Method, program and information processing system for providing information about potential customers

Abstract

To provide a method, a program, and an information processing system capable of providing information on characteristics of event visitors as potential customers. [Solution] Visitors who have behaved as prospective customers are identified as analysis subjects. A first prospective customer classification of the analysis subject is determined based on the attributes of the analysis subject, and a second prospective customer classification of the analysis subject is determined based on the behavior of the analysis subject. In determining the first prospective customer classification, a first index related to the ease of purchase is calculated based on the attributes of the analysis subject and the participants, and the first prospective customer classification is determined based on the first index. In determining the second prospective customer classification, a second index related to the analysis subject's willingness to purchase is calculated based on the behavior of the analysis subject, and the second prospective customer classification is determined based on the second index. Based on the results of determining the first prospective customer classification and the second prospective customer classification, information indicating the characteristics of the analysis subject as a prospective customer is generated.

Description

[Technical Field]

[0001] The present invention relates to a method, a program, and an information processing system for providing information about potential customers. [Background technology]

[0002] BACKGROUND ART Systems are known that automatically collect information on visitors who visit exhibition booths at exhibitions and the like, and create a database of the visitor's visit history (see the following patent documents). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-243516 Summary of the Invention [Problem to be solved by the invention]

[0004] By using a system such as that described in the above patent document, it is possible to obtain information about the behavior of each visitor at an exhibition (such as which exhibition booths they visited). Information about visitor behavior at an exhibition is expected to be useful for sales activities, marketing activities, etc.

[0005] Visitors contacted at exhibitions can become potential customers for sales activities. However, since it is not possible to accurately grasp the characteristics of potential customers based solely on information such as which exhibition booths they visited, it is difficult to formulate an appropriate sales activity policy.

[0006] The present invention has been made in consideration of the above circumstances, and its purpose is to provide a method, program, and information processing system that can provide information regarding the characteristics of event attendees as potential customers. [Means for solving the problem]

[0007] A method according to a first aspect of the present invention is a method in which an information processing system provides information on potential customers, wherein attributes related to visitors who attend an event are called visitor attributes, attributes related to participants who participate in the event are called participant attributes, visitor behavior is called visitor behavior, a visitor who has performed a specified visitor behavior that is recognized as a potential customer of a single participant is called an analysis target for that single participant, a classification of analysis targets based on visitor attributes that relates to the ease with which an analysis target for a single participant will reach the stage of purchasing the product of that single participant (hereinafter referred to as purchase ease) is called a first potential customer classification, and a classification of analysis targets based on visitor behavior that relates to the willingness of an analysis target for a single participant to purchase the product of that single participant (hereinafter referred to as purchase willingness).The information processing system has access to a storage device, and the storage device stores a plurality of pieces of visitor attribute information each including information on one or more visitor attributes related to one visitor, a plurality of pieces of participant attribute information each including information on one or more participant attributes related to one participant, and a plurality of pieces of behavioral information each including information on visitor behavior of one visitor. The information processing system includes an analysis target specifying step of specifying one or more analysis targets recognized as potential customers of one participant based on the behavioral information stored in the storage device, and a first prospective customer classification determining step of determining a first prospective customer classification of each of the one or more analysis targets specified for one participant, wherein determining the first prospective customer classification of one analysis target includes determining the first prospective customer classification of the one analysis target based on the participant attributes indicated in the participant attribute information of the one participant and the visitor attributes indicated in the visitor attribute information of the one analysis target. The method includes: a first prospective customer classification determination step including calculating a first index related to the purchasing ease of a subject to be analyzed and determining a first prospective customer classification based on the calculated first index; a second prospective customer classification determination step of determining a second prospective customer classification for each of one or more subjects to be analyzed identified for one participant, wherein determining the second prospective customer classification of one subject to be analyzed includes calculating a second index related to the subject's willingness to purchase based on behavioral information indicating that the subject to be analyzed has performed visitor behavior related to the participant, and determining the second prospective customer classification based on the calculated second index; and a first information display step of generating information indicating the subject's characteristics as a prospective customer based on the determination results of the first prospective customer classification and the second prospective customer classification, and displaying the information on a display device.

[0008] A program according to a second aspect of the present invention is a program including instructions for causing an information processing system to perform a process for providing information about potential customers, and the process performed by the information processing system in accordance with the instructions includes each step of the method according to the first aspect described above.

[0009] An information processing system according to a third aspect of the present invention is an information processing system that performs processing to provide information about potential customers, and has a processing unit and a memory unit that stores instructions for causing the processing unit to perform processing, and the processing performed by the processing unit in accordance with the instructions includes each step of the method according to the first aspect above.

[0010] An information processing system according to a fourth aspect of the present invention is an information processing system that performs processing to provide information about potential customers, and has means for performing each step of the method according to the first aspect described above. [Effects of the Invention]

[0011] According to the present invention, it is possible to provide a method, a program, and an information processing system that can provide information on the characteristics of event attendees as potential customers. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a system according to this embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of an information processing device. [Figure 3] FIG. 3 is a diagram for explaining an outline of the process involved in collecting visitor behavior records. [Figure 4] FIG. 4 is a flowchart illustrating an example of a process for collecting visitor behavior records. [Figure 5] FIG. 5 is a flowchart illustrating an example of a process for determining a potential customer classification and a process for displaying information based on the result of the determination of the potential customer classification. [Figure 6] Fig. 6A is a flowchart illustrating an example of a process for determining a first prospective customer classification for each analysis target person, and Fig. 6B is a flowchart illustrating an example of a process for calculating a first index. [Figure 7]Fig. 7A is a flowchart illustrating an example of a process for determining a second prospective customer classification for each analysis subject. Fig. 7B is a flowchart illustrating an example of a process for calculating a second index. [Figure 8] Figure 8A is a diagram showing an example of a method for distinguishing between classification sets, and Figure 8B is a diagram showing an example of a prospect list in which classification sets are represented by the method shown in Figure 8A. [Figure 9] Figure 9A is a diagram showing another example of a method for distinguishing between classification sets, and Figure 9B is a diagram showing an example of a prospect list in which classification sets are represented by the method shown in Figure 9A. [Figure 10] 10A and 10B are diagrams showing examples of distribution charts showing the number of analysis subjects for each classification set. [Figure 11] FIG. 11 is a flowchart illustrating an example of a process for generating information related to a sales activity plan. [Figure 12] FIG. 12 is a diagram showing an example of a sales activity plan set for each classification set. [Figure 13] FIG. 13 is a flowchart illustrating an example of a process for generating an e-mail draft. [Figure 14] FIG. 14 is a diagram showing an example of an e-mail proposal. [Figure 15] FIG. 15 is a diagram showing an example of a graph of the outcome evaluation index. DETAILED DESCRIPTION OF THE INVENTION

[0013] Fig. 1 is a diagram showing an example of the configuration of a system according to this embodiment. The system shown in the example of Fig. 1 includes an information processing device 1, a visitor terminal device 4, a participant terminal device 5, an operator terminal device 6, and a position detection device 7, which are capable of communicating with each other via a communication network 9 such as the Internet. A system including the information processing device 1 and the participant terminal device 5 is an example of an information processing system of the present invention.

[0014] The system shown in Figure 1 analyzes the characteristics of visitors as potential customers based on information collected about visitors attending an event (exhibition, seminar, etc.), and provides the results of the analysis to participants (exhibitors at the exhibition, etc.) attending the event.

[0015] [Information processing device 1] The information processing device 1 analyzes the characteristics of the visitor as a potential customer based on the visitor information and participant information stored in the storage device 2 described below, and determines the category that the visitor fits into among predetermined categories related to potential customers. The information processing device 1 generates information related to the characteristics of the visitor as a potential customer based on the visitor classification determination result. Furthermore, the information processing device 1 performs processing to generate information related to a sales activity plan, generate draft emails to be sent to visitors (potential customers), and generate predetermined indicators to evaluate the success of the event based on the visitor classification determination result.

[0016] For example, the information processing device 1 includes one or more computers. The information processing device 1 includes a communication unit 11, a storage unit 12, and a processing unit 13, as shown in FIG.

[0017] The communication unit 11 communicates with other devices (visitor terminal device 4, participant terminal device 5, operator terminal device 6, position detection device 7) via the communication network 9. The communication unit 11 includes a device (such as a network interface card) that communicates in accordance with a predetermined communication standard such as Ethernet (registered trademark) or wireless LAN.

[0018] The storage unit 12 stores one or more programs 121 including instructions to be executed by the processing unit 13, data temporarily saved during processing by the processing unit 13, data used in processing by the processing unit 13, data obtained as a result of processing by the processing unit 13, etc. The storage unit 12 may include, for example, a main storage device (RAM, ROM, etc.) and an auxiliary storage device (flash memory, SSD, hard disk, memory card, optical disk, etc.). The storage unit 12 may be composed of one storage device or multiple storage devices. When the storage unit 12 is composed of multiple storage devices, each storage device is connected to the processing unit 13 via a computer bus or any other communication means.

[0019] The processing unit 13 controls the overall operation of the information processing device 1 and performs predetermined information processing. The processing unit 13 includes, for example, one or more processors (such as a central processing unit (CPU), a micro-processing unit (MPU), a digital signal processor (DSP), a graphics processing unit (GPU), or a neural network processing unit (NPU)) that perform processing according to instructions in one or more programs 121 stored in the storage unit 12. The processing unit 13 operates as one or more computers by the one or more processors executing instructions in one or more programs 121 stored in the storage unit 12. The information processing device 1 may have multiple computers, and at least a part of the processing according to this embodiment may be performed in cooperation with the multiple computers.

[0020] The processing unit 13 may include one or more dedicated hardware (such as an ASIC (application specific integrated circuit) or FPGA (field-programmable gate array)) configured to realize a specific function. The processing unit 13 may perform all of the processing described in this embodiment on a computer, or may perform some of the processing on a computer and some of the dedicated hardware, or may perform all of the processing on dedicated hardware.

[0021] The program 121 may be recorded, for example, on a computer-readable recording medium (such as an optical disc, a memory card, a USB memory, or other non-transitory tangible medium). The processing unit 13 may read at least a portion of the one or more programs 121 recorded on such a recording medium using a recording medium reading device (such as an optical disc device) or an interface device (such as a USB interface), not shown, and write the read at least a portion of the one or more programs 121 to the storage unit 12. Alternatively, the processing unit 13 may download at least a portion of the one or more programs 121 from another device connected to the communication network 9 via the communication unit 11 and write the downloaded program to the storage unit 12. The one or more programs 121 may include instructions that cause the processing unit 13 to perform at least a portion of the processing according to this embodiment, which will be described later.

[0022] [Storage device 2] The storage device 2 stores various information used in the processing of the information processing device 1. The information processing device 1 and the storage device 2 can communicate with each other via any communication path (LAN, dedicated line network, Internet, etc.). For example, the storage device 2 may be included in a file server, database server, cloud server, etc. that accepts access from multiple devices, or may be a dedicated storage device accessible only to the information processing device 1. Alternatively, the storage device 2 may be a storage device connected to the processing unit 13 of the information processing device 1 via a computer bus.

[0023] 2, the storage device 2 stores an attendee database 201, a participant database 202, a participant product database 203, a panel management database 204, a content management database 205, a behavior record database 206, an analysis target database 207, a sales activity database 208, and an email template database 209. The storage device 2 also stores a plurality of contents 210 prepared for attendees by participants, etc. In the following description, database may be abbreviated to "DB."

[0024] The visitor DB 201 includes a plurality of visitor information items corresponding to a plurality of visitors. Each piece of visitor information includes information about one visitor. For example, each piece of visitor information includes at least some of the following information: Information that identifies individual visitors (visitor ID) Date and time when visitor information was registered Visitor-related attributes

[0025] As information on attributes related to visitors, the visitor information includes, for example, at least some of the following information: Age of visitors Visitor gender Visitor's occupation (field of work) Visitor's position · The organization to which the visitor belongs (company, department, division, etc.) The business / industry sector in which the visitor's organization is involved (industry type) · How visitors are involved in product purchasing decisions (deciding to purchase, recommending products, etc.) ·Business and industry areas of interest to visitors -Technological fields of interest to visitors · Categories of products and services that visitors are interested in

[0026] Among the attributes related to visitors, the attributes used to determine the first potential customer classification described below are specifically referred to herein as “visitor attributes.” Visitor information including information on one or more visitor attributes is an example of visitor attribute information of the present invention.

[0027] The participant DB 202 includes multiple pieces of participant information corresponding to multiple participants who will be attending the event. Each piece of participant information includes information about one participant (such as an exhibitor at an exhibition). Each piece of participant information includes, for example, at least some of the following information: Information that identifies individual participants (participant ID) Date and time when participant information was registered Participant's name (company name, etc.) Participant's contact information (address, telephone number, email address, etc.) Location of participants at the event venue (exhibition booth control number, etc.) Participant-related attributes

[0028] As information on attributes related to the participants, the participant information includes, for example, at least some of the following information: The business / industry sector to which the participant belongs -Technical fields related to the participants' work Category of products and services handled by the participant

[0029] Among the attributes related to participants, the attributes used to determine the first potential customer classification described below are specifically referred to herein as “participant attributes.” Participant information including information on one or more participant attributes is an example of participant attribute information of the present invention.

[0030] The participant information may also include the following information: · Attributes of visitors that participants expect as potential customers (expected visitor attributes) (Example) Visitor's position, occupation, and company industry Organizations that participants are paying attention to as potential customers (focused organizations) (Example) Company name, department name

[0031] The participant information including information on expected attendee attributes is an example of expected attendee attribute information of the present invention. The participant information including the information on the noted organization is an example of noted organization information of the present invention.

[0032] The participant product DB 203 includes multiple pieces of participant product information related to products handled by participants. Each piece of participant product information includes information about one product handled by one participant. Each piece of participant product information includes, for example, at least some of the following information: -Information that identifies each individual product (product ID) Product name (brand name, model name, etc.) Category to which the product belongs (product purpose, function, efficacy, ingredients, place of origin, place of sale, method of use, production method, etc.) Participant ID indicating the participant handling the product

[0033] In addition, the term "goods" as used in this specification broadly refers to anything that can be bought and sold, and is not limited to goods (products, etc.), but also includes, for example, services, rights (securities, etc.), information, content, etc.

[0034] The panel management DB 204 includes multiple pieces of panel information related to panels that are placed at the event venue to provide various information, materials, etc. to attendees. Each piece of panel information includes information about one panel. For example, one piece of panel information includes at least some of the following information: -Information identifying each panel (Panel ID) One or more product IDs that indicate the products associated with the panel One or more content IDs indicating the content associated with the panel - Panel installation location (exhibition booth control number, etc.)

[0035] An optical code such as a QR code (registered trademark) or a barcode is printed on the panel indicated by the panel ID, and this optical code contains the panel ID. The optical code on the panel is read by the visitor terminal device 4 of a visitor who visits the event venue, and is used to register behavioral information, which will be described later.

[0036] The content management DB 205 includes a plurality of pieces of content information related to content to be provided to visitors. Each piece of content information includes information related to one piece of content. For example, each piece of content information includes at least some of the following information: - Information that identifies individual content (content ID) - Information about the content (content name, type, data size, etc.) One or more product IDs that indicate the products related to the content One or more participant IDs indicating participants (exhibitors, etc.) related to the content · Where content is stored

[0037] Here, the "storage location of the content" is information about the location where the content (content 210 in FIG. 2) is stored in the storage device 2, and includes, for example, the directory and file name where the content 210 is stored. The storage location of the content 210 is not limited to the storage device 2, but may be another device (such as a data server) connected to the communication network 9.

[0038] The behavior record DB 206 includes multiple pieces of behavior information corresponding to multiple attendees. Each piece of behavior information includes a record of a specific behavior performed by one attendee. Each piece of behavior information includes, for example, at least some of the following information: Visitor ID indicating the visitor who performed a specific action Date and time when the visitor performed a specific action One or more product IDs that indicate the products that were the subject of a given action Participant ID indicating the participant related to the product that was the target of the specified action -Type of actions taken by visitors Details of the actions taken by visitors

[0039] Here, the "type of behavior performed by the visitor" includes, for example, the following: - The participant was checked in at their location at the event venue (exhibition booth, etc.) (example) The optical code on the admission pass is read by the participant terminal device 5 of the guide or other person. -Operating designated equipment (such as demo equipment for exhibits) at the participant's location - Having received an explanation from an instructor, etc. · Exchanging business cards with the guide, etc. - Participation in a seminar hosted by the participant - Acquiring content from participants (viewing, downloading, email forwarding, etc.) - Entering ratings or comments about products, etc. Accessing the web page for responding to the survey -Responding to a survey · Movement and stay at the event venue

[0040] Furthermore, the "content of the behavior performed by the visitor" is the content of the predetermined behavior indicated by the "type of behavior", and includes, for example, the following: - Devices operated by visitors at the participant's location (exhibition booth, etc.) ·The place where visitors exchanged business cards Content provided to visitors Seminars attended by visitors - Ratings and comments entered by visitors - Information provided by visitors in the survey (example) Degree of interest in the product, etc., desired content for business negotiations, planned introduction date of the product, etc. · The location and duration of the visitor's stay at the event venue

[0041] The analysis subject DB 207 includes a plurality of pieces of analysis subject information relating to analysis subjects who are visitors who have been subject to analysis as potential customers. Each piece of analysis subject information includes information relating to one analysis subject.

[0042] The subject of analysis for a given participant is a visitor who has performed a predetermined visitor behavior that qualifies them as a potential customer of that participant. Predetermined visitor behavior that qualifies them as a potential customer of a given participant includes, for example, undergoing a predetermined check-in process at the participant's location (exhibition booth, etc.), accessing the participant's web page using a visitor terminal device 4 and registering one's own information, etc. Visitor behavior that qualifies them as a potential customer also includes consent to the participant's use of the visitor's personal information (visitor's name, company name, department name, job title, occupation, etc.) for sales activities.

[0043] One analysis subject information includes, for example, at least a part of the following information: Visitor ID indicating the visitor being analyzed Participant ID indicating the participant who recognized the subject of analysis as a potential customer Date and time when the classification of the prospect was determined - First prospect classification results The value of the first indicator used to determine the first prospect classification - Values ​​of multiple index parameters used to calculate the first index - Second prospect classification results The value of the second indicator used to determine the second prospect classification - Values ​​of multiple index parameters used in calculating the second index

[0044] The "first potential customer classification" is a classification of the subjects of analysis based on visitor attributes, and is a classification regarding the ease with which the subjects of analysis for a given participant will reach the stage of purchasing the product of that participant (hereinafter referred to as "ease of purchase").

[0045] The "first index" is an index showing the ease of purchase, and is calculated using multiple index parameters based on visitor attributes.

[0046] The "second potential customer classification" is a classification of the subjects of analysis based on visitor behavior, and is a classification regarding the willingness of the subjects of analysis for a single participant to purchase the product of that single participant (hereinafter referred to as "purchase willingness").

[0047] The "second index" is an index that indicates purchasing intent, and is calculated using multiple index parameters based on visitor behavior.

[0048] Hereinafter, the first prospective customer classification and the second prospective customer classification will be referred to as "prospective customer classification" without distinction, and the determination result of the prospective customer classification will sometimes be simply referred to as "classification determination result." Furthermore, a combination of one classification in the first prospective customer classification and one classification in the second prospective customer classification will be referred to as a "classification set." The information processing device 1 determines a classification set (a combination of the first prospective customer classification and the second prospective customer classification) as the analysis result of the characteristics of prospective customers for the analysis subject.

[0049] The sales activity DB 208 includes multiple pieces of sales activity information related to sales activities conducted by participants based on the classification determination results. One piece of sales activity information includes information related to sales activities conducted by one participant toward analysis subjects who fit into one classification set. One piece of sales activity information includes, for example, at least some of the following information: Participant ID indicating the participant A classification set of prospects to target for sales activities Information regarding sales activity plans (plan information) (example) Sales activity policy, time from first contact to response, sales approach methods

[0050] The email template DB 209 includes multiple email template information items related to email templates that participants send to potential customers. Each email template information item includes a template (email template) that a participant uses to create the text of an email to be sent to an analysis subject (prospective customer) who fits into a classification set. Each email template information item includes, for example, at least some of the following information: Participant ID indicating the participant · Classification sets for leads to email Email template

[0051] The content 210 is content for visitors provided by participants (product descriptions, technical explanations, brand introductions, company guides, etc.), and includes, for example, document files, image files, video files, URLs for content, etc. Each piece of content 210 is assigned a content ID.

[0052] [Visitor terminal device 4] The visitor terminal device 4 is a device operated by visitors to the event, and is a device equipped with information and communication functions, such as a smartphone, tablet, or personal computer. The system shown in FIG. 1 has multiple visitor terminal devices 4 corresponding to multiple visitors. The visitor terminal device 4 is equipped with a processing unit, memory unit, and communication unit similar to the communication unit 11, memory unit 12, and processing unit 13 of the information processing device 1, as well as an input unit (input devices such as a touch panel, mouse, keyboard, or microphone) for inputting user instructions to the processing unit, a display unit (display device such as a liquid crystal display) for displaying information, a speaker for outputting sound, etc. The visitor terminal device 4 is also equipped with a camera capable of reading optical codes such as QR codes (registered trademark) and barcodes.

[0053] [Participant terminal device 5] The participant terminal device 5 is a device operated by an event participant (such as a staff member of a participating company), and is, for example, a device equipped with information and communication functions, such as a smartphone, tablet, or personal computer. The system shown in FIG. 1 has multiple participant terminal devices 5 corresponding to multiple participants. The participant terminal device 5 includes a processing unit, a memory unit, and a communication unit similar to the communication unit 11, memory unit 12, and processing unit 13 of the information processing device 1, as well as an input unit (input devices such as a touch panel, mouse, keyboard, or microphone) for inputting user instructions to the processing unit, a display unit (display device such as a liquid crystal display) for displaying information, and a speaker for outputting sound. The participant terminal device 5 also includes a camera capable of reading optical codes such as QR codes (registered trademark) and barcodes.

[0054] [Operator terminal device 6] The operator terminal device 6 is a device operated by an operator (such as the event organizer or operation staff) involved in holding and running the event, and is a device equipped with information and communication functions, such as a smartphone, tablet, or personal computer. The operator terminal device 6 is equipped with a processing unit, a memory unit, and a communication unit similar to the communication unit 11, memory unit 12, and processing unit 13 of the information processing device 1, as well as an input unit (input devices such as a touch panel, mouse, keyboard, or microphone) for inputting user instructions to the processing unit, a display unit (display device such as a liquid crystal display) for displaying information, a speaker for outputting sound, etc. The operator terminal device 6 is also equipped with a camera capable of reading optical codes such as QR Code (registered trademark) and barcodes.

[0055] [Position detection device 7] The position detection device 7 detects and records the position of each visitor at the event venue. For example, BLE (Bluetooth Low Energy) beacon transmitters are placed at various locations at the event venue, and each beacon transmitter transmits a beacon signal containing the beacon transmitter's position information within the event venue. The visitor terminal device 4 receives the beacon signals transmitted from each beacon transmitter and transmits information on the received signal strength along with the position information to a predetermined position detection device 7. The position detection device 7 calculates and records the position (coordinates, etc.) of each visitor's visitor terminal device 4 within the event venue based on the received signal strength and position information of each beacon signal received from the visitor terminal device 4. The position detection device 7 provides the calculated position information for each visitor to the information processing device 1.

[0056] The position detection device 7 may record information about the location within the event venue where each visitor stayed for a predetermined period of time or more (information about the exhibition booth, information about the exhibition zone, etc.) based on the record of the location information calculated for each visitor, as well as the start and end times of that stay. In this case, the information processing device 1 may obtain information about the stay location, start time of stay, and end time of stay of each visitor recorded by the position detection device 7 from the position detection device 7 at any timing (for example, at regular intervals), and may generate behavior information of each visitor based on this obtained information and record it in the behavior record DB 206.

[0057] The method of detecting the location of a visitor within an event venue is not limited to the method using beacon signals described above, and other methods may be used, such as detecting the location of the visitor terminal device 4 based on a wireless signal from the visitor terminal device 4 received by wireless LAN access points located throughout the event venue, or detecting the location based on other wireless signals. Alternatively, the location of a visitor may be detected based on images of the visitor captured by cameras installed throughout the event venue.

[0058] Here, we will explain the operation of the system having the above-mentioned configuration shown in Fig. 1. Fig. 3 is a diagram for explaining an outline of the processing involved in collecting visitor behavior records.

[0059] The event organizer prepares admission passes C1 to be distributed to each visitor. An optical code (QR code (registered trademark), barcode, etc.) containing identification information (visitor ID) assigned to each visitor in advance is printed on the admission pass C1. The visitor's name, the name of the event, the name of the venue, the date of the event, etc. may also be printed on the admission pass C1.

[0060] For example, when an event organizer accepts visitors at the entrance of an event venue, the organizer reads the optical code printed on the admission pass C1 given to the visitor using the organizer terminal device 6, and transmits the visitor ID contained in the read optical code from the organizer terminal device 6 to the information processing device 1. The information processing device 1 acquires behavior information including the visitor ID read from the admission pass C1 and registers it in the behavior record DB 206. As a result, the visitor's entry into the event venue is recorded in the behavior record DB 206.

[0061] On the other hand, event participants (exhibitors, etc.) upload content (electronic documents such as PDF files) to be provided to visitors at the event instead of printed materials to the information processing device 1 using the participant terminal device 5. In this case, the information processing device 1 stores the content 210 uploaded from the participant terminal device 5 in the storage device 2. In addition, in response to instructions from the participant terminal device 5, the information processing device 1 acquires content information indicating the association between the content 210 and the product, and the association between the content 210 and the participant, and registers the content information in the content management DB 205.

[0062] A participant installs a panel C2 in their own exhibition booth or the like to be displayed together with a product at the event venue. An optical code is printed on the panel C2, which is required for visitors to the participant's exhibition booth or the like to obtain content (electronic documents, etc.) related to the product or the like displayed there. The participant uses the participant terminal device 5 to transmit to the information processing device 1 identification information (panel ID) of the panel C2, information on the product or the like associated with the panel C2 (product ID, etc.), information on the content associated with the panel C2 (content ID, etc.), information on the installation location of the panel C2, etc. In this case, the information processing device 1 acquires panel information indicating the association between the panel ID and the product, the association between the panel ID and the content, and the association between the panel ID and the installation location of the panel C2 received from the participant terminal device 5, and registers the acquired panel information in the panel management DB 204.

[0063] The participant also reads the optical code printed on the admission pass C1 of the visitor they met at the exhibition booth or the like using the participant terminal device 5, and transmits the visitor ID contained in the read optical code from the participant terminal device 5 to the information processing device 1. The information processing device 1 acquires behavior information including the visitor ID read from the admission pass C1, and registers it in the behavior record DB 206. As a result, the fact that the visitor visited the participant's exhibition booth or the like is recorded in the behavior record DB 206.

[0064] In this case, the participant terminal device 5 may transmit an instruction to the information processing device 1 to permit the visitor to download the specified content, and the information processing device 1 may acquire behavioral information permitting the visitor to download the specified content in accordance with this instruction and register it in the behavior record DB 206. This allows the participant to provide appropriate content to the visitor while listening to the visitor's requests.

[0065] While the event is being held, participants can access information relating to visitor visits to exhibition booths, etc. (such as the number of visitors who visited and the number of content downloads) from the information processing device 1 using the participant terminal device 5. This allows participants to grasp the visitor visit status at their exhibition booths, product display locations, etc. in real time. After the event ends, participants can also access personal information of visitors who visited their exhibition booths, etc., and personal information of visitors who downloaded content related to their products, etc., from the organizer's server, etc., using the participant terminal device 5.

[0066] At the event venue, visitors carry admission pass C1 with an optical code including a visitor ID printed on it. When a visitor performs an operation to acquire content related to merchandise, etc., the visitor reads the optical code printed on their admission pass C1 using the visitor terminal device 4 and accesses the web application server operated by the information processing device 1 based on the address information (URI, etc.) contained in the read optical code. The information processing device 1 authenticates the visitor operating the visitor terminal device 4 based on the information (visitor ID, etc.) in the optical code of the admission pass C1 acquired from the visitor terminal device 4, and causes the visitor's dedicated screen (web application screen) to be displayed on the visitor terminal device 4.

[0067] When a visitor finds a product of interest at the event venue, the visitor reads the optical code of panel C2 installed near the display location from the web application screen of the visitor terminal device 4 and transmits the panel ID included in the read optical code to the information processing device 1. When the information processing device 1 receives the panel ID of panel C2 read on the web application screen of the visitor terminal device 4, it acquires behavioral information indicating that the visitor read the optical code of panel C2 and registers it in the behavior record DB 206. The information processing device 1 permits the visitor whose behavioral information is recorded to download, view, forward by email, or the like, content associated with the panel ID. For example, the information processing device 1 displays a list of content that is permitted to be downloaded, etc. based on the behavioral information on the web application screen of the visitor terminal device 4.

[0068] On the screen of the web application on the visitor terminal device 4, the visitor views a list of content for which downloading, etc. is permitted, and selects the desired content from the list. The visitor terminal device 4 then requests content related to the target selected by the visitor from the information processing device 1. In response to this request, the information processing device 1 reads the content requested by the visitor from the storage device 2 and provides it to the visitor terminal device 4 that made the request. That is, the information processing device 1 performs processing to display the content on the visitor terminal device 4 that made the request, and processing to download the content on the visitor terminal device 4 that made the request. Furthermore, when a forwarding email address is specified by the visitor terminal device 4, the information processing device 1 performs processing to forward the content read from the storage device 2 (or information such as a URL for downloading the content) to the specified email address.

[0069] FIG. 4 is a flowchart illustrating an example of a process for collecting visitor behavior records. The operator terminal device 6 reads the optical code printed on the admission pass C1 handed to the visitor at the entrance or the like of the event venue, and transmits the visitor ID contained in the read optical code to the information processing device 1 (ST100). The information processing device 1 acquires behavior information including the visitor ID read from the admission pass C1, and registers it in the behavior record DB 206 (ST105). This behavior information records that the visitor has entered the event venue.

[0070] The participant terminal device 5 reads the optical code on the admission pass C1 of a visitor who visited a participant's exhibition booth or the like at the event venue, and transmits the visitor ID contained in the read optical code to the information processing device 1 (ST110). The information processing device 1 acquires behavior information including the visitor ID read from the admission pass C1, and registers it in the behavior record DB 206 (ST115). This behavior information records that the visitor visited a specific participant's exhibition booth or the like (that the visitor's reception process was carried out).

[0071] A participant's representative or the like who has processed the reception process at an exhibition booth or the like will explain products to the visitor, and as a result of this interaction, will input an evaluation of the visitor (such as the visitor's level of interest in the products) into the participant terminal device 5. The participant terminal device 5 transmits the visitor's evaluation input by the representative or the like to the information processing device 1 (ST120). The information processing device 1 generates behavioral information based on the visitor's evaluation received from the participant terminal device 5, and registers the information in the behavior record DB 206 (ST125).

[0072] The visitor terminal device 4 reads the optical code printed on the visitor's admission pass C1 and accesses the web application server operated by the information processing device 1 based on the address information contained in the read optical code (ST130). The information processing device 1 authenticates the visitor operating the visitor terminal device 4 based on the information (visitor ID, etc.) in the optical code of the admission pass C1 obtained from the visitor terminal device 4, and causes the visitor's dedicated screen (web application screen) to be displayed on the visitor terminal device 4 (ST135).

[0073] The visitor terminal device 4 reads the optical code of panel C2 displayed together with a product at an exhibition booth or the like visited by the visitor, and transmits the panel ID included in the optical code to the information processing device 1 (ST140). When the information processing device 1 receives the panel ID of panel C2 read on the screen of the web application of the visitor terminal device 4, it acquires behavior information indicating that the optical code of panel C2 was read by the visitor, and registers this in the behavior record DB 206 (ST145). Based on the content ID associated with the panel ID in the behavior information, the information processing device 1 permits the visitor to download content corresponding to this content ID, etc.

[0074] The information processing device 1 displays a list of content for which downloading, etc. is permitted based on the behavioral information on the screen of the web application of the visitor terminal device 4. The visitor selects specific content from the available content displayed on the screen of the web application and inputs an instruction to the visitor terminal device 4 requesting that the content be provided in a specified manner (viewing, downloading, email forwarding, etc.). Upon inputting the visitor's instruction, the visitor terminal device 4 requests the information processing device 1 to provide the specific content in the specified manner (ST150). In response to the request from the visitor terminal device 4, the information processing device 1 executes a content providing process to provide the selected specific content to the visitor in the specified manner. For example, in response to a request from the visitor terminal device 4 operated by the visitor, the information processing device 1 performs processes such as displaying the content on the visitor terminal device 4, downloading the content to the visitor terminal device 4, and forwarding the content to an arbitrary address by email. When the information processing device 1 performs a process of providing content to a visitor in response to a request from the visitor terminal device 4, it acquires behavior information indicating that the visitor has received the content and registers it in the behavior record DB 206 (ST155).

[0075] Furthermore, visitors can input ratings for any product on the screen of a web application on the information processing device 1. When a rating for an object is input by, for example, pressing a "Like" button, the visitor terminal device 4 transmits the rating to the information processing device 1 (ST160). When the information processing device 1 receives a rating for an object input by a visitor, it acquires behavior information indicating that the visitor has input a rating for the object, and registers the behavior information in the behavior record DB 206 (ST165).

[0076] Furthermore, visitors can answer questionnaires created by participants, event organizers, etc. on the screen of a web application by the information processing device 1. When a response to a questionnaire about, for example, a specific product is entered, the visitor terminal device 4 transmits the response to the questionnaire to the information processing device 1 (ST170). When the information processing device 1 receives a response to a questionnaire entered by a visitor, it acquires behavior information indicating that the visitor has entered a response to the questionnaire, and registers the behavior information in the behavior record DB 206 (ST175).

[0077] FIG. 5 is a flowchart illustrating an example of a process for determining a potential customer classification and a process for displaying information based on the result of the determination of the potential customer classification. Step ST200 is an example of the step of specifying a person to be analyzed according to the present invention. Step ST205 is an example of a first potential customer classification determination step of the present invention. Step ST210 is an example of a second potential customer classification determination step of the present invention. Steps ST220 and ST225 are an example of a first information display step of the present invention. Steps ST235 and ST240 are an example of a second information display step of the present invention. Steps ST250 and ST255 are an example of a third information display step of the present invention. Steps ST265 and ST270 are an example of a fourth information display step of the present invention.

[0078] The information processing device 1 identifies one or more analysis subjects who are recognized as potential customers of one participant based on the behavior information registered in the behavior record DB 206 of the storage device 2 (ST200). That is, the information processing device 1 extracts behavior information indicating that a predetermined visitor behavior (such as reception processing at an exhibition booth) that is recognized as a potential customer has been performed from the behavior information about one participant registered in the behavior record DB 206, and identifies the analysis subjects based on the visitor ID included in the extracted behavior information.

[0079] The information processing device 1 determines a first prospective customer classification for each of the one or more analysis subjects identified in step ST200 (ST205). When determining the first prospective customer classification of one analysis subject, the information processing device 1 calculates a first index related to the ease of purchase of the one analysis subject based on the participant attributes indicated in the participant information (participant DB202) of the one analysis subject and the visitor attributes indicated in the visitor information (visitor DB201) of the one analysis subject, and determines the first prospective customer classification based on the first index.

[0080] FIG. 6A is a flowchart for explaining an example of the process (ST205: FIG. 5) for determining the first prospective customer classification of each analysis target person. The information processing device 1 selects one analysis subject identified in step ST200 (ST300). The information processing device 1 calculates a first index related to the ease of purchase based on the visitor information of the selected analysis subject (ST305), and determines a first potential customer classification based on the first index (ST310).

[0081] For example, the information processing device 1 calculates a first index having a value corresponding to the level of the purchase ease of the analysis target person (ST305), and determines a first prospective customer classification representing the level of the purchase ease depending on which of a plurality of predetermined ranges the first index falls within (ST310). The information processing device 1 registers the first prospective customer classification determined in step ST310 in the analysis target person information of the analysis target person DB207.

[0082] Note that, when an index parameter described below used to calculate the first index satisfies a predetermined condition, the information processing device 1 may determine a predetermined category as the first prospective customer category regardless of the value of the first index. For example, when an index parameter indicating that the industry of the person being analyzed and the industry of the participants are not related to each other is obtained, or when an index parameter indicating that the occupation of the person being analyzed and the industry or product of the participants are not related to each other is obtained, the information processing device 1 may determine a predetermined category with a relatively low ease of purchase as the first prospective customer category.

[0083] After determining the first prospective customer classification for one analysis subject, if there is another analysis subject for which the first prospective customer classification should be determined (Yes in ST315), the information processing device 1 selects that analysis subject (ST320) and performs the same processing of steps ST305 and ST310 as described above. The information processing device 1 repeats the processing of steps ST305 and ST310 until it has determined the first prospective customer classification for all analysis subjects identified in step ST200.

[0084] FIG. 6B is a flowchart for explaining an example of the process of calculating the first index (ST305: FIG. 6A). In the example of FIG. 6B, the information processing device 1 acquires a plurality of index parameters for calculating the first index (ST350), and calculates the first index based on the plurality of index parameters (ST355). For example, the information processing device 1 applies the plurality of index parameters as variables to a predetermined function, and calculates the value of the function as the first index. The information processing device 1 may calculate the sum of the plurality of index parameters as the first index. The information processing device 1 registers the index parameters acquired in step ST350 and the first index calculated in step ST355 in the analysis subject information of the analysis subject DB207.

[0085] The index parameters of the first index each have a value corresponding to the degree of ease of purchase, and for example, the higher the ease of purchase, the larger the value of the index parameter. When the first index is the sum of multiple index parameters, the higher the ease of purchase index parameter obtained, the higher the ease of purchase, the higher the first index obtained.

[0086] The index parameters of the first potential customer classification include, for example, at least some of the following parameters PA1 to PA4.

[0087] <Parameter PA1: Parameter based on the degree of involvement in product purchase decisions>

[0088] The parameter PA1 is a parameter based on a visitor attribute that indicates the degree of involvement in the decision to purchase a product (purchase decision involvement degree).

[0089] For example, the information processing device 1 acquires the parameter PA1 based on the position (management / president, executive, department manager / deputy manager, section manager, assistant manager / chief, etc.) of the person being analyzed included in the visitor information (visitor DB201). In this case, the higher the position, the higher the parameter PA1 acquired by the information processing device 1 indicating a higher degree of involvement in purchase decision. The information processing device 1 calculates a first index of higher ease of purchase as the degree of involvement in purchase decision indicated by the parameter PA1 increases. (Example of parameter PA1 value) "Manager / President"...30 points, "Executive"...25 points, "General Manager / Deputy General Manager"...20 points "Section chief"... 15 points, "Section chief / chief"... 10 points, "Regular employee / staff member"... 5 points

[0090] The information processing device 1 may also acquire the parameter PA1 based on the answers to a questionnaire included in the visitor information. Questions in the questionnaire related to the degree of involvement in purchase decisions may include, for example, "Question 1: Decide whether to purchase the product (Yes / No)" "Question 2: Recommend or designate a product for purchase (Yes / No)" "Question 3: Selling purchased items (Yes / No)" "Question 4: Use the purchased product (Yes / No)" In this example, when a "Yes" answer is obtained, the purchase decision involvement level of parameter PA1 is highest for the first question 1, and decreases in the order of questions 1 to 4. (Example of parameter PA1 value) "Question 1"...30 points, "Question 2"...20 points, "Question 3"...10 points, "Question 4"...5 points

[0091] By calculating the first index using the parameter PA1 based on the degree of involvement in purchase decision, it is possible to determine the first potential customer classification with high accuracy, which reflects the influence of the degree of involvement in purchase decision.

[0092] The information processing device 1 may acquire both the parameter PA1 based on the position and the parameter PA1 based on the answer to the questionnaire, or may acquire either one of them.

[0093] <Parameter PA2: Parameter based on the relationship between participant attributes and visitor attributes>

[0094] The parameter PA2 is a parameter based on the relevance (attribute relevance) between the participant attribute of one participant and the visitor attribute of one analysis target person.

[0095] The information processing device 1 determines the attribute relevance between the participant attributes and the visitor attributes, and if it determines that there is an attribute relevance, it acquires a parameter PA2 that increases the ease of purchase of the first index compared to when it determines that there is no attribute relevance.

[0096] For example, the information processing device 1 determines the relevance between the industry of the participant indicated in the participant information (participant DB 202) and the industry of the person being analyzed indicated in the visitor information (visitor DB 201), and acquires a parameter PA2 that increases the purchase ease of the first index when there is a relevance based on the determination result. For example, the information processing device 1 may determine that there is a relevance between the industries of the participant and the person being analyzed when the industries match, when one industry encompasses the other, etc. (Example of parameter PA2 value) "There is a correlation between the industries of participants and those being analyzed" - 25 points "There is no correlation between the industries of participants and those being analyzed"...0 points

[0097] Furthermore, the information processing device 1 determines the relevance between the industry of the participant indicated in the participant information (participant DB202) and the occupation of the person being analyzed indicated in the visitor information (visitor DB201), and acquires a parameter PA2 that increases the ease of purchase of the first indicator when there is a relevance based on the determination result. For example, the information processing device 1 may determine that there is a relevance between the industry of the participant and the occupation of the person being analyzed when one or more pre-set related occupations for the participant's industry match the visitor's occupation, when one occupation encompasses the other, etc. (Example of parameter PA2 value) "There is a correlation between the participants' industries and the occupations of the people being analyzed" - 25 points "There is no correlation between the participants' industries and the job types of the people being analyzed"...0 points

[0098] Furthermore, the information processing device 1 determines the relevance between the participant's product indicated by the participant product information (participant product DB203) and the industry of the person being analyzed indicated by the visitor information (visitor DB201), and acquires a parameter PA2 that increases the purchase ease of the first indicator when there is a relevance based on the determination result. For example, the information processing device 1 may determine that there is a relevance between the participant's product and the industry of the person being analyzed when one or more pre-set related industries for the participant's product match the industry of the visitor, when one industry encompasses the other industry, etc. (Example of parameter PA2 value) "There is a correlation between the participant's products and the industry of the person being analyzed" - 25 points "There is no correlation between the participant's products and the industry of the person being analyzed"...0 points

[0099] Furthermore, the information processing device 1 determines the relevance between the participant's products indicated in the participant product information (participant product DB203) and the occupation of the person being analyzed indicated in the visitor information (visitor DB201), and acquires a parameter PA2 that increases the purchase ease of the first indicator when there is a relevance based on the determination result. For example, the information processing device 1 may determine that there is a relevance between the participant's products and the industry of the person being analyzed when one or more pre-set related occupations for the participant's products match the visitor's occupation, when one occupation encompasses the other occupation, etc. (Example of parameter PA2 value) "There is a relationship between the participant's product and the occupation of the person being analyzed" - 25 points "There is no correlation between the participants' products and the occupations of the people being analyzed"...0 points

[0100] By calculating the first index using parameter PA2 based on the attribute relevance between participant attributes and visitor attributes, it is possible to accurately determine the first potential customer classification that reflects the influence of attribute relevance.

[0101] The information processing device 1 may acquire each of the four types of parameters PA2 mentioned above (parameter PA2 based on the relationship between the participant's industry and the person being analyzed's industry, parameter PA2 based on the relationship between the participant's industry and the person being analyzed's occupation, parameter PA2 based on the relationship between the participant's product and the person being analyzed's industry, and parameter PA2 based on the relationship between the participant's product and the person being analyzed's occupation), or may acquire some of the parameters PA2.

[0102] When the acquired parameter PA2 satisfies a predetermined condition, the information processing device 1 may determine a predetermined category as the first potential customer category, regardless of the value of the first index calculated in step ST355. For example, if there is no association between the business type of the analysis target and the business type and product of the participant, the information processing device 1 may determine a category with a relatively low purchase ease (NL, described later) as the first potential customer category. Furthermore, for example, even if there is no correlation between the occupation of the person being analyzed and the industry or product of the participant, the information processing device 1 may determine a category with a relatively low purchase ease (NL, described later) as the first potential customer category. This makes it possible to determine the first potential customer classification, which places emphasis on the low ease of purchase due to the lack of attribute relevance.

[0103] <Parameter PA3: Parameter based on expected visitor attributes>

[0104] Parameter PA3 is a parameter based on the correlation between the expected visitor attributes (attributes of visitors expected as potential customers) set in the participant information of one participant (participant DB202) and the visitor attributes indicated in the visitor information of one analysis subject (visitor DB201).

[0105] The information processing device 1 determines the attribute correlation between the expected visitor attributes and the visitor attributes, and if it determines that there is an attribute correlation, it acquires a parameter PA3 that increases the ease of purchase of the first index compared to when it determines that there is no attribute correlation.

[0106] For example, when the job title set in the expected visitor attribute of the participant information matches the job title of the person being analyzed indicated by the visitor information, or when one job title encompasses the other job title, the information processing device 1 determines that there is an attribute correlation between the expected visitor attribute and the visitor attribute, and acquires a parameter PA3 that increases the ease of purchase of the first indicator.

[0107] In addition, when the occupation set in the expected visitor attribute of the participant information matches the occupation of the person being analyzed indicated by the visitor information, or when one occupation encompasses the other occupation, the information processing device 1 determines that there is an attribute correlation between the expected visitor attribute and the visitor attribute, and acquires a parameter PA3 that increases the ease of purchase of the first indicator.

[0108] This makes it possible to determine a first potential customer classification that reflects the relationship between the visitor attributes that the participants envision as potential customers and the visitor attributes of the person being analyzed.

[0109] <Parameter PA4: Parameter based on the tissue of interest>

[0110] Parameter PA4 is a parameter based on the relationship between the organization of interest (the organization that the participant is interested in) set in the participant information (participant DB202) of a participant and the organization to which the subject of analysis belongs, as indicated in the visitor information (visitor DB201) of the subject of analysis.

[0111] The information processing device 1 determines whether the organization of interest set in the participant information matches the organization to which the person being analyzed belongs, as indicated by the visitor information, and if the organization to which the person being analyzed belongs matches the organization of interest, obtains a parameter PA4 that increases the ease of purchase of the first indicator compared to when they do not match.

[0112] This makes it possible to accurately determine the first potential customer classification that reflects the actual situation, even in cases where there are known organizations (such as companies that tend to purchase products even when the industry is not compatible) whose purchasing ease cannot be accurately grasped based solely on the correlation between the participant's industry and the industry of the person being analyzed.

[0113] Return to Figure 5. The information processing device 1 determines a second prospective customer classification for each of the one or more analysis subjects identified in step ST200 (ST210). When determining the second prospective customer classification of one analysis subject, the information processing device 1 calculates a second index related to the purchase intention of the one analysis subject based on behavior information (behavior record DB206) indicating that the one analysis subject has performed visitor behavior related to the one participant, and determines the second prospective customer classification based on the second index.

[0114] FIG. 7A is a flowchart for explaining an example of the process (ST210: FIG. 5) for determining the second prospective customer classification of each analysis target person. The information processing device 1 selects one analysis subject identified in step ST200 (ST400). The information processing device 1 calculates a second index related to purchase intention based on the behavioral information of the selected analysis subject (ST405), and determines a second potential customer classification based on the second index (ST410).

[0115] For example, the information processing device 1 calculates a second index having a value corresponding to the level of purchase willingness of the person being analyzed (ST405). That is, the information processing device 1 calculates the second index based on at least one of the content, number of times, frequency, time, and season of visitor behavior performed by one person being analyzed in relation to one participant. The information processing device 1 determines a second prospective customer classification that indicates the level of purchase willingness depending on which of multiple predetermined ranges the calculated second index falls within (ST410). The information processing device 1 registers the second prospective customer classification determined in step ST410 in the analysis subject information of the analysis subject DB207.

[0116] Note that, when an index parameter described below used to calculate the second index satisfies a predetermined condition, the information processing device 1 may determine a predetermined category as the second potential customer category regardless of the value of the second index.

[0117] After determining the second prospective customer classification for one analysis subject, if there is another analysis subject for which the second prospective customer classification should be determined (Yes in ST415), the information processing device 1 selects that analysis subject (ST420) and performs the same processing of steps ST405 and ST410 as described above. The information processing device 1 repeats the processing of steps ST405 and ST410 until the second prospective customer classifications of all analysis subjects identified in step ST200 have been determined.

[0118] FIG. 7B is a flowchart for explaining an example of the process of calculating the second index (ST405: FIG. 7A). In the example of FIG. 7B, the information processing device 1 acquires a plurality of index parameters for calculating the second index (ST450), and calculates the second index based on the plurality of index parameters (ST455). For example, the information processing device 1 applies the plurality of index parameters as variables to a predetermined function, and calculates the value of the function as the second index. The information processing device 1 may calculate the sum of the plurality of index parameters as the second index. The information processing device 1 registers the index parameters acquired in step ST450 and the second index calculated in step ST455 in the analysis subject information of the analysis subject DB207.

[0119] The index parameters of the second index each have a value corresponding to the level of willingness to purchase, and for example, the higher the willingness to purchase, the larger the value of the index parameter. If the second index is the sum of multiple index parameters, the higher the willingness to purchase, the higher the second index.

[0120] The index parameters of the second potential customer classification include, for example, at least some of the following parameters PB1 to PB10.

[0121] <Parameter PB1: Parameter based on the interest level answered in the questionnaire>

[0122] The parameter PB1 is a parameter based on the degree of interest in the product included in the questionnaire response in the behavior information (behavior record DB 206).

[0123] The information processing device 1 acquires a parameter PB1 based on the interest level of a product of a participant included in the participant's response to a questionnaire in the behavioral information of the subject of analysis. The information processing device 1 acquires the parameter PB1 such that the higher the interest level in the questionnaire response, the higher the purchase intention of the second index.

[0124] This makes it possible to accurately determine the second potential customer classification that reflects the purchase intention of the person being analyzed, as indicated by the degree of interest in the product.

[0125] <Parameter PB2: Parameter based on desired business negotiations answered in the questionnaire>

[0126] The parameter PB2 is a parameter based on the desired content for business negotiations included in the questionnaire responses in the behavioral information.

[0127] The information processing device 1 acquires a parameter PB2 based on the desired content of a business negotiation with a participant included in a response to a questionnaire for the participant in the behavioral information of the subject of analysis. The information processing device 1 acquires the parameter PB2 such that the stronger the positive tendency toward business negotiation in the questionnaire response, the higher the willingness to purchase as the second indicator. (Example of parameter PB2 value) "Interested in business negotiations": 20 points; "Want to be contacted at a later date": 10 points "Documents only": 5 points, "No response / No preference": 0 points

[0128] This makes it possible to accurately determine the second potential customer classification that reflects the purchasing intention of the person being analyzed, as expressed by their desired content for the business negotiation.

[0129] <Parameter PB3: Parameter based on the planned introduction date of the product as answered in the questionnaire>

[0130] Parameter PB3 is a parameter based on the planned introduction time of the product included in the questionnaire response in the behavioral information.

[0131] The information processing device 1 acquires a parameter PB3 based on the planned timing of product introduction by a participant included in the participant's response to a questionnaire in the behavioral information of the subject of analysis. The information processing device 1 acquires the parameter PB3 such that the purchase intention of the second indicator increases as the planned timing of product introduction in the questionnaire response becomes earlier. (Example of parameter PB3 value) "Within 3 months"...20 points, "Within 6 months"...10 points, “More than 1 year”…5 points, “Undecided”…0 points

[0132] This makes it possible to accurately determine the second potential customer classification that reflects the purchasing intention of the analysis subject, as indicated by the planned introduction date of the product.

[0133] <Parameter PB4: Parameter based on the submission of questionnaire responses>

[0134] Parameter PB4 is a parameter based on information indicating the questionnaire submission status included in the behavioral information.

[0135] The information processing device 1 acquires a parameter PB4, which indicates that the stronger the tendency to cooperate in answering the questionnaire, the higher the second indicator of purchase intention, based on information in the behavioral information of a subject of analysis indicating that the subject has answered a questionnaire for a participant and information indicating that the subject has accessed a web page for answering the questionnaire. (Example of parameter PB4 value) "Survey completed": 10 points, "Not completed but has web access": 5 points "No response and no web access": 0 points

[0136] This allows for accurate determination of the second potential customer classification that reflects the purchasing intention of the analysis subject as indicated by the questionnaire submission status.

[0137] <Parameter PB5: Parameter based on content acquisition from participants>

[0138] The parameter PB5 is a parameter based on information about the history of content acquisition from the participant included in the behavioral information.

[0139] The information processing device 1 acquires a parameter PB5 that increases the second indicator's willingness to purchase when content is acquired, based on information indicating a history of acquiring content from a participant, which is included in the behavioral information of a person to be analyzed. (Example of parameter PB5 value) "Downloading materials"... 5 points, "Forwarding materials by email"... 5 points "No content acquired"...0 points

[0140] This makes it possible to accurately determine the second potential customer classification that reflects the purchasing intention of the person being analyzed, as represented by the history of acquisition of content provided by the participants.

[0141] <Parameter PB6: Parameter based on behavior at the exhibition booth>

[0142] Parameter PB6 is a parameter based on information on visitor behavior at exhibition booths and the like, which is included in the behavior information.

[0143] The information processing device 1 acquires a parameter PB6 that increases the second index when behavior indicating interest in a product is observed, based on information about visitor behavior (such as operating demo equipment or receiving an explanation from an exhibitor) performed at a participant's exhibition booth, etc., which is included in the behavioral information of a single subject to be analyzed. (Example of parameter PB6 value) "Operating the demo equipment"... 15 points, "Receiving an explanation from the instructor"... 10 points "Only receive the materials"... 5 points, "No response"... 0 points

[0144] This allows for accurate determination of the second potential customer classification that reflects the purchasing intention of the person being analyzed as expressed by their behavior at the exhibition booth.

[0145] <Parameter PB7: Parameter based on business card exchange>

[0146] Parameter PB7 is a parameter based on information regarding business card exchange included in the behavior information.

[0147] The information processing device 1 acquires a parameter PB7 that indicates a higher willingness to purchase as the second indicator when a business card exchange occurs that indicates an intention to make contact with an explainer, etc., based on information regarding the exchange of business cards with a participant (whether or not business cards were exchanged, and the location of the business card exchange) contained in the behavioral information of a single analysis subject. (Example of parameter PB7 value) "Exchanging business cards inside the booth"... 5 points, "Exchanging business cards at the booth entrance"... 3 points "Exchanging business cards outside the booth"...0 points

[0148] This allows for accurate determination of the second potential customer classification that reflects the purchasing intention of the person being analyzed as indicated by the business card exchange situation.

[0149] <Parameter PB8: Parameter based on the number of revisits>

[0150] Parameter PB8 is a parameter based on information about visited places (places of stay) within the event venue, which is included in the behavior information.

[0151] The information processing device 1 extracts, from the behavior record DB 206, behavioral information of one subject to be analyzed that indicates that the subject has stayed at an exhibition booth or the like of one participant, and counts the number of times the subject to be analyzed has revisited the exhibition booth or the like of one participant based on the extracted behavioral information. The information processing device 1 acquires a parameter PB8 such that the greater the counted number of revisits, the higher the purchase intention of the second indicator becomes. (Example of parameter PB8 value) “Revisit 2 or more times”…10 points, “Revisit once”…5 points, “Revisit 0 times”…0 points,

[0152] This makes it possible to accurately determine the second potential customer classification that reflects the purchasing intention of the person being analyzed, as indicated by the number of times they return to an exhibition booth or the like.

[0153] <Parameter PB9: Parameter based on stay time> Parameter PB9 is a parameter based on information about the location and duration of stay within the event venue, which is included in the behavior information.

[0154] The information processing device 1 extracts, from the behavior record DB 206, behavioral information of one subject to be analyzed that indicates that the subject stayed at one participant's exhibition booth, etc., and, based on the extracted behavioral information, obtains the longest time that the subject to be analyzed stayed at the participant's exhibition booth, etc. The information processing device 1 obtains a parameter PB9 such that the longer the obtained stay time, the higher the purchase intention of the second indicator becomes. (Example of parameter PB8 value) "More than 3 minutes": 10 points, "30 seconds or more but less than 3 minutes": 5 points, "less than 30 seconds": 0 points,

[0155] This makes it possible to accurately determine the second potential customer classification that reflects the purchasing intention of the person being analyzed, as indicated by the length of time spent at an exhibition booth or the like.

[0156] <Parameter PB10: Parameter based on visitor behavior regarding other participants>

[0157] Parameter PB10 is a parameter based on visitor behavior regarding other participants dealing in related products (such as other companies dealing in products in the same category).

[0158] Based on the behavioral information (behavior record DB206) and participant product information (participant product DB203) stored in the storage device 2, the information processing device 1 acquires the number of times a predetermined visitor behavior (such as visiting an exhibition booth or attending a seminar) has been performed by a certain participant with respect to other participants who handle products related to the product handled by the certain participant. For example, the information processing device 1 identifies other participants who handle products related to the product handled by the certain participant based on the participant product information of each participant registered in the participant product DB203. The information processing device 1 extracts behavioral information indicating that the certain visitor behavior has been performed by the certain participant from the behavioral information about the identified other participants, and acquires the number of times the certain visitor behavior has been performed by the certain participant based on the extracted behavioral information. The information processing device 1 acquires a parameter PB10 such that the purchase intention of the second indicator increases as the number of times the certain visitor behavior has been performed by other participants who handle related products increases.

[0159] (Example 1 of parameter PB10 value) "Visit three or more consecutive exhibition booths selling related products" - 5 points "Visit two consecutive exhibition booths of participants selling related products" - 3 points

[0160] (Example 2 of parameter PB10 value) "Attend a seminar with one participant"...10 points "Attending seminars with other participants dealing with related products" - 5 points

[0161] This allows for an accurate determination of the second potential customer classification that reflects the purchasing intent of the person being analyzed, as expressed by visitor behavior (behavior observed when comparing and considering products) exhibited at other participants who handle related products.

[0162] Returning to Figure 5 again. Steps ST215 to ST270 show four processes (displaying the characteristics of potential customers, displaying the sales activity plan, displaying e-mail proposals, and displaying the event outcome evaluation index) for displaying information generated based on the classification set (a combination of the judgment results of the first potential customer classification and the judgment results of the second potential customer classification) on the display device of the participant terminal device 5. Each of these four processes will be described below.

[0163] <Displaying the characteristics of the prospect> The participant terminal device 5 accesses the information processing device 1 and requests the display of a screen (such as a web page) including information indicating the characteristics of each person being analyzed as a prospective customer (ST215). The information processing device 1, having received this request, generates information indicating the characteristics of each person being analyzed as a prospective customer based on the classification set of each person being analyzed determined in steps ST205 and ST210, and transmits this information to the participant terminal device 5 (ST220). The participant terminal device 5 causes the display device to display a screen including information indicating the characteristics of each person being analyzed as a prospective customer based on the information received from the information processing device 1 (ST225).

[0164] Fig. 8A is a diagram showing an example of a method for distinguishing classification sets. Fig. 8B is a diagram showing an example of a prospective customer list in which classification sets are represented by the method shown in Fig. 8A, and shows an example of information displayed on the display device of the participant terminal device 5 in step ST225.

[0165] 8A and 8B, the information processing device 1 determines three categories, "SQL," "MQL," and "NL," as first prospective customer categories, and three categories, "hot," "warm," and "cold," as second prospective customer categories. A category set is a combination of the three first prospective customer categories (SQL, MQL, NL) and the three second prospective customer categories (hot, warm, cold), and there are nine category sets in total.

[0166] The SQL (Sales Qualified Lead) category has the highest ease of purchase, the NL (Nurturing Lead) category has the lowest ease of purchase, and the MQL (Marketing Qualified Lead) category has an intermediate ease of purchase compared to the SQL and NL categories.

[0167] The Hot category has the highest purchase willingness, the Cold category has the lowest purchase willingness, and the Warm category has intermediate purchase willingness relative to the Hot and Cold categories.

[0168] In the example of Figure 8A, the three primary lead classifications (SQL, MQL, NL) are distinguished by three colors (red, yellow, green), and the three secondary lead classifications (hot, warm, cold) are distinguished by color intensity (dark, normal, light). However, since colors cannot be expressed on a diagram, text is used instead of color. In the example of the prospective customer list (list of analysis subjects) shown in FIG. 8B, the classification set of each prospective customer is represented by "color" and "color intensity" in the leftmost column. In this way, by representing the classification set with "color" and "color intensity," the characteristics of each prospective customer (ease of purchase, willingness to purchase) can be easily grasped at a glance.

[0169] Figure 9A is a diagram showing another example of a method for distinguishing between classification sets, and Figure 9B is a diagram showing an example of a prospect list in which classification sets are represented by the method shown in Figure 9A.

[0170] In the example of Figure 9A, the three primary prospect classifications (SQL, MQL, NL) are distinguished by three shapes (★, ●, ▲), and the three secondary prospect classifications (hot, warm, cold) are distinguished by color intensity (dark, normal, light). In the example of the prospect list (list of analysis subjects) shown in Figure 9B, the classification set for each prospect is represented by a "shape" and "color intensity" in the leftmost column. In this way, by representing the classification set using "shapes" and "color intensity," the characteristics of each potential customer (ease of purchase, willingness to purchase) can be easily grasped at a glance.

[0171] In the examples of Figures 9A and 9B, the three first prospective customer classifications (SQL, MQL, NL) are distinguished by shapes, but the first prospective customer classifications may also be distinguished by any symbol not limited to shapes, or by a combination of any shape and any symbol. Also, in the examples of Figures 9A and 9B, the second potential customer classifications (hot, warm, cold) are distinguished by color intensity, but they may also be distinguished by color or by a combination of color and color intensity.

[0172] 10A and 10B are diagrams showing examples of distribution charts representing the number of analysis subjects for each classification set, and each shows an example of information displayed on the display device of the participant terminal device 5 in step ST225.

[0173] The distribution charts shown in FIGS. 10A and 10B show the number of analysis subjects for each classification set among multiple analysis subjects identified for one participant. In the distribution diagram shown in Figure 10A, the position in the first direction (vertical direction of the drawing) on ​​the two-dimensional plane corresponds to the three first potential customer classifications (SQL, MQL, NL), the position in the second direction (horizontal direction of the drawing) on ​​the two-dimensional plane corresponds to the three second potential customer classifications (hot, warm, cold), and the display mode of the two-dimensional figure placed on the two-dimensional plane (size of the circle) corresponds to the number of people being analyzed. In the distribution diagram shown in Figure 10B, the position in the first direction (horizontal direction of the drawing) on ​​the two-dimensional plane corresponds to the three first potential customer classifications (SQL, MQL, NL), the position in the second direction (depth direction of the drawing) on ​​the two-dimensional plane corresponds to the three second potential customer classifications (hot, warm, cold), and the display mode of the three-dimensional figure rising from the two-dimensional plane (vertical length of the rectangular prism) corresponds to the number of people being analyzed.

[0174] The distribution charts shown in FIGS. 10A and 10B make it easy to grasp at a glance the trends in the number of people in each classification set among a large number of potential customers.

[0175] In this way, according to this embodiment, information about the characteristics of event attendees as potential customers can be provided to participants, who can use this information to formulate appropriate sales activities and increase the probability of closing a deal.

[0176] <Display sales activity plan> Returning to Figure 5 again. The participant terminal device 5 accesses the information processing device 1 and requests the display of a screen (such as a web page) containing information about a sales activity plan for the person being analyzed (prospective customer) (ST230). Upon receiving this request, the information processing device 1 generates information about a sales activity plan for the person being analyzed to reach the stage of purchasing the participant's product, based on the classification set of the person being analyzed determined in steps ST205 and ST210, and transmits this information to the participant terminal device 5 (ST235). Based on the information received from the information processing device 1, the participant terminal device 5 causes a screen containing information about the sales activity plan to be displayed on the display device (ST240).

[0177] FIG. 11 is a flowchart for explaining an example of the process of generating information related to a sales activity plan (ST235: FIG. 5). The information processing device 1 acquires a category set determined for one analysis subject from the analysis subject information (analysis subject DB207) of one analysis subject identified for one participant (ST500). Furthermore, the information processing device 1 reads out sales activity information for the one participant, which is associated with the category set acquired in step ST500, from the sales activity DB208, and acquires plan information (information about the sales activity plan) included in this sales activity information (ST510). Then, the information processing device 1 generates information about the sales activity plan for the one analysis subject based on the acquired plan information (ST515).

[0178] Figure 12 shows the sales activity plans set for each of the nine classification sets. In the example shown in Figure 12, the sales activity plans for each classification set include the sales activity policy, the time from the first contact to the actual sales response, and the means of approaching potential customers.

[0179] In this way, a clear sales activity plan corresponding to the classification set is presented to each prospective customer, making it possible to carry out consistent sales activities for prospective customers without relying on personal judgment.

[0180] Furthermore, by conducting sales activities according to the classification set, it is possible to efficiently utilize sales personnel resources while increasing the overall success rate.

[0181] <Show email proposal> Returning to Figure 5 again. The participant terminal device 5 accesses the information processing device 1 and requests the display of a screen (such as a web page) containing a proposal for an email to be sent to the person being analyzed (a potential customer) (ST245). The information processing device 1, having received this request, acquires an email template associated with the category set from email template information (email template DB 209) based on the category set of the person being analyzed determined in steps ST205 and ST210. The information processing device 1 generates a proposal for the email text based on the acquired email template and sends it to the participant terminal device 5 (ST250). The participant terminal device 5 displays on its display device a screen containing the proposal for the email text received from the information processing device 1 (ST255).

[0182] FIG. 13 is a flowchart for explaining an example of the process of generating a proposal for an e-mail (ST250: FIG. 5). The information processing device 1 acquires the category set determined for one analysis subject from the analysis subject information (analysis subject DB207) of one analysis subject identified for one participant (ST600). Furthermore, the information processing device 1 reads out email template information for the one participant, which is associated with the category set acquired in step ST600, from the email template DB209, and acquires the email template included in this email template information (ST605). Then, the information processing device 1 generates a proposal for an email to be sent to the one analysis subject based on the acquired email template (ST615). Figure 14 is a diagram showing an example of an email proposal generated based on the email template.

[0183] In this way, by using email templates prepared according to the classification set, it becomes possible to easily create appropriate emails that match the characteristics of prospective customers, thereby reducing the workload of sales representatives and improving the efficiency of sales activities, while also increasing the probability of closing a deal.

[0184] <Displaying event performance indicators> Returning to Figure 5 again. The participant terminal device 5 accesses the information processing device 1 and requests the display of a screen (web page, etc.) including indicators for evaluating the outcome of the event (outcome evaluation indicators) (ST260). Upon receiving this request, the information processing device 1 calculates outcome evaluation indicators (number of potential customers, number of people in classification SQL, etc.) based on the classification set of the analysis subjects determined in steps ST205 and ST210, and transmits them to the participant terminal device 5 (ST265). The participant terminal device 5 displays the screen including the outcome evaluation indicators received from the information processing device 1 on the display device (ST270).

[0185] FIG. 15 is a diagram showing an example of a graph of performance evaluation indicators. In the example of FIG. 15, the achievement rates (percentages of pre-set target values) of four main performance evaluation indicators (number of prospects, number of SQLs, number of negotiations, and number of successful deals) are represented by bar graphs. The target values ​​are set, for example, based on performance evaluation indicators obtained in similar past events. The number of prospects is the number of people analyzed identified for one participant, and the number of SQLs is the number of people analyzed in the SQL category. The number of negotiations and number of successful deals are the results obtained through sales activities after the event, and are updated as necessary.

[0186] In this way, the performance evaluation index based on the classification set determined for each analysis subject can be visualized, making it possible to clearly grasp the results of the event. This makes it easier to quantitatively manage the results of sales using the event and to improve sales activities.

[0187] The present invention is not limited to the above-described embodiment, but includes various variations.

[0188] Some of the processing of the information processing device 1 in the above-described embodiment may be executed by another device (such as the participant terminal device 5). For example, if some of the above-described processing of the information processing device 1 is executed by the participant terminal device 5, it can be said that a computer system is configured that includes the computer of the information processing device 1 and the computer of the participant terminal device 5, and that the processing according to this embodiment is executed by cooperation between the multiple computers in this computer system.

[0189] The configuration of the databases (201 to 209) in the above-described embodiment is an example, and the present embodiment is not limited to this example. That is, some of the above-described databases may be replaced with one or more other databases. Furthermore, the information handled in the processing of the present embodiment (visitor information, participant information, behavior information, etc.) does not necessarily have to be contained in a single database record, and may be distributed across, for example, two or more database records. [Explanation of symbols]

[0190] 1...information processing device, 11...communication unit, 12...storage unit, 121...program, 13...processing unit, 2...storage device, 201...visitor DB, 202...participant DB, 203...participant product DB, 204...panel management DB, 205...content management DB, 206...behavior record DB, 207...analysis subject DB, 208...sales activity DB, 209...email template DB, 210...content, 4...visitor terminal device, 5...participant terminal device, 6...operator terminal device, 7...location detection device, 9...communication network

Claims

1. A method for providing information about a potential customer in an information processing system, comprising: Attributes related to visitors to an event are called visitor attributes. Attributes related to participants attending the event are called participant attributes, The behavior of the visitors is called the visitor behavior. The visitor who has performed the predetermined visitor behavior and is recognized as the potential customer of one of the participants is called an analysis subject for that one participant; A classification of the analysis subjects based on the visitor attributes, which is related to the ease with which the analysis subject for one of the participants will reach the stage of purchasing a product of the one participant (hereinafter referred to as purchase ease), is called a first potential customer classification; A classification of the analysis subjects based on the visitor behavior, which is a classification regarding the willingness of the analysis subject for one of the participants to purchase the product of the one participant (hereinafter referred to as purchase willingness), is called a second potential customer classification, the information processing system is capable of accessing a storage device; The storage device includes: a plurality of pieces of visitor attribute information, each of which includes information on one or more of the visitor attributes related to one of the visitors; a plurality of participant attribute information pieces, each of which includes information on one or more of the participant attributes associated with one of the participants; a plurality of pieces of behavioral information each containing information about the visitor behavior of one of the visitors; I remember the an analysis subject identification step of identifying one or more analysis subjects recognized as the potential customers of one of the participants based on the behavioral information stored in the storage device; a first prospective customer classification determination step of determining the first prospective customer classification of each of the one or more analysis subjects identified for one of the participants, Determining the first potential customer classification of one of the analysis subjects, calculating a first index related to the ease of purchase of the one analysis subject based on the participant attributes indicated in the participant attribute information of the one analysis subject and the visitor attributes indicated in the visitor attribute information of the one analysis subject; determining the first potential customer classification based on the calculated first index; a first prospect classification determination step including: A second prospective customer classification determination step of determining the second prospective customer classification of each of the one or more analysis subjects identified for one of the participants, Determining the second potential customer classification of one of the analysis subjects, Calculating a second index related to the purchase intention of the one analysis subject based on the behavioral information indicating that the visitor behavior related to the one participant was performed by the one analysis subject; determining the second potential customer classification based on the calculated second index; A second prospect classification determination step including: a first information display step of generating information indicating characteristics of the analysis subject as a prospective customer based on the determination result of the first prospective customer classification and the determination result of the second prospective customer classification, and displaying the information on a display device; A method having the following.

2. In the first prospective customer classification determination step, calculating the first index of one of the analysis subjects identified for one of the participants, determining a relevance between the participant attribute of the one participant and the visitor attribute of the one analysis subject; When it is determined that there is a correlation, calculating the first index so that the ease of purchase is increased compared to when it is determined that there is no correlation. The method of claim 1.

3. In calculating the first index of one of the analysis subjects identified for one of the participants, determining a correlation between the participant attribute of the one of the participants and the visitor attribute of the one of the analysis subjects, Determining the relevance between the industry of the one participant and the industry and / or occupation of the one analysis subject; and determining a relevance between the product of the one participant and the industry and / or occupation of the one analysis target person. The method of claim 2.

4. In the first prospective customer classification determination step, calculating the first index of one of the analysis subjects, calculating the first index such that the purchase ease increases as the visitor attribute of the one analysis subject becomes more involved in the decision to purchase a product; The method of claim 1.

5. The visitor attributes that the participant assumes as the potential customer are called expected visitor attributes, the storage device stores a plurality of pieces of expected attendee attribute information, each of which includes information on the expected attendee attribute set for one of the attendees; In the first prospective customer classification determination step, calculating the first index of one of the analysis subjects identified for one of the participants, determining a relevance between the expected visitor attribute indicated by the expected visitor attribute information of the one participant and the visitor attribute indicated by the visitor attribute information of the one analysis target; and when it is determined that there is a correlation, calculating the first index so that the ease of purchase is increased compared to when it is determined that there is no correlation. The method of claim 1.

6. The organization that the participant focuses on as the potential customer is called a "focused organization," the storage device stores a plurality of pieces of notable organization information, each of which includes information on the notable organization set for one of the participants; In the first prospective customer classification determination step, calculating the first index of one of the analysis subjects identified for one of the participants, determining whether the organization to which the one analysis subject belongs is the noted organization indicated by the noted organization information of the one participant; and calculating the first index so that, when the organization to which the user belongs is the noted organization, the ease of purchase is increased compared to when the organization to which the user belongs is not the noted organization. The method of claim 1.

7. In the second prospective customer classification determination step, calculating the second index of one of the analysis subjects identified for one of the participants, calculating the second index based on at least one of the content, number, frequency, time, and season of the visitor behavior performed by the one analysis subject in relation to the one participant; The method of claim 1.

8. the storage device stores a plurality of participant product information items, each of which includes information about a product handled by one of the participants; In the second prospective customer classification determination step, calculating the second index of one of the analysis subjects identified for one of the participants, Based on the behavioral information and the participant product information stored in the storage device, acquiring the number of times that the one participant has performed the predetermined visitor behavior with respect to other participants who handle products related to the products handled by the one participant; calculating the second index so that the greater the number of times the predetermined visitor behavior is acquired, the stronger the purchase intention; The method of claim 1.

9. The determination result of the first prospective customer classification and the determination result of the second prospective customer classification are referred to as classification determination results, the first information display step displays the classification determination results obtained for one or more of the analysis subjects, Displaying the classification determination results so that the determination results of the first potential customer classification are distinguished by color and the determination results of the second potential customer classification are distinguished by color intensity; Or, displaying the classification determination results so that the determination results of the first potential customer classification are distinguished by graphics and / or symbols, and the determination results of the second potential customer classification are distinguished by colors and / or color depths. The method of claim 1.

10. A combination of one category in the first prospect classification and one category in the second prospect classification is called a classification set, The first information display step includes displaying a distribution map showing the number of analysis subjects for each of the classification sets among the plurality of analysis subjects identified for one of the participants, wherein a position in a first direction on a two-dimensional plane corresponds to the determination result of the first prospective customer classification, a position in a second direction on the two-dimensional plane corresponds to the determination result of the second prospective customer classification, and a display mode of a two-dimensional figure placed on the two-dimensional plane or a three-dimensional figure rising from the two-dimensional plane corresponds to the number of analysis subjects. The method of claim 1.

11. a second information display step of generating information on a sales activity plan for one of the analysis subjects identified for one of the participants based on the determination result of the first potential customer classification and the determination result of the second potential customer classification for the one of the analysis subjects identified for one of the participants, and displaying the information on a display device; The method of claim 1.

12. A combination of one category in the first prospect classification and one category in the second prospect classification is called a classification set, the storage device stores a plurality of pieces of sales activity information, each of which includes plan information relating to a sales activity plan set for one of the participants; One of the business activity information includes one of the plan information associated with one of the classification sets, The second information display step includes: Acquiring the plan information associated with the classification set corresponding to a combination of the determination result of the first prospective customer classification and the determination result of the second prospective customer classification for one of the analysis subjects identified for one of the participants from the sales activity information of the one of the participants; generating information regarding a plan for the business activities based on the acquired plan information; The method of claim 11.

13. A combination of one category in the first prospect classification and one category in the second prospect classification is called a classification set, the storage device stores a plurality of email template information, each including an email template for creating an email message to be sent by one of the participants to a prospective customer; One of the email template information includes one of the email templates associated with one of the classification sets, a third information display step of generating a draft of the text of the email to be sent to the potential customer and displaying the draft on a display device; The third information display step includes: Acquire, from the email template information of one of the participants, the email template associated with the classification set corresponding to a combination of the determination result of the first prospective customer classification and the determination result of the second prospective customer classification for one of the analysis subjects identified for the one of the participants; generating a proposal for the email to be sent to the one analysis subject based on the acquired email template; The method of claim 1.

14. a fourth information display step of calculating a performance evaluation index for evaluating the performance of the event based on the determination result of the first prospective customer classification and the determination result of the second prospective customer classification for one or more of the analysis subjects identified for one of the participants, and displaying the calculated performance evaluation index on a display device; The method of claim 1.

15. A program including instructions for causing an information processing system to perform a process of providing information about potential customers, Attributes related to visitors to an event are called visitor attributes. Attributes related to participants attending the event are called participant attributes, The behavior of the visitors is called the visitor behavior. The visitor who has performed the predetermined visitor behavior and is recognized as the potential customer of one of the participants is called an analysis subject for that one participant; A classification of the analysis subjects based on the visitor attributes, which is related to the ease with which the analysis subject for one of the participants will reach the stage of purchasing a product of the one participant (hereinafter referred to as purchase ease), is called a first potential customer classification; A classification of the analysis subjects based on the visitor behavior, which is a classification regarding the willingness of the analysis subject for one of the participants to purchase the product of the one participant (hereinafter referred to as purchase willingness), is called a second potential customer classification, the information processing system is capable of accessing a storage device; The storage device includes: a plurality of pieces of visitor attribute information, each of which includes information on one or more of the visitor attributes related to one of the visitors; a plurality of participant attribute information pieces, each of which includes information on one or more of the participant attributes associated with one of the participants; a plurality of pieces of behavioral information each containing information about the visitor behavior of one of the visitors; I remember the The processing performed by the information processing system in accordance with the instructions includes each step of the method described in any one of claims 1 to 14. program.

16. An information processing system that performs processing to provide information about potential customers, Attributes related to visitors to an event are called visitor attributes. Attributes related to participants attending the event are called participant attributes, The behavior of the visitors is called the visitor behavior. The visitor who has performed the predetermined visitor behavior and is recognized as the potential customer of one of the participants is called an analysis subject for that one participant; A classification of the analysis subjects based on the visitor attributes, which is related to the ease with which the analysis subject for one of the participants will reach the stage of purchasing a product of the one participant (hereinafter referred to as purchase ease), is called a first potential customer classification; A classification of the analysis subjects based on the visitor behavior, which is a classification regarding the willingness of the analysis subject for one of the participants to purchase the product of the one participant (hereinafter referred to as purchase willingness), is called a second potential customer classification, a processing unit; a storage unit that stores instructions for causing the processing unit to perform processing; the processing unit is capable of accessing a storage device; The storage device includes: a plurality of pieces of visitor attribute information, each of which includes information on one or more of the visitor attributes related to one of the visitors; a plurality of participant attribute information pieces, each of which includes information on one or more of the participant attributes associated with one of the participants; a plurality of pieces of behavioral information each containing information about the visitor behavior of one of the visitors; I remember the The processing performed by the processing unit in accordance with the instructions includes each step of the method described in any one of claims 1 to 14. Information processing system.

17. An information processing system that performs processing to provide information about potential customers, Attributes related to visitors to an event are called visitor attributes. Attributes related to participants attending the event are called participant attributes, The behavior of the visitors is called the visitor behavior. The visitor who has performed the predetermined visitor behavior and is recognized as the potential customer of one of the participants is called an analysis subject for that one participant; A classification of the analysis subjects based on the visitor attributes, which is related to the ease with which the analysis subject for one of the participants will reach the stage of purchasing a product of the one participant (hereinafter referred to as purchase ease), is called a first potential customer classification; A classification of the analysis subjects based on the visitor behavior, which is a classification regarding the willingness of the analysis subject for one of the participants to purchase the product of the one participant (hereinafter referred to as purchase willingness), is called a second potential customer classification, the information processing system is capable of accessing a storage device; The storage device includes: a plurality of pieces of visitor attribute information, each of which includes information on one or more of the visitor attributes related to one of the visitors; a plurality of participant attribute information pieces, each of which includes information on one or more of the participant attributes associated with one of the participants; a plurality of pieces of behavioral information each containing information about the visitor behavior of one of the visitors; I remember the A method for manufacturing a computer-readable recording medium, comprising: a means for performing each step of the method according to any one of claims 1 to 14; Information processing system.

Images