JP2018173821A - Point assigning system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a service menu for promoting motivation of use of points given to purchase activities of customers.
A point database for storing the type of information provided by a customer who owns a plant and the amount of points given in accordance with the provision of information from the customer, and a plurality of service menus according to the number of points are registered. A service menu database, a customer point database in which information on the number of points acquired and held by the customer and the usage history of the points is registered, a point exercise frequency analysis unit for extracting the usage frequency of customer points registered in the customer point database, A point granting system comprising a guidance information output unit for outputting guide information regarding changes in the number of points corresponding to the type of information provision from the customer or the number of points corresponding to the service menu based on the analysis result of the point exercise frequency analysis unit by.
[Selection] Figure 1

Description

The present invention relates to a point grant system that gives points to information provided by a customer and provides a use environment of the points effective for the customer.

  For example, those disclosed in Patent Documents 1 to 5 are known as management systems for points given to purchase activities of customers.

  By using the system, a customer who has points can exercise points at any timing after acquiring points. Here, the points are exercised in a format selected by various users from a service menu prepared in advance by the service provider.

JP2005-332296 JP2003-044733 JP2003-271764 JP2001-005881 JP2014-115736

  When operating the point management system as described above, if the frequency of exercising points is low at the customer, that is, if the turnover rate of the granted points is low, the motivation for exercising points is insufficient for the customer It is expected to be.

  In this case, unless a device for increasing the turnover rate of points is used, there is a possibility that the customer's purchasing activity is affected and the motivation of the purchasing activity is also reduced. Therefore, in order to increase the point rotation rate, a device such as increasing the type of service menu or increasing the point exchange rate is required. In this case, it is necessary to obtain information serving as a trigger for reviewing what kind of service menu the customer desires.

  An object of this invention is to provide the point grant system which provides a customer with the service menu effective in motivating utilization of the point provided to the purchase activity of the customer who owns a plant.

In order to solve the above-mentioned problems, the present invention relates to a point granting system, which is a type of information provided from a customer who owns a plant, and an amount of points given in accordance with the provision of information from the customer. , A point database for storing, a service menu database in which a plurality of service menus according to the number of points are registered, and a customer point in which information on the number of points acquired and held by the customer and usage history of the points is registered Corresponding to the type of information provided from the customer based on the analysis result of the database, the point exercise frequency analysis unit that extracts the usage frequency of the customer's points registered in the customer point database, and the point exercise frequency analysis unit Change of the number of points or points corresponding to the service menu And guidance information output unit for outputting the guide information about,
It is provided with.

  ADVANTAGE OF THE INVENTION According to this invention, the service menu effective in motivating utilization of the point provided to the purchase activity of the customer who owns a plant can be provided to a customer.

It is a system configuration figure showing an embodiment of a point grant system concerning the present invention. It is a functional block diagram which shows the function structure of the guidance system contained in the said point provision system. It is a functional block diagram which shows another functional structure of the guidance system contained in the said point provision system. It is a functional block diagram which shows the function structure of the point exercise frequency analysis system contained in the said point grant system. It is a system configuration figure showing another embodiment of the point grant system concerning the present invention. It is a system configuration figure showing another embodiment of the point grant system concerning the present invention.

  Hereinafter, embodiments of the point granting system according to the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating an overall configuration of a point granting system 1 according to the present embodiment. The point granting system 1 is capable of acquiring guidance information that triggers a change in the “service menu for point use” presented to the customer according to the frequency (rotation rate) of point exercise by the plant user. It has features.

  As shown in FIG. 1, the point granting system 1 includes a point exercise frequency analysis system 10, a guidance system 20, a customer point DB (database) 30, a service menu DB 40, a point DB 50, and a point exercise information registration / analysis system. 60 and an output system 70. Each of the plurality of systems and the plurality of DBs constituting the point grant system 1 implements the functions described below in a computer. That is, the point grant system 1 has each function realized by a point grant program executed on one or a plurality of computers. The computer constituting the point grant system 1 has a minimum configuration of a CPU, a ROM for storing a program executed by the CPU, and a RAM serving as a work area used when executing the program by the CPU. An input means for inputting information from the network, an output means for outputting information to the outside, and an interface for exchanging information with an external device, another computer, or a DB via a communication line .

[Outline of Point Exercise Frequency Analysis System 10]
The point exercise frequency analysis system 10 constitutes a point exercise frequency analysis unit that extracts the usage frequency of customer points from the customer point DB 30. The point exercising frequency analysis system 10 analyzes the point rotation rate determined by the comparison between the point assignment and the exercising of each customer based on the data read from the customer point DB 30. For example, data is analyzed so that a result such as “the point exercise speed of customer A is 1000 points / month” is obtained. In addition, the point exercise frequency analysis system 10 analyzes the points given for the product purchase and the points given for the information provision separately. As a result, it is possible to obtain information close to the actual flow of funds from the analysis of only points for product purchase. Moreover, if the point exchange rate according to the profit rate for each product is set based on this analysis, the profit rate can be predicted.

[Guidance system 20]
Based on the analysis result of the point exercise frequency analysis system 10, the guidance system 20 outputs guidance information regarding the number of points corresponding to the type of information provision from the customer, the number of points corresponding to the service menu, and guide information regarding these changes. An information output unit is configured.

  The guidance system 20 receives the analysis result data output from the point exercise frequency analysis system 10 and outputs guidance information related to the improvement of the operation of the point granting system 1. Here, the “guidance information” is information including a point exchange rate change plan and a service menu change plan.

  “Analysis result data” from the point exercise frequency analysis system 10 input to the guidance system 20 indicates “contents to be improved” regarding the point exercise menu in the point granting system 1. The “contents to be improved” includes, for example, data indicating a point exchange rate change proposal, a service menu new / removal proposal, a service proposal for a specific customer, and the like.

  The guidance system 20 outputs guidance information as an improvement plan based on input results of “analysis result data” output from the point exercise frequency analysis system 10, for example, “point rotation rate data” and “content to be improved”. . The output guidance information is recorded in the service menu DB 40 and the point DB 50.

[Outline of Customer Point DB 30]
The customer point DB 30 is a database that records and accumulates the points and usage history for each customer in a state that can be identified for each customer. In the customer point DB 30, all data related to point grant and use is recorded and stored in a state that can be identified for each customer.

[Outline of Service Menu DB 40]
The service menu DB 40 stores the amount of points required for each type of service menu included in the guidance information output from the guidance system 20 (the amount of points necessary for exercising points).

[Overview of Point DB 50]
The point DB 50 accumulates the point exchange rate for each product and the point exchange rate for each information included in the guidance information output from the guidance system 20.

[Outline of Point Exercise Information Registration Analysis System 60]
The point exercise information registration / analysis system 60 receives information on points given by the business operator for each customer, and accumulates the information in the customer point DB 30. Further, the point exercise information registration / analysis system 60 receives information on points exercised by the customer against the business operator, and accumulates a point usage history for each customer. The point exercise information registration / analysis system 60 analyzes the breakdown of point grant and exercise.

[Outline of output system 70]
The information stored in the service menu DB 40 and the point DB 50 is read out, the information regarding the type of the service menu and the point exchange rate, the information about the point grant target product, the type of information and the point exchange rate, and the state that can be confirmed by the customer Form.

[About point grant according to the present invention]
Hereinafter, “point grant” according to the present invention will be described, and functions and effects of the point grant system 1 according to the present embodiment will also be described. In an actual business environment to which the point granting system 1 can be applied, “point grant” means that when a business sells a product or provides a service to a customer and the price is paid, the business provides the customer with the customer. On the other hand, it is performed according to the type of product or service purchased by the customer, the number of purchases, and the purchase price.

  The point granting according to the present invention is not limited to the “purchasing activity” as described above, and is performed, for example, for “providing useful information” from a customer (hereinafter simply referred to as “information provision”). Is called. In this respect, it is different from general point grant. Here, for example, “providing information on the operation rate / failure rate of products sold by a business to a customer”, “providing information provided by a business other than the business to the customer” "Providing information on the operation rate / failure rate of similar products", "Providing information on customer inventory status regarding replacement parts used for repair / maintenance of the product", "Region and industry to which the customer belongs (chemical industry / steel industry / Automotive industry / independent power generation company / mobile phone telecommunications industry / other service industries, etc.) Supply / demand information of products and share information compared to similar products of other companies "," Provide information about product reputation "," Similar to products " "Providing information on product price comparisons", "Providing information on performance comparison of products and similar products", "Products and maintainers of companies in employees belonging to customer companies" "Providing information on the number of engineers / capabilities / specialized fields", "Providing information on the political / economic information of the region to which the customer belongs", "Management information of client companies / Medium-term management plan / Medium-term investment plan" "Providing information about customer-specific improvement cases related to products", "Providing information related to the situation in the region and industry to which the customer belongs in relation to securing engineers / workers involved in product installation / construction", etc. Is included. In the environment where the point granting system 1 according to the present invention is operated, points are given to the customer from the business operator according to the importance of each information.

  The business operator prepares a service menu that can be received by exercising points to the customer. In the service menu, the number of points that need to be exercised for receiving the service is presented for each menu. As a general rule, customers can receive services by exercising points within the total points they have.

  As an exception, you may be able to receive a service that exceeds the total points you have. In this case, since the customer will be liable to the business operator, a separate action is required such that the customer enters into a contract to purchase a certain amount of goods within a certain period.

  The service menu may include some or all of the products, or may be completely different. Examples of service menus that are different from products include: “Menu for repairing and repairing products held by customers and presentation of availability information for engineers who perform maintenance”, “Technical staff dispatched in preference to others” Menu related to the granting of rights that can be obtained "," menu related to obtaining the optimal driving conditions based on the results of output and analysis of driving information of products held by customers ", and" rights to receive remote monitoring technology preferentially " Menu ”,“ Menu for service that predicts how much the performance will change when the customer modifies / uses the product for modification / use of the customer's product ”,“ Simulation based on natural science ”,“ The right to purchase / advance prior use of new products prior to official release (Payment may or may not occur separately) Menu, guidance menu for contents that can be handled by the customer by himself / herself regarding the maintenance of the product and repair of the product, a menu regarding the express priority for every response of the operator, and the maintenance and repair of the product. In the case where the customer does not have the inventory of the spare parts corresponding to this, the menu relating to the inventory status of the spare parts and the information on the owner is included. Spare parts necessary for maintenance are often owned by business operators, but may be held by other customers or manufacturers of the spare parts.

  Desirable as corporate economic activities are "a lot of sales and a high profit margin", "a lot of sales and an increase in profit margin", and "a lot of sales and a small fluctuation in profit margin". Moreover, it is preferable that the funds circulate at an appropriate speed without stagnation in one place. Therefore, by measuring the turnover rate (exercise speed) of points, it is possible to judge the quality of economic activities including companies. If the economic activity is good, the point turnover rate should be fast.

  In actual economic activities, funds flow to various places. Funds supplied by a company do not always return to the same company. It is impossible to accurately measure the flow of funds. On the other hand, according to the point grant system 1 according to the present embodiment, the points supplied from the operator are limited to either the point flow stagnation or the return to the operator due to the customer holding. The measurement accuracy when measuring the economic situation is better for the point granting system 1 than for the actual economic activity.

  Next, a detailed configuration of the guidance system 20 included in the point granting system 1 will be described with reference to FIG. As shown in FIG. 2, the guidance system 20 includes a model verification unit 21 and a guidance information generation unit 22.

  The model verification unit 21 realizes a function of predicting the point rotation rate by numerical analysis and correcting the model program so that the predicted value matches the actual value. Specifically, a process for correcting the economic model used in the numerical analysis to match the actual situation is executed. The economic model is stored in the economic model DB, and is referred to via the economic model reference unit 2102.

  The guidance information generation unit 22 predicts the future point rotation rate using the analysis program corrected by the model verification unit 21. At this time, the calculation condition such as the point exchange rate for each service menu is changed, and the influence (sensitivity) of the change in the calculation condition on the point rotation rate is analyzed. This calculation is repeated, and a guidance result is output as to what conditions should be set in order for the point rotation rate predicted value of the analysis result to exceed the desired value.

  The model verification unit 21 includes a model construction numerical analysis unit 2101, an economic model DB 2102, and a model comparison verification unit 2103.

  The model construction numerical analysis unit 2101 uses actual business environment customer information, other company information, economic trends, product content and point exchange rate, service menu content and point exchange rate as environmental conditions and analysis parameters for numerical analysis. These analysis parameters correspond to boundary conditions and initial conditions in natural science simulation. That is, the model construction numerical analysis unit 2101 refers to the economic model DB 2102 with the input analysis parameter as an initial condition, and numerically analyzes the time change of each customer's economic trend. In addition, based on the numerical analysis result, when the customer's action related to the grant / exercise of points occurs, the points are transferred from the business operator to the customer or from the customer to the business operator.

  The economic model DB 2102 stores various data related to the economic model referred to by the model construction numerical analysis unit 2101.

  The model comparison / verification unit 2103 executes a process of comparing the analysis result in the model construction numerical analysis unit 2101 and the point exercise result input from the point exercise frequency analysis system 10. As a result of the comparison processing in the model comparison verification unit 2103, if the difference between the analysis result and the actual result is equal to or less than a predetermined value, the analysis result is considered to withstand use in the actual business. On the other hand, when the deviation is large, the analysis program needs to be corrected. Here, the most common cause of the deviation is that the used economic model becomes old and there is an inaccurate part.

  The laws of economics change from time to time, unlike that of natural science, so it is necessary to constantly update the model. Therefore, the contents of the economic model DB 2102 are updated so that the analysis result can reproduce the actual result. Also, the analysis logic (analysis program) in the guidance numerical value analysis unit 2201 is updated.

  The guidance information generation unit 22 will be described. The guidance information generation unit 22 includes a guidance numerical value analysis unit 2201, a sensitivity analysis unit 2202, and an effect comparison verification unit 2203.

  The guidance numerical value analysis unit 2201 executes analysis processing for future prediction. In the analysis processing, first, management environment customer information, other company information, economic trends, product content and point exchange rate, service menu content and point exchange rate, etc. are input as analysis parameters. The analysis parameter input here is not necessarily an actual value. For example, when it is desired to change the future point exchange rate, a desired condition such as a future planned value may be used as the point exchange rate instead of the current value.

  The purpose of using the guidance system 20 is to predict the degree of influence on the whole when a specific situation occurs, or to set an initial condition to be set at the present time when a specific result is desired to be generated. There is to choose.

  In these cases, the guidance numerical value analysis unit 2201 executes calculation processing a plurality of times while changing the initial conditions and the like, and the analysis result comparison unit 2203 compares the analysis result as the calculation result. Therefore, the guidance numerical value analysis unit 2201 executes the calculation by determining how many times the calculation should be performed with which combination of initial conditions and using what economic model according to the contents of the analysis parameter.

  The sensitivity analysis unit 2202 analyzes how much the result of the specific economic activity is affected by the change of the specific initial condition based on the calculation result data input from the guidance numerical value analysis unit 2201. For example, when the point exchange rate of a specific service menu is changed, it is analyzed which type of information provision is most likely to change in relation to information provision from a customer.

  The effect comparison / verification unit 2203 executes processing for determining whether the analysis result in the sensitivity analysis unit 2202 satisfies a desired value. Here, when the request is satisfied, the guide information is output as the final result. If the request is not satisfied, the result is input to the guidance numerical value analysis unit 2201 and the calculation is executed again.

  Next, a detailed configuration of the point exercise frequency analysis system 10 included in the point granting system 1 will be described. FIG. 3 is a diagram illustrating the point assignment content analysis unit 2110 included in the point exercise frequency analysis system 10. As shown in FIG. 3, the point grant content analysis unit 2110 includes a consumption rate analysis unit 2111, a consumption content analysis unit 2112, a point grant amount analysis unit 2113, a model comparison verification unit 2115, a model correction / influence factor sensitivity correction unit 2116, Have The point grant content analysis unit 2110 realizes a function of numerically analyzing economic activity until a customer receives points through product purchase / information provision.

  The consumption speed analysis unit 2111 is a mathematical model of external economic trends, factors of other companies in the same industry, management conditions of the target company, environmental factors surrounding the target company, macroeconomic models, and empirical rules as input parameters. Execute processing to analyze the total consumption rate by industry and industry. In addition, the consumption rate analysis unit 2111 executes a process of analyzing the total consumption rate (not for each customer) regarding the product and service fields in which the business operator is involved. In addition, the consumption rate analysis unit 2111 executes processing for analyzing the total consumption amount for each specific customer.

  Here, the mathematical model of the external economic trend used in the consumption rate analysis unit 2111 includes a mathematical model of world economy / country or regional economy / intra-industry economy. In addition, the mathematical model of factors of other companies in the same industry includes a mathematical model of product composition and competitiveness, sales profit margin and its change over time, and sales performance by region. In addition, the mathematical model of the management situation of the target company includes a mathematical model of the overall balance, the power generation department balance, and the medium-term management policy. In addition, the mathematical model of the environmental factors surrounding the target company includes a mathematical model of the state of the used plant, the number of years of the used plant, the repair history of the used plant, the business type and personnel composition of the target company, and regional characteristics.

  The forecast here is mainly the overall economic trend. Even if an operator has a good product, if the overall economic activity is inactive, the product cannot be sold. Therefore, the conditions of input parameters to the consumption rate analysis unit 2111 are mainly related to overall trends / policies, such as global / regional economic trends, business trends by industry, customer management status and management policies, etc. It is.

  The consumption content analysis unit 2112 executes processing for analyzing the breakdown of consumption. The consumption content analysis unit 2112 analyzes the ratio of the consumption amount of a specific customer and the consumption rate of a specific product to the whole. The consumption content analysis unit 2112 takes as input parameters a mathematical model of the consumption content influencing factors, an economic model, and the experience side. The input parameter in the consumption content analysis unit 2112 is set as an input condition that represents a difference in competitiveness of each product, an individual situation for each customer who uses the product, and the like.

  The input conditions include, for example, the price difference / performance difference of the product compared to other companies in the same industry (when the overall economic activity is inactive, only the most competitive product can be sold), used by the customer The situation of the products (degradation level, age, etc.), the industry and personnel composition of the target company (if the customer has a small number of technicians who can handle the product, the dependence on the company in product maintenance increases. ), Business balance of customers (when the business unit dealing with the product has a good balance, investment related to the product is likely to increase).

  Further, the experience side includes data in which the breakdown of investment is predicted from past results for each customer, and data in which the failure probability is predicted from the elapsed years of the plant used.

  The point grant amount analysis unit 2113 adjusts the exchange rate for each product point to the consumption rate for each customer and each product obtained by combining the analysis result of the consumption rate analysis unit 2111 and the analysis result of the consumption content analysis unit 2112. The process which outputs another point provision amount predicted value is performed.

  The model comparison verification unit 2115 executes a process of comparing the product-specific point grant amount predicted value with the product-specific point grant amount actual value. As a result of this comparison processing, when the discrepancy between the product point grant amount predicted value and the product point grant amount actual value is large, the model correction / influence factor sensitivity correction unit 2116 is instructed to correct the model contents.

  The model correction / influencing factor sensitivity correction unit 2116 corrects the contents of the model according to an instruction from the model comparison verification unit 2115.

  Next, of the detailed configuration of the point exercise frequency analysis system 10 included in the point granting system 1, the point exercise content analysis unit 2120 will be described with reference to FIG. As shown in FIG. 4, the point exercise content analysis unit 2120 includes a point possession amount calculation unit 2121, a service menu exercise behavior prediction unit 2122, a service menu exercise behavior prediction result DB 2123, a model correction / influence factor sensitivity comparison unit 2124, a service menu. It has an exercising action result DB 2125 and a desired item comparison unit 2126. The point exercise content analysis unit 2120 realizes a function of analyzing the point use speed in the point exercise frequency analysis system 10.

  The point possession amount calculation unit 2121 realizes a process of calculating the point possession amount for each customer based on the calculation result of the point grant speed predicted by the point grant content analysis unit 2110. The point possession amount calculation unit 2121 uses the product type / customer point grant amount prediction (actual) value as one of the input parameters.

  In the point holding amount calculation unit 2121, the point grant speed for providing information is not calculated. The point grant speed for providing information is separately calculated and input to the service menu exercise behavior prediction unit 2122. Since there is no money exchange for providing information, the processing result in the point grant content analysis unit 2110 cannot be used as it is. Therefore, the point grant amount prediction (actual) value for each information type / customer is used as a customer behavior prediction model, and this customer behavior prediction model is set as one of the input parameters to the point possession amount calculation unit 2121.

  Here, as a method of giving the point granting speed for information provision, the following can be considered. For example, “adopting actual values”, “statistically predicting past / present / future values based on changes over time in actual values”, “numerical analysis using customer behavior prediction model”, and the like.

  The service menu exercising behavior predicting unit 2122 realizes processing for predicting the customer's point exercising behavior using an economic model. The point exercising behavior predicted by the service menu exercising behavior predicting unit 2122 has many similarities to the behavior of purchasing a product using the currency held by the customer. Therefore, it is possible to make predictions based on economic models. The service menu exercise behavior prediction unit 2122 includes an economic model general rule that includes an investment amount (point usage amount) with respect to the amount of money (points) held, a semi-experience model that includes point use content with respect to point exercise content, etc. Prediction based on an economic model is executed using a statistical model including a future behavior prediction obtained from the point use history. The result predicted by the service menu exercising behavior prediction unit 2122 can be used as follows. For example, “the model is updated by comparing the calculated value and the actual value”, “the point granting system is improved by using the prediction by sensitivity analysis”, and the like.

  The service menu exercise behavior prediction result DB 2123 stores the results predicted by the service menu exercise behavior prediction unit 2122.

  The model correction / influencing factor sensitivity comparison unit 2124 compares the prediction result accumulated in the service menu exercise behavior prediction result DB 2123 with the actual data accumulated in the service menu exercise behavior result DB 2125, and corrects the model and affects the influence factor sensitivity. Whether or not correction is necessary is determined. When it is determined that these corrections are necessary, the model correction / influence factor sensitivity comparison unit 2124 outputs the respective correction contents. Here, if the correction content to be output is related to, for example, “environmental factors surrounding the target company”, the status of the plant used, the age of the plant used, the repair history of the plant used, the industry type and personnel composition of the target company, For example, locality. As for “consumption factor influencing consumption”, the status of the plant used, the age of the plant used, the repair history of the plant used, the industry and personnel composition of the target company, regional characteristics, competitiveness compared to other companies in the same industry, etc.

  The service menu exercising behavior DB 2125 is a database that accumulates the selection results of service menus selected in exercising points by customers.

  The desired item comparison unit 2126 compares the desired item data stored in the service menu exercising behavior prediction result DB 2123 with the desired item target value input from the outside, and outputs the guide information including the optimum exchange rate. Run. The output optimum exchange rate is input to the service menu exercising behavior prediction unit 2122 as a service menu point exchange rate.

  Next, still another example of the point grant system 1 according to the embodiment of the present invention will be described with reference to FIG. First, the already described point grant system 1 is also a point grant target for providing information that does not involve money exchange. However, there are also problems that arise due to the fact that money is not exchanged. Therefore, the point grant system 1a according to the fifth embodiment includes a function that can solve this problem.

  The point is not the currency itself, but may be treated as a pseudo-currency. The exchange of points is not a currency exchange itself, but it is not completely separated from actual accounting. Granting points is considered a debt to the customer, and the point issue balance may be considered a liability. Also, giving points is regarded as a discount for customers, and an amount equivalent to the discount may be deducted from sales. Therefore, if the outstanding point issuance is more than necessary, due to an increase in debt (there is enough reserve to return debt), a decrease in sales (decrease in company size), and a decrease in profit (decrease in corporate performance), It will be a situation where the survival of the company is jeopardized. When a customer gives points for merchandise purchase involving money exchange, there is an upper limit on the customer's economic power, so the point issue balance does not increase indefinitely. However, if points are awarded for information provision without money transfer, there is a possibility that the point issue balance will increase indefinitely.

  Moreover, if the point exchange rate for the information presented to the customer is set lower than that for the product, there will be no debt due to points on the business side. However, if the point exchange rate is set low, it is difficult to collect useful information.

  FIG. 5 is a diagram illustrating a functional configuration of the information value determination system 80 included in the point grant system 1a that can cope with the above-described problem. As shown in FIG. 5, the information value determination system 80 includes a value determination unit 801 and a point exchange rate setting unit 802. After the information is provided, the information value determination system 80 determines the value of the information. If high-value information is provided, bonus points are awarded at a later date according to the value. Bonus point exchange rate is set only once, and it will not be passed on to the same kind of information provision thereafter.

  More specifically, the value judgment unit 801 pays the price among “point grant with payment” and “point grant without payment”, which are distinguished in the point exercise information registration analysis system 60. The data related to the point grant without any is used as input data. The value determination unit 801 executes processing for determining the value of information provision related to input data. Here, the value judgment includes human judgment. The criteria for value judgment in the value judgment unit 801 are based on, for example, “possibility to lead to the latest order”, “future value (new product development information, etc.)”, and the like. By using these as indicators for value judgment and setting judgment criteria for each indicator, the value of the content of information provision is judged.

  The point exchange rate setting unit 802 sets the point exchange rate (one time only) according to the determination result in the value determination unit 801. The point exchange rate setting unit 802 notifies the customer of the result when bonus points are generated.

  The information value judgment system 80 may include human judgments instead of processing all by the computer. For example, on the basis of the evaluation result output from the value determination unit 801, the setting of the exchange rate for the point exchange rate setting unit 802 may not be automatically input, but may be manually input by a human.

  Next, still another example of the point granting system 1 according to the embodiment of the present invention will be described with reference to FIG. In the information value judgment system 80 shown in the fifth embodiment, the point exchange rate for providing information to be presented in advance to the customer is set lower than the exchange rate for products. The data analysis system 900 according to the present embodiment does not always provide points for providing information, but implements a process of setting a period and performing irregularly.

  The menu for the information points and the point exchange rate are presented to the customer in advance. However, the menu is not fixed and changes periodically. In addition, there is a period during which points are not provided for providing information. In the present embodiment, by constantly observing / analyzing the provision information of information points, it is possible to prevent the point issuing balance from increasing infinitely.

  When a lot of high-value information in a specific field is provided, it is advantageous for management policy determination, but the point issuing balance may increase indefinitely. In this case, for providing information in the relevant field, the point granting period is shortened. For areas that are important to businesses or where the number of information provided is small, the point granting period should be extended. In addition, this method makes it easy to obtain information important for management depending on the type of information to be given points and the method for setting the period.

  More specifically, the data analysis system 900 receives from the point exercise information registration / analysis system 60 the information-based point exercise results and the service menu-based exercise results in the data analysis unit 901. The data analysis unit 901 outputs the following relational expression related to the point exercising behavior related to information based on each input result.

(Formula 1) Information type vs. total point rotation rate

(Formula 2) Type of information vs. number of point rotations per service menu

(Formula 3) Type of information vs. point rotation rate for each customer

  Each of the above formulas is used as guidance information for the point exchange rate in the output system 70. Each of the above equations is also used in the customer behavior prediction model used in the point holding amount calculation unit 2121 of the point exercise content analysis unit 2120.

  There is no money exchange for point exercises related to information. Therefore, general economic laws are difficult to apply, and business operators must collect data. In this case, it is easier to clarify the relevance if the number of types of information to be handled is reduced, so that an empirical rule for predicting customer behavior can be obtained quickly.

1: point grant system, 10: point exercise frequency analysis system, 20: guidance system, 21: model verification unit, 22: guidance information generation unit, 60: point exercise information registration analysis system, 70: output system, 80: information value Determination system, 90: Data analysis system, 801: Value determination unit, 802: Point exchange rate setting unit, 901: Data analysis unit, 2101: Model construction numerical analysis unit, 2102: Economic model reference unit, 2103: Model comparison verification unit 2110: Point grant content analysis unit, 2111: Consumption rate analysis unit, 2112: Consumption content analysis unit, 2113: Point grant amount analysis unit, 2115: Model comparison verification unit, 2116: Influence factor sensitivity correction unit, 2120: Point exercise Content analysis unit, 2121: Point holding amount calculation unit, 2122: Sir Scan menu exercise behavior prediction unit, 2124: Effect factor sensitivity comparing section, 2126: hope item comparing unit, 2201: Guidance numerical analysis unit, 2202: Sensitivity analysis unit, 2203: effect comparison verification unit

Claims (5)

A point database for storing the type of information provided by a customer who owns the plant, and the amount of points given in accordance with the provision of information from the customer;
A service menu database in which multiple service menus according to the number of points are registered,
A customer point database in which information related to the number of points acquired and held by the customer and usage history of the points is registered;
A point exercise frequency analysis unit for extracting the use frequency of the customer's points registered in the customer point database;
Based on the analysis result of the point exercise frequency analysis unit, a guidance information output unit that outputs guide information related to a change in the number of points corresponding to the type of information provision from the customer or the number of points corresponding to the service menu;
A point granting system characterized by comprising: The guidance information output unit
A model verification unit for correcting the program so that the predicted value and the actual value of the point rotation rate in the numerical analysis programmed based on the preset economic model match;
Guidance information generation for predicting the point rotation rate using a program modified in the model verification unit, and generating guide information related to the change in the number of points for the predicted value to exceed a desired value based on a prediction result And
The point grant system of Claim 1 provided with. The point exercise frequency analysis unit
Point grant content analysis unit that numerically analyzes economic activity for generating points for providing information from the customer;
A point exercise content analysis unit for analyzing the use speed of the point;
The point granting system according to claim 1, comprising: A value determination unit for determining the value of the information to which the points are given;
A point exchange rate setting unit for setting the number of points related to information provision according to the determination result of the value;
The point grant system as described in any one of Claims 1 thru | or 3 provided with these. Predetermined relationship related to point exercising behavior regarding information based on point exercising results by information and exercising results by service menu input from point exercise information registration analysis unit for registering point grant and point exercise for each customer in the point database The point granting system according to any one of claims 1 to 4, further comprising a data analysis unit that outputs an expression.