WO2018134884A1 - User action encouragement system and user action encouragement method - Google Patents

Abstract

A user action encouragement system has: an action conversion unit for storing user action score information which associates user actions, which include purchase actions which involve purchasing a product or service and also include non-purchase actions which are actions other than the purchase actions, with a score assigned to the user who performed a user action, acquiring information about the user action performed by the user and user identification information for the user, and determining a score to be assigned to the user for the user action by referring to the user action score information; a score totaling unit for calculating score total values by totaling for each user the scores given to the user; and a benefit determination unit for ranking the users on the basis of the score total values, and determining a user to be given a benefit and a benefit to be given to the user on the basis of the ranking. The benefit is given to the user on the basis of the user ranking which is assigned on the basis of the user actions; hence, it is possible to encourage various user actions, because incentives are given not only for purchase actions, but also for non-purchase actions.

Description

User action promotion system and user action promotion method

The present invention relates to a technology for promoting various behaviors including purchasing behavior for purchasing goods or services.

There is a point card system as a mechanism to motivate users to purchase. In the point card system described in Patent Document 1, when a user who owns a point card purchases a product or service, points are given according to the purchase amount. In the point card system described in Patent Document 2, a common point service can be used in a plurality of commercial facilities. This type of point service is common in the market, and many companies and many individuals use the service widely.

Businesses will be partners for point services, and individuals will become members of point services. When a user who has become a member purchases a product or service at a store of a partner company, points corresponding to a certain amount of money (return rate) with respect to the purchase amount are given to the user (point return). In addition, the store here includes various forms such as a virtual store on the Internet in addition to a store that actually exists. The user can use the accumulated points as a part or all of the price when purchasing goods or services at a partner company store.

The partner company can expect the effect of attracting customers using the user's mind that they want to purchase at a store where points are given rather than stores where points are not given when purchasing goods or services. On the other hand, the user can obtain a financial merit that the stored points can be used for purchase of goods or services.

In the point service as described above, the resources for returning points to the user are directly borne by the partner company where the user purchases the product or service. When a user purchases a product or service at a store of a partner company, points are given to the user at the burden of the partner company. The correspondence between the purchase price of a product or service and the points given thereby is determined as a return rate. The monetary value of points is also clearly related. For example, an association is made such that one point corresponds to one yen. Therefore, the merit obtained by the user is the same as receiving a discount according to the return rate.

Although giving points is effective in promoting user actions, since the partner company bears the points and the amount of money associated with each other, the action of the user who gives points is a product. Or it will be limited to the purchasing action of purchasing a service. That is, the point service is promoted only to the purchase behavior of the user.

On the other hand, there are actions that contribute indirectly to the purchase of goods or services. The action of a user viewing an advertisement related to a product or service is an action that may lead to purchase if the user likes the product or service. The action of the user going to the store is also an action that may lead to purchase when the user likes a product or service sold at the store. The action of recommending or introducing a product or service to another person is an action that the other person may purchase the product or service. Patent Document 3 discloses a technique for giving points to such indirect actions.

In addition, in the actual point service, a predetermined point is given only by joining a point card, or a point is given only by requesting an estimate. ing.

JP 11-339128 A Table 2011/002018 JP 2009-129293 A

As described above, points are clearly related to monetary value. On the other hand, points are also given to indirect actions that indirectly contribute to purchasing actions. However, there is no guarantee that indirect behavior will lead to purchasing behavior that generates money. Therefore, when indirect behavior occurs but purchase behavior does not occur as much as expected, there is a risk of loss in the business that provides the source of points to be given to indirect behavior. It is desirable to prevent incurring losses beyond expectations while giving incentives not only to purchasing behavior but also to non-purchasing behavior.

An object of the present invention is to provide a technique that can incentivize not only purchasing behavior but also non-purchasing behavior to promote various behaviors of the user.

A user behavior promotion system according to an embodiment of the present invention is provided to a user behavior including a purchase behavior for purchasing a product or a service and a non-purchasing behavior other than the purchase behavior, and a user who has performed the user behavior. The user behavior score information associated with the score is obtained, the user behavior information performed by the user and the user identification information of the user are acquired, and the user behavior score information is referred to, thereby obtaining the user behavior score information. Based on an action conversion unit that determines a score to be given to the user with respect to an action, a score integration unit that calculates a score integrated value by integrating the score to be given to the user for each user, and the score integrated value And ranking the users, and based on the ranking, a user who gives a privilege and a privilege determination unit that determines the privilege given to the user

According to the present invention, since the privilege is given to the user based on the ranking of the user ranked based on the user's behavior, the non-purchasing behavior is not necessarily thought while giving incentives not only to the purchasing behavior but also to the non-purchasing behavior. Thus, even if it does not lead to purchasing behavior, it is possible to prevent a loss more than expected and to promote various behaviors of the user.

It is a figure for demonstrating the mechanism of user action promotion by Example 1. FIG. It is a block diagram which shows the structure of the user action promotion system by Example 1. FIG. It is a sequence diagram for demonstrating the user action process in Example 1. FIG. It is a figure which shows an example of the action score information in Example 1. It is a sequence diagram for demonstrating the privilege determination process in Example 1. FIG. It is a sequence diagram for demonstrating the data provision process in Example 1. FIG. It is a figure for demonstrating calculation of the correlation value in Example 1. FIG. It is a block diagram which shows the structure of the user action promotion system by Example 2. 10 is a flowchart illustrating a conversion rate control process according to a second embodiment. It is a block diagram which shows the structure of the user action promotion system by Example 3. 12 is a flowchart illustrating indirect action extraction processing according to the third embodiment. It is a block diagram which shows the structure of the user action promotion system by Example 4. 12 is a flowchart illustrating action tracking processing according to a fourth embodiment.

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

FIG. 1 is a diagram for explaining a mechanism for promoting user behavior according to the first embodiment. The user behavior promotion system 10 is disposed in the center and can be connected via various networks from the various external devices. As external devices that can be connected to the user behavior promotion system 10, there are a store device 21, a store leader 22, a member device 23, a user terminal 24, and a server device 25. These may be collectively referred to as the external device 20.

In this system, a predetermined score is given to a user who has performed a predetermined action, and a privilege is returned to the user based on the ranking based on the integrated value of the score. A smartphone, tablet, or personal computer of a user who has joined the system can be the external device 20. Further, for example, when a merchant that sells goods or services is a member of this system, the various devices that the member has can be the external device 20.

In the example of FIG. 1, there is a server device 25 that provides a Web site and / or an EC site at the member site w. Although one server device 25 is shown in FIG. 1, a plurality of members can join the system, and a plurality of member server devices 25 may be connected.

Further, in the example of FIG. 1, a store device 21, a store leader 22, and a member device 23 are arranged in the store y of the member. Moreover, the store apparatus 21 is arrange | positioned in the store z of another member.

The store apparatus 21 is, for example, a POS (Point Of Sales) terminal. When the user purchases a product or service at the store, the store apparatus 21 notifies the user behavior promotion system 10 who has purchased what.

The store reader 22 is, for example, an IC card reader. For example, by reading information from an IC card built in the user's smartphone, the store reader 22 knows who has visited the store and notifies the user behavior promotion system 10. For example, if it is installed at an event venue and the visitor touches the store leader 22 with a smartphone, the attendee at the event can be grasped.

The member device 23 is a device that constitutes an information system in the member company, and can acquire data accumulated in the user behavior promotion system 10 and information calculated based on the data.

FIG. 2 is a block diagram illustrating a configuration of the user behavior promotion system according to the first embodiment. The user behavior promotion system 10 includes a behavior conversion unit 11, a score integration unit 12, a privilege determination unit 13, a data provision unit 14, and a contribution degree calculation unit 15. As an example, the user behavior promotion system 10 is configured by a computer in which a processor executes a software program. The behavior conversion unit 11, the score integration unit 12, the privilege determination unit 13, the data provision unit 14, and the contribution calculation unit 15 illustrated in FIG. 2 are executed by a processor included in the user behavior promotion system 10 executing a software program. It is realized by.

The behavior conversion unit 11 holds user behavior score information that associates a user behavior with a score given to the user behavior. The user behavior includes purchase behavior for purchasing goods or services and non-purchase behavior other than purchase behavior. When the user performs user behavior, the behavior conversion unit 11 acquires information on the user behavior performed by the user and the user identification information of the user from the external device 20, and refers to the user behavior score information to thereby obtain the user. A score to be given to the user for the action is determined. The behavior conversion unit 11 accumulates user identification information, user behavior information, and score information given to the user.

The external device 20 can be a variety of devices depending on the type of user action. For example, if the user behavior is purchase of a product, the purchase behavior information and the user identification information of the user can be acquired from the merchant that sold the product or the store apparatus 21 of the store. If the user behavior is non-purchasing behavior such as posting on SNS, “share”, “like”, etc., those information can be acquired from SNS.

The score integration unit 12 integrates the score given to the user for each user, and calculates a score integrated value.

The privilege determination unit 13 ranks the users based on the integrated value of the scores, and determines a supporter who gives the privilege and a privilege given to the supporter based on the ranking.

In this embodiment, since the user is ranked based on the user behavior and the privilege to be given to the user is determined based on the ranking, the non-purchasing behavior is given while giving incentives not only to the purchasing behavior but also to the non-purchasing behavior. Even if it does not necessarily lead to purchasing behavior as expected, it is possible to prevent a loss more than expected.

The data providing unit 14 provides the member with the stored information or information obtained by processing the information.

FIG. 3 is a sequence diagram for explaining user behavior processing in the first embodiment. The behavior conversion unit 11 receives information on user behavior performed by the user from the external device 20 (step 101). Examples of the external device 20 include a store device 21, a store leader 22, a member device 23, a user terminal 24, a server device 25, an SNS, and the like. User action information includes a user ID and action ID. The action ID is identification information for identifying each of various user actions.

The behavior conversion unit 11 that has received the user behavior information accumulates the information in the database as behavior data (step 102). Further, the behavior conversion unit 11 determines a score to be given to the supporter with respect to the support behavior performed by the supporter by the score conversion process (step 103). A score conversion process is a process which determines the score corresponding to a user action with reference to user action score information.

The behavior conversion unit 11 notifies the score integration unit 12 of user behavior information including the user ID of the user who performed the user behavior and the score information to be given to the behavior (step 104). The score integration unit 12 requests the database for individual score data including the integrated value of the individual score of the user indicated by the user ID (step 105).

When the score integrating unit 12 receives the message of the individual score data of the corresponding user from the database (step 106), the score integrating unit 12 acquires the individual score data from the message (step 107). Further, the score integrating unit 12 adds the score given this time to the integrated value of the score included in the individual score data (step 108), and the score including the new integrated value (total value) of the score and the user ID Update information is stored in the database (step 109).

In addition, when the privilege determination unit 13 requests score data of all supporters from the database (step 110) and receives a score data message from the database (step 111), the score data is acquired from the message (step 112). . Then, the privilege determination unit 13 recalculates the rank of the supporter (step 113), and notifies the external device 20 of rank information including the recalculated rank (step 114).

Note that the processing of steps 110 to 114 may be executed asynchronously with the user action, for example, at regular intervals.

FIG. 4 is a diagram illustrating an example of user behavior score information in the first embodiment. For each user action identified by the user action ID, a score to be given to the user who performed the action is defined. In this embodiment, the score for the user action is fixedly determined.

For example, 300 points are given as a score for the action “buy product x” with user action ID = A. 60 points are given as a score for the action of “participating in an event at store y” with user action ID = B. 50 points are given as a score for the action “go to store y” with user action ID = C. Forty points are given as a score for the action “buy service w” with user action ID = D.

Similarly, 20 points are given as a score for an action of “Share product x via SNS” with user action ID = G. Ten points are given as a score for an action “browse advertisement of product x” with user action ID = M. Two points are given as a score for an action of “Like“ Goods x with SNS ”for user action ID = X. One point is given as a score for the action of “Like” to the store y by SNS ”with the user action ID = Y.

FIG. 5 is a sequence diagram for explaining the privilege determination process in the first embodiment. When the privilege is to be determined, the privilege determination unit 13 first requests score data for all users from the database (step 201).

When the privilege determination unit 13 receives a message including score data from the database (step 202), the privilege determination unit 13 acquires score data of all users from the message (step 203). And the privilege determination part 13 compares the integrated value of the score of all the users, and ranks in order with a large score integrated value (step 204), and the privilege given to the user who gives a privilege according to a ranking, and the user Is determined (step 205). The privilege determination unit 13 notifies privilege return information including information on the privilege to be given to the user terminal 24 of the user who gives the privilege (step 206).

FIG. 6 is a sequence diagram for explaining the data providing process in the first embodiment.

It should be noted that the non-purchasing behavior in this embodiment includes active behavior and passive behavior. Hereinafter, specific examples of this embodiment will be shown.

Suppose, for example, that a department store AA creates a group as a unit for returning a privilege by accumulating scores, and a restaurant BB, a travel agency CC, and a delivery company DD join the group. A user who joins a group can get a score when shopping at a department store AA. Also, if you like the article on the Internet of department store AA, you will get a score. If you introduce a friend to department store AA, you will get a score. Also, if you participate in an event held at department store AA, you will get a score. You can get a score by reading the advertisement on the Internet of department store AA and "Like". If you eat at restaurant BB, you will get a score. You can get a score if you use travel agency CC. You can get a score if you use the courier DD.

These are active actions, but for example, a score may be obtained simply by displaying an advertisement on the user terminal 24. In that case, the advertisement being displayed on the user terminal 24 is a passive action.

Also, the non-purchasing behavior set in the user behavior score information as giving a score may be an indirect behavior that indirectly contributes to the purchasing behavior. By doing so, incentives can be given not only to purchasing behavior but also to indirect behavior that indirectly contributes to purchasing behavior. Can do.

Further, in the present embodiment, the contribution calculation unit 15 calculates the contribution to the purchase action by the indirect action. Since it is possible to quantitatively know how much the indirect action contributes to the purchasing action, it is possible to formulate a more effective score distribution to the indirect action.

As an example, the indirect behavior is browsing of advertisements for products or services, and the corresponding purchasing behavior is purchasing behavior for users who have viewed the advertisements to purchase the products or services. Since it is possible to quantitatively measure how much the user or the user who presented the advertisement purchased the product or service that is the object of the advertisement, it is possible to know the obvious effect of the advertisement.

As another example, an indirect action is a recommendation or introduction of a product or service to a user, and a corresponding purchase behavior is that a user who recommended or introduced the product or service purchased the product or service. It is purchasing behavior. The introduction or recommendation here is, for example, “share” on SNS. Since it is possible to quantitatively measure how much the user who recommended or introduced the product or service purchased the product or service, it is possible to know the obvious effect of the introduction or recommendation of the product or service.

As yet another example, the indirect action is a positive intention expression for a product or service, and the corresponding purchase action is a purchase action for purchasing the product or service for which a positive intention expression has been made. The positive intention display here is, for example, “Like” on SNS. Know the obvious effect of giving a positive impression to a product or service because you can quantitatively measure how much the user has purchased the product or service. Can do.

In this embodiment, the degree of contribution is indicated by, for example, a correlation coefficient between indirect behavior and purchase behavior. For example, if the correlation coefficient between indirect behavior and purchasing behavior is high, it can be said that the degree of contribution of the indirect behavior to the purchasing behavior is high. Thus, according to the present embodiment, the degree of contribution can be easily measured by a quantitative index called a correlation coefficient.

FIG. 7 is a diagram for explaining the calculation of the correlation value in the first embodiment. Here, an example of calculating the correlation coefficient between the actions A and B is shown. In order to simplify the calculation, it is assumed that the history information of the four users user1 to user4 is acquired for the actions A and B.

The correlation coefficient between the action A and the action B can be obtained by Expression (1). Correlation coefficient between action A and action B = (covariance of action A and action B) ÷ (standard deviation of action A × standard deviation of action B) (1)
Hereinafter, the calculation method will be described.

When each user performs a certain user action, a combination of the user identification information and the user action identification information is accumulated. Therefore, it is possible to obtain information from the database as to whether or not each user has performed action A and action B as indicated by circles (circle) and x (cross) in FIG. Here, ◯ (circle) indicates that the action has been performed, and x (X) indicates that the action has not been performed.

Here, if action A is being performed, x = 1, if not, x = 0, if action B is being performed, y = 1, and if not, y = 0 is set. What is necessary is just to calculate the number of relations.

The contribution calculation unit 15 acquires information on whether or not the user has performed the actions A and B from the database, calculates the deviations of the actions A and B, and further deviates the actions A and B. Each square value is calculated. Each standard deviation can be obtained from the square of each deviation of the actions A and B. Further, the covariance between the actions A and B can be obtained from the deviations of the actions A and B of each user. From the standard deviation of the behavior A, the standard deviation of the behavior B, and the covariance of the behavior A and the behavior B, the correlation coefficient between the behavior A and the behavior B can be obtained by Expression (1).

In the example shown in FIG. 7, the standard deviation of the action A is 0.433013, the standard deviation of the action B is 0.5, and the covariance between the actions A and B is 0.125. Therefore, the correlation coefficient between the actions A and B is 0.5773349817128585 according to the expression (1).

In Example 1, the behavior score conversion rate which is the conversion rate between the user behavior and the score is fixed in the behavior score information, but Example 2 shows an example in which the behavior score conversion rate can be changed.

FIG. 8 is a block diagram illustrating a configuration of a user behavior promotion system according to the second embodiment. In the second embodiment, the user behavior promotion system 10 includes a behavior conversion unit 11, a score integration unit 12, a privilege determination unit 13, a data provision unit 14, a contribution calculation unit 15, and a conversion rate control unit 16. The user action promotion system 10 of the second embodiment is different from that of the first embodiment shown in FIG. 2 in that it has a conversion rate control unit 16. As an example, the user behavior promotion system 10 is configured by a computer in which a processor executes a software program. The behavior conversion unit 11, the score integration unit 12, the privilege determination unit 13, the data provision unit 14, the contribution calculation unit 15, and the conversion rate control unit 16 illustrated in FIG. This is realized by executing a software program.

The behavior conversion unit 11 accumulates, as user behavior history information, a combination of user behavior identification information and user identification information of the user who performed the user behavior. The user behavior history information includes information that associates indirect behavior related to a product or service with the product or service. The indirect behavior related to the product or service is determined in advance assuming that it indirectly contributes to the purchase behavior of the product or service.

The conversion rate control unit 16 controls the behavior score conversion rate for the indirect behavior according to the degree of contribution to the purchase behavior related to the product or service by the indirect behavior related to the product or service calculated based on the user behavior history information. . Thereby, since the action score conversion rate of the indirect action can be controlled according to the contribution degree of the indirect action, a high incentive is given to the indirect action with a high contribution degree, and the effect of promoting the purchasing action can be enhanced.

FIG. 9 is a flowchart showing the conversion rate control process according to the second embodiment. The conversion rate control unit 16 compares the degree of contribution to the purchase behavior by the indirect behavior with the first threshold (step 501). If the contribution is higher than the first threshold, the contribution of the indirect action to the purchase action is sufficiently high. Therefore, if the frequency of indirect action is increased by increasing the action score conversion rate, It means that sales can be improved. Therefore, if the contribution is higher than the first threshold, the conversion rate control unit 16 increases the action score conversion rate in the indirect action and the purchase action (step 502).

If the contribution is less than or equal to the first threshold, the conversion rate control unit 16 then compares the contribution with the second threshold (step 503). If the contribution is lower than the second threshold, the contribution of the indirect action to the purchase action is sufficiently low. Therefore, even if the action score conversion rate is lowered and the frequency of indirect action is reduced, the product or This means that the impact of lower service sales is small. Therefore, if the contribution is lower than the second threshold, the conversion rate control unit 16 decreases the behavior score conversion rate (step 504).

In the second embodiment, an example is shown in which only the behavior score conversion rate of indirect behavior is controllable and the behavior score conversion rate of purchase behavior is fixed. However, the behavior score conversion rate of purchase behavior may be controllable. . For example, the sales of a product or service may be measured and compared with a predetermined sales threshold, and the behavior score conversion rate may be controlled based on the comparison result. When it is better to increase sales, the action score conversion rate is increased to increase the score given to the purchase of goods or services.

In Example 1, the association between purchasing behavior and indirect behavior was predetermined, but Example 3 shows an example of extracting indirect behavior that contributes to certain purchasing behavior. In the third embodiment, a score is assigned to the extracted indirect action or a contribution is calculated.

FIG. 10 is a block diagram illustrating the configuration of the user behavior promotion system according to the third embodiment. The user behavior promotion system 10 includes a behavior conversion unit 11, a score integration unit 12, a privilege determination unit 13, a data provision unit 14, a contribution calculation unit 15, and an indirect behavior extraction unit 17. The user action promoting system 10 of the third embodiment is different from the person of the first embodiment shown in FIG. As an example, the user behavior promotion system 10 is configured by a computer in which a processor executes a software program. The processor included in the user behavior promotion system 10 includes the behavior conversion unit 11, the score integration unit 12, the privilege determination unit 13, the data provision unit 14, the contribution calculation unit 15, and the indirect behavior extraction unit 17 illustrated in FIG. 10. This is realized by executing a software program.

The indirect behavior extraction unit 17 extracts indirect behavior that contributes to purchase behavior from historical information on user behavior performed in the past. In the present embodiment, the contribution calculation unit 15 calculates the contribution of the extracted indirect action to the purchase action. Since indirect behavior that contributes to purchasing behavior is extracted from past non-purchasing behavior of the user who performed purchasing behavior, indirect behavior that contributes to purchasing behavior even from non-purchasing behavior that is not clearly related to purchasing behavior Can be found.

FIG. 11 is a flowchart showing indirect action extraction processing according to the third embodiment. The indirect action extraction unit 17 first extracts a non-purchase action performed by a user who has performed a purchase action for extracting an indirect action before performing the purchase action (step 601). If a plurality of non-purchasing actions are extracted at this time, the following steps 602 to 604 are performed for each non-purchasing action.

The indirect behavior extraction unit 17 associates the extracted non-purchasing behavior with the target purchasing behavior (step 602). Next, the indirect action extraction unit 17 calculates the contribution degree of the non-purchase actions associated with each other to the purchase action (step 603). Next, the indirect action extracting unit 17 determines a non-purchasing action whose calculated contribution exceeds a predetermined contribution threshold as an indirect action with respect to the purchasing action (step 604).

According to the present embodiment, since non-purchasing behavior that is a candidate for indirect behavior that contributes to purchasing behavior is extracted using the user as a key, indirect behavior related to purchasing behavior can be appropriately extracted in a series of user behaviors. it can. As a result, it is possible to formulate score distribution to effective indirect behavior for guiding the user to purchasing behavior.

In the first embodiment, the history information of the performed user actions is stored in the database. However, the fourth embodiment further shows an example in which user actions are tracked and analyzed based on the stored information. .

FIG. 12 is a block diagram illustrating a configuration of a user behavior promotion system according to the fourth embodiment. The user behavior promotion system 10 includes a behavior conversion unit 11, a score integration unit 12, a privilege determination unit 13, a data provision unit 14, a contribution calculation unit 15, and a behavior tracking unit 18. As an example, the user behavior promotion system 10 is configured by a computer in which a processor executes a software program. The behavior conversion unit 11, the score integration unit 12, the privilege determination unit 13, the data provision unit 14, the contribution calculation unit 15, and the behavior tracking unit 18 illustrated in FIG. It is realized by executing the program.

The user behavior promotion system 10 of the fourth embodiment is different from that of the first embodiment shown in FIG.

The behavior tracking unit 18 extracts in time series what kind of non-purchasing behavior the user who performed the purchasing behavior performed before performing the purchasing behavior, and for each time-series non-purchasing behavior, The ratio of the users who have made non-purchasing behavior to the current stage of non-purchasing behavior is calculated. Effective non-purchasing behavior can be determined by focusing on which behaviors of a series of previous behaviors of users who have made purchasing behaviors can be promoted effectively. It is possible to formulate score distribution to

FIG. 13 is a flowchart showing the action tracking process according to the fourth embodiment. The behavior tracking unit 18 first extracts the non-purchasing behavior that the user who has performed the purchasing behavior to be tracked before has performed in time series (step 701). Next, the behavior tracking unit 18 extracts the first non-purchasing behavior in time series (step 702).

Next, the behavior tracking unit 18 determines whether or not there is a next non-purchasing behavior (step 703). If there is no next non-purchasing action, the person who performed the target purchasing action is extracted from those who performed the previous non-purchasing action (step 704). Furthermore, the behavior tracking unit 18 calculates the ratio of the target purchase behavior performer to the previous non-purchase behavior performer (step 705).

If there is a next non-purchasing behavior in the determination in step 703, the behavior tracking unit 18 extracts an implementer who has performed the current non-purchasing behavior from the performers of the previous non-purchasing behavior (step 706). Further, the behavior tracking unit 18 calculates the ratio of the current non-purchasing behavior implementer to the previous non-purchasing behavior performer (step 707), and returns to step 703.

The embodiments of the present invention described above are examples for explaining the present invention, and are not intended to limit the scope of the present invention only to those embodiments. Those skilled in the art can implement the present invention in various other modes without departing from the gist of the present invention.

DESCRIPTION OF SYMBOLS 10 ... User action promotion system, 11 ... Action conversion part, 12 ... Score integrating part, 13 ... Benefit determination part, 14 ... Data provision part, 15 ... Contribution calculation part, 16 ... Conversion rate control part, 17 ... Indirect action extraction , 18 ... Action tracking unit, 20 ... External device, 21 ... Store device, 22 ... Store leader, 23 ... Member device, 24 ... User terminal, 25 ... Server device, 30 ... Network

Claims (12)

It holds user behavior score information in which user behavior including purchase behavior for purchasing goods or services and non-purchasing behavior other than the purchase behavior is associated with a score given to a user who has performed the user behavior. The action of determining the score to be given to the user action with respect to the user action by acquiring information on the user action performed by the user and the user identification information of the user and referring to the user action score information A conversion unit;
A score accumulating unit for accumulating a score to be given to the user for each user, and calculating the score accumulated value;
The user action promotion system which ranks the said user based on the said score integrated value, and has the privilege determination part which determines the user who gives a privilege and the privilege given to this user based on the said ranking. The user behavior promotion system according to claim 1, wherein the non-purchasing behavior is an indirect behavior that indirectly contributes to the purchasing behavior. The user behavior promotion system according to claim 2, further comprising a contribution calculation unit that calculates a contribution to the purchase behavior by the indirect behavior. The indirect action is browsing advertisements for goods or services;
The purchase behavior is a purchase behavior in which the user who viewed the advertisement purchased the product or the service,
The user behavior promotion system according to claim 3. The indirect action is a recommendation or introduction of a product or service to a user;
The purchase behavior is a purchase behavior in which the user who recommended or introduced the product or service purchased the product or service.
The user behavior promotion system according to claim 3. The indirect action is a positive intention to the goods or services;
The purchasing behavior is the purchasing behavior of purchasing the product or the service for which the positive intention has been indicated;
The user behavior promotion system according to claim 3. 4. The user behavior promotion system according to claim 3, wherein the degree of contribution is indicated by a correlation coefficient between the indirect behavior and the purchase behavior. The behavior conversion unit accumulates user behavior history information in which indirect behavior related to a product or service is associated with the product or service,
The user behavior promotion system includes:
A conversion rate control unit that controls an action score conversion rate for the indirect behavior according to the degree of contribution to the purchase behavior related to the product or service by the indirect behavior related to the product or service calculated based on the user behavior history information. The user behavior promotion system according to any one of claims 3 to 7, further comprising: An indirect action extraction unit that extracts indirect actions that contribute to the purchase action from past user actions;
The contribution calculation unit calculates a contribution of the extracted indirect action to the purchase action;
The user behavior promotion system according to claim 3. The indirect action extraction unit
Extracting non-purchasing behavior performed by the user who performed the purchasing behavior before performing the purchasing behavior,
Correlating the extracted non-purchasing behavior with the purchasing behavior,
Calculating the degree of contribution of the non-purchasing behaviors associated with each other to the purchasing behaviors,
Non-purchasing behavior in which the degree of contribution exceeds a predetermined contribution threshold is defined as indirect behavior with respect to the purchasing behavior.
The user behavior promotion system according to claim 8. The non-purchasing behavior of the next stage is extracted for each of the non-purchasing behaviors in the time series by extracting in time series what kind of non-purchasing behavior the user who performed the purchasing behavior performed before performing the purchasing behavior. It further has an action tracking unit that calculates the percentage of the performed,
The user behavior promotion system according to claim 1. (Method claim equivalent to claim 1)
User behavior in which the behavior conversion means associates a user behavior including a purchasing behavior for purchasing a product or a service and a non-purchasing behavior other than the purchasing behavior with a score given to a user who has performed the user behavior. It holds score information, acquires information on user behavior performed by the user and user identification information of the user, and gives the user behavior to the user by referring to the user behavior score information Determine the score,
The score integrating means integrates the score to be given to the user for each user, calculates the score integrated value,
A user behavior promotion method in which a privilege determining unit ranks the users based on the score integrated value, and determines a user who gives a privilege and a privilege given to the user based on the ranking.

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