JP6383284B2 - Server apparatus, system, information processing method, and program - Google Patents

Description

  The present invention relates to a server device, a system, an information processing method, and a program.

  Along with the spread of the Internet, many companies have opened their own web pages, and access analysis is performed on who accessed the company's website and what actions were taken in the site, and made it available to users. A system to present has been proposed. Examples of such a system include systems disclosed in Patent Documents 1 and 2.

JP 2008-97259 A JP 2012-53523 A

In recent years, with the advance of information processing technology, the use of big data has been promoted, and it has become possible to analyze a huge amount of data that has been difficult until now. As a result, data analysis from an unprecedented viewpoint is also performed. However, in the prior arts such as Patent Documents 1 and 2, the object of analysis is limited to access to the Web page of each individual company, and comprehensively collects access data to Web pages of various business partners, There is a problem that there is no mechanism to utilize.
Accordingly, an object of the present invention is to comprehensively collect access data to a business partner's Web page, and to output data that can be used for analysis of the business partner based on the collected access data.

Accordingly, the server device of the present invention extracts a business partner company that satisfies the first condition set from the plurality of business partners based on the access history information of the websites of the business partners. and means, and output means for outputting information about the business partners extracted by the extraction means possess, the extracting unit is included in the access history information, the plurality of business partners in a set period of time The number of accesses to the website of the customer is aggregated for each company of the access source, and based on the total number of accesses to the website of the business partner company for the company of the access source, the supplier that satisfies the first condition Extract companies .

  ADVANTAGE OF THE INVENTION According to this invention, the access data to the client company's Web page can be collected comprehensively, and based on the collected access data, the data which can be utilized for the analysis of the client company can be output.

FIG. 1 is a diagram illustrating an example of a system configuration and the like of a supplier information output system. FIG. 2 is a diagram illustrating an example of a hardware configuration of the management server. FIG. 3 is a diagram illustrating an example of a functional configuration of the management server. FIG. 4 is a diagram illustrating an example of a relationship between companies indicated by access history information. FIG. 5 is a diagram showing an example of the IP address company information correspondence table. FIG. 6 is a diagram illustrating an example of access history information. FIG. 7 is a diagram illustrating an example of the total result. FIG. 8 is a diagram illustrating an example of the evaluation information calculation process. FIG. 9 is a diagram illustrating an example of a credit risk evaluation value table. FIG. 10 is a diagram illustrating an example of a total result. FIG. 11 is a diagram illustrating an example of the evaluation information calculation process. FIG. 12 is a diagram illustrating an example of the interest level evaluation value table. FIG. 13 is a diagram illustrating an example of a supplier company list. FIG. 14 is a diagram illustrating an example of a total result. FIG. 15 is a diagram illustrating an example of a total result. FIG. 16 is a diagram illustrating an example of the evaluation information calculation process. FIG. 17 is a diagram illustrating an example of a popularity rating value table. FIG. 18 is a diagram illustrating an example of output data. FIG. 19 is a diagram illustrating an example of output data. FIG. 20 is a diagram illustrating an example of output data. FIG. 21 is a diagram illustrating an example of an access frequency increase rate calculation result. FIG. 22 is a diagram illustrating an example of output data. FIG. 23 is a diagram illustrating an example of output data. FIG. 24 is a diagram illustrating an example of output data. FIG. 25 is a diagram illustrating an example of output data. FIG. 26 is a diagram illustrating an example of output data. FIG. 27 is a diagram illustrating an example of output data. FIG. 28 is a diagram illustrating an example of a system configuration and the like of the supplier information output system. FIG. 29 is a diagram illustrating an example of a functional configuration of the management server. FIG. 30 is a diagram illustrating an example of a total result.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<Embodiment 1>
FIG. 1 is a diagram illustrating an example of a system configuration of a supplier information output system. Company A, Company B, and Company C are assumed to be bank customers. In the following, a bank customer company is referred to as a bank customer company.
The supplier information output system includes a management server 100, an in-bank system 101, an IP address company name matching system 102, Web sites 106 to 108, and the like.
Web sites 106 to 108 are Web sites of Company A, Company B, and Company C, respectively. Upon receiving access, the Web sites 106 to 108 transmit the cookie information of the access source to the IP address company name matching system 102 as access history information. Web sites 106 to 108 include Web pages about products of Company A, Company B, and Company C, respectively.

The IP address company name matching system 102 acquires the cookie information of the access source from the Web sites 106 to 108 as access history information. The IP address company name matching system 102 specifies a company that has accessed the Web site corresponding to the access history information based on the acquired IP address of the access history information. The IP address company name matching system 102 is assumed to be composed of a server device including a storage device that stores access history information for each bank company.
The IP address company name matching system 102 includes access history information DBs 103 to 105. The access history information DBs 103 to 105 store access history information of the Web sites 106 to 108, respectively.

The management server 100 acquires the access history information of the websites 106 to 108 from the IP address company name matching system 102, and extracts the bank trading company. In addition, the management server 100 outputs the extracted information relating to the bank trading company to the in-bank system 101. In the present embodiment, it is assumed that the management server 100 is configured by a single server device. The management server 100 periodically acquires information such as the access source company information specified from the access history information and the number of accesses to the website from the IP address company name matching system 102. The management server 100 arbitrarily sets the timing for acquiring the information, such as every access to the website, every access to the website exceeding a certain number, every week, every half month, every month, etc. it can.
The in-bank system 101 is connected to the management server 100 by wire or wireless, and displays output data output from the management server 100 on a user interface or stores it in a storage device. The in-bank system 101 includes a computer in the bank, a database server in the bank, and the like.

FIG. 2 is a diagram illustrating an example of a hardware configuration of the management server 100. The management server 100 includes a CPU 200, a RAM 201, a storage device 202, a network I / F 203, and the like.
The CPU 200 is a CPU that executes a control program read into the RAM 201 and controls the management server in an integrated manner. The RAM 201 is a main storage device that functions as a main memory or work memory of the CPU 200. The storage device 202 is a storage device that stores programs, data, and the like, and includes a ROM, a hard disk, and the like. A network I / F 203 is a network interface used for connection with the in-bank system 101, the IP address company name matching system 102, and the like.
When the CPU 200 executes processing based on a program stored in a storage device such as the storage device 202, the functions of the management server 100 described later and the processing of the flowchart are realized.

FIG. 3 is a diagram illustrating an example of a functional configuration of the management server 100. The management server 100 includes a calculation unit 300, an output unit 301, and the like.
Based on the access history information of a plurality of bank partner companies (Company A, Company B, Company C) acquired from the IP address company name matching system 102, the calculation unit 300 is based on comprehensive conditions. And extract information about the extracted bank trading company.
The output unit 301 outputs the information calculated by the calculation unit 300 to the in-bank system 101.
FIG. 4 is a diagram illustrating an example of a relationship between companies indicated by access history information. FIG. 4 shows an example of the relationship between companies indicated in the access history information acquired by the management server 100 from the IP address company name matching system 102. Company A, B, and C are bank customers. FIG. 4 shows that companies D, E, and F have accessed the website of company A. FIG. 4 shows that Company G and Company H have accessed the website of Company B, and Company I has accessed Company C.

Hereinafter, information processing of the supplier information output system in the present embodiment will be described.
The management server 100 comprehensively extracts bank trading companies based on the access history information of the websites 106 to 108 of the companies A, B, and C, which are business partners. Reference information used for sales promotion. Comprehensive extraction is not based on conditions based on access history information for each single company's website, but also considers relationships between multiple companies based on access history information on websites of multiple companies. It means extraction under conditions.
In the present embodiment, it is assumed that an access analysis tag is loaded on the Web sites 106 to 108. The IP address company name matching system 102 acquires access history information from the websites 106 to 108 via the access analysis tag.

The IP address company name matching system 102 acquires access history information from the websites 106 to 108 for each bank trading company.
In this embodiment, the IP address company name matching system 102 holds correspondence information between IP addresses and company names. An example of the correspondence information is shown in FIG. FIG. 5 is a diagram showing an example of the IP address company information correspondence table 500. It is assumed that IP addresses “***. ***. ***. ***. ***” shown in FIG. 5 are set differently for each company.
In the present embodiment, the IP address company name matching system 102 holds an IP address company information correspondence table 500 as the correspondence information. The IP address company information correspondence table 500 is assumed to be stored in a storage device such as a hard disk in the IP address company name matching system 102.
The IP address company name matching system 102 obtains the company name corresponding to the IP address of the acquired access history information from the IP address company information correspondence table 500, so that the company that has accessed the website corresponding to the access history information is identified. Identify. The IP address company name matching system 102 adds the company name of the specified company to the access history information. The IP address company information correspondence table 500 is an example of IP address company name conversion information. The IP address company name matching system 102 may be configured to allow browsing of specified company information from a browser of a bank partner company corresponding to the Web site.

FIG. 6 is a diagram illustrating an example of access history information. FIG. 6 shows an example of access history information acquired from the websites 106 to 108 by the IP address company name matching system 102. The IP address company name matching system 102 transmits the access history information acquired from the websites 106 to 108 to the management server 100.
In this embodiment, it is assumed that the IP address company name matching system 102 acquires access history information from the websites 106 to 108 each time the websites 106 to 108 are accessed. The IP address company name matching system 102 transmits the access history information to the management server 100 every time the access history information is acquired from the websites 106 to 108. Each time the management server 100 acquires the access history information from the IP address company name matching system 102, the management server 100 performs a supplier information output process of the bank supplier company. Therefore, the supplier information output system of this embodiment can perform the supplier information output process of the bank supplier company in real time considering the access history information to the latest Web sites 106 to 108.

The access history information transmitted from the IP address company name matching system 102 to the management server 100 includes a company code that identifies the company that visited the Web site. The management server 100 associates the company code included in the access history information with the company code in the in-bank system 101 and can output information on each bank trading company to the in-bank system 101.
The management server 100 performs the following supplier information output processing based on the access history information transmitted from the IP address company name matching system 102.

[Customer information output processing for credit management purposes]
Based on the access history information of the websites 106 to 108 acquired from the IP address company name matching system 102, the CPU 200 counts the number of accesses to the website for each bank partner company during the period indicated by the set conditions. . The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.
FIG. 7 is a diagram illustrating an example of the total result. FIG. 7 shows an example in which the number of accesses to the Web site in the last 30 days is tabulated for each bank partner company. The table 700 includes items of “company” and “number of accesses”. An item “company” in the table 700 indicates a bank partner company, and an item “number of accesses” in the table 700 indicates a total result of the number of accesses to the corresponding “company” website.

FIG. 8 is a diagram illustrating an example of the evaluation information calculation process. The processing of the present embodiment in the following case will be described with reference to FIG. That is, a process will be described in a case where the condition “extract the bank partner company having the number of accesses of 5000 times or more from the top two companies in the number of accesses to the website in the last 30 days” is described. Assume that the table 700 in FIG. 7 shows the result of totaling the number of accesses to the Web site for the last 30 days for each bank partner company.
In step S <b> 801, the CPU 200 acquires information on the bank business partners with the top two access counts from the counting results of the table 700 based on the above conditions. N in S801 in FIG. 8A is 2 from the above condition. The CPU 200 extracts information on the B company and the C company, which are the top two companies, from the totaled results in the table 700.
In S802, the CPU 200 determines whether or not the processing in S803 to S804 has been completed for all the bank counterparties extracted in S801. If the CPU 200 determines that the processes of S803 to S804 have been completed for all the bank trading companies extracted in S801, the CPU 200 ends the process of FIG. If the CPU 200 determines that the processes of S803 to S804 have not been completed for all the bank trading companies extracted in S801, the CPU 200 proceeds to the process of S803.

  In S803, the CPU 200 determines whether or not the number of accesses is equal to or greater than the reference value indicated in the above condition for one of the bank partner companies extracted in S801. If the CPU 200 determines that the number of accesses for the company is equal to or greater than the reference value indicated in the condition, the CPU 200 proceeds to the process of S804. If the CPU 200 determines that the number of accesses for the company is not greater than or equal to the reference value indicated in the condition, the CPU 200 proceeds to the process of S802. The reference value is 5000 times from the above condition. The CPU 200 determines that the B company is less than the reference value, and the C company determines that the B company is greater than the reference value.

In S <b> 804, the CPU 200 assigns an evaluation value related to credit risk to the company that has been determined in S <b> 803 that the number of accesses is equal to or greater than a reference value. The CPU 200 gives the credit risk evaluation value to the company C. The CPU 200 determines the credit risk evaluation value to be assigned by referring to the credit risk evaluation value table. The evaluation value is an example of evaluation information.
FIG. 9 is a diagram illustrating an example of a credit risk evaluation value table. The credit risk increases in the order of the evaluation values “A” to “C”, the evaluation value “A” indicates that the credit risk is the lowest, and the evaluation value “C” indicates that the credit risk is the highest. The credit risk evaluation value table 900 in FIG. 9 holds evaluation values corresponding to the number of accesses for 30 days.
The CPU 200 refers to the access count item in the credit risk evaluation value table 900 and determines which range the access count of the company C belongs. The CPU 200 determines that it belongs to the range of “5000 times or more” because the access number of the company C is 7890. The CPU 200 refers to “A”, which is an evaluation value corresponding to “5000 times or more”, and assigns the evaluation value “A” to the C company.
The CPU 200 outputs the company name of the bank partner company extracted in S801 and the evaluation value assigned in S804 to the in-bank system 101.

Moreover, the process of this embodiment in the following case is demonstrated using FIG.8 (b). That is, a process will be described in the case where the condition “extracting a bank partner company with the number of accesses less than 100 out of the lower two companies with the number of accesses to the Web site in the last 30 days” is defined. Assume that a table 700 is a result of totaling the number of accesses to the Web site for the most recent 30 days for each bank partner company.
In step S <b> 805, the CPU 200 acquires information on bank trading companies whose number of accesses is the lower two companies from the counting result of the table 700 based on the above condition. The CPU 200 extracts information of the A company and the B company that are the lower two companies from the totaled results of the table 700.
The process of S806 is the same as the process of S802.
In S807, the CPU 200 determines whether the number of accesses is less than the reference value indicated in the above condition for one company that has not yet been processed among the bank partner companies extracted in S805. If the CPU 200 determines that the number of accesses for the company is less than the reference value indicated in the condition, the CPU 200 proceeds to the process of S808. If the CPU 200 determines that the number of accesses for the company is not less than the reference value indicated in the condition, the CPU 200 proceeds to the process of S806. The reference value is 100 times from the above condition. The CPU 200 determines that the company A is less than the reference value, and the company B determines that the company B is not less than the reference value.

In S808, the CPU 200 assigns an evaluation value related to credit risk to the bank transaction precedent determined that the number of accesses is less than the reference value in S807. The CPU 200 assigns a credit risk evaluation value to the A company.
The CPU 200 refers to the access count item in the credit risk evaluation value table 900 and determines which range the access count of the company A belongs. The CPU 200 determines that it belongs to the range of “less than 100 times” because the access number of the company A is 12. The CPU 200 refers to “C”, which is an evaluation value corresponding to “less than 100 times”, and assigns the evaluation value “C” to the company A.
The CPU 200 outputs the bank customer company name extracted in S805 and the evaluation value of the bank customer company to the in-bank system 101.
A user of the customer information output system such as a bank employee uses the in-bank system 101 to refer to the evaluation value of the bank customer company given by the management server 100 and determines the credit risk for each bank customer company. It will be.

[Business partner information output processing for business matching purposes]
Based on the access history information of the websites 106 to 108 acquired from the IP address company name matching system 102, the CPU 200 accesses the total number of accesses to the website for each bank partner company during the period indicated by the set conditions. Do it for each source. The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.
FIG. 10 is a diagram illustrating an example of a total result. FIG. 10 shows an example in which the number of accesses to the website of Company A over the last 30 days is tabulated for each access source. The table 1000 includes items “visit company to company A site” and “number of accesses”. The item “visit company to company A site” in the table 1000 indicates a company that has accessed the website of company A, and the item “number of accesses” in table 1000 represents the corresponding “visit company to company A site”. "Indicates the result of counting the number of accesses to the website of Company A.

FIG. 11 is a diagram illustrating an example of the evaluation information calculation process. A process will be described in a case where a condition that “extracting a bank partner company having an access source company having an access count of 100 or more times in the most recent 30 days” is defined. The CPU 200 counts the number of accesses for each access source for each bank trading company. Assume that the table 1000 in FIG. 10 shows the result of counting the number of accesses to the website of Company A over the last 30 days for each access source. First, since there is an access source company (Company E) whose number of accesses to the Web site is 100 times or more, the CPU 200 extracts Company A.
In S1101, the CPU 200 determines whether or not the processing of S1102 to S1103 has been completed for all the companies that have visited the company A site in the table 1000. If the CPU 200 determines that the processing of S1102 to S1103 has been completed for all the companies that have visited the A company site in the table 1000, the CPU 200 ends the processing of FIG. If the CPU 200 determines that the processes of S1102 to S1103 have not been completed for all the companies that visit the company A site in the table 1000, the CPU 200 proceeds to the process of S1102.
In step S1102, the CPU 200 determines whether or not the number of accesses is greater than or equal to a reference value for one company that has not yet been processed among the companies that visit the company A site in the table 1000. If the CPU 200 determines that the number of accesses for the company is equal to or greater than a reference value, the CPU 200 proceeds to the process of S1103. If the CPU 200 determines that the number of accesses for the company is not greater than or equal to the reference value, the CPU 200 proceeds to the process of S1101. The CPU 200 determines that the number of accesses for the E company is equal to or greater than the reference value, and determines that the number of accesses for the D and F companies is not equal to or greater than the reference value.

In S <b> 1103, the CPU 200 gives an evaluation value related to the degree of interest in the A company to the visiting company to the A company site that is determined that the number of accesses is equal to or greater than the reference value in S <b> 1102. The CPU 200 gives the evaluation value of the degree of interest in the A company to the E company. The CPU 200 refers to the interest level evaluation value table to determine the evaluation value of the interest level for the company A to be assigned.
FIG. 12 is a diagram illustrating an example of the interest level evaluation value table. The degree of interest increases in the order of the evaluation values “C” to “A”, the evaluation value “A” indicates the highest interest, and the evaluation value “C” indicates the lowest interest. The interest level evaluation value table 1200 in FIG. 12 holds evaluation values corresponding to the number of accesses for 30 days.
The CPU 200 refers to the access count item of the interest evaluation value table 1200 and determines which range the access count of company E belongs to. The CPU 200 determines that it belongs to the range of “100 times or more” because the number of accesses by the company E to the company A site is 123. The CPU 200 refers to “A”, which is an evaluation value corresponding to “100 times or more”, and assigns the evaluation value “A” to the E company.
The CPU 200 also performs the above processing for other bank business partners such as Company B and Company C.
The CPU 200 outputs the bank partner company name and the evaluation value given to the access source corresponding to the bank transaction precedence to the in-bank system 101.

A user (bank employee or the like) of the supplier information output system refers to the evaluation value of the website access source of each bank supplier company assigned by the management server 100 using the computer of the in-bank system 101 or the like. Then, the user determines the possibility of business matching between the bank partner company and the company that is the access source of the bank partner company's Web site.
For example, the user introduces the company A to the company E when the company E who is considered to be more interested in the company A than the normal company is a customer of the bank. The CPU 200 may determine whether or not a company that has a higher interest than usual in the bank business partner is the bank business partner, and may output the determination result to the in-bank system 101. CPU200 performs the process which searches the said company from the customer list which the said bank has as a determination whether the said company is the customer of the said bank, and when it searches, the said company will be the customer of the said bank It is determined that An example of the supplier list is shown in FIG.

[Business partner information output processing for sales promotion purposes]
Based on the access history information of the websites 106 to 108 acquired from the IP address company name matching system 102, the CPU 200 counts the number of accesses to the web page for each bank partner company product during the period indicated by the set conditions. I do. The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.

FIG. 14 is a diagram illustrating an example of a total result. FIG. 14 shows an example in which the number of accesses to the Web site in the last 30 days is tabulated for each product of the bank business partner company. Tables 1400, 1401, and 1402 have items of “page” and “number of accesses”. The item “page” in the tables 1400, 1401, and 1402 indicates the product introduction web page of the bank partner company, and the item “access count” in the tables 1400, 1401, and 1402 indicates the corresponding “page” web page. The total number of accesses to is shown.
In this embodiment, Company A, Company B, and Company C are companies that handle the same type of products, and products a1, b1, and c1 in FIG. 14 belong to the same product field (field 1). Also, the products a2, b2, and c2 belong to the same product field (field 2), and the products a3, b3, and c3 also belong to the same product field (field 3).
The CPU 200 calculates a share rate of the number of accesses to the Web page for each product field for the A company, the B company, and the C company. The calculated results are shown in FIG. FIG. 15 is a diagram illustrating an example of a total result. The product field may be classified in advance, or may be classified by the management server 100 based on the inflow keyword (search keyword in the search engine) when the website is accessed. The search keyword may be one keyword, a plurality of keywords, or all keywords related to access to the website.

FIG. 16 is a diagram illustrating an example of the evaluation information calculation process. The processing of this embodiment in the following case will be described with reference to FIG. That is, a process when the condition “extracting a bank partner company having a product with a share rate of the number of accesses to the Web page in the last 30 days of 75% or more” is defined will be described. The CPU 200 counts the number of accesses to the Web site for the last 30 days for each product of the bank partner company. Assume that the aggregation results are tables 1400, 1401, and 1402. In addition, regarding the company A, the company B, and the company C, the share rate of the number of accesses to the Web page for each product field is assumed to be a table 1500. CPU200 extracts A company which has a product of a share rate of 75% or more.
In S1601, the CPU 200 determines whether or not the processing of S1602 to S1603 has been completed for all the product fields in the table 1500. If the CPU 200 determines that the processes of S1602 to S1603 have been completed for all the product fields in the table 1500, the CPU 200 ends the process of FIG. If the CPU 200 determines that the processing of S1602 to S1603 has not been completed for all the product fields in the table 1500, the CPU 200 proceeds to the processing of S1602.
In S1602, the CPU 200 determines whether or not the share rate is equal to or higher than a reference value for one of the product fields in the company A in the table 1500 that has not yet been processed. If the CPU 200 determines that the share rate is greater than or equal to the reference value for the field in Company A, the CPU 200 proceeds to the process of S1603. When the CPU 200 determines that the share rate is not equal to or higher than the reference value for the field in the company A, the CPU 200 proceeds to the process of S1601. The CPU 200 determines that the share rate for the field 1 is equal to or higher than the reference value, and determines that the share rate for the fields 2 and 3 is not equal to or higher than the reference value.

In S <b> 1603, the CPU 200 assigns an evaluation value related to the degree of popularity to the product field of Company A for which the share rate is determined to be greater than or equal to the reference value in S <b> 1602. The CPU 200 assigns an evaluation value of popularity to the field 1. The CPU 200 determines the evaluation value of the popularity to be given by referring to the popularity evaluation value table.
FIG. 17 is a diagram illustrating an example of a popularity rating value table. The degree of popularity increases in the order of evaluation values “C” to “A”, with the evaluation value “A” indicating the highest popularity and the evaluation value “C” indicating the lowest popularity.
The CPU 200 refers to the item of the share rate in the popularity evaluation value table 1700 and determines which range the share rate of the field 1 of the company A belongs. The CPU 200 determines that it belongs to the range of “75% or more” because the share ratio of the field 1 of the company A is 79%. The CPU 200 refers to the evaluation value “A” corresponding to “75% or more” and assigns the evaluation value “A” to the field 1 of the company A.
The CPU 200 outputs the extracted bank partner company name and the evaluation value assigned to the product in S1603 to the in-bank system 101.

In addition, processing of the present embodiment in the following case will be described with reference to FIG. That is, a process when the condition “extracting a bank partner company having a product with a share ratio of the number of accesses to a Web page in the last 30 days is less than 10%” will be described. Assume that tables 1400, 1401, and 1402 are the results of totaling the number of accesses to the Web site for the last 30 days for each product of the bank partner company. In addition, regarding the company A, the company B, and the company C, the share rate of the number of accesses to the Web page for each product field is assumed to be a table 1500. CPU 200 extracts Company A and Company B having products with a share rate of less than 10%.
In step S <b> 1604, the CPU 200 determines whether the processing in steps S <b> 1605 to S <b> 1606 has been completed for all the product fields in the table 1500. If the CPU 200 determines that the processes in S1605 to S1606 have been completed for all the product fields in the table 1500, the CPU 200 ends the process in FIG. If the CPU 200 determines that the processing in S1605 to S1606 has not been completed for all the product fields in the table 1500, the CPU 200 proceeds to the processing in S1605.
In step S <b> 1605, the CPU 200 determines whether or not the share rate is less than the reference value for one field that has not yet been processed among the product fields in the company A in the table 1500. If the CPU 200 determines that the share rate is less than the reference value for the field in Company A, the CPU 200 proceeds to the process of S1606. When the CPU 200 determines that the share rate is not less than the reference value for the field in Company A, the CPU 200 proceeds to the process of S1604. The CPU 200 determines that the share rate for the field 3 is less than the reference value, and determines that the share rate for the fields 1 and 2 is not less than the reference value.

In S <b> 1606, the CPU 200 assigns an evaluation value related to the degree of popularity to the product field of Company A for which the share rate is determined to be less than the reference value in S <b> 1605. The CPU 200 assigns an evaluation value of popularity to the field 3. The CPU 200 refers to the item of the share rate in the popularity evaluation value table 1700 and determines which range the share rate of the field 3 of the company A belongs. The CPU 200 determines that it belongs to the range of “less than 10%” because the share rate of the field 3 of the company A is 6%. The CPU 200 refers to the evaluation value “C” corresponding to “less than 10%” and assigns the evaluation value “C” to the field 3 of the company A.
The CPU 200 performs the above processing for the company B as well.
The CPU 200 outputs the extracted bank partner company name and the evaluation value assigned in S1606 to the in-bank system 101.

  The user of the customer information output system such as a bank employee uses, for example, the in-bank system 101 to refer to the evaluation value of the access source of the website of each bank customer company assigned by the management server 100, and You can determine the loan amount for the business related to the products of the other company. For example, the user increases the loan amount for the business related to the product in the field 1 of the company A, and decreases the loan amount to the business related to the product in the field 3 in the company A and the product in the field 1 in the company B. decide.

Through the processing of this embodiment, the supplier information output system comprehensively collects access data to the Web pages of the supplier companies, and outputs data that can be used for analysis of the supplier companies based on the collected access data. can do.
With the introduction of the supplier information output system of this embodiment, the bank can output information about the bank supplier company in real time, so that it is possible to discover risks and the like at an early stage. In addition, the bank can acquire information on business partners and information recognized in the industry that cannot be obtained only by information inside the bank, and can use the information for credit management and customer sales support.
The bank can grasp the degree of recognition, the trend, etc. in the market of the bank partner company by analyzing the transition of the number of accesses of the website of the bank partner company in time series. The bank can grasp the position and recognition of the bank partner company in the market from the faces of companies interested in the bank partner company. Furthermore, the bank can grasp the trend of the market itself macroscopically from the transition of the face of the company interested in the bank partner company.
A bank can be used for consulting services such as mediating business matching for each bank partner company when the bank partner company exists in the company interested in the bank partner company. As a result, bank business partners can expect banking consulting services.
According to the present embodiment, the user uses the analysis result regarding the access history of the partner company to the Web site in the credit management, business matching and sales promotion for the partner company. As a result, users can extract target companies from a different perspective from the financial information index that has been used so far, and acquire related information, so credit management, business matching and sales promotion can be performed. It becomes possible to carry out more effectively.

<Embodiment 2>
In the first embodiment, the supplier information output system outputs the supplier company name that satisfies the set condition and the calculated evaluation value. However, in this embodiment, the supplier information output system outputs information related to supplier companies that satisfy the set conditions.
The hardware configuration and functional configuration of the management server 100 in this embodiment are the same as those in the first embodiment. Details of the bank system 101 in the present embodiment are the same as those in the first embodiment. Assume that the IP address company name matching system 102 in this embodiment acquires access history information not only from the three companies, Company A, Company B, and Company C, but also from the websites of a large number of bank customers.
Processing of the supplier information output system in the present embodiment will be described.

[Customer information output processing for credit management purposes]
It is assumed that a condition is set that “a bank partner company that has accessed 5000 or more websites in the last 30 days is extracted”.
The CPU 200 compiles the number of accesses to the website for each bank partner company based on the access history information of the bank partner company website acquired from the IP address company name matching system 102 during the period indicated by the set condition. I do. The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.
Based on the above conditions, the CPU 200 extracts a bank trading company whose number of accesses is 5000 or more from the counting result. The CPU 200 acquires the extracted information relating to the bank business partner from the storage device 202 of the management server and outputs it to the in-bank system 101.
FIG. 18 is a diagram illustrating an example of output data. The output data includes the name of the bank partner company that satisfies the set condition, the total number of accesses within the period of the set condition, the address, the telephone number, the person in charge, and the like.

[Business partner information output processing for business matching purposes]
It is assumed that a condition is defined that “a bank partner company that has an access source with 100 or more accesses to a Web site in the last 30 days” is extracted.
The CPU 200 compiles the number of accesses to the website for each bank partner company based on the access history information of the bank partner company website acquired from the IP address company name matching system 102 during the period indicated by the set condition. For each access source. The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.
The CPU 200 extracts a company A having an access source with an access count of 100 times or more. The CPU 200 extracts all access sources having the number of accesses to the company A site of 100 times or more from the total result of the access history information. The CPU 200 acquires the extracted information relating to the bank business partner from the storage device 202 of the management server and outputs it to the in-bank system 101.
FIG. 19 is a diagram illustrating an example of output data. The output data includes the name of an access-source bank trading company that satisfies the set condition, the total number of accesses within the period of the set condition, an address, a telephone number, a person in charge name, and the like.

[Business partner information output processing for sales promotion purposes]
It is assumed that a condition is set that “a bank partner company having a product with a share rate of the number of accesses to the Web page of the product field 1 in the last 30 days is 75% or more” is defined.
Based on the access history information of the bank partner company's website acquired from the IP address company name matching system 102, the CPU 200 accesses the web page for each bank partner company product during the period indicated by the set conditions. Tally. The condition may be stored in advance in the management server 100 as a file or the like. A computer in the in-bank system 101 can acquire the setting information of the condition via a user interface such as a display or an input device, and can transmit the setting information to the management server 100. The management server 100 can change the contents of the condition held as a file or the like based on the setting information transmitted from the computer.

The CPU 200 calculates the share rate of the number of accesses to the Web page for each product field for each bank trading company. The CPU 200 extracts bank counterparties having a share rate of 75% or more for the product field 1 from the calculated result. The CPU 200 acquires the extracted information relating to the bank business partner from the storage device 202 of the management server and outputs it to the in-bank system 101.
FIG. 20 is a diagram illustrating an example of output data. The output data includes the name of the banking company of the access source that satisfies the set conditions, the access rate share rate, the address, the telephone number, the name of the person in charge, and the like.
Further, the CPU 200 can output the number of visitors to the website of the bank partner company, the number of inflows, the average staying time, the bounce rate, etc. as information related to the bank partner company based on the access history information.
By the processing of the present embodiment, the user can acquire various information related to the bank trading company that satisfies the set conditions.

<Embodiment 3>
In the first and second embodiments, the supplier information output system generates output data based on the total number of accesses to the Web site within a certain period. In the present embodiment, the supplier information output system generates output data based on a comparison with the past number of accesses.
The hardware configuration and functional configuration of the management server 100 in this embodiment are the same as those in the first embodiment. Details of the bank system 101 in the present embodiment are the same as those in the first embodiment. Assume that the IP address company name matching system 102 in this embodiment acquires access history information not only from the three companies, Company A, Company B, and Company C, but also from the websites of a large number of bank customers.
For example, the CPU 200 compiles the number of accesses to the websites of each bank partner company in January and February based on the access history information of the bank partner company website acquired from the IP address company name matching system 102. To get. Then, the CPU 200 calculates an increase rate indicating how much the total number of accesses in February has increased from the total number of accesses in January. FIG. 21 shows the calculated rate of increase.

FIG. 21 is a diagram illustrating an example of an access frequency increase rate calculation result. “Company” in the table of FIG. 21 indicates each bank trading company, and “Number of accesses” indicates the total number of accesses to the websites of the corresponding companies in each month. Further, “Rate of increase in access to previous month” in the table of FIG. 21 indicates a rate of increase in the number of accesses compared to the previous month.
For example, it is assumed that the condition that “the rate of increase in the number of accesses to the website from the previous month is 100% or more” is defined. In the example of FIG. 21, the CPU 200 extracts Company A having an access increase rate of 187.5% with respect to the previous month.
The CPU 200 may use a threshold value of the access increase rate such as 100% in the above condition as a value such as an average value, a median value, or a standard deviation of the access increase rate of each company.
CPU200 outputs the information regarding the extracted company. An example of output data is shown in FIG. The output data includes the name of the bank partner company that satisfies the set conditions, the rate of increase in the number of accesses, the address, the telephone number, the name of the person in charge, and the like. Further, the CPU 200 may output an evaluation value of the extracted company instead of the information on the extracted company.

In addition, the CPU 200 may extract the bank trading company under the condition of the top number of companies among which the rate of increase in the number of accesses to the website from the previous month is 100% or more. The CPU 200 calculates the rate of increase in the number of accesses based on the monthly count, but may determine the rate of increase based on the weekly count instead of the monthly count, or based on the semi-annual count. An increase rate may be calculated | required and an increase rate may be calculated | required based on the total for every other period.
With the processing of this embodiment, the management server 100 can output information related to access history information acquired from the IP address company name matching system 102 in consideration of time-series variations. For example, the user can determine that the credit risk is low when the rate of increase in the number of access histories from the previous month is higher than a threshold.

<Embodiment 4>
In the present embodiment, a more specific usage situation for the processes of the first to third embodiments will be described.
The hardware configuration and functional configuration of the management server 100 in this embodiment are the same as those in the first embodiment. Details of the bank system 101 in the present embodiment are the same as those in the first embodiment. Assume that the IP address company name matching system 102 in this embodiment acquires access history information not only from the three companies, Company A, Company B, and Company C, but also from the websites of a large number of bank customers.
Below, the process of this embodiment is demonstrated.

[Customer information output processing for credit management purposes]
“Company A, Company B, Company C is aggregated with various information such as the number of visitors in the most recent month, and the average stay time is calculated to extract Company A, Company B, Company C”. A case will be described. The CPU 200 aggregates various information such as the number of visitors for each company A, company B, and company C over the most recent month, calculates the average stay time, etc., and outputs the results of the aggregation and calculation to the in-bank system 101 To do. The output data is shown in FIG. Based on the access history information acquired from the IP address company name matching system 102, the CPU 200 aggregates various information such as the number of visitors for each bank partner company based on the set conditions, and calculates the average stay time, etc. Is calculated.
FIG. 23 is a diagram illustrating an example of output data. The output data of FIG. 23 includes the number of visiting companies, the number of visitors, the number of PV, the number of inflows, the average stay time, the bounce rate, the CIF number, and the like.
CPU200 can extract the company which satisfy | fills conditions regarding the frequency | count of inflow, average stay time, bounce rate, etc. by calculating | requiring the frequency | count of inflow, average stay time, bounce rate etc.

In addition, a case where the condition “extract Company A, Company B, Company C in April, May, and June” is set will be described. The CPU 200 totals the number of accesses for each of Company A, Company B, and Company C in April, May, and June, calculates the average and standard deviation, and outputs the results of the aggregation and calculation to the in-bank system 101. . The CPU 200 also outputs an evaluation value for each bank customer. Further, the CPU 200 may output the rate of increase in the number of accesses compared to the previous month. The output data is shown in the table of FIG.
FIG. 24 is a diagram illustrating an example of output data. The table of FIG. 24 includes the number of visiting companies, the number of visitors, the number of PV, the cumulative total, the average, the standard deviation, the rank, and the like. RANK is a value indicating the ranking of the cumulative number of visits. Based on the data shown in FIG. 24, time series analysis or the like is possible.
As an example of time series analysis, the CPU 200, for example, is a company whose performance is strong and whose credit risk is low based on the output data of FIG. May be extracted as For example, in the example of the output data shown in FIG. 24, when “the access increase rate has increased by 100% or more for two consecutive months” is set in advance as a condition for a company with a low credit risk, the CPU 200 Company A is extracted as a low-risk company. On the contrary, as a condition of a company with a high credit risk, for example, when “the number of accesses has decreased by 100 or more for two consecutive months” is set in advance, the CPU 200 sets company B as a company with a high credit risk. Will be extracted.
Further, the CPU 200 may set, as a condition, up to how many companies are subject to extraction based on a user operation on the operation unit or the like of the management server 100. In addition, the CPU 200 may perform the same analysis on the access history of the page for each product, and may extract a company that satisfies a predetermined condition as a loan target company for business expansion for the purpose of sales support.

[Business partner information output processing for business matching purposes]
A case will be described in which a condition is set that “the result of performing the aggregation of the number of accesses to the Web site in one month for each access source for Company A and the extraction of Company A”. The CPU 200 totals the number of accesses of the company A in one month for each access source, calculates an average, a standard deviation, and the like, and outputs the totalization and calculation results to the in-bank system 101. The output data is shown in the table of FIG.
FIG. 25 is a diagram illustrating an example of output data. The output data in FIG. 25 includes the number of visitors, the number of PV, the number of inflows, the average stay time, the bounce rate, the CIF number, and the like.
The user can grasp that company a has accessed the website of company A most frequently.

Next, the user instructs the management server 100 to set a condition that “the number of accesses to the website in April, May, and June is aggregated for each access source and all bank trading companies are extracted”. Then, the user instructs the management server 100 to perform extraction under the above conditions.
The CPU 200 aggregates the number of accesses to the website in April, May, and June for all bank customers, acquires information about bank customers and the evaluation value of the access source, Output to in-bank system 101. The method for obtaining information related to the bank partner company is the same as that in the second embodiment, and the method for obtaining the evaluation value of the access source is the same as that in the first embodiment. The output data is shown in FIG.

  FIG. 26 is a diagram illustrating an example of output data. The output data in FIG. 26 includes the number of PV, the cumulative total, the average, the standard deviation, the rank, and the like. The user verifies the transition of the number of accesses in April to June with reference to FIG. 26 for the company a that visited the website of company A most frequently from the data of FIG. In the example of FIG. 26, since the number of accesses of company a has increased for two consecutive months, the user can grasp that company a is interested in company A. The user can make proposals such as introducing company a to company A and proposing collaboration.

[Business partner information output processing for sales promotion purposes]
The management server 100 can acquire from the access history information what kind of keyword has been used for a visit when a visitor accesses the website. Therefore, the management server 100 can perform supplier information output processing based on the search keyword.
A case will be described in which the condition “the number of accesses to the website of Company A in April, May, and June is tabulated for each keyword and Company A is extracted” is set.
The CPU 200 counts the number of accesses to the website of Company A in April, May, and June for each keyword and outputs it to the in-bank system 101. The output data is shown in FIG.

FIG. 27 is an example of output data. The output data in FIG. 27 shows the monthly transition of the number of accesses for each search keyword.
By referring to the output data in FIG. 27, the user can grasp that the number of searches for the product name X and the number of searches for the keyword XX related to the product X are increasing for the product X of company A. The user captures that Company A's product X is highly evaluated in the market.
When the number of searches by the keyword XX has increased by 50% or more for two consecutive months, the CPU 200 may attach an evaluation value indicating that the product X is highly evaluated in the market to the output.
Further, for example, the CPU 200 may acquire the number of accesses of the keyword XXX other than the keyword XX as a keyword related to the product X, and sum up and output the increase rate of the number of searches as the entire keyword related to the product X. . Further, the CPU 200 outputs an evaluation value indicating that the product X of the company A is highly evaluated in the market when, for example, the increase rate satisfies a set condition such as an increase of 50% or more for three consecutive months. You may make it attach to.

Further, the CPU 200 has, for example, a bank transaction having a product that has been highly evaluated in the market by comparing with the access history of the site of another bank trading company that handles products in the same field as the product X. You may extract the company.
Further, the CPU 200 generates output data based on “the number of accesses for each introduction page of the products a1, a2,...” In the examples shown in FIGS. The output data may be generated based on the “number of accesses”.
For example, when the table of FIG. 14 is replaced with the table of FIG. 30, the CPU 200 calculates the share rate of the number of accesses by each product-related keyword for each of the same product fields for Company A, Company B, and Company C. Will get the result. The related keyword may be one keyword, a plurality of keywords, or all related keywords.
Further, the CPU 200 may generate output data based on both the number of accesses for each Web page and the number of accesses for each related keyword. That is, the CPU 200 can generate output data based on at least one of the number of accesses for each Web page, the number of accesses for each related keyword, and the like.
For example, a user such as a financial institution sales person or a person in charge of financing can grasp a product that is highly interested in the market by referring to the output data. As a result, the user can conduct business to increase the loan amount for the bank trading company that manufactures and sells the product, and can increase the credit rating possessed inside the financial institution. . In addition, the user sells output data serving as a material for determining business matching by instructing the management server 100 to extract a company accessing the website of a bank partner company that manufactures and sells the product. Can do.

<Embodiment 5>
The supplier information output systems of the first to fourth embodiments include the management server 100 and the IP address company name matching system 102 separately. However, in this embodiment, the management server 100 has the functions of the management server 100 and the IP address company name matching system 102 in the first embodiment. Therefore, the supplier information output system in the present embodiment has a format that does not include the IP address company name matching system 102.
FIG. 28 is a diagram illustrating an example of a system configuration of the supplier information output system. FIG. 28 shows the system configuration of the supplier information output system in this embodiment. The system configuration of FIG. 28 differs from the system configuration of FIG. 1 in that there is no IP address company name matching system 102 and that the management server 100 obtains access history information directly from the Web sites 106-108. Other configurations and details of the system configuration in FIG. 28 are the same as those in FIG.

The management server 100 acquires access history information from the websites 106 to 108, and outputs information related to the bank business partner based on the access history information. In addition, the management server 100 outputs information on the bank trading company to the in-bank system 101. In the present embodiment, it is assumed that the management server 100 is configured by a single server device.
The management server 100 acquires access source cookie information from the Web sites 106 to 108 as access history information. The management server 100 identifies a company that has accessed the website corresponding to the access history information based on the IP address of the acquired access history information.
The hardware configuration of the management server 100 in this embodiment is the same as that in FIG.
FIG. 29 is a diagram illustrating an example of a functional configuration of the management server 100. The functional configuration of the management server in this embodiment is different from the functional configuration of FIG. 3 in that an access history information acquisition unit 1900 is included.
The access history information acquisition unit 1900 acquires access history information from the websites 106 to 108.

About the process of this embodiment, it is the same as that of Embodiment 1-4.
With the system configuration of the present embodiment, the system installer does not have to prepare the IP address company name matching system 102 separately. For example, compared with the case where the mechanism of the IP address company name matching system 102 is outsourced to other companies. Spending can be reduced.

<Other embodiments>
In the first to fifth embodiments, the supplier information output system outputs to the in-bank system 101. However, the supplier information output system may output to the printing apparatus, may be output by sending output data to the outside as an email, or may be output by being displayed on the display unit. Good.
In the first embodiment, it is assumed that there are three bank partner companies: Company A, Company B, and Company C. However, the number of bank customers is not limited to three, and may be more or less than three.
In the first to fourth embodiments, the management server 100 is configured by a single server device, but may be configured by a plurality of server devices.

In the first to fourth embodiments, the management server 100 performs real-time processing that executes processing every time a website of a bank business partner is accessed. However, the management server 100 may execute the process at a set time instead of executing the process every time the website of the bank business partner is accessed, or in response to a request from the in-bank system 101. Processing may be executed accordingly. The management server 100 may execute the process every time a set number of access history information is acquired.
In the first to fourth embodiments, in the supplier information output process for credit management purposes, the CPU 200 outputs information related to the bank supplier company that satisfies the set condition. The conditions are as follows: “Extracting bank customers with 5000 or more accesses from the top two companies accessing the website in the last 30 days” and other bank customers This is a condition regarding relevance and the number of accesses. However, the CPU 200 may perform the extraction of the bank partner company under the conditions regarding the period and the number of accesses, such as “extract bank partner companies having access count of 5000 or more in the last 30 days”. In addition, the CPU 200 determines whether the banking conditions are related to the period, the relationship with other banking companies, and the conditions such as “Extract the banking companies with the lowest two websites in the last 30 days”. You may extract a business partner.

In the first to fourth embodiments, the credit risk evaluation value table 900 and the interest level evaluation value table 1200 hold evaluation values corresponding to the number of accesses for 30 days. However, the credit risk evaluation value table 900 and the interest level evaluation value table 1200 may hold evaluation values corresponding to the number of accesses in various periods such as one week, one month, and half a year. The management server 100 refers to the credit risk evaluation value table 900 and the interest level evaluation value table 1200 corresponding to the period indicated by the set condition.
In the first embodiment, the management server 100 outputs an evaluation value obtained by referring to the credit risk evaluation value table 900, the interest degree evaluation value table 1200, the popularity degree evaluation value table 1700, and the like as a result of the evaluation information calculation process. Then. However, the management server 100 may output a binarized signal indicating whether a set condition is satisfied instead of the evaluation value. For example, the management server 100 may output 1 when the condition is satisfied, and output 0 when the condition is not satisfied.

In the first to fourth embodiments, a threshold (5000 times) related to the number of accesses in a set condition (for example, “the number of accesses in the last 30 days is 5000 times or more”) is set in advance, or the in-bank system 101 is set. It is assumed that it is set via However, the CPU 200 may calculate the threshold based on the number of accesses to the websites of the respective bank customers. For example, the CPU 200 may calculate an average value, a median value, a standard deviation, and the like of the number of accesses to the websites of each banking company as the threshold value.
In the first to fourth embodiments, in the business partner information output process for business promotion purposes, the CPU 200 performs the business partner information output process based on the number of accesses to the Web page for each product of the bank business partner company. However, the CPU 200 may perform the supplier information output process based on the name of the company that visits the Web page of the bank supplier company, the inflow medium, the inflow keyword, and the like. In addition, the CPU 200 outputs the customer information output process based on the comparison result between the number of accesses to the Web page for each product of the current bank customer company and the number of accesses to the Web page for each product of the past bank customer company. May be performed.
The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific embodiments, and various modifications can be made within the scope of the gist of the present invention described in the claims. Deformation / change is possible.

100 management server, 101 bank system, 102 IP address company name matching system, 200 CPU

Claims (14)

Extraction means for extracting a supplier company that satisfies the first condition set from the plurality of supplier companies based on the access history information of the websites of the plurality of supplier companies;
Output means for outputting information on the supplier company extracted by the extraction means;
I have a,
The extraction means totals the number of accesses to the websites of the plurality of business partners for a set period included in the access history information for each company of the access source, and for each company of the access source that has been tabulated A server device that extracts a supplier company that satisfies the first condition based on the number of accesses to a supplier company's Web site . The extraction means sets a second number of accesses to a website of a supplier company for each of the access source companies out of the plurality of supplier companies based on the access history information . 2. The server apparatus according to claim 1, wherein a client company that satisfies the condition and satisfies the first condition, which is a condition that an access source company is a client company, is extracted. Extraction means for extracting a supplier company that satisfies the first condition set from the plurality of supplier companies based on the access history information of the websites of the plurality of supplier companies;
Output means for outputting information on the supplier company extracted by the extraction means;
Have
The extraction means includes at least one of the number of accesses to the Web page for each product of the plurality of partner companies and the number of accesses for each search keyword included in the access history information as a supplier. A supplier company that satisfies the first condition on the basis of the number of accesses to the Web page for each product of the company or the number of accesses for each search keyword. Server device to extract . Based on at least one of the number of accesses to the web page for each product of the aggregated supplier company and the number of accesses for each search keyword, the extraction means determines the product of each supplier company in the same type of product field. to the total number of accesses to the Web site, determine the ratio of the number of accesses to the Web site of the products in each business partners, on the basis of the ratio, according to claim 3 for extracting the first condition is satisfied business partners The server apparatus of description. The extraction means, the first condition is satisfied suppliers extracts the enterprise claims 1 to 4 server apparatus according to any one that has been set with respect to a reference value obtained based on the access history information. The extraction means, when on the basis of transition of the sequence of access history to the Web site of the plurality of client companies, the first condition is satisfied suppliers extracts the enterprise claims 1 to 4 any one of claims Server device. It further has an acquisition means for acquiring access history information of websites of a plurality of business partners,
Said extraction means, based on said access history information acquired by the acquisition unit, in any one of claims 1 to 6 to extract the first condition is satisfied business partners from the plurality of business partners 1 The server device according to item. The server device according to claim 7 , wherein the acquisition unit acquires the access history information including a company code that identifies a company that has visited the Web site . Extraction means for extracting a supplier company that satisfies the first condition set from the plurality of supplier companies based on the access history information of the websites of the plurality of supplier companies;
Output means for outputting information on the supplier company extracted by the extraction means;
Have
The extraction means totals the number of accesses to the websites of the plurality of business partners for a set period included in the access history information for each company of the access source, and for each company of the access source that has been tabulated A system for extracting a supplier company that satisfies the first condition based on the number of accesses to the Web site of the supplier company. Extraction means for extracting a supplier company that satisfies the first condition set from the plurality of supplier companies based on the access history information of the websites of the plurality of supplier companies;
Output means for outputting information on the supplier company extracted by the extraction means;
Have
The extraction means includes at least one of the number of accesses to the Web page for each product of the plurality of partner companies and the number of accesses for each search keyword included in the access history information as a supplier. A system that aggregates each product of a company and extracts a partner company that satisfies the first condition based on the number of accesses to the Web page for each product of the partner company. Obtaining means for obtaining access history information of websites of a plurality of business partners;
Conversion means for converting an IP address included in the access history information acquired by the acquisition means into a corresponding company name based on correspondence information between an IP address and a company name;
Further comprising
The extraction unit extracts a supplier company that satisfies the first condition from the plurality of supplier companies based on the access history information in which the IP address is converted into the company name by the conversion unit. The system according to claim 9 or 10. An information processing method executed by a server device,
An extraction step of extracting a business partner company that satisfies the first condition set from the plurality of business partners based on the access history information of the websites of the business partners;
An output step of outputting information on the supplier company extracted in the extraction step;
Including
In the extraction step, the number of accesses to the websites of the plurality of business partners in the set period included in the access history information is totaled for each source company, and the total number for each source company An information processing method for extracting a business partner company that satisfies the first condition based on the number of accesses to a business site of a business partner company. An information processing method executed by a server device,
An extraction step of extracting a business partner company that satisfies the first condition set from the plurality of business partners based on the access history information of the websites of the business partners;
An output step of outputting information on the supplier company extracted in the extraction step;
Including
In the extracting step, at least one of the number of accesses to the Web page for each product of the plurality of business partners and the number of accesses for each search keyword included in the access history information is set as a business partner. A supplier company that satisfies the first condition on the basis of the number of accesses to the Web page for each product of the company or the number of accesses for each search keyword. Information processing method for extracting The program for functioning a computer as each means of the server apparatus in any one of Claims 1 thru | or 8.

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