Data processing device, data processing method and program

Abstract

To provide a data processing device and program capable of supporting the planning of promotions corresponding to various recipients.SOLUTION: A data processing device is equipped with generalizing means for analyzing promotion information describing project contents of a promotion, and generalizing elements described in the promotion information, creating means for creating recipient information indicating characteristics of each attribute of the recipients, on the basis of the attribute and behavior history of the recipient collected from the plurality of recipients, first deriving means for deriving a first target model expressing a recipient image on the basis of the elements generalized by the generalizing means, second deriving means for deriving a second target model expressing a recipient image for each attribute on the basis of the recipient information, and first deciding means for deciding a target model to be promoted, on the basis of the first target model and the second target model. The first deriving means and the second deriving means form one module, and can switch it with other modules different in a driving method.SELECTED DRAWING: Figure 3

Description

Technical field

[0001] Embodiments of the present invention relate to a data processing device and a program. [Background technology]

[0002] Suppliers such as manufacturers, advertising companies, and retail stores promote sales of products by planning and implementing various promotions. Furthermore, conventionally, a technology has been proposed in which detailed data of customers in alliance companies is analyzed and promotions created from the analysis results are provided to the customers.

[0003] By the way, the mainstream of current promotions is to target recipients according to a scenario devised by the supplier. For example, conventionally, promotions to be carried out at a store are planned based on a scenario in which customers who use the store are the recipients.

[0004] However, in recent years, the image of recipients has become more diverse due to the spread of social networking services (SNS), etc. Therefore, in the conventional method, there is a possibility that a discrepancy occurs between the image of the recipient assumed by the supplier and the image of the actual recipient, and there is room for further improvement. [Summary of the invention] [Problem to be solved by the invention]

[0005] The problem to be solved by the present invention is to provide a data processing device and a program that can support planning of promotions corresponding to various recipients. [Means to solve the problem]

[0006] The data processing device of the embodiment includes a generalization means, a generation means, a first derivation means, a second derivation means, and a first determination means. The generalization means analyzes promotion information in which the content of a promotion plan is described, and generalizes the elements described in the promotion information. The generating means generates recipient information indicating the characteristics of each attribute of the recipient based on the recipient's attributes and behavior history collected from a plurality of recipients. The first derivation means derives a first target model representing a beneficiary image based on the elements generalized by the generalization means. The second deriving means derives a second target model representing a beneficiary image for each of the attributes based on the beneficiary information. The first determining means determines a target model to be targeted for the promotion based on the first target model and the second target model. Further, the first derivation means and the second derivation means form one module, and are configured to be switchable with other modules having different derivation methods. [Brief explanation of drawings]

[0007]

Figure 1

Figure 2

[0008] Hereinafter, embodiments will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments described below.

[0009] FIG. 1 is a diagram showing an example of the configuration of a promotion support system according to an embodiment. As shown in FIG. 1, the promotion support system 1 includes a supplier device 10, a recipient device 20, and a promotion support server 30. The supplier device 10 and the recipient device 20 are communicably connected to a promotion support server 30 via a network N such as the Internet. Note that the number of supplier devices 10 and recipient devices 20 connected to network N does not particularly matter.

[0010] The supplier device 10 is an information processing device operated by a supplier who plans a promotion. Examples of suppliers include manufacturers that manufacture and sell products, advertising agencies that create advertisements, and retail stores. The supplier device 10 transmits promotion information describing the content of plans such as sales promotions to the promotion support server 30 in response to instructions from the supplier.

[0011] Promotion information is composed of four elements: "target", "time", "value", and "notification", for example. “Target” is an element for specifying recipients to whom the promotion is provided. "Time" is an element indicating the time to implement the promotion, the expiration date, etc. "Value" is an element indicating the information and services provided to recipients through promotion. “Notification” is an element that indicates how the promotion is provided. The elements included in the promotional information will be based on the scenario envisioned by the supplier. Note that the promotion information may include all of the above-mentioned four elements, or may include some of the elements. In the latter case, the promotional information shall include at least an element related to "value."

[0012] The recipient device 20 is an information processing device operated by a user who can be a recipient of the promotion (hereinafter also referred to as a recipient). In this embodiment, the recipients are assumed to be an unspecified number of general consumers, but the recipients are not limited to this, and may be, for example, members who have registered as members in advance. The recipient device 20 is, for example, a stationary terminal device such as a PC (Personal Computer), a notebook PC, a tablet terminal, a smartphone, or the like. Further, the recipient device 20 may be a terminal device installed in a retail store, a restaurant, etc. that can be operated by the recipient.

[0013] The recipient device 20 stores profile information that includes the name, age, gender, hobbies and preferences, etc. of the recipient who operates the device. In addition, the recipient device 20 sequentially records the history of actions performed by the recipient as an action history.

[0014] Note that the method for acquiring the behavior history is not particularly limited, and various methods can be employed. For example, the beneficiary device 20 may store a history of operations on its own device and usage details of external services used through its own device as an action history. As an example, the beneficiary device 20 records posted content posted to SNS (Social Networking Service) via its own device as an action history. In addition, the recipient device 20 records the usage history of electronic payment services used at retail stores and the like as an action history. In addition, the recipient device 20 records the purchase history at the online shopping service as an action history.

[0015] Additionally, the recipient device 20 transmits profile information and action history to the promotion support server 30. Here, the recipient device 20 may transmit the profile information and the action history at the same time or at different timings. However, identification information such as a user ID shall be attached to both data so that it can be identified that the profile information and action history are related to the same recipient.

[0016] Promotion support server 30 is an example of a data processing device. The promotion support server 30 analyzes the data transmitted from the supplier device 10 and the recipient device 20, and determines the recipient to whom the promotion will be supplied and the promotion supply method.

[0017] In this embodiment, an example will be described in which the promotion support server 30 is realized by a single server device, but the promotion support server 30 is not limited to this. Good too.

[0018] Next, the configuration of the promotion support server 30 mentioned above will be explained. FIG. 2 is a diagram showing an example of the hardware configuration of the promotion support server 30. As shown in FIG. 2, the promotion support server 30 includes a computer configuration such as a CPU (Central Processing Unit) 31, a ROM (Read Only Memory) 32, and a RAM (Random Access Memory) 33.

[0019] The CPU 31 is an example of a processor, and centrally controls each part of the promotion support server 30. ROM32 stores various programs. RAM33 is a workspace where programs and various data are expanded.

[0020] Further, the promotion support server 30 includes a storage section 34, a display section 35, an operation section 36, and a communication section 37.

[0021] The storage unit 34 is composed of a storage medium such as an HDD (Hard Disk Drive) or a flash memory, and maintains the stored contents even if the power is cut off. The storage unit 34 stores programs that can be executed by the CPU 31 and various setting information. Further, the storage unit 34 functions as a storage area for storing various data transmitted from external devices such as the supplier device 10 and the recipient device 20, and a storage area for storing processing results.

[0022] The display unit 35 is composed of a display device such as an LCD (Liquid Crystal Display). The display unit 35 displays various information under the control of the CPU 31. The operation unit 36 ​​includes a keyboard, a pointing device, and the like. The operation unit 36 ​​outputs the operation contents received from the operator to the CPU 31. Note that the operation unit 36 ​​may be a touch panel provided on the display screen of the display unit 35.

[0023] The communication unit 37 is a communication interface connectable to the network N. The communication unit 37 communicates with external devices such as the supplier device 10 and the recipient device 20 via the network N.

[0024] Next, with reference to FIG. 3, the functional configuration of the promotion support server 30 will be described. FIG. 3 is a diagram showing an example of the functional configuration of the promotion support server 30.

[0025] As shown in FIG. 3, the promotion support server 30 includes an acquisition section 311, a processing section 312, an analysis section 313, a planning section 314, and a distribution section 315 as functional components.

[0026] A part or all of the functional configuration provided by the promotion support server 30 is a software configuration realized by cooperation between the processor (e.g., CPU 31) of the promotion support server 30 and the program stored in the memory (e.g., ROM 32, storage unit 34). It may be. Further, part or all of the functional configuration provided in the promotion support server 30 may be a hardware configuration realized by a dedicated circuit installed in the promotion support server 30.

[0027] The acquisition unit 311 is an example of a first acquisition means and a second acquisition means. The acquisition unit 311 acquires (or collects) various data transmitted from external devices such as the supplier device 10 and the recipient device 20 via the communication unit 37. Specifically, the acquisition unit 311 acquires promotional information transmitted from each of the supplier devices 10. Further, the acquisition unit 311 acquires profile information and behavior history transmitted from each of the recipient devices 20. The data acquired by the acquisition unit 311 is stored in the storage unit 34.

[0028] The processing unit 312 is an example of a generalization means and a generation means. The processing unit 312 processes the data acquired by the acquisition unit 311. The processing unit 312 performs different processing on promotion information, profile information, and action history. The processing that the processing unit 312 performs on each data will be described below.

[0029] The processing unit 312 analyzes promotion information that describes the contents of a promotion plan, and performs processing to generalize the elements described in the promotion information. Specifically, the processing unit 312 generalizes the meaning (or intention) of the promotion information plan by analyzing the elements described in the promotion information at the linguistic level of words, phrases, etc.

[0030] For example, the processing unit 312 generalizes one element described in the promotion information based on the meaning of the element or the relationship with other elements. Furthermore, for example, the processing unit 312 may derive elements that are not described in the promotion information from existing elements described in the promotion information by generalization. As an example, the processing unit 312 may change the information from the description "beer discount coupon" corresponding to the "value" element to "20s and above", "beer lover", "saver", etc. corresponding to the "target" element. Elements may also be derived. Note that the technology related to the generalization of promotional information is not particularly important. For example, techniques related to syntax analysis or natural language processing may be used.

[0031] The processing unit 312 generates and outputs the result of generalizing the elements described in the promotion information as generalized promotion information. Then, the processing unit 312 stores the generated promotion information in the storage unit 34 in association with the original promotion information and the like.

[0032] Further, the processing unit 312 performs processing on each piece of profile information to anonymize the personal information included in the profile information. Specifically, the processing unit 312 anonymizes the personal information included in the profile information and categorizes it by attributes such as gender and age. Note that the granularity of attributes to be categorized does not particularly matter.

[0033] Further, the processing unit 312 performs processing on each behavior history to classify the behavioral trends and characteristics described in the behavior history for each attribute of the corresponding recipient. Specifically, the processing unit 312 extracts behavioral trends and characteristics (hereinafter also collectively referred to as recipient characteristics) for each attribute from each behavior history.

[0034] Then, the processing unit 312 associates the attributes of the anonymized and categorized recipients with the recipient characteristics of the recipients belonging to the attributes, and stores them in the storage unit 34 as recipient information. The recipient information is used to derive a recipient target model, which will be described later.

[0035] Note that there is no particular limitation on the timing of processing performed on each of the promotion information, profile information, and action history. For example, the processing unit 312 may generate generalized promotion information at the timing when the acquisition unit 311 acquires the promotion information. Further, for example, by storing the profile information and behavior history acquired by the acquisition unit 311 in the storage unit 34, the processing unit 312 can process the profile information and behavior history acquired in a predetermined period as described above. Processing may be performed.

[0036] The analysis section 313 is an example of a control means. The analysis unit 313 analyzes the data processed by the processing unit 312 to derive a target model to be promoted from the supplier and recipient perspectives. Here, the target model corresponds to the above-mentioned "target" element, and defines the image of the person to whom the promotion is provided, that is, the attributes and conditions of the recipient.

[0037] FIG. 4 is a diagram showing an example of the configuration of the analysis section 313. As shown in FIG. 4, the analysis unit 313 includes a target analysis engine 3130 that is the main body of processing performed by the analysis unit 313.

[0038] The target analysis engine 3130 includes a first analysis section 3131, a first target model catalog 3132, a second analysis section 3133, and a second target model catalog 3134.

[0039] The first analysis section 3131 is an example of the first derivation means. The first analysis unit 3131 uses the first target model catalog 3132 to analyze the generalized promotion information to create a target model (hereinafter also referred to as a supplier target model) that represents the image of the recipient from the supplier's perspective. Derive. Here, the supplier target model is an example of a first target model.

[0040] The first target model catalog 3132 includes trained models, dictionary data, rule sets, etc. that can derive supplier target models related to various elements included in the generalized promotion information. The first analysis unit 3131 analyzes the generalized promotion information using the first target model catalog 3132 to derive a supplier target model corresponding to the elements defined in the generalized promotion information.

[0041] Specifically, the first analysis unit 3131 changes the method for deriving the supplier target model depending on whether the generalized promotion information includes an element related to "target".

[0042] When an element related to a "target" exists in the generalized promotion information, the first analysis unit 3131 combines and expands the elements related to the "target" based on the first target model catalog 3132, so that one or more Derive a supplier target model.

[0043] For example, if the elements related to the "target" included in the generalized promotion information are "20s and older" and "alcohol lover," the first analysis department 3131 determines from these factors that "people in their 20s and older regularly drink alcoholic beverages." The supplier target model is derived as “purchasing on a regular basis”.

[0044] In addition, if the generalized promotion information does not include an element related to a "target," the first analysis unit 3131 selects one from other elements included in the generalized promotion information based on the first target model catalog 3132. Or derive a multi-supplier target model by estimation.

[0045] The supplier target model derived by the first analysis unit 3131 is stored in the storage unit 34 in association with, for example, corresponding promotion information and general-purpose promotion information. Note that the first analysis section 3131 may be configured to integrally include the first target model catalog 3132.

[0046] The second analysis unit 3133 is an example of second derivation means. The second analysis unit 3133 analyzes the beneficiary information using the second target model catalog 3134 to create a target model (hereinafter also referred to as beneficiary target model) that represents the beneficiary image from the beneficiary's perspective. Derived for each attribute. In other words, the recipient target model is a target model that reflects the actual situation of the recipient. Here, the beneficiary target model is an example of a second target model.

[0047] The second target model catalog 3134 is, for example, a trained model, dictionary data, a rule set, etc. that can derive a beneficiary target model corresponding to various conditions of beneficiary characteristics. The second analysis unit 3133 uses the second target model catalog 3134 to derive by estimation a beneficiary target model that corresponds to the conditions of the beneficiary characteristics defined in the beneficiary information. Specifically, the second analysis unit 3133 derives one or more recipient target models for each recipient attribute.

[0048] The recipient target model derived by the second analysis unit 3133 is stored in the storage unit 34 in association with each attribute of recipient information, for example. Note that the second analysis section 3133 may be configured to integrally include the second target model catalog 3134.

[0049] Further, the target analysis engine 3130 configured as described above forms one module, and is configured to be switchable with another target analysis engine 3130 with a different derivation method. Specifically, the analysis unit 313 maintains a plurality of target analysis engines 3130 with different derivation methods such as parameters and algorithms related to derivation, and switches between target analysis engines 3130 for use.

[0050] For example, the target analysis engine 3130 may be prepared in accordance with the supplier's industry, supplier characteristics, and promotion plan. By switching the target analysis engine 3130, the analysis unit 313 can obtain a derivation result according to the target analysis engine 3130 used.

[0051] Note that the target analysis engine 3130 may be switched manually or automatically. In the latter case, the analysis unit 313 switches the target analysis engine 3130 used to derive the supplier target model and the recipient target model based on the promotion-related conditions.

[0052] For example, the analysis unit 313 may switch the target analysis engine 3130 to be used depending on the supplier who planned the promotion and the industry of the supplier. Furthermore, for example, the analysis unit 313 may switch the target analysis engine 3130 to be used depending on the supplier device 10 that transmitted the promotion information. Furthermore, for example, the analysis unit 313 may switch the target analysis engine 3130 to be used depending on the contents of the promotion information (for example, elements such as targets) by collaborating with the processing unit 312 and the like.

[0053] As an example, if the company that planned the promotion is a women's apparel manufacturer, the analysis unit 313 uses a target analysis engine prepared for the company that can derive mainly women as a supplier target model or a recipient target model. Switch to 3130. Thereby, the analysis unit 313 can select a target model suitable for the company of the supplier device 10.

[0054] Returning to FIG. 3, the planning unit 314 plans a promotion based on the analysis result of the analysis unit 313. Specifically, the planning unit 314 includes a target model determining unit 3141 and a timetable determining unit 3142.

[0055] The target model determining unit 3141 is an example of first determining means. The target model determination unit 3141 determines a target model to be promoted based on the supplier target model and the recipient target model derived by the analysis unit 313.

[0056] Specifically, the target model determining unit 3141 matches the supplier target model and the recipient target model, and determines the recipient target model corresponding to the supplier target model as the target model. The matching method is not particularly limited, and various methods can be employed.

[0057] For example, the target model determination unit 3141 selects, from among the beneficiary target models, those that meet the conditions of the supplier target model, that is, some or all of the words and phrases (including similar words) that define the supplier target model. Identify. Further, for example, the target model determining unit 3141 identifies, from among the recipient target models, those whose match rate with the words that define the supplier target model is equal to or higher than a predetermined value. Then, the target model determining unit 3141 determines the specified beneficiary target model as the target model.

[0058] The timetable determining unit 3142 is an example of second determining means. The timetable determination unit 3142 determines a timetable that defines the timing and method of promotion. Here, the timetable corresponds to "time", "value", and "notification" among the four elements described above.

[0059] Here, the method for determining the timetable is not particularly limited, and various methods can be employed. For example, the timetable determining unit 3142 may determine the timetable based on the characteristics of the target model determined by the target model determining unit 3141. Specifically, the timetable may be determined based on conditions related to "time," "value," and "notification" that define the target model. Further, for example, the timetable determining unit 3142 may determine the timetable based on elements such as "time", "value", and "notification" included in the promotion information.

[0060] In addition, the timetable determination unit 3142 may make adjustments such as shifting the timing so that the promotion decided for one promotion information does not affect the promotion of other promotion information and so that the timing of the promotion does not overlap. preferable.

[0061] The distribution unit 315 distributes the promotion planned by the planning unit 314. Specifically, the distribution unit 315 executes promotion for the target model determined by the planning unit 314 based on the timetable determined by the planning unit 314.

[0062] For example, the distribution unit 315 executes the promotion planned by the planning unit 314 by notifying the target model and timetable determined by the planning unit 314 to an external device or an external organization that conducts promotional activities such as distributing promotions. let

[0063] Next, an example of the operation of the above-mentioned acquisition section 311, processing section 312, analysis section 313, planning section 314, and distribution section 315 will be described with reference to FIG. Here, FIG. 5 is a diagram for explaining the operation of the promotion support server 30. Note that in FIG. 5, the "Supplier" column shows an example of processing related to data originating from the supplier device 10. Furthermore, the “recipient” column shows an example of processing related to data derived from the recipient device 20.

[0064] First, the acquisition unit 311 acquires promotion information from the supplier device 10. Further, the acquisition unit 311 acquires profile information and behavior history from the recipient device 20.

[0065] For example, as shown in FIG. 5, the promotion information describes the content of the promotion plan, such as "issuing beer discount coupons to everyone." In this case, "all" relates to the "target" element. Furthermore, "issue discount coupons for beer" relates to the element of "value." Note that since "everyone" refers to an unspecified number of people, it may be considered that the element of "target" is not defined.

[0066] Subsequently, the processing unit 312 generalizes the promotion information acquired by the acquisition unit 311 to generate generalized promotion information. For example, the processing unit 312 generalizes the above-mentioned promotional information such as "20s and above," "beer lover," "alcohol lover," "saver," "purchasing luxury goods at a store," " Generate generalized promotional information that includes elements such as "drinking at home."

[0067] Here, "20s and above," "beer lover," and "alcohol lover" are elements obtained by generalizing "all" and "beer" described in the promotional information. Furthermore, "saver," "purchases luxury items at a store," and "drinks alcohol at home" are elements obtained by generalizing "beer" and "discount coupon" described in the promotional information. Note that each element of the generalized promotion information described above is related to the "target" element, but the target of generalization is not limited to this element.

[0068] Further, the processing unit 312 performs anonymization of the profile information and behavior history acquired by the acquisition unit 311, and categorization for each attribute. Specifically, the processing unit 312 categorizes the anonymized profile information by attribute, extracts recipient characteristics from the behavior history of each attribute, and generates recipient information that associates attributes and recipient characteristics. do.

[0069] For example, the processing unit 312 categorizes the anonymized profile information by age and gender. Furthermore, the processing unit 312 extracts recipient characteristics of recipients belonging to the categorized attribute from the behavior history of the attribute. In Figure 5, for men in their 30s, we extract beneficiary characteristics such as ``regularly buys beer,'' ``works until 5pm,'' ``often drinks after work,'' and ``often buys cheap food.'' .

[0070] Next, the analysis unit 313 (first analysis unit 3131) uses the first target model catalog 3132 to derive a supplier target model from the generalized promotion information. Here, if an element related to a "target" is defined in the generalized promotion information, the first analysis unit 3131 derives a supplier target model based on the element. For example, the first analysis unit 3131 combines the elements of the generalized promotion information shown in FIG. "Purchase" etc. are derived as a supplier target model.

[0071] Furthermore, the analysis unit 313 (second analysis unit 3133) uses the second target model catalog 3134 to derive a recipient target model from the recipient information. Specifically, a beneficiary target model is derived for each attribute by combining the beneficiary characteristics for each attribute included in the beneficiary information. For example, as shown in FIG. "Purchase" etc. are derived as a beneficiary target model.

[0072] Next, the planning unit 314 determines a target model and timetable. Specifically, the target model determining unit 3141 determines the target model to be promoted by matching the supplier target model and the recipient target model. For example, in the case of FIG. 5, the target model determining unit 3141 determines "a man in his 30s returning from work" as the target model by matching the supplier target model and the recipient target model.

[0073] Further, the timetable determining unit 3142 determines a timetable based on promotion information, recipient characteristics, etc. related to the target model determined by the target model determining unit 3141. For example, in FIG. 5, the timetable determining unit 3142 determines, as a timetable, ``play a commercial at the end of work'', ``issue a beer discount coupon when visiting the store'', etc.

[0074] Subsequently, the distribution unit 315 distributes the promotion based on the target model and timetable planned by the planning unit 314. For example, the distribution unit 315 performs control to distribute a beer commercial from 17:00 to a user's recipient device 20 (for example, a smartphone, etc.) used by a man in his 30s via a video distribution site or the like. Further, for example, the distribution unit 315 performs control to issue beer discount coupons to men in their 30s who visit the store after 6:00 pm via a signage terminal or the like placed in the store.

[0075] As described above, the promotion support server 30 matches the supplier target model and the recipient target model and determines the target model to be promoted. As a result, the promotion support server 30 can determine the target model for the promotion planned by the supplier based on the recipient target model derived based on the actual circumstances of various recipients, so it can accommodate a variety of recipients. It is possible to efficiently plan promotions.

[0076] An example of the process executed by the promotion support server 30 of this embodiment will be described below.

[0077] FIG. 6 is a flowchart showing an example of a process executed by the promotion support server 30. Note that this process assumes that the derivation of recipient information has been completed based on the profile information and behavior history acquired from each of the recipient devices 20.

[0078] First, the acquisition unit 311 acquires promotion information from the supplier device 10 (step S11). Next, the processing unit 312 generalizes the elements described in the promotion information acquired in step S11, and generates generalized promotion information (step S12).

[0079] Next, the analysis unit 313 selects the target analysis engine 3130 to be used depending on the supplier etc. that sent the promotion information (step S13). Furthermore, the analysis unit 313 causes the selected target analysis engine 3130 to execute the processes of steps S14 and S15.

[0080] Specifically, the first analysis unit 3131 uses the first target model catalog 3132 to derive a supplier target model based on the generalized promotion information (step S14). Furthermore, the second analysis unit 3133 derives a beneficiary target model based on the beneficiary information by using the second target model catalog 3134 (step S15).

[0081] Subsequently, the target model determining unit 3141 matches the supplier target model derived in step S14 with the recipient target model derived in step S15, and determines a target model (step S16). Furthermore, the timetable determining unit 3142 determines a timetable based on the promotion information and the characteristics of the target model determined in step S16 (step S17).

[0082] The distribution unit 315 then distributes the promotion based on the target model and timetable determined in step S16 and step S17 (step S18), and ends this process.

[0083] As described above, the promotion support server 30 of this embodiment analyzes promotion information in which a promotion plan is described, and generalizes the elements described in the promotion information. The promotion support server 30 derives a provider target model representing a target image from the supplier's perspective based on the generalized elements. Further, the promotion support server 30 generates beneficiary information showing the characteristics of each attribute of the beneficiary based on the attributes and behavior history of the beneficiary collected from a plurality of beneficiaries, and Then, a beneficiary target model representing the target image from the beneficiary's perspective is derived for each attribute. The promotion support server 30 then determines a target model to be promoted based on the derived supplier target model and recipient target model.

[0084] Thereby, the promotion support server 30 determines the target model to be promoted from the supplier target model derived based on the promotion intention and the recipient target model derived based on the actual situation of various recipients. I can do it. Therefore, the promotion support server 30 can support planning of promotions corresponding to a variety of recipients.

[0085] Further, the promotion support server 30 changes the method of deriving the supplier target model and recipient target model by switching the target analysis engine 3130 to be used according to the conditions of the supplier and the like. As a result, by preparing a target analysis engine 3130 suitable for each condition of the supplier, etc., the promotion support server 30 can derive a supplier target model and a beneficiary target model suitable for each condition. can. Therefore, the promotion support server 30 can support planning of promotions compatible with various suppliers and recipients.

[0086] Furthermore, the promotion support server 30 determines when and how to provide the promotion based on the characteristics of the determined target model. As a result, the promotion support server 30 can develop a promotion at a time and in a manner appropriate to the characteristics of the target model, thereby supporting the planning of an effective promotion.

[0087] Note that the embodiments described above can be modified and implemented as appropriate by changing part of the configuration or function of each of the devices described above. Therefore, some modified examples of the above-described embodiment will be described below as other embodiments. Note that, below, points that are different from the embodiments described above will be mainly explained, and detailed explanations of points that are common to those already explained will be omitted. Further, the modified examples described below may be implemented individually or in appropriate combinations.

[0088] (Modification example 1) In the embodiment described above, an example has been described in which the analysis unit 313 analyzes generalized promotion information and recipient information, and outputs a supplier target model and a recipient target model as analysis results. However, the analysis target of the analysis unit 313 is not limited to the above-described embodiment. For example, the analysis unit 313 may analyze the results of promotion. The configuration of the promotion support server 30 according to this modification will be described below with reference to FIGS. 7 and 8.

[0089] FIG. 7 is a diagram illustrating an example of the functional configuration of the promotion support server 30 according to Modification 1. In the figure, an acquisition unit 311 acquires data transmitted from the supplier device 10 and recipient device 20 via the communication unit 37, and also acquires promotion implementation results transmitted from the research institution device 40.

[0090] The research agency device 40 is an information processing device operated by a research agency that collects promotion implementation results. Examples of research organizations include manufacturers that manufacture and sell products, advertising agencies that create advertisements, and retail stores.

[0091] The promotion implementation result includes information that can specify the relationship between the implemented promotion and the sales performance of the product promoted by the promotion. For example, the promotion implementation results may include changes in the number of products sold for promotion, changes in the number of sales for each attribute of product purchasers, etc. over a predetermined period that includes the period in which the promotion is implemented. Further, the promotion implementation result may be purchase information such as an electronic receipt issued when each user (recipient) purchases a product. In this case, the purchase information includes the store where the user purchased the product, the purchased product, the date and time of the purchase, and the like.

[0092] Note that there are no particular restrictions on the method of collecting promotion results, and any publicly known or publicly used technology may be used.

[0093] Upon acquiring the promotion implementation result from the research institution device 40, the acquisition unit 311 outputs the promotion implementation result to the analysis unit 313.

[0094] Here, if the promotion execution results include information that can identify an individual such as a user ID, the acquisition unit 311 outputs the promotion execution results to the processing unit 312, so that the processing unit 312 can anonymize and classify the information for each attribute. Categorization may also be performed. In this case, for example, the processing unit 312 refers to a member master that associates an identifier such as a user ID with the profile information of the user corresponding to the identifier, and anonymizes the promotion results and categorizes them by attribute. Just go. The processing unit 312 then outputs the processed promotion implementation results to the analysis unit 313.

[0095] The analysis unit 313 analyzes the input promotion implementation results and outputs the analysis results. FIG. 8 is a diagram showing an example of the configuration of the analysis section 313 according to this modification. As shown in FIG. 8, the analysis unit 313 includes an implementation result analysis engine 3135 in addition to the configuration described in FIG.

[0096] The implementation result analysis engine 3135 includes a third analysis section 3136. The third analysis unit 3136 analyzes the promotion implementation results and outputs an index value indicating the effectiveness of the promotion as an analysis result. Note that the method for analyzing the promotion implementation results is not particularly limited, and a known marketing analysis method or the like may be used.

[0097] For example, the third analysis unit 3136 analyzes the difference in the purchase rate of a product targeted for promotion between the target model and the model other than the target model, the difference in the purchase rate between the promotion period and the period other than the promotion period, etc. as analysis results. Output.

[0098] The analysis result of the third analysis unit 3136 may be stored in the storage unit 34 or may be provided to the supplier device 10 or the like via the distribution unit 315. Furthermore, the analysis results of the third analysis unit 3136 may be used as data for improving the derivation accuracy of the first target model catalog 3132 or the second target model catalog 3134. For example, when the first target model catalog 3132 or the second target model catalog 3134 is composed of trained models, the analysis results of the third analysis unit 3136 may be used as the learning data.

[0099] Further, the implementation result analysis engine 3135 may have a modular configuration similar to the target analysis engine 3130, so that it can be switched with other implementation result analysis engines 3135 that use different analysis methods. In this case, the analysis unit 313 maintains a plurality of implementation result analysis engines 3135 with different analysis methods such as analysis parameters and algorithms, and switches between implementation result analysis engines 3135 for use.

[0100] For example, the implementation result analysis engine 3135 may be prepared in accordance with the supplier's industry, supplier characteristics, and promotion plan. By switching the implementation result analysis engine 3135, the analysis unit 313 can obtain analysis results according to the implementation result analysis engine 3135 used.

[0101] Note that switching of the implementation result analysis engine 3135 may be performed manually like the target analysis engine 3130, or may be performed automatically. In the latter case, for example, the analysis unit 313 may switch the implementation result analysis engine 3135 to be used depending on the content of the implemented promotion or the supplier who planned the promotion.

[0102] As a result, the promotion support server 30 according to this modification can perform a series of processes from planning and implementation of promotions to analysis of implementation results, so it can more efficiently support promotions planned by suppliers. It can be carried out.

[0103] (Variation 2) In the embodiment described above, the entire target analysis engine 3130 is configured to be switchable, but the present invention is not limited to this, and a part of the target analysis engine 3130 may be configured to be switchable.

[0104] For example, among the configurations of the target analysis engine 3130, the first target model catalog 3132 may be configured to be switchable with another first target model catalog 3132 with a different derivation method. Similarly, among the configurations of the target analysis engine 3130, the second target model catalog 3134 may be configured to be switchable with another second target model catalog 3134 with a different derivation method.

[0105] Note that the programs executed by each device of the above-described embodiments are provided in a state that is pre-installed in a ROM, a storage unit, or the like. The programs executed on each device of the above-described embodiments are files in an installable or executable format and can be stored on a computer such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk). It may be configured to be recorded on a readable recording medium and provided.

[0106] Furthermore, the programs executed by each device of the above-described embodiments may be stored on a computer connected to a network such as the Internet, and may be provided by being downloaded via the network. Furthermore, the programs executed by each device of the above-described embodiments may be provided or distributed via a network such as the Internet.

[0107] Although the embodiment of the present invention has been described above, this embodiment is presented as an example and is not intended to limit the scope of the invention. These novel embodiments and their modifications can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included within the scope and gist of the invention, as well as within the scope of the invention described in the claims and its equivalents. [Explanation of symbols]

[0108] 1 Promotion support system 10 Supplier equipment 20 Beneficiary Equipment 30 Data processing server 40 Investigation agency equipment 311 Acquisition Department 312 Processing Department 313 Analysis Department 3130 Target Analysis Engine 3131 1st Analysis Department 3132 1st target model catalog 3133 Second Analysis Department 3134 2nd target model catalog 3135 Implementation result analysis engine 3136 Third Analysis Department 314 Planning Department 315 Distribution Department [Prior art documents] [Patent document]

[0109] [Patent Document 1] Japanese Patent Application Publication No. 2015-79331

Claims

1. a first derivation means for deriving a first target model representing an image of a recipient based on promotion information describing the content of a promotion plan; A second derivation means for deriving a second target model representing a recipient image for each attribute based on recipient information indicating characteristics for each attribute of a plurality of recipients; a first determination means for determining a target model to be a target of the promotion based on the first target model and the second target model; an execution means for executing the promotion on the target model determined by the first determination means; A data processing device comprising:

2. Further comprising a first acquisition means for acquiring the promotion information, The first derivation means derives the first target model based on the promotion information acquired by the first acquisition means.

2. A data processing apparatus according to claim 1.

3. A second acquisition means for acquiring attributes and behavioral histories of a plurality of recipients; A generating means for generating the recipient information indicating characteristics for each attribute of the recipient based on the attributes and behavior history of the recipient acquired by the second acquiring means; Further comprising: The second derivation means derives the second target model for each of the attributes based on the recipient information generated by the generation means.

2. A data processing apparatus according to claim 1.

4. The generating means anonymizes the information acquired by the second acquiring means to generate the recipient information.

4. A data processing device according to claim 3.

5. The data processing device according to claim 1, wherein the first derivation means and the second derivation means form a single module and are configured to be switchable with other modules having different derivation methods.

6. Further comprising a control means for controlling switching of the module, The control means switches the module used to derive the first target model and the second target model based on a condition related to the promotion.

6. A data processing apparatus according to claim 5.

7. The method further comprises a second determination means for determining a time or a manner of implementing the promotion based on the characteristics of the target model determined by the first determination means; The execution means executes the promotion based on the time or method determined by the second determination means.

2. A data processing apparatus according to claim 1.

8. The execution means distributes a commercial and / or issues a coupon as the promotion.

2. A data processing apparatus according to claim 1.

9. The second derivation means derives, for each attribute, conditions of a recipient profile corresponding to the recipient's characteristics shown in the recipient information as a second target model by using a target model catalog capable of deriving conditions of a recipient profile corresponding to the recipient's characteristics from the recipient's characteristics.

2. A data processing apparatus according to claim 1.

10. A generalization means for analyzing promotion information in which a promotion plan is described, and generalizing elements described in the promotion information, The first derivation means derives a first target model representing an image of a recipient based on the elements generalized by the generalization means.

2. A data processing apparatus according to claim 1.

11. The generalization means performs a process of analyzing promotion information described on a language level based on predetermined elements that define the content of the promotion plan, and converting the elements described in the promotion information into elements that are not described in the promotion information, and / or a process of converting the content that is meant by the promotion plan in the promotion information into elements expressed using words described in the promotion information.

11. A data processing apparatus according to claim 10.

12. The first derivation means derives a first target model that specifies the conditions of a person who is a target of the promotion by combining the elements converted by the generalization means.

12. A data processing device according to claim 10 or 11.

13. A data processing method executed by a data processing device, comprising: a first derivation step of deriving a first target model representing an image of a recipient based on promotion information describing the content of a promotion plan; a second derivation step of deriving a second target model representing a recipient image for each attribute based on recipient information indicating characteristics for each attribute of a plurality of recipients; a determining step of determining a target model to be a target of the promotion based on the first target model and the second target model; an execution step of executing the promotion on the target model determined in the determination step; (c) a method for processing data,

14. A computer of a data processing device, a first derivation means for deriving a first target model representing an image of a recipient based on promotion information describing the content of a promotion plan; A second derivation means for deriving a second target model representing a recipient image for each attribute based on recipient information indicating characteristics for each attribute of a plurality of recipients; a first determination means for determining a target model to be a target of the promotion based on the first target model and the second target model; an execution means for executing the promotion on the target model determined by the first determination means; A program to make it function as such.

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