction information #4 also includes the item "Extroversion" and the correction value "+4". Therefore, the correction unit 134 adds the correction value "-3" and the correction value "+4" to calculate a total value of "+1" corresponding to the item "Extroversion".

[0092] The correction unit 134 calculates overall values ​​for conscientiousness, cooperativeness, and neuroticism in the same manner. Figure 9 shows an example in which the correction unit 134 calculates an overall value of "-5" for conscientiousness, "+5" for cooperativeness, and "+5" for neuroticism.

[0093] The correction unit 134 then performs a correction to increase the index of the openness item in the radar chart RC1 by "5" according to the item "Openness" and the overall value "+5". The correction unit 134 also performs a correction to increase the index of the extroversion item in the radar chart RC1 by "1" according to the item "Extroversion" and the overall value "+1". The correction unit 134 also performs a correction to decrease the index of the conscientiousness item in the radar chart RC1 by "5" according to the item "Conscientiousness" and the overall value "-5". The correction unit 134 also performs a correction to increase the index of the agreeableness item in the radar chart RC1 by "5" according to the item "Agreeableness" and the overall value "+5". The correction unit 134 also performs a correction to increase the index of the neuroticism item in the radar chart RC1 by "5" according to the item "Neuroticism" and the overall value "+5".

[0094] Furthermore, if there are multiple correction values ​​for a single item, the correction unit 134 may calculate the overall value by multiplying the correction values ​​rather than adding them together. If there are multiple correction values ​​for a single item, the correction unit 134 may combine the correction values ​​to calculate the overall value, which may be the rate of increase or decrease of the index.

[0095] Furthermore, if, for example, multiple products are purchased simultaneously and the corresponding product information PDN is received, the correction unit 134 may calculate the total value of each item for each product based on the product information PDN for each product. Also, if the correction unit 134 has calculated the total value of each item for each product, it may combine the total values ​​across products for each item to calculate the final total value.

[0096] Furthermore, if multiple identical items are purchased simultaneously, the correction unit 134 may treat the simultaneous purchase of multiple identical items as a single item purchase and calculate the total value accordingly. For example, if two One Piece PDs are purchased simultaneously, the product information PDN for each One Piece PD is received, but the correction unit 134 may calculate the total value based on only one of the two product information PDNs.

[0097] Returning to Figure 8, the presentation unit 135 generates a screen G in which the corrected real-world state information and the ideal state information are displayed in a comparable manner (step S806). For example, the presentation unit 135 generates a screen G in which the radar chart RC1' and radar chart RC2, composed of the corrected indices, are displayed in a comparable manner, and presents the generated screen G to the user U.

[0098] Then, the display unit 135 controls the display so that screen G is displayed on user U's user device 10 (step S807).

[0099] (Execution section 136) Returning to Figure 5, the execution unit 136 executes a process to grant benefits to user U. In addition, the execution unit 136 executes a reset process that returns the current real state information to the real state information before correction, in accordance with the granting of benefits.

[0100] For example, if a user operation is performed by the execution unit 136 to request a reward (e.g., points) corresponding to the current real-world state information, the execution unit 136 executes a point granting process to grant the user U a reward whose content corresponds to the degree of approximation, which indicates how closely the current real-world state information approximates the ideal state information.

[0101] Here, the user operation includes specifying the desired type of benefit from among several different types of benefits, and for each type of benefit, condition information is defined to return to the real state information before correction. Therefore, the execution unit 136 returns the current real state information to the state information based on the previous real state information, based on the condition information corresponding to the desired type specified by the user operation from among the condition information defined for each type of benefit.

[0102] To give a specific example, user operations include specifying a desired point service from among several different types of point services that offer points as rewards. Also, as explained in Figure 7, reset conditions are defined in the reward data storage unit 123 as conditional information to return to the real state information before correction. In the reset process, the current real state information is not completely returned to the real state information before correction, but may be returned to an approximate state based on the real state information before correction. The reset conditions are conditional information that specifies what this approximate state should be. Therefore, the execution unit 136 executes a reset process that returns the current real state information to state information based on the previous real state information, based on the conditional information corresponding to the desired point service specified in the user operation, from among the reset conditions defined for each point service.

[0103] Here, the operation procedure of the server device 100 related to the point granting process and reset process will be explained using Figure 10. Figure 10 is a flowchart showing the procedure for the point granting process and reset process according to the embodiment.

[0104] In the example shown in Figure 10, the reception unit 131 determines whether or not it has received an exchange request from user U specifying the desired point service from among several types of point services (step S1001). If the reception unit 131 has not received an exchange request (step S1001; No), it waits until it receives an exchange request.

[0105] If the execution unit 136 receives an exchange request (step S1001; Yes), it calculates a degree of approximation indicating how closely the current real state information of user U who made the exchange request approximates the ideal state information (step S1002). For example, the execution unit 136 may calculate the degree of approximation as the degree of difference in shape when comparing the current shape of radar chart RC1 with the shape of radar chart RC2.

[0106] The execution unit 136 refers to the reward data storage unit 123 and identifies the number of points (points to be awarded) corresponding to the specified desired point service and degree of similarity (step S1003). Then, the execution unit 136 awards the identified points to user U (step S1004). For example, the execution unit 136 adds the identified points to the user's points managed by the storage unit 120.

[0107] For example, if the specified desired point service is "Service SA1" and the degree of similarity is "70%", the execution unit 136 determines, using the example in Figure 7, that it will award "100 points" from the points provided by Service SA1. The execution unit 136 then adds 100 points to the points associated with Service SA1 from the user's points managed by the storage unit 120.

[0108] Next, the execution unit 136 refers to the reward data storage unit 123 and extracts the reset conditions corresponding to the specified desired point service (step S1005).

[0109] The execution unit 136 uses the extracted reset conditions to perform a reset process that returns the current real state information to the real state information before correction (step S1006). For example, if the specified desired point service is "Service SA1", the execution unit 136 extracts a "reset condition" that, using the example in Figure 7, maintains the current index of the cooperativeness item (does not return it to the index of the cooperativeness item before correction), while resetting the indices of other items to their previous state (returns them to the indices of each item before correction). Then, the execution unit 136 resets the radar chart RC1 at the current time according to the reset conditions.

[0110] Furthermore, the execution unit 136 registers the real-time status information after the reset process as the latest real-time status information in the customer data storage unit 121 (step S1007).

[0111] (Adjustment section 137) Let's return to the explanation of Figure 5. For example, if the correction information (a pair of an item and a correction value) is fixed, there is a possibility that users U could devise a strategy to beat the game GA. Specifically, the content of the correction information may be guessed, such as "If you purchase item △△ at store ○○, the index of the extraversion item will increase by 2," which could diminish the fun of the game GA.

[0112] Therefore, the adjustment unit 137 adjusts the correction information to prevent strategies from being devised to beat the game GA. For example, even if the same product is purchased, the adjustment unit 137 adjusts the target item and its index so that they differ depending on the individual purchaser, the purchase situation, and the purchase location. In other words, the adjustment unit 137 adjusts the correction content indicated by the correction information according to a predetermined context.

[0113] For example, the adjustment unit 137 may adjust the correction content indicated by the target correction information depending on whether the place where user U purchased the product is included in user U's living area. In this case, the correction unit 134 corrects the real-world state information using the adjusted target correction information. This point will be explained with reference to Figure 11. Figure 11 is a diagram showing an example of the correction information adjustment process according to the embodiment.

[0114] Figure 11(a) shows the adjustment condition CD, which is used to adjust the correction information so that it differs depending on whether the same product is purchased at a store SHx within the user's living area or at a store SHx outside the user's living area. The adjustment condition CD may be managed by the storage unit 120.

[0115] According to adjustment condition CD, the living area AR1 is defined as the area within a radius D1 centered on user U's place of residence P, and "adjustment value: +1" is associated with it. "Adjustment value: +1" corresponds to conditional information that, when a product is purchased at store SHx within living area AR1, increases the target correction information (e.g., index) extracted based on the product information PDN of that product by "1".

[0116] Furthermore, according to adjustment condition CD, the area within a radius D2 centered on user U's place of residence P, excluding the living area AR1, is defined as the area outside the living area AR2, and the "adjustment value: -2" is associated with it. The "adjustment value: -2" corresponds to conditional information that, if a product is purchased at store SHx within the area outside the living area AR2, the target correction information (e.g., index) extracted based on the product information PDN of that product is reduced by "2".

[0117] Furthermore, according to adjustment condition CD, the area within a radius D3 centered on user U's place of residence P, excluding the living area AR1 and the area outside the living area AR2, is defined as the area outside the living area AR3, and the adjustment value "+3" is associated with it. The adjustment value "+3" corresponds to conditional information that, if a product is purchased at store SHx within the area outside the living area AR3, the target correction information (e.g., index) extracted based on the product information PDN of that product is increased by "3".

[0118] Figure 11(b) shows an example of adjustments made depending on whether the location where user U purchased the product is within user U's living area, and the total correction value calculated as shown in Figure 9 is adjusted accordingly. For example, if user U purchases a one-piece dress PD at store SH1 within living area AR1, the adjustment unit 137 adjusts the total correction value for each item according to "Adjustment Value: +1". As another example, if user U purchases a one-piece dress PD at store SH2 within AR2 outside of living area, the adjustment unit 137 adjusts the total correction value for each item according to "Adjustment Value: -2".

[0119] According to the adjustment process according to this embodiment, even if information such as "If you purchase product △△ at store XX, your extroversion index will increase by 2" is circulated, the index may not necessarily be "2" depending on whether store XX is within the user's living area, making it difficult for user U to take advantage of the system.

[0120] Furthermore, the adjustment unit 137 may adjust the correction information according to contexts other than whether or not the place where user U purchased the product is included in user U's living area.

[0121] For example, the adjustment unit 137 may adjust the correction information according to the elapsed time since the correction information was set in the product master data of the product master data storage unit 122. For example, in the example in Figure 6, for the store code "SH1", the "correction information" is set as a set of the item "openness" and the correction value "+1", and a set of the item "extroversion" and the correction value "-3".

[0122] Therefore, the adjustment unit 137 may perform adjustments such as adding a random value to each of the current correction values ​​as time progresses (for example, every week). As another example, the adjustment unit 137 may perform adjustments such as adding a random value to each of the current correction values ​​at predetermined intervals (for example, every time the time of day or day of the week changes).

[0123] Furthermore, the adjustment unit 137 may perform adjustments such as adding a random value to each of the current correction values ​​when a product registered as product master data becomes an off-season product.

[0124] In the example above, the living area AR1 is defined as the area within a radius D1 centered on user U's place of residence P. However, place of residence P can be determined by any method. For example, the server device 100 may be configured to take user U's place of residence P as input, or it may be configured to estimate place of residence P based on user U's location information.

[0125] Furthermore, the living area AR1 does not necessarily have to be defined as an area within a radius D1 centered on the place of residence P. For example, the server device 100 may define the living area AR1 based on the location information of user U. As one example, the server device 100 may determine the area where user U's movements are concentrated as the living area AR1 based on changes in user U's location information (movement history). As another example, the server device 100 may determine the area where user U stays for a long period of time as the living area AR1 based on changes in user U's location information (movement history).

[0126] (Promotion Department 138) Returning to Figure 5, the acceleration unit 138 performs acceleration processing to recommend actions that are advantageous to user U, determining what actions should be taken to bring the real state information closer to the ideal state information. The acceleration unit 138 may be implemented as a boost function that user U can use. For example, an application installed on user device 10 (for example, an application for sending and receiving information with server device 100) may be equipped with a boost function, and user U can switch the boost function ON / OFF.

[0127] Here, the operation procedure of the server device 100 involved in the acceleration process will be explained using Figure 12. Figure 12 is a flowchart showing the procedure of the acceleration process according to the embodiment.

[0128] In the example shown in Figure 12, the reception unit 131 determines whether or not it has received product information PDNs related to the purchased product from the store device 20 when user U purchases a product (step S1201). If the reception unit 131 has not received product information PDNs (step S1201; No), it waits until it receives product information PDNs.

[0129] If the product information PDN is received (step S1201; Yes), the acceleration unit 138 determines whether the boost function is ON or OFF (step S1202). If the boost function is OFF (step S1202; No), the acceleration unit 138 does not perform the acceleration process.

[0130] On the other hand, if the boost function is ON (step S1202; Yes), the acceleration unit 138 compares the current real state information with the ideal state information and calculates the control values ​​necessary to bring the real state information closer to the ideal state information (step S1203). For example, the acceleration unit 138 compares the current radar chart RC1 (or radar chart RC1' if corrected) with radar chart RC2 and calculates the control values ​​necessary for approximation, determining which items' indices should be controlled and how to control them to approximate (match or resemble) radar chart RC2. The control values ​​may be specific numerical values ​​for raising or lowering the indices, or they may be percentage increases or decreases.

[0131] The acceleration unit 138 refers to the product master data storage unit 122 and searches for information that can satisfy the control value (step S1204).

[0132] Then, the presentation unit 135 presents the information based on the search results to the user U as boost information (step S1205).

[0133] For example, suppose in step S1203, the acceleration unit 138 calculates a control value of "+3" because reducing the index of the openness item by "3" would make the current radar chart RC1 approximate radar chart RC2. In such a case, in step S1204, the acceleration unit 138 may search for a classification unit to which the correction value "+3" is associated as information that can satisfy the control value of "+3".

[0134] For example, suppose the promotion unit 138 was able to find a combination of classification units to which the correction value "+3" is associated, namely store code "SH1", product category (large) "Fashion", product category (small) "Dress", and brand "Brand B". Then, the presentation unit 135 generates boost information (recommendation information) that encourages action based on the combination of classification units. For example, the presentation unit 135 may present a complete answer to approximate the current radar chart RC1 to radar chart RC2, such as, "If you buy a dress from brand B at store SH1, the index for the openness item will decrease by 3." On the other hand, the presentation unit 135 may only present a small hint to approximate the current radar chart RC1 to radar chart RC2, such as, "Something good might happen if you buy something from brand B at store SH1." The presentation unit 135 can also present an intermediate hint such as, "If you buy a dress at store SH1, one of the indices will decrease."

[0135] [5. Variations] In the above embodiment, an example was shown in which the execution unit 136 performs point awarding and resetting processes. However, the execution unit 136 may perform other processes to support user U. For example, if user U has tried the game GA several times but has not been able to approximate the real state information to the ideal state information, the execution unit 136 may perform a process that provides hints that may allow user U to approximate the real state information to the ideal state information.

[0136] Here, the operation procedure of the server device 100 involved in the hint presentation process will be explained using Figure 113. Figure 13 is a flowchart of the hint presentation process according to the embodiment.

[0137] In the example shown in Figure 13, the execution unit 136 calculates the number of times user U has attempted the game GA (step S1301). For example, the execution unit 136 can calculate the number of attempts based on the purchase history (update history of real state information) stored in the customer data storage unit 121.

[0138] The execution unit 136 determines whether the number of attempts has exceeded the threshold (step S1302). If the number of attempts has not exceeded the threshold (step S1302; No), the execution unit 136 waits until the number of attempts exceeds the threshold.

[0139] On the other hand, if the number of attempts exceeds a threshold (step S1302; Yes), the execution unit 136 calculates a degree of approximation indicating how closely the current real state information of user U approximates the ideal state information (step S1303). For example, the execution unit 136 may calculate the degree of approximation as the degree of difference in shape when comparing the current shape of radar chart RC1 with the shape of radar chart RC2.

[0140] The execution unit 136 determines whether the degree of approximation is below a certain threshold (step S1304). If the degree of approximation is not below a certain threshold (step S1304; No), the execution unit 136 terminates the process. In other words, the execution unit 136 terminates the process if it determines that, as a result of user U trying the game GA several times, it has been able to approximate the real state information to the ideal state information to a certain extent.

[0141] On the other hand, if the degree of approximation is below a certain threshold (step S1304; Yes), the execution unit 136 refers to the product master data storage unit 122 and generates hint information (step S1305). In other words, if the execution unit 136 determines that user U has tried the game GA many times but has not been able to approximate the real state information to the ideal state information, it will present hint information.

[0142] For example, the execution unit 136 may generate hint information that indicates how the index of each item will change depending on the purchasing behavior. The execution unit 136 may also generate hint information that indicates how the index of each item will change depending on the purchasing behavior. Furthermore, the execution unit 136 may include specific numerical values ​​regarding how the index will change, such as "it will increase by 2" or "it will decrease by 3," or it may simply include only the manner of change in the index, such as "it will increase" or "it will decrease."

[0143] Then, the presentation unit 135 presents the generated hint information to the user U (step S1306).

[0144] According to the hint presentation process of this embodiment, it is possible to prevent situations where users repeatedly purchase products in an attempt to match real-world state information with ideal state information, but ultimately fail and lose their desire to purchase. According to the hint presentation process of this embodiment, users U who are persistently challenging the GA game can prepare in advance and check their answers.

[0145] Furthermore, the execution unit 136 may periodically release hint information not only when it determines that user U has failed to approximate the real state information to the ideal state information despite repeatedly attempting the game GA, but also at other times. For example, the execution unit 136 may control the system so that hint information is released to all users U on specific days, such as days ending in 5 or Sundays.

[0146] [6. Other Embodiments] In the embodiments described above, the purchase of goods has been used as an example of purchasing behavior. However, the proposed technology of the present invention is applicable to any purchasing behavior. For example, the proposed technology of the present invention is applicable to purchasing behaviors such as dining at restaurants, using entertainment facilities (amusement parks, movie theaters, etc.), and using moving services.

[0147] Furthermore, in the above embodiment, the predetermined target was shown to be user U, who is challenging the game GA. However, the predetermined target may not be user U, who is challenging the game GA, but for example, another person designated by user U.

[0148] [7. Hardware Configuration] The server device 100 corresponding to the information processing device according to the embodiment may be realized by the configuration shown in Figure 14. Figure 14 is a hardware configuration diagram showing an example of a computer according to the embodiment. The computer 1000 has a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

[0149] The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400, controlling various components. The ROM 1300 stores boot programs executed by the CPU 1100 when the computer 1000 starts up, as well as programs that depend on the computer 1000's hardware.

[0150] The HDD1400 stores programs executed by the CPU1100, as well as data used by such programs. The communication interface1500 receives data from other devices via a predetermined communication network and sends it to the CPU1100, and transmits data generated by the CPU1100 to other devices via the predetermined communication network.

[0151] The CPU 1100 controls output devices such as displays and input devices such as keyboards via the input / output interface 1600. The CPU 1100 acquires data from input devices via the input / output interface 1600. The CPU 1100 also outputs the generated data to output devices via the input / output interface 1600.

[0152] The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0153] For example, when the computer 1000 functions as a server device 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 130 by executing programs loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be obtained from other devices via a predetermined communication network.

[0154] [8. Other] Furthermore, among the processes described in each of the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0155] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0156] Furthermore, the above embodiments can be combined as appropriate, provided that the processing content is not contradictory.

[0157] Although some embodiments of the present invention have been described in detail above with reference to the drawings, these are illustrative examples, and the present invention can be implemented in various other forms with modifications and improvements based on the knowledge of those skilled in the art, including the embodiments described in the section on the present invention. [Explanation of Symbols]

[0158] 1. Information Processing System 10 User devices 20 Store Equipment 30 Operator equipment 100 Server Devices 110 Communications Department 120 Storage section 121 Customer Data Storage Unit 122 Product Master Data Storage Unit 123 Reward data storage unit 130 Control Unit 131 Reception Department 132 Acquisition Department 133 Extraction part 134 Correction section 135 Presentation section 136 Execution Department 137 Adjustment section 138 Promotion Department

Claims

1. An acquisition unit that acquires first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object, When a user purchases a product, an extraction unit extracts the relevant correction information from the correction information that corresponds to the purchased product, A correction unit that corrects the first state information using the target correction information, A presentation unit that presents the corrected first state information and the second state information to the user in a state where they can be compared, An information processing device equipped with the following features.

2. The extraction unit extracts the target correction information corresponding to the purchased product from the correction information set for each predetermined unit. The information processing apparatus according to claim 1.

3. The predetermined unit includes a first unit and a second unit different from the first unit, as units that are in a hierarchical relationship with each other. The extraction unit extracts combinations of the first unit and the second unit that are linked to the information of the purchased product, and extracts the correction information set for the first unit and the second unit included in the extracted combination as the target correction information. The correction unit corrects the first state information using a plurality of target correction information extracted according to the combination. The information processing apparatus according to claim 2.

4. An adjustment unit adjusts the correction content indicated by the correction information according to a predetermined context. To prepare further, The information processing apparatus according to claim 1.

5. The adjustment unit adjusts the correction content indicated by the target correction information depending on whether the place where the user purchased the product is included in the user's living area. The correction unit corrects the first state information using the adjusted target correction information. The information processing apparatus according to claim 4.

6. The adjustment unit adjusts the correction content indicated by the correction information according to a predetermined elapsed time. The extraction unit extracts the target correction information corresponding to the purchased product from the adjusted correction information. The information processing apparatus according to claim 4.

7. When a user operation is performed to request a benefit corresponding to the current first state information, an execution unit executes a process to grant the user a benefit whose content corresponds to the degree of approximation indicating how closely the current first state information approximates the second state information. A control unit that, in response to the granting of the aforementioned benefits, returns the current first state information to the first state information before correction, Furthermore, The information processing apparatus according to claim 1.

8. The aforementioned user operation includes the operation of specifying the desired type of benefit from among several different types of benefits. For each type of benefit, condition information is defined to return to the first state information before correction. The control unit, based on the condition information corresponding to the desired type specified by the user operation among the condition information for each type, returns the current first state information to the state information based on the previous first state information. The information processing apparatus according to claim 7.

9. An information processing method performed by an information processing device, An acquisition step of acquiring first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object, When a user purchases a product, the extraction process involves extracting the relevant correction information from the correction information that corresponds to the purchased product. A correction step of correcting the first state information using the target correction information, A presentation step of presenting the corrected first state information and the second state information to the user in a state where they can be compared, An information processing method that includes [the following].

10. An acquisition procedure for acquiring first state information indicating a first state of a predetermined object and second state information indicating a second state of the predetermined object, When a user purchases a product, an extraction procedure is used to extract the relevant correction information from the correction information that corresponds to the purchased product. A correction procedure for correcting the first state information using the aforementioned target correction information, A presentation procedure for presenting the corrected first state information and the second state information to the user in a state where they can be compared, An information processing program that causes a computer to execute something.

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