Information processing device, information processing method, and program

Abstract

To select a service person or a counselor suitable to the skin of a customer.SOLUTION: An information processing device for matching a customer for cosmetics and a counselor for performing counseling about the beauty of the customer includes means for calculating a first similarity between a first customer and each counselor with reference to first customer skin information on a problem of a future skin of the first customer and counselor skin information on past or present skin problems of each of a plurality of counselors, means for selecting counselor identification information for identifying a first counselor who should perform counseling to the first customer on the basis of the first similarity, and means for storing first customer identification information for identifying the first customer with the counselor identification information to store them.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] In various stores, sales staff (hereinafter also referred to as "customer service staff") have traditionally served customers who visited the store. For example, in stores selling cosmetics, beauty consultants measure the condition of customers' skin and provide skin counseling to customers.

[0003] In order to support the allocation of an appropriate responder to a customer, Patent Document 1 proposes a responder to respond to the customer from among a plurality of responders based at least on the response record and the response status. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-174096 Summary of the Invention [Problem to be solved by the invention]

[0005] However, with conventional methods, customers have few opportunities to be served by a service person who understands their skin concerns firsthand.

[0006] Therefore, the present invention aims to select a customer service representative or counselor suited to the customer's skin. [Means for solving the problem]

[0007] One embodiment of the present invention comprises: An information processing device that matches cosmetic customers with counselors who provide beauty counseling to the customers, a means for calculating a first similarity between the first customer and each counselor by referring to first customer skin information relating to future skin problems of the first customer and counselor skin information relating to past or present skin problems of each of the plurality of counselors; a means for selecting, based on the first similarity, counselor identification information for identifying a first counselor who should provide counseling to the first customer; a means for storing first customer identification information for identifying the first customer and the counselor identification information in association with each other; It is an information processing device. [Effects of the Invention]

[0008] According to the present invention, it is possible to select a customer service representative or counselor suited to the customer's skin. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is an overall configuration diagram according to a first embodiment. [Figure 2] 1 is a functional block diagram of a person selection device 10 according to a first embodiment. [Figure 3] FIG. 2 is a diagram for explaining skin characteristics identified based on genes according to the first embodiment. [Figure 4] FIG. 2 is a diagram for explaining skin characteristics identified based on genes according to the first embodiment. [Figure 5] 10 is a flowchart of a person selection process according to the first embodiment. [Figure 6] 1 is a block diagram showing an example of a hardware configuration of a person selection device according to a first embodiment. [Figure 7] FIG. 2 is a block diagram showing an example of a hardware configuration of a customer terminal according to the first embodiment. [Figure 8] FIG. 10 is an explanatory diagram of an overview of a second embodiment. [Figure 9] FIG. 10 is a diagram showing the data structures of a customer information database and a counselor information database according to the second embodiment. [Figure 10]FIG. 10 is a sequence diagram of a counselor selection process according to the second embodiment. [Figure 11] 11A and 11B are diagrams showing examples of screens displayed in the information processing of FIG. 10. [Figure 12] FIG. 10 is an explanatory diagram of an overview of a third embodiment. [Figure 13] FIG. 11 is a sequence diagram of a counselor selection process according to the third embodiment. [Figure 14] FIG. 10 is an explanatory diagram of an overview of a fourth embodiment. [Figure 15] 13 is a diagram showing the data structures of a customer makeup log information database and a counselor makeup log information database according to a fourth embodiment. FIG. [Figure 16] FIG. 13 is a diagram showing the data structures of a customer action log information database and a counselor action log information database according to the fourth embodiment. [Figure 17] FIG. 13 is a diagram showing the data structures of a customer skin diagnosis log information database and a counselor skin diagnosis log information database according to the fourth embodiment. [Figure 18] FIG. 13 is a diagram showing the data structures of a customer environment log information database and a counselor environment log information database according to the fourth embodiment. [Figure 19] FIG. 13 is a diagram showing the data structures of a customer biometric log information database and a counselor biometric log information database according to the fourth embodiment. [Figure 20] FIG. 10 is an explanatory diagram of an overview of a fifth embodiment. [Figure 21] FIG. 13 is a sequence diagram of a counselor selection process according to the fifth embodiment. [Figure 22] FIG. 13 is an explanatory diagram of an overview of a sixth embodiment. [Figure 23] FIG. 20 is a sequence diagram of a counselor selection process according to the sixth embodiment. [Figure 24] FIG. 13 is an explanatory diagram of an overview of a seventh embodiment. [Figure 25] FIG. 20 is a sequence diagram of a recommendation process according to the seventh embodiment. [Figure 26] 26 is a diagram showing an example of a screen displayed in the information processing of FIG. 25. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] This embodiment mainly describes an embodiment of customer service in the sale of cosmetics, but it is not limited to this and can also be applied to customer service in the sale of supplements, health foods and drinks, customer service in the sale of beauty equipment, customer service in aesthetic salons, etc. In this embodiment, the explanation will be mainly given of customer service in a store or over the Internet, but the present invention is not limited to this and can also be applied to customer service over the phone. In this embodiment, an example in which a host is selected when a customer is served will be mainly described, but the present invention is not limited to this example and can also be applied to a case in which a host is selected when a customer is booked for a service. In this embodiment, "cosmetics" includes both makeup and skin care. In this embodiment, "cosmetics" includes both makeup products and skin care products.

[0012] (1) First embodiment A first embodiment will be described.

[0013] (1.1) Overall Configuration of the First Embodiment The overall configuration of the first embodiment will be described below. Fig. 1 is a diagram showing the overall configuration of the first embodiment.

[0014] Example 1 In the first embodiment, a server can be selected to serve customers in a store. Specifically, the person selection device 10 selects, from among a plurality of servers, a server 11 having skin characteristics identical to or similar to the skin characteristics of a customer 21 visiting the store. The selected server then serves the customer.

[0015] <Example 2> In the first embodiment, a service provider can be selected for online customer service (e.g., customer service via chat, messages, emails, etc.). Specifically, a customer 21 uses a customer terminal 20 to access a website that sells cosmetics and the like. The customer 21 then requests online customer service using the customer terminal 20. The person selection device 10 then selects, from among multiple service providers, a service provider 11 that has the same skin characteristics as the customer 21 or skin characteristics similar to the customer 21's skin characteristics. The selected service provider then serves the customer.

[0016] (1.2) Functional Blocks of the Person Selection Device of the First Embodiment A functional block diagram of the person selection device 10 according to the first embodiment will be described below. Fig. 2 is a functional block diagram of the person selection device 10 according to the first embodiment.

[0017] 2, the person selection device 10 can include an identification unit 101, a selection unit 102, a customer skin characteristic storage unit 103, and a customer skin characteristic storage unit 104. Furthermore, the person selection device 10 can function as the identification unit 101 and the selection unit 102 by executing a program.

[0018] For example, a first person (e.g., a customer or a cosmetics customer) is a person who gives beauty advice to a second person (e.g., a customer service representative such as a beauty consultant, or a counselor who provides beauty counseling to customers). Also, for example, the second person is a person who receives beauty advice from the first person.

[0019] The identification unit 101 identifies the skin characteristics of a first person. For example, the identification unit 101 acquires information for identifying the first person (for example, a customer ID, a customer name, etc.). Furthermore, the identification unit 101 refers to the skin characteristics of the first person in the customer skin characteristic storage unit 103 based on the information for identifying the first person.

[0020] The selection unit 102 selects, from a plurality of second persons (for example, a plurality of waiters at a store), a person who has skin features that are the same as or similar to the skin features of the first person identified by the identification unit 101. The selection unit 102 outputs (for example, displays) information about the selected second person.

[0021] The selection unit 102 can select and output a plurality of persons having skin characteristics similar to those of the first person in order of most similar. The selection unit 102 can also select a person from the plurality of second persons who is available to serve customers (for example, a person who is not currently serving customers). The selection unit 102 can also select a person from the plurality of second persons who is older than the first person (i.e., a person who can give advice to the first person about future skin changes based on their own experience of dealing with past skin changes).

[0022] The customer skin characteristic storage unit 103 stores information about the skin characteristics of a first person. For example, the customer skin characteristic storage unit 103 stores genetic information about the first person. Also, for example, the customer skin characteristic storage unit 103 stores measured values ​​of the skin condition of the first person. Also, for example, the customer skin characteristic storage unit 103 stores the results of a medical interview about the first person's skin.

[0023] The customer service person skin characteristic storage unit 104 stores information about the skin characteristics of the second person. For example, the customer service person skin characteristic storage unit 104 stores genetic information about the second person. Also, for example, the customer service person skin characteristic storage unit 104 stores measured values ​​of the skin condition of the second person. Also, for example, the customer service person skin characteristic storage unit 104 stores the results of a medical interview about the second person's skin.

[0024] It is assumed that permission or consent has been obtained in advance for the genetic information, etc. of the first person and the genetic information, etc. of the second person to be stored.

[0025] (1.3) Identifying Skin Characteristics in the First Embodiment Identification of skin characteristics in the first embodiment will be described below, divided into identification based on genes, identification based on measurements of skin condition, and identification based on the results of a skin-related interview.

[0026] (1.3.1) Gene-Based Identification of the First Embodiment In the first embodiment, the skin characteristics of the first person and the second person are identified based on genes. For example, the skin characteristics are identified based on genetic SNPs (Single Nucleotide Polymorphisms). For example, the genes are related to stratum corneum moisture, dermal collagen degradation, vascular function, UV sensitivity of the skin, skin antioxidants, skin troubles, body odor, and acne. This will be described in detail below with reference to FIGS. 3 and 4.

[0027] FIG. 3 is a diagram for explaining skin characteristics identified based on genes according to the first embodiment. In the first embodiment, the first person and the second person are identified based on the seven genes shown in FIG. 3 (specifically, genes related to stratum corneum moisture, dermal collagen degradation, vascular function, UV sensitivity of the skin, antioxidation of the skin, skin trouble, body odor, and acne). 7 (Because there are three groups for each of the seven genes)

[0028] <<Number 1>> We will explain number 1 in Figure 3. The gene is "BLMH," the SNP (RS number) is "rs1050565," and the function is "stratum corneum moisturization." There are three groups: "Homo1," "Hetero," and "Homo2."

[0029] <<Number 2>> The number 2 in Figure 3 will be explained. The gene is "MMP-1", the SNP (RS number) is "rs1799750", and the function is "dermal collagen degradation". There are three groups: ", "Hetero" and "Homo2".

[0030] <<Number 3>> Let us explain number 3 in Figure 3. The gene is "VEGFA," the SNP (RS number) is "rs833061," and the function is "vascular function." There are three groups: "Homo1," "Hetero," and "Homo2."

[0031] <<Number 4>> Let us explain number 4 in Figure 3. The gene is "OCA2", the SNP (RS number) is "rs74653330", and the function is "skin UV sensitivity". There are three groups: "Homo1", "Hetero", and "Homo2".

[0032] <<Number 5>> Let us explain number 5 in Figure 3. The gene is "S0D2", the SNP (RS number) is "rs4880", and the function is "skin antioxidant". There are three groups: "Homo1", "Hetero", and "Homo2".

[0033] <<Number 6>> Let us now consider number 6 in Figure 3. The gene is "TNF(a)", the SNP (RS number) is "rs1799724", and the function is "skin problems". There are three groups: "Homo1", "Hetero", and "Homo2".

[0034] <<Number 7>> Let us explain number 7 in Figure 3. The gene is "ABCC11", the SNP (RS number) is "rs17822931", and the function is "body odor, acne". There are three groups: "Homo1", "Hetero", and "Homo2".

[0035] FIG. 4 is a diagram for explaining skin characteristics identified based on genes according to the first embodiment. As shown in FIG. 4, the first person and the second person are divided into 2187 (=3 7 (Because there are three groups for each of the seven genes)

[0036] By using seven-digit numbers like this, the genetic similarity between groups becomes clear at a glance. It is easy to see which SNPs match and which SNPs differ. For example, "1111111," "1111112," and "1111113" match six SNPs and differ in only one SNP (the seventh SNP) ("1111111" indicates that the seventh SNP is Homo1, "1111112" indicates that the seventh SNP is Hetero, and "1111113" indicates that the seventh SNP is Homo2).

[0037] In the case of genetic identification, the selection unit 102 determines that the skin features of the first person and the second person are identical if the group of the first person (i.e., all seven digits) and the group of the second person (i.e., all seven digits) are identical. Furthermore, the selection unit 102 determines that the skin features of the first person and the second person are similar if a predetermined number of digits of the first person (i.e., a portion of the seven digits) and a predetermined number of digits of the second person (i.e., a portion of the seven digits) are identical. The selection unit 102 can determine that the skin features of the first person and the second person are more similar the greater the number of identical digits in the seven digits.

[0038] In addition, each gene may be weighted (for example, if the genes related to stratum corneum moisture are the same, the skin characteristics of the first person and the skin characteristics of the second person may be determined to be more similar than if the genes related to dermal collagen degradation are the same).

[0039] (1.3.2) Identification of Skin Condition Based on Measurement Values ​​in the First Embodiment In the first embodiment, the skin characteristics of the first person and the second person are identified based on values ​​measured for the skin condition. For example, the values ​​measured for the skin condition are values ​​measured for each of the following items: Skin condition: sebum amount, pore size, stratum corneum moisture content, stratum corneum barrier (transepidermal water loss), etc. Skin shape: depth of wrinkles, length of wrinkles, area of ​​wrinkles, size of eye bags, prominence of nasolabial folds, degree of sagging, etc. Skin color characteristics: skin color, size of spots, number of spots, darkness of spots, dullness, dark circles around the eyes, etc.

[0040] In the case of identification based on skin condition measurement values, if the measurement values ​​of all items of the first person and the measurement values ​​of all items of the second person are identical, the selection unit 102 determines that the skin features of the first person and the second person are identical. Furthermore, if the measurement values ​​of a predetermined number or more items of the first person and the measurement values ​​of a predetermined number or more items of the second person are identical, the selection unit 102 determines that the skin features of the first person and the second person are similar. The selection unit 102 can determine that the skin features of the first person and the second person are more similar the more items with identical measurement values ​​there are.

[0041] It is also possible to weight each item (for example, if the measurement value of item 1 is the same, it is determined that the skin characteristics of the first person and the second person are more similar than if the measurement value of item 2 is the same).

[0042] (1.3.3) Identification based on the results of skin-related interviews in the first embodiment In the first embodiment, the skin characteristics of the first person and the second person are identified based on the results of a skin-related medical interview, such as a medical interview about changes in skin after sunburn, skin type, skin troubles, and earwax condition.

[0043] In a specific case based on the results of a skin-related medical interview, if the answers to all of the medical interviews of the first person and the answers to all of the medical interviews of the second person are identical, the selection unit 102 determines that the skin features of the first person and the second person are identical. Furthermore, if the answers to a predetermined number or more of the medical interviews of the first person and the answers to a predetermined number or more of the medical interviews of the second person are identical, the selection unit 102 determines that the skin features of the first person and the second person are similar. The selection unit 102 can determine that the more medical interviews with the same answers there are, the more similar the skin features of the first person and the second person are.

[0044] It is also possible to weight each question (for example, if the answers to Question 1 are the same, it is determined that the skin characteristics of the first person and the second person are more similar than if the answers to Question 2 are the same).

[0045] Below is an example of a skin-related questionnaire. For each question, answer 1 is the answer that indicates the most negative skin characteristics (i.e., the skin is prone to problems).

[0046] Question 1. How does your skin change when you get sunburned? Please choose the one that best applies to you. Answer 1. It doesn't turn red, it turns black Answer 2. It hardly turns red, but turns black Answer 3. It doesn't turn red very much, but turns black quickly Answer 4. It turns red and then black. A5: Immediate redness followed by slight darkening A6: My skin turns red easily, but it doesn't turn black.

[0047] I would like to ask about your skin type. Question 2: Please choose one that best describes your "usual facial skin condition." Answer 1. Oily skin (moisturized but sticky) Answer 2. Dry oily skin (oily but dry) Answer 3. Dry skin (dry and prone to rashes) Answer 4. Normal skin (moist and fresh) Answer 5: I don't know

[0048] Questionnaire 3: Were you ever diagnosed with atopic dermatitis as a child? Answer 1: Yes Answer 2: No

[0049] Question 4: Please select all that apply to your skin from the list below. Answer 1. I have visited a dermatologist and received treatment for cosmetic problems in the past. Answer 2: I have previously visited a doctor or received treatment for rough skin or rashes (including problems caused by hay fever). A3: Have you ever experienced symptoms such as redness, bumps, or swelling after using cosmetics (e.g., when switching to new products)? A4: Have you ever experienced symptoms such as itching, burning, or tingling after using cosmetics (e.g., when switching to new products)? A5. Have you ever experienced symptoms such as redness, itching, or a rash after coming into contact with precious metals, such as jewelry? Answer 6: Have you ever been diagnosed with atopic dermatitis since your 20s? A7: I was diagnosed with atopic dermatitis before my 20s. Answer 8. I have large moles, birthmarks, scars, or burn marks on my face. A9. Have you ever experienced symptoms such as eczema or hives when exposed to sunlight? A10. Have a family member (parent, sibling, child) diagnosed with atopic dermatitis? Answer 11: None of the above

[0050] Question 5: Is your skin sensitive? Answer 1: Very sensitive Answer 2. Sensitive Answer 3. Normal Answer 4: A little

[0051] Question 6: Is your skin easily irritated? Answer 1. Very prone to irritation Answer 2. It's a little rough Answer 3. Normal Answer 4. Less likely to irritate

[0052] Question 7: Please choose the answer that best describes the current skin tone of your face. Answer 1. I think it's white. Answer 2. I think it's black. Answer 3. I think it's yellow. Answer 4. I think it's red. Answer 5. I think it's blue. Answer 6. Other

[0053] Question 8: Please choose the answer that best describes the color tendency of your natural skin (areas not exposed to the sun, belly, etc.). Answer 1. I think it's white. Answer 2. I think it's black. Answer 3. I think it's yellow. Answer 4. I think it's red. Answer 5. I think it's blue. Answer 6. Other

[0054] I would like to ask you about your skin problems. Question 9: Do you have dull skin on your face? Answer 1: Yes Answer 2: No

[0055] Question 10. Do you have any spots on your skin? Answer 1: Yes Answer 2: No

[0056] Question 11. Do you have wrinkles on your skin? Answer 1: Yes Answer 2: No

[0057] Question 12: Do you have any noticeable blackheads (clogged pores) on your skin, especially around your nose? Answer 1: Yes Answer 2: No

[0058] Question 13. Does your skin often feel sticky or oily? Answer 1: Yes Answer 2: No

[0059] Question 14: Have you ever had acne or pimples on your skin? Answer 1: Yes Answer 2: No

[0060] Question 15: Does your skin often become dry or flaky? Answer 1: Yes Answer 2: No

[0061] Question 16. Do you have any noticeable pores on your skin? Answer 1: Yes Answer 2: No

[0062] Question 17: Do you have any noticeable acne scars on your skin? Answer 1: Yes Answer 2: No

[0063] Question 18: Do you have any loose skin? Answer 1: Yes Answer 2: No

[0064] Question 19. Do you have dark circles on your skin? Answer 1: Yes Answer 2: No

[0065] I would like to ask you about your earwax condition. Question 20: Which of the following best describes your usual earwax condition? Answer 1: It's damp Answer 2: Dry Answer 3: It varies from day to day.

[0066] (1.4) Person Selection Process in the First Embodiment The person selection process according to the first embodiment will be described with reference to Fig. 5, which is a flowchart of the person selection process according to the first embodiment.

[0067] In step 1 (S1), the identification unit 101 identifies the skin characteristics of a first person. For example, the identification unit 101 acquires information for identifying the first person (e.g., a customer ID, a customer name, etc.). Next, the identification unit 101 refers to the skin characteristics of the first person in the customer skin characteristic storage unit 103 based on the information for identifying the first person.

[0068] In step 2 (S2), the selection unit 102 selects from a plurality of second persons (e.g., a plurality of customer service staff in a store) a person who has skin characteristics identical to or similar to the skin characteristics of the first person identified in S1.

[0069] The selection unit 102 can select and output a plurality of persons having skin characteristics similar to those of the first person in order of most similar. The selection unit 102 can also select a person from the plurality of second persons who is available to serve customers (for example, a person who is not currently serving customers). The selection unit 102 can also select a person from the plurality of second persons who is older than the first person (i.e., a person who can give advice to the first person about future skin changes based on their own experience of dealing with past skin changes).

[0070] (1.5) Effects of the First Embodiment In this way, in the first embodiment, a customer service representative with the same or similar skin characteristics as the customer can provide service. The customer service representative is likely to have the same skin concerns as the customer (or have had the same skin concerns as the customer). Therefore, the customer service representative can empathize with the customer's skin concerns and provide service tailored to the customer's skin characteristics (for example, suggesting cosmetics, dietary habits, and exercises).

[0071] In the first embodiment, customers and beauty consultants can be matched based on genetic similarities. Just as some people are prone to reddening and others are not even exposed to the same amount of UV rays, people's reactivity to UV rays differs depending on their original genetic differences. It is believed that differences in skin characteristics can be inherited. The skin characteristics of the consultant and the customer are the same or similar, due to genetic factors, rather than skin characteristics due to environmental factors. Therefore, even if the environmental factors of the consultant and the customer are different, the consultant can empathize with the customer's skin concerns and provide customer service that is tailored to the customer's skin characteristics (for example, suggesting cosmetics, dietary habits, and exercises).

[0072] In the first embodiment, a customer and a beauty consultant can be matched based on the age difference between them. Because skin changes with age, the beauty consultant can give advice to the customer about future skin changes based on their past experience of dealing with their own skin changes.

[0073] (1.6) Hardware Configuration of the First Embodiment The hardware configuration of the first embodiment will be described.

[0074] (1.6.1) Hardware configuration of the person selection device of the first embodiment A description will be given of the hardware configuration of the person selecting device 10 according to the first embodiment. Fig. 6 is a block diagram showing an example of the hardware configuration of the person selecting device according to the first embodiment.

[0075] The person selection device 10 is a client computer or a host computer (an example of an "information processing device"). The client computer is a computer (an example of an "information processing device") that can realize its functions without communicating with other computers (for example, the customer terminal 20). A host computer is a computer (for example, a server) that is connected to other computers via a network (for example, the Internet or an intranet) and can realize functions by communicating with other computers.

[0076] 6, the person selection device 10 has a CPU (Central Processing Unit) 1001, a ROM (Read Only Memory) 1002, and a RAM (Random Access Memory) 1003. The CPU 1001, the ROM 1002, and the RAM 1003 form a so-called computer.

[0077] The person selection device 10 may also have an auxiliary storage device 1004, a display device 1005, an operation device 1006, an I / F (Interface) device 1007, and a drive device 1008. The hardware components of the person selection device 10 are connected to each other via a bus B.

[0078] The CPU 1001 is a computing device that executes various programs installed in the auxiliary storage device 1004 .

[0079] The ROM 1002 is a non-volatile memory. The ROM 1002 functions as a main storage device that stores various programs, data, etc. required for the CPU 1001 to execute various programs installed in the auxiliary storage device 1004. Specifically, the ROM 1002 functions as a main storage device that stores boot programs such as a BIOS (Basic Input / Output System) and an EFI (Extensible Firmware Interface).

[0080] The RAM 1003 is a volatile memory such as a dynamic random access memory (DRAM) or a static random access memory (SRAM). The RAM 1003 functions as a main storage device that provides a working area in which various programs installed in the auxiliary storage device 1004 are expanded when the CPU 1001 executes them.

[0081] The auxiliary storage device 1004 is an auxiliary storage device that stores various programs and information used when the various programs are executed.

[0082] The display device 1005 is a display device that displays the internal state of the person selection device 10 and the like.

[0083] The operation device 1006 is an input device through which the administrator of the person selecting device 10 inputs various instructions to the person selecting device 10 .

[0084] The I / F device 1007 is a communication device that connects to a network and communicates with other devices.

[0085] Drive device 1008 is a device for loading storage medium 1009. The storage medium 1009 here includes media that record information optically, electrically, or magnetically, such as CD-ROMs, flexible disks, and magneto-optical disks. Storage medium 1009 may also include semiconductor memories that record information electrically, such as EPROMs (Erasable Programmable Read Only Memory) and flash memories.

[0086] The various programs to be installed in the auxiliary storage device 1004 are installed, for example, by setting the distributed storage medium 1009 in the drive device 1008 and reading out the various programs recorded on the storage medium 1009 by the drive device 1008. Alternatively, the various programs to be installed in the auxiliary storage device 1004 may be installed by being downloaded from a network via the I / F device 1007.

[0087] (1.6.2) Hardware configuration of the customer terminal in the first embodiment A description will be given of the hardware configuration of the customer terminal 20 according to the first embodiment. Fig. 7 is a block diagram showing an example of the hardware configuration of the customer terminal according to the first embodiment.

[0088] The customer terminal 20 is a client computer that can communicate with the person selection device 10 that functions as a host computer.

[0089] 7, the customer terminal 20 includes a CPU 2001, a ROM 2002, and a RAM 2003. The CPU 2001, the ROM 2002, and the RAM 2003 form a so-called computer.

[0090] The customer terminal 20 may also have an auxiliary storage device 2004, a display device 2005, an operation device 2006, an I / F device 2007, and a drive device 2008. The hardware components of the customer terminal 20 are connected to each other via a bus B.

[0091] The CPU 2001 is a computing device that executes various programs installed in the auxiliary storage device 2004 .

[0092] The ROM 2002 is a non-volatile memory. The ROM 2002 functions as a main storage device that stores various programs, data, etc. required for the CPU 2001 to execute various programs installed in the auxiliary storage device 2004. Specifically, the ROM 2002 functions as a main storage device that stores boot programs such as BIOS and EFI.

[0093] The RAM 2003 is a volatile memory such as a DRAM or an SRAM. The RAM 2003 functions as a main storage device that provides a working area in which various programs installed in the auxiliary storage device 2004 are expanded when the CPU 2001 executes them.

[0094] The auxiliary storage device 2004 is an auxiliary storage device that stores various programs and information used when the various programs are executed.

[0095] The display device 2005 is a display device that displays the internal state of the customer terminal 20 and the like.

[0096] The operation device 2006 is an input device through which the manager of the customer terminal 20 inputs various instructions to the customer terminal 20 .

[0097] The I / F device 2007 is a communication device that connects to a network and communicates with other devices.

[0098] Drive device 2008 is a device for loading storage medium 2009. Storage medium 2009 here includes media that record information optically, electrically, or magnetically, such as CD-ROMs, flexible disks, and magneto-optical disks. Storage medium 2009 may also include semiconductor memories that record information electrically, such as EPROMs and flash memories.

[0099] The various programs to be installed in the auxiliary storage device 2004 are installed, for example, by setting the distributed storage medium 2009 in the drive device 2008 and reading out the various programs recorded in the storage medium 2009 by the drive device 2008. Alternatively, the various programs to be installed in the auxiliary storage device 2004 may be installed by being downloaded from a network via the I / F device 2007.

[0100] (1.7) Supplementary notes for the first embodiment The first aspect of the first embodiment is identifying skin characteristics of a first person; selecting, from the plurality of second persons, persons having skin characteristics identical to or similar to skin characteristics of the first person; The information processing method includes:

[0101] A second aspect of the first embodiment is The first person is a person who gives beauty advice to the second person. In the information processing method according to the first aspect, the second person is a person who receives beauty advice from the first person.

[0102] A third aspect of the first embodiment is In the information processing method according to the first or second aspect, the skin characteristics are identified based on genes.

[0103] A fourth aspect of the first embodiment is In the information processing method according to the third aspect, the skin characteristics are identified based on genetic SNPs.

[0104] A fifth aspect of the first embodiment is This is an information processing method according to the third aspect, wherein the genes are genes related to stratum corneum moisture, dermal collagen degradation, vascular function, skin UV sensitivity, skin antioxidant activity, skin troubles, body odor, and acne.

[0105] A sixth aspect of the first embodiment is In the information processing method according to the first or second aspect, the skin characteristics are identified based on values ​​obtained by measuring the skin condition.

[0106] A seventh aspect of the first embodiment is This is the information processing method according to the sixth aspect, wherein the values ​​are values ​​relating to the amount of sebum, size of pores, moisture content of the stratum corneum, stratum corneum barrier (transepidermal water loss), wrinkle depth, wrinkle length, wrinkle area, size of bags under the eyes, prominence of nasolabial folds, degree of sagging, skin color, size of spots, number of spots, darkness of spots, degree of dullness, and degree of dark circles around the eyes.

[0107] An eighth aspect of the first embodiment is In the information processing method according to the first or second aspect, the skin characteristics are identified based on the results of a skin-related interview.

[0108] A ninth aspect of the first embodiment is In the information processing method according to the eighth aspect, the medical interview is an interview about changes in the case of sunburn, skin type, skin troubles, and earwax condition.

[0109] A tenth aspect of the first embodiment is means for identifying skin characteristics of the first person; a means for selecting, from a plurality of second persons, a person having skin characteristics identical to or similar to the skin characteristics of the first person; The information processing device is provided with:

[0110] (2) Second embodiment A second embodiment will be described. The second embodiment is an example in which a counselor suitable for a customer is selected based on the degree of similarity between information about the customer's future skin problems and information about the counselor's past or present skin problems. Descriptions similar to those of the above-mentioned embodiment will be omitted.

[0111] (2.1) Overview of the Second Embodiment An outline of the second embodiment will be explained below: Fig. 8 is an explanatory diagram of the outline of the second embodiment.

[0112] As shown in FIG. 8, in the second embodiment, the person selecting device 10 stores customer skin information and counselor skin information. The customer skin information is information about future skin problems of the cosmetic customer (for example, troubles predicted to occur in the customer's skin in the future). Counselor skin information is information about past or present skin problems of a counselor who provides beauty counseling to a client.

[0113] Skin problems include, for example, at least one of the following: Skin problems Skin problems

[0114] The person selection device 10 calculates a first similarity by comparing customer characteristic information (hereinafter referred to as "first customer characteristic information") of a customer (hereinafter referred to as "first customer") who is the subject of counseling with counselor characteristic information of a counselor. The first similarity is the level of similarity between the customer characteristic information and the counselor characteristic information of each counselor.

[0115] The person selection device 10 selects a counselor (hereinafter referred to as "first counselor") who should provide counseling to the first client based on the first similarity.

[0116] The person selecting device 10 stores customer identification information of the first customer (hereinafter referred to as "first customer identification information") and counselor identification information of the first counselor (hereinafter referred to as "first counselor identification information") in association with each other.

[0117] The person selecting device 10 presents the first counselor identification information to the customer terminal 20 used by the first customer, thereby notifying the first customer of the first counselor who will be in charge of the first customer.

[0118] (2.2) Database of the Second Embodiment The database of the second embodiment will be described.

[0119] (2.2.1) Customer Information Database and Counselor Information Database of the Second Embodiment A description will be given of the customer information database and the counselor information database of the second embodiment. Fig. 9 is a diagram showing the data structures of the customer information database and the counselor information database of the second embodiment.

[0120] 9A stores customer information, which is information about each of a plurality of customers. The customer information database includes a "customer ID" field, a "customer name" field, an "address" field, a "customer attribute" field, a "customer genetics" field, a "customer skin type" field, and a "counselor ID" field. Each field is associated with the others.

[0121] The "customer ID" field stores a customer ID. The customer ID is an example of information that identifies a customer (hereinafter referred to as "customer identification information").

[0122] The "customer name" field stores customer name information. The customer name information is information about the name of the customer. The customer name information is an example of customer identification information.

[0123] The "address" field stores customer address information, which is information about the customer's address.

[0124] The "customer attribute" field stores customer attribute information. The customer attribute information is information about the attributes of a customer. The "customer attribute" field includes a "gender" field, an "age" field, a "race" field, a "height" field, and a "weight" field.

[0125] The "gender" field stores customer gender information, which is information about the gender of the customer.

[0126] The "age" field stores customer age information, which is information about the age of the customer.

[0127] The "race" field stores customer race information, which is information about the race of the customer.

[0128] The "height" field stores customer height information. The customer height information is information about the height of the customer.

[0129] The "weight" field stores customer weight information. The customer weight information is information about the weight of the customer.

[0130] The "customer genetic" field stores customer genetic information. The customer genetic information is information about the customer's genes. The customer genetic information is, for example, information about the results of a customer's DNA (DeoxyriboNucleic Acid) test.

[0131] The "Customer Skin" field stores customer skin information. The customer skin information is information about the innate characteristics of the customer's skin and the customer's current and future skin problems. The customer skin information is identified, for example, based on the information in the "Customer Genetics" field. The innate characteristics and skin problems include, for example, at least one of the following: · Moisturizes the stratum corneum Degradation of dermal collagen Vascular function Skin sensitivity to UV rays Antioxidant for skin ·body odor Acne

[0132] The "Counselor ID" field stores the counselor ID of the first counselor for each customer.

[0133] Counselor information is stored in the counselor information database of Fig. 9B. The counselor information is information about each of a plurality of counselors. The counselor information database includes a "counselor ID" field, a "counselor name" field, an "address" field, a "counselor attribute" field, a "counselor genetics" field, and a "counselor skin type" field. Each field is associated with the other fields.

[0134] The "Counselor ID" field stores a counselor ID. The counselor ID is an example of information for identifying a counselor (hereinafter referred to as "counselor identification information").

[0135] The "Counselor Name" field stores counselor name information. The counselor name information is information about the name of the counselor. The counselor name information is an example of counselor identification information.

[0136] The "Address" field stores counselor address information, which is information about the counselor's address.

[0137] The "Counselor Attributes" field stores counselor attribute information. The counselor attribute information is information about the attributes of a counselor. The "Counselor Attributes" field includes a "Gender" field, an "Age" field, a "Race" field, a "Height" field, and a "Weight" field.

[0138] The "gender" field stores counselor gender information, which is information about the gender of the counselor.

[0139] The "age" field stores counselor age information, which is information about the counselor's age.

[0140] The "race" field stores counselor race information, which is information about the race of the counselor.

[0141] The "height" field stores counselor height information. The counselor height information is information about the counselor's height.

[0142] The "weight" field stores counselor weight information, which is information about the weight of the counselor.

[0143] The "Counselor Genetics" field stores counselor genetic information. The counselor genetic information is information about the counselor's genes. For example, the counselor genetic information is information about the results of a DNA test performed on the counselor.

[0144] The "Counselor Skin" field stores counselor skin information. The counselor skin information is information about the counselor's innate skin characteristics and the counselor's current and future skin problems. The counselor skin information is identified, for example, based on the information in the "Counselor Genetics" field. The counselor skin information includes, for example, at least one of the following: · Moisturizes the stratum corneum Degradation of dermal collagen Vascular function Skin sensitivity to UV rays Antioxidant for skin ·body odor Acne

[0145] (2.3) Information Processing in the Second Embodiment The information processing of the second embodiment will be described below. Fig. 10 is a sequence diagram of the counselor selection processing of the second embodiment. Fig. 11 is a diagram showing an example of a screen displayed in the information processing of Fig. 10.

[0146] The trigger for the processing in FIG. 10 is, for example, an instruction from the customer (hereinafter referred to as "customer instruction") to display screen P2120 (FIG. 11).

[0147] The customer terminal 20 receives the customer instruction (S2120). Specifically, the CPU 2001 displays a screen P2120 (FIG. 11) on the display device 2005.

[0148] The screen P2120 includes an operation object B2120 and a field object F2120.

[0149] The field object F2120 is an object that receives a customer instruction for inputting a customer ID.

[0150] The operation object B2120 is an object that receives a customer instruction for confirming the customer instruction input to the field object F2120.

[0151] After step S2120, the customer terminal 20 executes a matching request (S2121). Specifically, when a customer inputs his / her customer ID into the field object F2120 and operates the operation object B2120, the CPU 2001 transmits matching request data to the person selecting device 10. The matching request data includes the customer ID input into the field object F2120.

[0152] After step S2121, the person selection device 10 executes estimation of future skin problems (S2110).

[0153] In a first example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0154] CPU 1001 refers to the customer information database (Figure 9A) and identifies the genetic information (hereinafter referred to as "first customer genetic information") in the "customer genetics" field associated with the customer ID (hereinafter referred to as "first customer ID") included in the matching request data. The CPU 1001 inputs the first customer genetic information into a skin problem estimation model to estimate future skin problems of the first customer.

[0155] In a second example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and the results of a medical interview, and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0156] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetics" field associated with the first customer ID included in the matching request data. The CPU 1001 refers to the customer skin characteristic storage unit 103 to identify the results of the medical interview of the first customer. The CPU 1001 inputs the first customer's genetic information and the results of the medical interview of the first customer into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0157] After step S2110, the person selecting device 10 executes calculation of the first similarity (S2111). Specifically, CPU 1001 calculates the similarity between the first customer and each counselor (hereinafter referred to as "first similarity") by comparing the counselor skin information in the "Counselor Skin" field in the counselor information database (Figure 9B) with the estimated results of the first customer's future skin problems.

[0158] After step S2111, the person selecting device 10 selects a first counselor (S2112).

[0159] Specifically, CPU 1001 identifies, as a first counselor ID, the counselor ID of the counselor corresponding to the first similarity that satisfies a predetermined condition from the processing results of step S2111 (ie, the first similarity). The first similarity condition is, for example, at least one of the following. The first similarity is the largest. - The counselor has many negative answers to the questionnaire questions that match or are similar to those of the first client (for example, "Question 6: Is your skin prone to irritation?" to "Answer 1: Very prone to irritation").

[0160] After step S2112, the person selecting device 10 updates the database (S2113). Specifically, CPU 1001 stores the first counselor ID identified in step S2112 in the "counselor" field associated with the customer ID of the first customer in the customer information database (FIG. 9A).

[0161] After step S2113, the person selecting device 10 executes a matching response (S2114). Specifically, the CPU 1001 refers to the counselor information database (FIG. 9B) to identify the counselor information associated with the first counselor ID. The CPU 1001 transmits the matching response data to the client terminal 20. The matching response data includes the identified counselor information (for example, counselor ID, counselor name, gender, and age).

[0162] After step S2114, the customer terminal 20 presents counselor information (S2122). Specifically, the CPU 2001 displays a screen P2121 (FIG. 11) on the display device 2005.

[0163] The screen P2121 displays the counselor information contained in the matching response data.

[0164] (2.4) Effects of the Second Embodiment According to the second embodiment, a first counselor who has a high degree of similarity with the first customer regarding future skin problems is selected, thereby making it possible to assign a counselor who is suitable for solving future skin problems to the first customer.

[0165] (2.4) Modification of the second embodiment In step S2112, if there are multiple counselors who meet the first similarity condition, the person selecting device 10 may re-execute the calculation of the first similarity (S2111). Specifically, CPU 1001 refers to the first customer's cosmetic purchase history (for example, customer behavior log information (FIG. 16A) described later) and identifies the area corresponding to the first customer's future skin concerns based on the types of cosmetics frequently purchased. For example, if the first customer frequently purchases eye care cosmetics, CPU 1001 estimates that the first customer's future skin concerns will be predominant around the eyes. The CPU 1001 increases the weighting coefficient for future skin concerns around the eyes for each counselor's first similarity, and recalculates the first similarity using the weighting coefficient. As a result, a counselor with a high first similarity regarding future skin concerns estimated from cosmetics frequently purchased by the first customer is selected as the first counselor.

[0166] (3) Third embodiment A third embodiment will be described. The third embodiment is an example in which a first counselor suitable for a first customer is selected based on a second similarity between a second customer similar to the first customer and the counselor. Explanations similar to those of the above embodiments will be omitted.

[0167] (3.1) Overview of the third embodiment An outline of the third embodiment of the present invention will be described below with reference to Fig. 12, which is an explanatory diagram of the outline of the third embodiment.

[0168] As shown in FIG. 12, in the third embodiment, the person selecting device 10 stores customer skin information and counselor skin information. The customer skin information is information regarding future skin problems of the cosmetic customer. Counselor skin information is information about past or present skin problems of a counselor who provides beauty counseling to a client.

[0169] Skin problems include, for example, at least one of the following: Skin problems Skin problems

[0170] The person selection device 10 calculates a second similarity by comparing the first customer skin information of the first customer who is the subject of counseling with customer skin information (hereinafter referred to as "second customer skin information") of a customer other than the first customer (hereinafter referred to as "second customer"). The second similarity is the level of similarity between the first customer skin information and the second customer skin information.

[0171] The person selection device 10 selects a customer whose future skin problem is similar to that of the first customer (hereinafter referred to as a "similar customer") based on the second similarity.

[0172] The person selecting device 10 calculates the first similarity by comparing the second customer characteristic information of the similar customer with the counselor characteristic information of the counselor.

[0173] The person selection device 10 selects a first counselor to provide counseling to the first customer based on the first similarity.

[0174] The person selecting device 10 stores the first customer identification information and the first counselor identification information in association with each other.

[0175] The person selecting device 10 presents the first counselor identification information to the customer terminal 20 used by the first customer, thereby notifying the first customer of the first counselor who will be in charge of the first customer.

[0176] (3.2) Information Processing in the Third Embodiment The information processing of the third embodiment of the present invention will be described below with reference to Fig. 13, which is a sequence diagram of the counselor selection processing of the third embodiment.

[0177] The trigger for the processing in FIG. 13 is, for example, a customer instruction to display the counselor selection processing screen P2120 (FIG. 11).

[0178] The customer terminal 20 executes the steps from receiving customer instructions (S2120) to making a matching request (S2121) in the same manner as in the second embodiment.

[0179] After step S2121, the person selection device 10 executes estimation of future skin problems (S3110). Specifically, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0180] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID. The CPU 1001 inputs the first customer genetic information into a skin problem estimation model to estimate future skin problems of the first customer.

[0181] CPU 1001 refers to the customer information database (Figure 9A) and identifies the genetic information in the "customer genetic" field (hereinafter referred to as "second customer genetic information") associated with the customer ID of the second customer (hereinafter referred to as "second customer ID"). The CPU 1001 inputs the second customer genetic information into a skin problem estimation model to estimate future skin problems of the second customer.

[0182] After step S3110, the person selecting device 10 executes calculation of the second similarity (S3111). Specifically, the CPU 1001 calculates a second similarity between the first customer and the second customer by comparing the estimated results of future skin problems of the first customer with the estimated results of future skin problems of the second customer.

[0183] After step S3111, the person selecting device 10 executes the selection of similar customers (S3112). Specifically, CPU 1001 selects the customer ID of a similar customer (hereinafter referred to as a "similar customer ID") corresponding to the second similarity that satisfies a predetermined condition from the processing results of step S3111 (that is, the second similarity). The second similarity condition is, for example, at least one of the following. The second similarity is the maximum. - The second customer had many negative answers to the questionnaire that matched or were similar to those of the first customer (for example, "Question 5: Is your skin sensitive?" to "Answer 2: Very sensitive"). The second similarity is that the second customer has used the cosmetics used by the first customer for a longer period than the first customer. The second similarity is that of a second customer who is older than the first customer (i.e., a customer who has had experience dealing with changes in their own skin in the past). - The second similarity is that of a second customer whose genetic information and cosmetic use history match or are similar.

[0184] After step S3112, the person selecting device 10 executes calculation of the first similarity (S3113).

[0185] The CPU 1001 calculates the similarity between similar customers and each counselor as the first similarity by comparing the counselor skin information in the "Counselor Skin" field in the counselor information database (Figure 9B) with the estimated results of future skin problems of similar customers.

[0186] After step S3113, the person selecting device 10 executes the steps from selection of a first counselor (S2112) to matching response (S2114) in the same manner as in the second embodiment. After step S2114, the customer terminal 20 presents counselor information (S2122).

[0187] (3.3) Effects of the Third Embodiment According to the third embodiment, a counselor suitable for similar customers to the first customer is selected as the first counselor for the first customer, thereby making it possible to assign to the first customer a counselor suitable for solving future skin problems.

[0188] (3.4) Modification of the third embodiment In step S3112, if there are a plurality of similar customers who meet the second similarity condition, the person selecting device 10 may re-execute the calculation of the second similarity (S3111). Specifically, CPU 1001 refers to the first customer's cosmetic purchase history (for example, customer behavior log information (FIG. 16A) described later) and identifies the area corresponding to the first customer's future skin concerns based on the types of cosmetics frequently purchased. For example, if the first customer frequently purchases eye care cosmetics, CPU 1001 estimates that the first customer's future skin concerns will be predominant around the eyes. The CPU 1001 increases the weighting coefficient for future skin concerns around the eyes for the second similarity of each similar customer, and recalculates the second similarity using the weighting coefficient. As a result, a second customer having a high second similarity in terms of future skin concerns estimated from cosmetics frequently purchased by the first customer is selected as a similar customer.

[0189] (4) Fourth embodiment A fourth embodiment will be described. The fourth embodiment is an example in which a counselor suitable for a customer is selected based on the degree of similarity between customer skin information and customer log information and counselor skin information and counselor log information. Explanations similar to those of the above embodiments will be omitted.

[0190] (4.1) Overview of the Fourth Embodiment An outline of the fourth embodiment of the present invention will be described below with reference to Fig. 14, which is an explanatory diagram of the outline of the fourth embodiment.

[0191] As shown in FIG. 14, in the fourth embodiment, the person selecting device 10 stores customer skin information, customer log information, counselor skin information, and counselor log information. The customer log information is customer information in chronological order. The counselor log information is counselor information in chronological order.

[0192] The person selection device 10 calculates the first similarity by comparing the first customer characteristic information and customer log information (hereinafter referred to as "first customer log information") of the first customer who is the subject of counseling with the counselor characteristic information and counselor log information of the counselor.

[0193] The person selection device 10 selects a first counselor to provide counseling to the first customer based on the first similarity.

[0194] The person selecting device 10 stores the first customer identification information of the first customer and the first counselor identification information of the first counselor in association with each other.

[0195] The person selecting device 10 presents the first counselor identification information to the customer terminal 20 used by the first customer, thereby notifying the first customer of the first counselor who will be in charge of the first customer.

[0196] (4.2) Database of the Fourth Embodiment The database of the fourth embodiment will be described.

[0197] (4.2.1) Customer Makeup Log Information Database and Counselor Makeup Log Information Database of the Fourth Embodiment A description will be given of a customer makeup log information database and a counselor makeup log information database according to the fourth embodiment. Fig. 15 is a diagram showing the data structures of the customer makeup log information database and the counselor makeup log information database according to the fourth embodiment.

[0198] 15A stores customer makeup log information. The customer makeup log information is information related to the customer's makeup history. The customer makeup log information is updated based on information transmitted from a container that contains cosmetics used by the customer, is capable of acquiring the cosmetic identification information and remaining amount of the cosmetics, and is capable of communicating with the person selection device 10. The customer makeup log information database includes a "timestamp" field, a "cosmetic product" field, a "method of use" field, a "amount used" field, and a "time of use" field. Each field is associated with the other fields. The customer makeup log information database is associated with a customer ID.

[0199] The "timestamp" field stores customer makeup log timestamp information, which is information about when a customer used cosmetics.

[0200] The "Cosmetics" field stores cosmetics information. The cosmetics information includes, for example, at least one of the following: Information identifying the cosmetics used by the customer (e.g., product number or product name of the cosmetics) · Cosmetics brands used by customers within a certain period (e.g., one year) - The types of cosmetics used by customers within a certain period of time The number of cosmetics used by the customer within a certain period of time

[0201] The "usage" field stores customer usage information. The customer usage information is information about how the customer uses the cosmetic product. The usage of the cosmetic product includes, for example, at least one of the following: The difference between morning and evening skin care methods · Number of skin care routines per day At least one cosmetic product per use

[0202] The "usage amount" field stores information about the amount of cosmetics used by the customer. The information about the amount of cosmetics used by the customer is information about the amount of cosmetics used by the customer (for example, the amount used in one application of makeup).

[0203] The "Usage Time" field stores customer cosmetic use time information. The customer cosmetic use time information is information about the time a customer uses cosmetics (hereinafter referred to as "use time"). The use time includes, for example, at least one of the following: Time required for one makeup application · Usage time for each cosmetic product ·Time of day to perform skin care

[0204] 15B stores counselor makeup log information. The counselor makeup log information is information related to the makeup history of a counselor. The counselor makeup log information is updated based on information transmitted from a container that contains cosmetics used by a counselor, is capable of acquiring the cosmetic identification information and remaining amount of the cosmetics, and is capable of communicating with the person selection device 10. The counselor makeup log information database includes a "timestamp" field, a "cosmetics" field, a "method of use" field, a "amount used" field, and a "time of use" field. Each field is associated with the other fields. The counselor makeup log information database is associated with the counselor ID.

[0205] The "timestamp" field stores counselor makeup log timestamp information, which is information about the timing at which the counselor used cosmetics.

[0206] The "cosmetics" field stores cosmetic information, which identifies the cosmetics used by the counselor.

[0207] The "usage" field stores counselor usage information, which is information about how a counselor uses a cosmetic product.

[0208] The "usage amount" field stores information about the amount of cosmetics used by the counselor. The information about the amount of cosmetics used by the counselor in one application of makeup is information about the amount of cosmetics used by the counselor in one application of makeup.

[0209] The "Use Time" field stores counselor cosmetic use time information, which is information about the time a counselor uses a cosmetic product.

[0210] (4.2.2) Customer Action Log Information Database and Counselor Action Log Information Database of the Fourth Embodiment A customer behavior log information database and a counselor behavior information database according to the fourth embodiment will now be described. Fig. 16 is a diagram showing the data structures of the customer behavior log information database and the counselor behavior log information database according to the fourth embodiment.

[0211] The customer behavior log information database in Figure 16A stores customer behavior log information. The customer behavior log information is information related to the history of customer behavior. The customer behavior log information is information transmitted from at least one of a wearable device worn by a customer and a web server. The customer behavior log information database includes a "timestamp" field and an "behavior" field, each of which is associated with the other. The customer behavior log information database is associated with a customer ID.

[0212] The "timestamp" field stores customer action log timestamp information, which is information about the timing of a customer's action.

[0213] The "behavior" field stores behavior information. The behavior information is information about the behavior of the customer. The behavior includes, for example, at least one of the following: ·meal Walking ·motion Browsing the website · Purchasing products (e.g., cosmetics)

[0214] The counselor action log information database in Fig. 16B stores counselor action log information. The counselor action log information is information about the history of a counselor's actions. The counselor action log information is information transmitted from at least one of a wearable device worn by a counselor and a web server. The counselor action log information database includes a "timestamp" field and an "action" field, each of which is associated with the other. The counselor action log information database is associated with the counselor ID.

[0215] The "timestamp" field stores counselor action log timestamp information, which is information about the timing at which the counselor took action.

[0216] The "behavior" field stores counselor behavior information, which is information about the behavior of the counselor.

[0217] (4.2.3) Customer Skin Diagnosis Log Information Database and Counselor Skin Diagnosis Log Information Database of the Fourth Embodiment A description will be given of a customer skin diagnosis log information database and a counselor skin diagnosis log information database according to the fourth embodiment. Fig. 17 is a diagram showing the data structures of a customer skin diagnosis log information database and a counselor skin diagnosis log information database according to the fourth embodiment.

[0218] The customer skin diagnosis log information database in FIG. 17A stores customer skin diagnosis log information. The customer skin diagnosis log information is information related to the history of the results of a customer's skin diagnosis. The most recent result of a customer's skin diagnosis indicates the customer's current skin condition. The skin diagnosis is performed based on, for example, at least one of an image taken by a smartphone camera and the sensing results of a skin measurement device equipped with a sensor. The customer skin diagnosis log information database includes a "timestamp" field and a "skin diagnosis" field. Each field is associated with the other. The customer skin diagnosis log information database is associated with the customer ID.

[0219] The "timestamp" field stores customer skin diagnosis log timestamp information. The customer skin diagnosis log timestamp information is information about the timing of when the customer had their skin diagnosed.

[0220] The "skin diagnosis" field stores customer skin diagnosis information. The customer skin diagnosis information is information about the results of a customer's skin diagnosis.

[0221] Counselor skin diagnosis log information is stored in the counselor skin diagnosis log information database of Fig. 17B. The counselor skin diagnosis log information is information about the history of the results of skin diagnoses by counselors. The counselor skin diagnosis log information database includes a "timestamp" field and a "skin diagnosis" field. Each field is associated with the other. The counselor skin diagnosis log information database is associated with the counselor ID.

[0222] The "timestamp" field stores counselor skin diagnosis log timestamp information, which is information about the timing when the counselor performed the skin diagnosis.

[0223] The "skin diagnosis" field stores counselor skin diagnosis information, which is information about the results of a counselor's skin diagnosis.

[0224] (4.2.4) Customer environment log information database and counselor environment log information database of the fourth embodiment A description will be given of a customer environment log information database and a counselor environment log information database according to the fourth embodiment. Fig. 18 is a diagram showing the data structures of the customer environment log information database and the counselor environment log information database according to the fourth embodiment.

[0225] The customer environment log information database in Figure 18A stores customer environment log information. The customer environment log information is information about the history of the customer's external environment. The customer environment log information is transmitted from the wearable device worn by the customer and the smartphone carried by the customer. The customer environment log information database includes a "timestamp" field and an "environment" field, each of which is associated with the other. The customer environment log information database is associated with the customer ID.

[0226] The "timestamp" field stores customer environment log timestamp information. The customer environment log timestamp information is information about the timing of the customer's environment.

[0227] The "environment" field stores customer environment information. The customer environment information is information about the customer's environment. For example, the customer environment information indicates at least one of the following: Climate (e.g., temperature or humidity) ·UV exposure amount -Time spent in the area where the air conditioner is installed

[0228] The counselor environment log information database in Fig. 18B stores counselor environment log information. The counselor environment log information is information about the history of the counselor's environment. The counselor environment log information is transmitted from a wearable device worn by the counselor. The counselor environment log information database includes a "timestamp" field and an "environment" field, each of which is associated with the other. The counselor environment log information database is associated with the counselor ID.

[0229] The "timestamp" field stores counselor environment log timestamp information, which is information about the timing of the counselor's environment.

[0230] The "environment" field stores counselor environment information. The counselor environment information is information about the counselor's environment. The counselor environment information indicates, for example, at least one of the following: Climate (e.g., temperature or humidity) ·UV exposure amount -Time spent in the area where the air conditioner is installed

[0231] (4.2.5) Customer Biometric Log Information Database and Counselor Biometric Log Information Database of the Fourth Embodiment A customer biometric log information database and a counselor biometric log information database according to the fourth embodiment will now be described. Fig. 19 is a diagram showing the data structures of the customer biometric log information database and the counselor biometric log information database according to the fourth embodiment.

[0232] The customer biometric log information database in Fig. 19A stores customer biometric log information. The customer biometric log information is information related to the history of information about the customer's body (hereinafter referred to as "customer biometric information"). The customer biometric information is, for example, at least one of information that can be identified from an image and information transmitted from a wearable device worn by the customer. The customer biometric log information database includes a "timestamp" field, an "image" field, a "respiratory rate" field, a "pulse rate" field, a "skin temperature" field, a "facial expression" field, and a "comfort index" field. Each field is associated with another field. The customer biometric log information database is associated with the customer ID.

[0233] The "timestamp" field stores customer biometric log timestamp information. The customer biometric log timestamp information is information about the timing of a customer's biometric examination.

[0234] The "image" field stores a customer image. The customer image is, for example, an image of the customer's body (for example, a face). The customer image is a moving image.

[0235] The "breathing frequency" field stores customer breathing frequency information. The customer breathing frequency information is, for example, information about the number of breaths a customer takes per unit time (for example, one minute).

[0236] The "pulse" field stores customer pulse information, which is information about the customer's pulse per unit time.

[0237] The "skin temperature" field stores customer skin temperature information, which is information about the average skin temperature of the customer.

[0238] The "Facial Expression" field stores customer facial expression information. The customer facial expression information is information related to an index of a customer's facial expression (hereinafter referred to as an "facial expression index"). The facial expression index includes, for example, at least one of the following emotional states: Categorised emotional states (e.g. feeling angry, feeling happy, or feeling sad) A continuum of emotional states (e.g., positive, negative, excited, calm, uncomfortable, relaxed, or bored)

[0239] The "comfort index" field stores a customer comfort index. The customer comfort index is information about the level of comfort felt by a customer. The customer comfort index is determined by at least one of customer respiratory rate information, customer pulse information, customer skin temperature information, and customer facial expression information.

[0240] The counselor biolog information database in Figure 19B stores counselor biolog information. The counselor biolog information is information about the history of information about the counselor's body (hereinafter referred to as "counselor biolog information"). The counselor biolog information is at least one of information that can be identified from an image and information transmitted from a wearable device worn by the counselor. The counselor biolog information database includes a "timestamp" field, an "image" field, a "respiratory rate" field, a "pulse rate" field, a "skin temperature" field, a "facial expression" field, and a "comfort index" field. Each field is associated with another field. The counselor biometric log information database is associated with the counselor ID.

[0241] The "timestamp" field stores counselor biometric log timestamp information, which is information about the timing of a counselor's biometric activity.

[0242] The "image" field stores a counselor image. The counselor image is, for example, an image of the counselor's body (for example, a face). The counselor image is a moving image.

[0243] The "breathing frequency" field stores counselor breathing frequency information, which is, for example, information about the number of breaths taken by the counselor per unit time.

[0244] The "pulse" field stores counselor pulse information, which is information about the counselor's pulse per unit time.

[0245] The "skin temperature" field stores counselor skin temperature information, which is information about the counselor's average skin temperature.

[0246] The "Facial Expression" field stores counselor facial expression information. The counselor facial expression information is information related to an index of the counselor's facial expression (hereinafter referred to as "facial expression index"). The facial expression index includes, for example, at least one of the following emotional states: Categorised emotional states (e.g. feeling angry, feeling happy, or feeling sad) A continuum of emotional states (e.g., positive, negative, excited, calm, uncomfortable, relaxed, or bored)

[0247] The "comfort index" field stores a counselor comfort index. The counselor comfort index is information about the comfort level felt by the counselor. The counselor comfort index is determined by at least one of counselor respiratory rate information, counselor pulse information, counselor skin temperature information, and counselor facial expression information.

[0248] (4.3) Information Processing in the Fourth Embodiment Information processing according to the fourth embodiment of the present invention will be described.

[0249] In the counselor selection process of the fourth embodiment of this embodiment, the customer terminal 20 executes the steps from receiving customer instructions (S2120) to making a matching request (S2121) in the same manner as in the second embodiment.

[0250] After step S2121, the person selection device 10 executes estimation of future skin problems (S2110).

[0251] In a first example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and makeup log information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0252] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID.

[0253] CPU 1001 refers to the customer makeup log information database (Figure 15A) associated with the first customer ID and identifies at least one of the information in the "Cosmetics" field, "Method of Use" field, "Amount Used" field, and "Use Time" field of a record whose information in the "Timestamp" field is included within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the first customer genetic information and the customer makeup log information of the specified field into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0254] CPU 1001 refers to the counselor makeup log information database (Figure 15B) and identifies at least one of the information in the "Cosmetics" field, "Method of Use" field, "Amount Used" field, and "Use Time" field of a record whose information in the "Timestamp" field is included within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the counselor's genetic information and the counselor's makeup log information in the specified field into a skin problem estimation model, thereby estimating the counselor's future skin problems.

[0255] This allows, for example, at least one of the following future skin problems to be predicted: Future skin problems that depend on the history of cosmetic use Future skin problems that depend on how you use cosmetics Future skin problems that depend on the duration of use of cosmetics Future skin problems that depend on the time of day you use cosmetics Future skin problems that depend on usage at specific times (for example, a specific morning or evening time, a morning or evening time designated by the customer, or a morning or evening time identified from the customer's behavior log information).

[0256] In a second example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and behavior log information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0257] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID.

[0258] The CPU 1001 refers to the customer behavior log information database (Figure 16A) associated with the first customer ID and identifies the information in the "Behavior" field of a record whose information in the "Timestamp" field is within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the first customer genetic information and the customer behavior log information of the identified field into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0259] CPU 1001 refers to the counselor action log information database (FIG. 16B) and identifies the information in the "action" field of the record whose "timestamp" field information is within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the counselor genetic information and the counselor action log information of the identified field into a skin problem estimation model, thereby estimating the counselor's future skin problems.

[0260] This allows, for example, at least one of the following future skin problems to be predicted: Future skin problems that depend on activity patterns (for example, the type of activity or the time of day (morning or evening)) Future skin problems that depend on sleep habits (for example, sleep time or sleep duration) Future skin problems that depend on eating habits (for example, meal times or food contents) Future skin problems that depend on exercise habits (for example, exercise time, exercise frequency, exercise type, or exercise amount) Future skin problems that depend on outdoor habits (for example, the time of day or frequency of outdoor activities) Future skin problems depending on sun exposure patterns (e.g., non-exposure time, exposure frequency, or exposure time) Future skin problems depending on home working habits (for example, working hours, frequency, or duration of working from home)

[0261] In a third example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and skin diagnosis log information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0262] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID.

[0263] CPU 1001 refers to the customer skin diagnosis log information database (FIG. 17A) associated with the first customer ID and identifies information in the “skin diagnosis” field of a record whose information in the “timestamp” field satisfies a predetermined condition. The predetermined condition includes, for example, at least one of the following: It must be included in a certain period (for example, one week prior to the execution date and time of step S2122). · It must fall within a specific season (spring, summer, autumn, winter). - Applies to a specific time of day (for example, morning or evening).

[0264] The CPU 1001 inputs the first customer genetic information and the customer skin diagnosis log information of the specified field into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0265] CPU 1001 refers to the counselor skin diagnosis log information database (Figure 16B) to identify the information in the "skin diagnosis" field of the record whose information in the "timestamp" field is within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the counselor genetic information and the counselor skin diagnosis log information of the specified field into a skin problem estimation model, thereby estimating the counselor's future skin problems.

[0266] This allows, for example, prediction of future skin problems depending on the skin diagnosis results of the customer and counselor.

[0267] In a fourth example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and environmental log information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0268] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID.

[0269] CPU 1001 refers to the customer environment log information database (Figure 18A) associated with the first customer ID and identifies the information in the "Environment" field of the record whose information in the "Timestamp" field is within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the first customer genetic information and the customer environmental log information of the identified field into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0270] CPU 1001 refers to the counselor environment log information database (FIG. 18B) and identifies the information in the "environment" field of the record whose "timestamp" field information falls within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the counselor genetic information and the counselor environmental log information of the identified field into a skin problem estimation model, thereby estimating the counselor's future skin problems.

[0271] This allows, for example, prediction of future skin problems depending on the environment in which the client and counselor spend their time.

[0272] In a fifth example of step S2110, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between a person's genetic information and biolog information and the person's future skin problems. The skin problem estimation model is a rule-based model or a trained model trained by machine learning.

[0273] CPU 1001 refers to the customer information database (FIG. 9A) and identifies the first customer genetic information in the "customer genetic" field associated with the first customer ID.

[0274] CPU 1001 refers to the customer biometric log information database (Figure 19A) associated with the first customer ID and identifies the information in the "Image" field, "Respiration rate" field, "Pulse rate" field, "Skin temperature" field, and "Facial expression" field of the record whose information in the "Timestamp" field is included within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the first customer genetic information and the customer biometric log information of the identified field into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0275] CPU 1001 refers to the counselor biolog information database (Figure 19B) and identifies the information in the "Image" field, "Respiration rate" field, "Pulse rate" field, "Skin temperature" field, and "Facial expression" field of the record whose "Timestamp" field information is included within a certain period (for example, one week prior to the execution date and time of step S2122). The CPU 1001 inputs the counselor's genetic information and the counselor's biolog information of the specified field into a skin problem estimation model, thereby estimating the counselor's future skin problems.

[0276] This allows, for example, prediction of future skin problems depending on the biometric information of the customer and the counselor.

[0277] After step S2113, the person selecting device 10 executes calculation of the first similarity (S3113).

[0278] CPU 1001 calculates the similarity between similar customers and each counselor as the first similarity by comparing the counselor skin information in the "Counselor Skin" field in the counselor information database (Figure 9B) with the estimated results of future skin problems of similar customers among the second customers obtained in step S3111.

[0279] After step S3113, the person selecting device 10 executes the steps from selection of a first counselor (S2112) to matching response (S2114) in the same manner as in the second embodiment. After step S2114, the customer terminal 20 presents counselor information (S2122).

[0280] (4.4) Effects of the Fourth Embodiment According to the fourth embodiment, the first similarity is calculated based on the log information (i.e., time-series information) of each customer and counselor, thereby allowing the first customer to be assigned to a counselor who has a high similarity to the first customer in terms of the progression of the customer's skin problem.

[0281] (5) Fifth embodiment A fifth embodiment will be described. The fifth embodiment is an example in which the counselor in charge of a first customer is changed according to an index of the first customer's comfort level with counseling (hereinafter referred to as the "comfort index"). Explanations similar to those of the above-mentioned embodiments will be omitted.

[0282] (5.1) Overview of the fifth embodiment An outline of the fifth embodiment of the present invention will be described below with reference to Fig. 20, which is an explanatory diagram of the outline of the fifth embodiment.

[0283] As shown in FIG. 20, in the fifth embodiment, the customer biometric log information database (FIG. 19A) stores first customer biometric information recorded when a first customer received counseling from a first counselor. The person selection device 10 refers to the first customer's biological information and calculates a comfort index that the first customer feels in response to counseling by the first counselor. If the comfort index is below a predetermined threshold (i.e., the first customer does not feel comfortable with counseling by the first counselor), the person selection device 10 selects a new counselor (hereinafter referred to as a "second counselor") different from the first counselor.

[0284] The person selecting device 10 stores the first customer identification information and the second counselor identification information in association with each other.

[0285] The person selection device 10 presents the second counselor identification information to the customer terminal 20 used by the first customer, thereby notifying the first customer of the new counselor (second counselor) who will be in charge of the first customer.

[0286] (5.2) Information Processing of the Fifth Embodiment The information processing of the fifth embodiment of the present invention will be described below with reference to Fig. 21, which is a sequence diagram of the counselor selection processing of the fifth embodiment.

[0287] The trigger for the process in FIG. 21 is, for example, the passage of a certain period of time (for example, one month) since the previous process.

[0288] As shown in FIG. 21, the customer terminal 20 executes the steps from receiving a customer instruction (S2120) to requesting a matching (S2121) in the same manner as in the second embodiment.

[0289] After step S2121, the person selection device 10 acquires customer biometric information (S5110).

[0290] In a first example of step S5110, CPU 1001 refers to the customer biometric log information database (Figure 19A) and identifies the first customer biometric information recorded when the first customer received counseling from the first counselor from among the first customer biometric information associated with the first customer identification information of the first customer who is the target of the counselor selection process.

[0291] In a second example of step S5110, CPU 1001 refers to the customer biometric log information database (Figure 19A) to identify image information in the ``Image'' field associated with the first customer identification information of the first customer who is the target of the counselor selection process. Based on the identified image information, the CPU 1001 identifies at least one of the number of breaths, pulse rate, skin temperature, and facial expression of the first customer as the first customer biometric information.

[0292] After step S5110, the person selection device 10 executes calculation of the comfort index (S5111). Specifically, a comfort index calculation model is stored in the storage medium 1009. The comfort index calculation model describes the correlation between biological information and the comfort index. CPU 1001 inputs the first customer biological information identified in step S5110 into a comfort index calculation model, and outputs a comfort index when counseling is performed for the first customer by the first counselor.

[0293] After step S5111, the person selecting device 10 determines whether to change the counselor (S5112). Specifically, CPU 1001 determines whether the comfort index obtained in step S5111 is less than a predetermined threshold value. If the comfort index is equal to or greater than the threshold, the CPU 1001 ends the counselor selection process. If the comfort index is less than the threshold value, the person selecting device 10 executes the steps from estimating future skin problems (S2110) to calculating the first similarity (S2111) in the same manner as in the second embodiment.

[0294] After step S2111, the person selecting device 10 selects a second counselor (S5113). Specifically, for counselors other than the first counselor, CPU 1001 identifies, as the second counselor ID, the counselor ID of the counselor corresponding to the first similarity that satisfies the predetermined condition from the processing results of step S2111 (i.e., the first similarity).

[0295] After step S5113, the person selecting device 10 updates the database (S2113). Specifically, CPU 1001 stores the second counselor ID identified in step S5113 in the "Counselor" field associated with the customer ID of the first customer in the customer information database (FIG. 9A).

[0296] After step S5114, the person selecting device 10 executes a matching response (S5115). Specifically, the CPU 1001 refers to the counselor information database (FIG. 9B) to identify the counselor information associated with the second counselor ID. The CPU 1001 transmits the matching response data to the client terminal 20. The matching response data includes the identified counselor information (for example, counselor ID, counselor name, gender, and age).

[0297] After step S5115, the customer terminal 20 presents counselor information (S2122) in the same manner as in the second embodiment.

[0298] (5.3) Effects of the Fifth Embodiment According to the fifth embodiment, if the first customer feels a low level of comfort with the counseling provided by the first counselor, the counselor is changed, thereby allowing the first customer to be assigned a counselor who is compatible with the first customer.

[0299] (6) Sixth embodiment A sixth embodiment will be described. The sixth embodiment is an example in which the counselor in charge of the first customer is changed according to an index of the effectiveness of counseling by the first counselor (hereinafter referred to as "effectiveness index"). Explanations similar to those of the above-mentioned embodiments will be omitted.

[0300] (6.1) Overview of the Sixth Embodiment An outline of the sixth embodiment of the present invention will be described below with reference to Fig. 22, which is an explanatory diagram of the outline of the sixth embodiment.

[0301] As shown in Figure 22, in the sixth embodiment, the customer biometric log information database (Figure 19A) stores first customer skin information before counseling is conducted for the first customer by the first counselor, and first customer skin information after the counseling is conducted. The person selection device 10 refers to the first customer skin information before the counseling session and the first customer skin information after the counseling session, and calculates an effect index of the counseling session by the first counselor. If the effectiveness index is less than a predetermined threshold (that is, the effectiveness of counseling by the first counselor is low), the person selection device 10 selects the second counselor.

[0302] The person selecting device 10 stores the first customer identification information and the second counselor identification information in association with each other.

[0303] The person selection device 10 presents the second counselor identification information to the customer terminal 20 used by the first customer, thereby notifying the first customer of the new counselor (second counselor) who will be in charge of the first customer.

[0304] (6.2) Information Processing of the Sixth Embodiment The information processing of the sixth embodiment of the present invention will be described below with reference to Fig. 23, which is a sequence diagram of the counselor selection processing of the sixth embodiment.

[0305] The trigger for the process in FIG. 23 is, for example, the passage of a certain period of time (for example, one month) since the previous process.

[0306] As shown in FIG. 23, the customer terminal 20 executes the steps from receiving a customer instruction (S2120) to requesting a matching (S2121) in the same manner as in the second embodiment.

[0307] After step S2121, the person selecting device 10 executes calculation of the effect index (S6110). Specifically, an effect index calculation model is stored in the storage medium 1009. The effect index calculation model describes the correlation between changes in skin information and the effect index. CPU 1001 refers to the customer skin diagnosis log information database (Figure 17A) and identifies, among the "timestamp" fields associated with the customer ID included in the matching request data, records that include a "timestamp" field immediately before the date and time when counseling was first conducted as pre-intervention records, and identifies, as post-intervention records, records that include a "timestamp" field immediately after the date and time when counseling was last conducted. The CPU 1001 identifies the information in the "skin diagnosis" field included in the pre-implementation record as pre-implementation skin information, and identifies the information in the "skin diagnosis" field included in the post-implementation record as post-implementation skin information. The CPU 1001 calculates the difference between the pre-treatment skin information and the post-treatment skin information (hereinafter referred to as "skin change information"). The CPU 1001 inputs the skin change information into the effect index calculation model, and outputs the counseling effect index.

[0308] After step S6110, the person selecting device 10 determines whether to change the counselor (S6111). Specifically, CPU 1001 determines whether the effect index obtained in step S6110 is less than a predetermined threshold value. If the effect index is equal to or greater than the threshold value, the person selecting device 10 ends the counselor selection process. If the effect index is less than the threshold value, the person selecting device 10 executes the steps from estimating future skin problems (S2110) to calculating the first similarity (S2111) in the same manner as in the second embodiment.

[0309] After step S2111, the person selecting device 10 executes the steps from the selection of the second counselor (S5113) to the matching response (S5115) in the same manner as in the fifth embodiment.

[0310] After step S5115, the customer terminal 20 presents counselor information (S2122) in the same manner as in the second embodiment.

[0311] (6.3) Effects of the Sixth Embodiment According to the sixth embodiment, if the counseling by the first counselor has little effect on the skin, the counselor is changed, thereby allowing the first customer to be assigned a counselor who is suitable for solving the first customer's future skin problems.

[0312] (7) Seventh embodiment A seventh embodiment will be described. The seventh embodiment is an example of estimating a skin problem of a first customer using information about the first customer and information about similar customers similar to the first customer. Descriptions similar to those of the above-mentioned embodiments will be omitted.

[0313] (7.1) Overview of the Seventh Embodiment An outline of the sixth embodiment of the present invention will be described below. Fig. 24 is an explanatory diagram of the outline of the seventh embodiment.

[0314] As shown in FIG. 24, the person selection device 10 stores, for each of a plurality of customers, genetic information of each customer, cosmetic information regarding the cosmetics used by each customer, usage method information regarding how each customer uses the cosmetics, usage time information regarding the time for which each customer uses the cosmetics, and skin diagnosis information regarding skin problems of each customer, all in association with each other.

[0315] The person selection device 10 identifies similar customers who have genetic information (hereinafter referred to as "second customer genetic information") that matches or is similar to the first customer genetic information.

[0316] The person selection device 10 calculates the degree of influence by referring to the cosmetic information, usage method information, usage time information, and skin diagnosis information of each similar customer for each similar customer. The degree of influence is the magnitude of the effect that the cosmetic product, usage method, and usage time have on the skin problems of each similar customer.

[0317] The person selection device 10 estimates the skin problem of the first customer by referring to the cosmetic information of the first customer, the usage method information of the first customer, the usage time information of the first customer, and the impact degree.

[0318] The person selection device 10 transmits recommendation information including the estimation result of the skin problem of the first customer to the customer terminal 20.

[0319] The CPU 2001 presents the recommendation information transmitted from the person selecting device 10 to the first customer.

[0320] (7.2) Information Processing of the Seventh Embodiment Information processing according to the seventh embodiment of the present invention will be described. Fig. 25 is a sequence diagram of the recommendation processing according to the seventh embodiment. Fig. 26 is a diagram showing an example of a screen displayed in the information processing of Fig. 25.

[0321] The trigger for the processing in FIG. 25 is, for example, a customer instruction to display screen P2120 (FIG. 11).

[0322] As shown in FIG. 25, the customer terminal 20 receives a customer instruction (S2120) in the same manner as in the second embodiment.

[0323] After step S2120, the customer terminal 20 executes a recommendation request (S7120). Specifically, when a customer inputs his / her customer ID into the field object F2120 and operates the operation object B2120, the CPU 2001 transmits recommendation request data to the person selection device 10. The recommendation request data includes the customer ID input into the field object F2120.

[0324] After step S7120, the person selecting device 10 executes the selection of similar customers (S7110). Specifically, the customer information database (FIG. 9A) is referenced to identify the first customer genetic information in the "customer genetic" field associated with the first customer ID included in the recommendation request data. CPU 1001 refers to the "customer genetics" field of the customer information database and identifies a customer ID associated with customer genetic information that is the same as or similar to the first customer genetic information (hereinafter referred to as a "similar customer ID").

[0325] After step S7110, the person selecting device 10 executes calculation of the influence degree (S7111). Specifically, an influence calculation model is stored in the storage medium 1009. The influence calculation model describes the correlation between the cosmetic product, the method of use, the duration of use, and the results of the skin diagnosis, and the influence. CPU 1001 refers to the customer makeup log information database (Figure 15A) and the customer skin diagnosis log information database (Figure 17A) associated with the similar customer ID, and identifies information in the "Cosmetics" field, information in the "Method of Use" field, information in the "Usage Time" field, and information in the "Skin Diagnosis" field. The CPU 1001 inputs the identified information (that is, the cosmetic information, the usage method information, the usage time information, and the skin diagnosis information of the similar customer) into an influence calculation model, and outputs the influence of the similar customer.

[0326] After step S7111, the person selecting device 10 performs skin problem estimation (S7112). Specifically, a skin problem estimation model is stored in the storage medium 1009. The skin problem estimation model describes the correlation between the degree of influence, the results of the skin diagnosis, and the skin problem. The CPU 1001 refers to the customer skin diagnosis log information database (FIG. 17A) associated with the first customer ID and identifies information in the "skin diagnosis" field. CPU 1001 inputs the impact degree obtained in step S7111 and the identified information (i.e., the results of the skin diagnosis of the first customer) into a skin problem estimation model, and outputs the estimation result of the skin problem of the first customer.

[0327] After step S7112, the person selecting device 10 updates the database (S7113). Specifically, CPU 1001 refers to the customer information database (FIG. 9A) to identify the record associated with the first customer ID. The CPU 1001 stores the output obtained in step S7112 (that is, the estimation result of the first customer's skin problem) in the "customer's skin" field of the identified record.

[0328] After step S7113, the person selecting device 10 executes a recommendation response (S7114). Specifically, the CPU 1001 transmits recommendation response data to the customer terminal 20. The recommendation response data includes the estimation result of the skin problem of the first customer obtained in step S7112.

[0329] After step S7114, the customer terminal 20 executes the presentation of recommendation information (S7121). Specifically, the CPU 2001 displays a screen P7120 (FIG. 26) on the display device 2005.

[0330] Screen P7120 displays the information included in the recommendation response data sent in step S7114 (that is, the estimation result of the first customer's skin problem).

[0331] (7.3) Effects of the Seventh Embodiment According to the seventh embodiment, the skin problem of the first customer is estimated by taking into consideration the degree of influence based on the cosmetics, usage method, and usage time of similar customers who are similar to the first customer, thereby improving the accuracy of estimating the skin problem of the first customer.

[0332] (8) Variations A modification of this embodiment will now be described.

[0333] (8.1) Variation 1 A first modification of this embodiment will be described below. The first modification is an example in which the first similarity is calculated by referring to attribute information in addition to genetic information.

[0334] (8.1.1) Information processing of variant 1 The information processing of the first modification of this embodiment will be described.

[0335] In the first modification, the customer terminal 20 executes the steps from receiving a customer instruction (S2120) to making a matching request (S2121) in the same manner as in the second embodiment.

[0336] After step S2121, the person selecting device 10 executes calculation of the first similarity (S2111). Specifically, the skin problem estimation model describes the correlation between a person's genetic information and attribute information (e.g., at least one of gender, race, height, and weight) and the person's future skin problems.

[0337] CPU 1001 refers to the customer information database (Figure 9A) and identifies the first genetic information in the ``Customer Genetics'' field associated with the customer ID included in the matching request data and the customer attribute information in the ``Customer Attributes'' field (hereinafter referred to as ``First Customer Attribute Information''). The CPU 1001 inputs the first customer genetic information and the first customer attribute information into a skin problem estimation model to estimate future skin problems of the first customer.

[0338] The CPU 1001 calculates a first similarity between the first customer and each counselor by comparing the counselor skin information in the "Counselor Skin" field in the counselor information database (Figure 9B) with the estimated results of the first customer's future skin problems.

[0339] After step S2111, the person selecting device 10 executes the steps from selection of a first counselor (S2112) to matching response (S2114) in the same manner as in the second embodiment. After step S2114, the customer terminal 20 presents counselor information (S2122) in the same manner as in the second embodiment.

[0340] (8.1.2) Effect of Modification 1 According to the first modification, the first similarity is calculated by referring to the attribute information in addition to the genetic information, which makes it possible to select a first counselor who is more suitable for the first customer.

[0341] (8.2) Variation 2 A second modification of this embodiment will now be described. The second modification is an example in which the first similarity is calculated by referring to address information in addition to genetic information.

[0342] (8.2.1) Information processing of variation 2 The information processing of the second modification of this embodiment will be described.

[0343] In the second modification, the customer terminal 20 executes the steps from receiving a customer instruction (S2120) to making a matching request (S2121) in the same manner as in the second embodiment.

[0344] After step S2121, the person selecting device 10 executes calculation of the first similarity (S2111). Specifically, storage medium 1009 stores a lifestyle pattern estimation model. The lifestyle pattern estimation model describes correlations between lifestyle bases (e.g., addresses) and lifestyle patterns. The lifestyle pattern estimation model is a rule-based model or a trained model trained by machine learning. The lifestyle patterns include, for example, at least one of the following: ·climate Diet (for example, fish or meat as the staple food) Lifestyle (for example, frequency of going out, sleep time, work hours, or frequency of psychological stress)

[0345] The skin problem estimation model describes the correlation between a person's genetic information and lifestyle patterns and the person's future skin problems.

[0346] CPU 1001 refers to the customer information database (Figure 9A) and identifies the first genetic information in the ``Customer Genetics'' field associated with the customer ID included in the matching request data and the customer address information in the ``Address'' field (hereinafter referred to as ``First Customer Address Information''). CPU 1001 inputs the estimated first customer address information into a lifestyle pattern estimation model to estimate information about the lifestyle pattern of the first customer (hereinafter referred to as "first lifestyle pattern information"). The CPU 1001 inputs the first customer genetic information and the first customer lifestyle pattern information into a skin problem estimation model, thereby estimating future skin problems of the first customer.

[0347] The CPU 1001 calculates a first similarity between the first customer and each counselor by comparing the counselor skin information in the "Counselor Skin" field in the counselor information database (Figure 9B) with the estimated results of the first customer's future skin problems.

[0348] After step S2111, the person selecting device 10 executes the steps from selection of a first counselor (S2112) to matching response (S2114) in the same manner as in the second embodiment. After step S2114, the customer terminal 20 presents counselor information (S2122) in the same manner as in the second embodiment.

[0349] (8.2.2) Effect of Modification 2 According to the second modification, the first similarity is calculated by referring to the address information in addition to the genetic information, which makes it possible to select a first counselor who is more suitable for the first customer.

[0350] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to the above-described embodiments. Furthermore, the above-described embodiments can be improved or modified in various ways without departing from the spirit of the present invention. Furthermore, the above-described embodiments and modifications can be combined.

[0351] (9) Supplementary Notes The first aspect of this embodiment is An information processing device (e.g., a person selection device 10) that matches cosmetic customers with counselors who provide beauty counseling to the customers, a means for calculating a first similarity between the first customer and each counselor by referring to first customer skin information relating to future skin problems of the first customer and counselor skin information relating to past or present skin problems of each of the plurality of counselors; a means for selecting, based on the first similarity, counselor identification information for identifying a first counselor who should provide counseling to the first client; a means for storing first customer identification information for identifying the first customer and counselor identification information in association with each other; It is an information processing device (for example, a person selection device 10).

[0352] According to the first aspect, a first counselor having a high degree of similarity to the first customer regarding future skin problems is selected, thereby making it possible to assign a counselor suited to solving future skin problems to the first customer.

[0353] A second aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the genetic information of each counselor and the genetic information of the first customer; It is an information processing device (for example, a person selection device 10).

[0354] According to the second aspect, the first similarity may be calculated by further referring to genetic information, thereby making it possible to assign to the first customer a counselor who is more suitable for solving future skin problems.

[0355] A third aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to a history of cosmetics used by the first customer and a history of cosmetics used by each counselor; It is an information processing device (for example, a person selection device 10).

[0356] According to a fourth aspect, the first similarity may be calculated by further referring to the history of use of cosmetics, thereby making it possible to assign the first customer to a counselor who is more suitable for solving future skin problems.

[0357] A fourth aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the history of how the first customer uses the cosmetic product and the history of how each counselor uses the cosmetic product; It is an information processing device (for example, a person selection device 10).

[0358] According to a fourth aspect, the first similarity may be calculated by further referring to the usage method of the cosmetic product, thereby making it possible to assign the first customer to a counselor who is more suitable for solving future skin problems.

[0359] A fifth aspect of this embodiment is The usage method includes at least one of the time required for makeup application, the time for using each cosmetic product, the time of day when skin care is performed, the difference between the skin care method in the morning and the skin care method in the evening, the number of times skin care is performed in a day, and the amount of cosmetic product used per time. It is an information processing device (for example, a person selection device 10).

[0360] According to a fifth aspect, the first similarity may be calculated by further referring to at least one of the following: the time required for makeup application, the time spent using each cosmetic product, the time of day when skin care is performed, the difference between the skin care method in the morning and the skin care method in the evening, the number of times skin care is performed in a day, and the amount of cosmetic product used per session. This allows the first customer to be assigned a counselor who is more suitable for solving future skin problems.

[0361] A sixth aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the history of skin diagnosis results of the first customer and the history of skin diagnosis results of each counselor; It is an information processing device (for example, a person selection device 10).

[0362] According to a sixth aspect, the first similarity may be calculated by further referring to the history of skin diagnosis results, thereby enabling the first customer to be assigned a counselor who is more suited to solving future skin problems.

[0363] A seventh aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the behavioral history of the first customer and the behavioral history of each counselor; It is an information processing device (for example, a person selection device 10).

[0364] According to a seventh aspect, the first similarity may be calculated by further referring to the behavioral history, thereby making it possible to assign to the first customer a counselor who is more suitable for solving future skin problems.

[0365] An eighth aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the environmental information of the first customer and the environmental information of each counselor; It is an information processing device (for example, a person selection device 10).

[0366] According to an eighth aspect, the first similarity may be calculated by further referring to environmental information, thereby making it possible to assign to the first customer a counselor who is more suitable for solving future skin problems.

[0367] A ninth aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the lifestyle pattern of the first customer and the lifestyle patterns of each counselor; It is an information processing device (for example, a person selection device 10).

[0368] According to a ninth aspect, the first similarity may be calculated by further referring to the lifestyle pattern, thereby making it possible to assign to the first customer a counselor who is more suitable for solving future skin problems.

[0369] A tenth aspect of this embodiment is the means for calculating the first similarity calculates the first similarity by referring to the biometric information of the first customer and the biometric information of each counselor; It is an information processing device (for example, a person selection device 10).

[0370] According to a tenth aspect, the first similarity may be calculated by further referring to the biometric information, thereby making it possible to assign to the first customer a counselor who is more suitable for solving future skin problems.

[0371] An eleventh aspect of this embodiment is the means for calculating the first similarity includes means for calculating a comfort index of the first client when counseling is conducted based on biometric information of the first client when counseling is conducted by the first counselor; the selecting means, when the comfort index is equal to or less than a predetermined value, selects second counselor identification information that identifies a second counselor different from the first counselor based on the first similarity; The storage means stores the first customer identification information and the second counselor identification information in association with each other. It is an information processing device (for example, a person selection device 10).

[0372] According to the eleventh aspect, if the first customer feels a low level of comfort with the counseling by the first counselor, the counselor is changed. This allows the first customer to be assigned a counselor who is compatible with the first customer.

[0373] A twelfth aspect of this embodiment is The means for calculating the comfort index includes means for identifying at least one of the number of breaths, pulse rate, skin temperature, and facial expression of the first client based on an analysis result of an image of the first client when the first counselor provides counseling to the first client; the means for calculating a comfort index calculates the comfort index based on at least one of the number of breaths, the pulse rate, the skin temperature, and the facial expression; It is an information processing device (for example, a person selection device 10).

[0374] According to the twelfth aspect, a comfort index is calculated based on at least one of the number of breaths, pulse rate, skin temperature, and facial expression, thereby making it possible to assign a counselor who is more compatible with the first customer to the first customer.

[0375] A thirteenth aspect of this embodiment is The means for calculating the first similarity includes means for calculating an effect index for the first client when counseling is conducted based on a change between skin information of the first client before the first counselor conducts counseling for the first client and skin information of the first client after the first counselor conducts counseling for the first client, the selecting means, when the effectiveness index is equal to or less than a predetermined value, selects second counselor identification information that identifies a second counselor different from the first counselor based on the first similarity; The storage means stores the first customer identification information and the second counselor identification information in association with each other. It is an information processing device (for example, a person selection device 10).

[0376] According to the thirteenth aspect, if the first customer feels a low level of comfort with the counseling by the first counselor, the counselor is changed, thereby allowing the first customer to be assigned a counselor who is more suitable for solving the first customer's skin problem.

[0377] A fourteenth aspect of this embodiment is a means for estimating second customer skin information relating to future skin problems of a plurality of second customers other than the first customer; a means for calculating a second similarity between the first customer and the second customer by referring to the first customer skin information and the second customer skin information; a means for identifying a similar customer who is similar to the first customer from among the second customers by referring to the second similarity; The means for calculating the first similarity calculates the first similarity between the similar customer and each counselor. It is an information processing device (for example, a person selection device 10).

[0378] According to the fourteenth aspect, a counselor suitable for similar customers to the first customer is selected as the first counselor for the first customer, thereby making it possible to select a counselor suitable for the first customer.

[0379] A fifteenth aspect of this embodiment is The means for identifying a similar customer includes identifying a second customer who has been using the cosmetics used by the first customer for a longer period than the first customer as a similar customer; It is an information processing device (for example, a person selection device 10).

[0380] According to the fifteenth aspect, similar customers are selected from among second customers who have used cosmetics for a longer period than the first customer, thereby making it possible to select a counselor who is more suitable for solving future skin problems of the first customer.

[0381] A sixteenth aspect of this embodiment is The means for identifying a similar customer includes identifying a second customer who is older than the first customer as a similar customer; It is an information processing device (for example, a person selection device 10).

[0382] According to the sixteenth aspect, similar customers are selected from among second customers who are older than the first customer in terms of age, thereby making it possible to select a counselor who is more suitable for solving future skin problems of the first customer.

[0383] A seventeenth aspect of this embodiment is The means for identifying similar customers identifies second customers whose genetic information and cosmetic use history match or are similar to those of the first customer as similar customers; It is an information processing device (for example, a person selection device 10).

[0384] According to the seventeenth aspect, similar customers who are similar to the first customer in terms of genetic information and usage history are selected, thereby making it possible to select a counselor who is more suitable for solving future skin problems of the first customer.

[0385] An 18th aspect of this embodiment is The system comprises a means for storing, in association with each other, genetic information of each customer, cosmetic information relating to the cosmetics used by each customer, usage method information relating to the method of using the cosmetics of each customer, usage time information relating to the time for which the cosmetics are used by each customer, and skin diagnosis information relating to skin problems of each customer, for each of a plurality of customers; a means for identifying similar customers having genetic information that matches or is similar to the genetic information of the first customer; a means for calculating an impact level, which is the magnitude of the impact that the cosmetics, usage method, and usage time have on the skin problems of each similar customer, by referring to the cosmetic information of each similar customer, usage method information of each similar customer, usage time information of each similar customer, and skin diagnosis information of each similar customer; a means for estimating a skin problem of the first customer by referring to the cosmetic information of the first customer, the usage method information of the first customer, the usage time information of the first customer, and the degree of impact; It is an information processing device (for example, a person selection device 10).

[0386] According to the eighteenth aspect, the skin problem of the first customer is estimated by taking into consideration the degree of influence based on the cosmetics, usage method, and usage time of similar customers who are similar to the first customer, thereby improving the accuracy of estimating the skin problem of the first customer.

[0387] A 19th aspect of this embodiment is It is a program for causing a computer to function as each of the above means.

[0388] According to the nineteenth aspect, it is possible to obtain the same effect as any one of the first to eighteenth aspects.

[0389] A twentieth aspect of this embodiment is An information processing method for matching cosmetic customers with counselors who provide beauty counseling to the customers, comprising: The method includes a step of calculating a first similarity between the first customer and each counselor by referring to first customer skin information related to future skin problems of the first customer and counselor skin information related to past or present skin problems of each of the plurality of counselors, selecting, based on the first similarity, counselor identification information for identifying a first counselor who is to provide counseling to the first customer; The method includes a step of storing first customer identification information that identifies the first customer and counselor identification information in association with each other. It is an information processing method.

[0390] According to the twentieth aspect, the same effects as those of the first aspect can be obtained.

[0391] (10) Other embodiments Other modifications will be described.

[0392] The storage medium 1009 may be connected to the person selection device 10 via a network NW. The storage medium 2009 may be connected to the customer terminal 20 via a network NW.

[0393] Each step of the above information processing can be executed by either the person selection device 10 or the customer terminal 20. For example, if the customer terminal 20 is capable of executing all the steps of the above-mentioned information processing, the customer terminal 20 functions as an information processing device that operates stand-alone without transmitting a request to the person selection device 10. In this embodiment, the person selection device 10 may change at least one of the morning time zone and the evening time zone according to any of the following. Customer instructions Customer behavior history This allows the first customer to be assigned a counselor that is most suitable for the first customer.

[0394] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to the above-described embodiments. Furthermore, the above-described embodiments can be improved or modified in various ways without departing from the spirit of the present invention. Furthermore, the above-described embodiments and modifications can be combined. [Explanation of symbols]

[0395] 10: Person selection device 11: Customer service person 20: Customer terminal 21:Customer 101: Specific part 102: Selection section 103: Customer skin characteristics memory unit 104: Customer skin characteristics memory unit 1001: CPU 1002:ROM 1003: RAM 1004 :Auxiliary storage device 1005:Display device 1006: Operating device 1007 :Device 1007 :I / F device 1008: Drive device 1009:Storage medium 2001: CPU 2002:ROM 2003:RAM 2004 :Auxiliary storage 2005 :Display device 2006 :Operating device 2007 :I / F device 2008: Drive unit 2009:Storage media

Claims

1. An information processing device that matches cosmetic customers with counselors who provide beauty counseling to the customers, a means for calculating a first similarity between the first customer and each counselor by referring to first customer skin information relating to future skin problems of the first customer and counselor skin information relating to past or present skin problems of each of the plurality of counselors; a means for selecting, based on the first similarity, counselor identification information for identifying a first counselor who is to provide counseling to the first customer; a means for storing first customer identification information for identifying the first customer and the counselor identification information in association with each other; Information processing device.

2. the means for calculating the first similarity calculates the first similarity by referring to genetic information of each counselor and genetic information of the first customer; The information processing device according to claim 1 .

3. the means for calculating the first similarity calculates the first similarity by referring to a history of cosmetics used by the first customer and a history of cosmetics used by each counselor; 3. The information processing device according to claim 1.

4. the means for calculating the first similarity calculates the first similarity by referring to a history of how the first customer uses the cosmetic product and a history of how each counselor uses the cosmetic product; 4. The information processing device according to claim 1.

5. The method of use includes at least one of the time required for makeup application, the time for using each cosmetic product, the time period for skin care, the difference between the skin care method in the morning and the skin care method in the evening, the number of times skin care is performed in a day, and the amount of cosmetic product used in one application. The information processing device according to claim 4 .

6. the means for calculating the first similarity calculates the first similarity by referring to a history of skin diagnosis results of the first customer and a history of skin diagnosis results of each counselor; 6. The information processing device according to claim 1.

7. the means for calculating the first similarity calculates the first similarity by referring to the behavioral history of the first customer and the behavioral history of each counselor; 7. The information processing device according to claim 1.

8. the means for calculating the first similarity calculates the first similarity by referring to environmental information of the first customer and environmental information of each counselor; 8. The information processing device according to claim 1.

9. the means for calculating the first similarity calculates the first similarity by referring to a lifestyle pattern of the first customer and a lifestyle pattern of each counselor; 9. The information processing device according to claim 1.

10. the means for calculating the first similarity calculates the first similarity by referring to biometric information of the first customer and biometric information of each counselor; 10. The information processing device according to claim 1.

11. the means for calculating the first similarity includes means for calculating a comfort index of the first customer when the counseling is conducted based on biometric information of the first customer when the first counselor conducts counseling for the first customer; the selecting means, when the comfort index is equal to or less than a predetermined value, selects second counselor identification information that identifies a second counselor different from the first counselor based on the first similarity; the storage means stores the first customer identification information and the second counselor identification information in association with each other; The information processing device according to any one of claims 1 to 10.

12. The means for calculating the comfort index includes means for identifying at least one of the number of breaths, pulse rate, skin temperature, and facial expression of the first customer based on an analysis result of an image of the first customer when the first counselor provides counseling to the first customer, the means for calculating the comfort index calculates the comfort index based on at least one of the number of breaths, pulse rate, skin temperature, and facial expression. The information processing device according to claim 11.

13. The means for calculating the first similarity includes means for calculating an effect index for the first customer when the counseling is conducted based on a change between skin information of the first customer before the first counselor conducts counseling for the first customer and skin information of the first customer after the first counselor conducts counseling for the first customer, the selecting means, when the effect index is equal to or less than a predetermined value, selects second counselor identification information that identifies a second counselor different from the first counselor based on the first similarity; the storage means stores the first customer identification information and the second counselor identification information in association with each other; The information processing device according to any one of claims 1 to 12.

14. a means for estimating second customer skin information relating to future skin problems of a plurality of second customers other than the first customer; a means for calculating a second similarity between the first customer and the second customer by referring to the first customer skin information and the second customer skin information; a means for identifying a similar customer who is similar to the first customer from among the second customers by referring to the second similarity; the means for calculating the first similarity calculates the first similarity between the similar customer and each counselor; The information processing device according to any one of claims 1 to 13.

15. the means for identifying a similar customer identifies a second customer who has been using the cosmetics used by the first customer for a longer period of time than the first customer as the similar customer; The information processing device according to claim 14.

16. the means for identifying a similar customer identifies a second customer who is older than the first customer as the similar customer; 16. The information processing device according to claim 14 or 15.

17. the means for identifying a similar customer identifies a second customer whose genetic information and cosmetic use history match or are similar to those of the first customer as the similar customer; The information processing device according to any one of claims 14 to 16.

18. The system comprises a means for storing, in association with each other, genetic information of each customer, cosmetic information relating to the cosmetics used by each customer, usage method information relating to the method of using the cosmetics of each customer, usage time information relating to the time for which the cosmetics are used by each customer, and skin diagnosis information relating to skin problems of each customer, for each of a plurality of customers; a means for identifying similar customers having genetic information that matches or is similar to the genetic information of the first customer; a means for calculating an impact level, which is the magnitude of the impact that the cosmetics, usage method, and usage time have on the skin problems of each similar customer, by referring to the cosmetic information of each similar customer, usage method information of each similar customer, usage time information of each similar customer, and skin diagnosis information of each similar customer; an information processing device comprising means for estimating a skin problem of the first customer by referring to cosmetic information of the first customer, usage method information of the first customer, usage time information of the first customer, and the degree of impact.

19. A program for causing a computer to function as any of the means recited in any one of claims 1 to 18.

20. An information processing method for matching cosmetic customers with counselors who provide beauty counseling to said customers using a computer, comprising: The computer includes a step of calculating a first similarity between the first customer and each counselor by referring to first customer skin information related to future skin problems of the first customer and counselor skin information related to past or present skin problems of each of the plurality of counselors, a step of selecting, by the computer, counselor identification information that identifies a first counselor who is to provide counseling to the first customer based on the first similarity; The computer includes a step of storing first customer identification information that identifies the first customer and the counselor identification information in association with each other. Information processing methods.

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