JP7102320B2 - Data management system and method - Google Patents

Description

The present invention relates to a technique for managing data related to a business of providing a product to a customer.

In the business of selling products to customers, it is attracting attention that information on products sold to customers and information on customers are used for sales activities, product planning for developing products that meet customer tastes, and the like.

Patent Document 1 discloses a system for analyzing a customer's purchasing preference type for a product. The system has a purchase history storage unit that stores purchase history data that describes a customer's product purchase history, a customer, a customer's purchase preference type, and a preference that represents a correspondence relationship between products purchased by a customer having the purchase preference type. It is equipped with a relation matrix data storage unit that stores the relation matrix data that describes the type correspondence, and an evaluator that evaluates the preference type correspondence that the relation matrix data describes and outputs the evaluation result. In the evaluator, to what extent the correspondence between the purchase preference type and the product described in the relationship matrix data matches the correspondence between the customer and the product purchase history described in the purchase history data. By calculating the degree of agreement indicating whether or not the product is used, it is evaluated how correctly the preference type correspondence relationship describes the customer's purchasing preference type. It is possible to correctly associate a customer with a product that the customer likes and utilize the associated information in business.

Japanese Unexamined Patent Publication No. 2016-126648

For products that the customer continuously uses, the customer's characteristics may be reflected in the history of the customer's use of the product. The technique of Patent Document 1 associates a customer with a product based on their respective characteristics, but does not consider the characteristics of the customer appearing in the history of use of the product by the customer. Information considering the nature could not be utilized for business.

An object of the present invention is to provide a technique that enables acquisition of information on the nature of a customer that appears in the usage history of the product by the customer.

A data management system according to one aspect has a storage unit that stores usage history information that is information on the usage history of a product provided to a customer, and a feature amount that acquires the usage feature amount based on the usage history information. It has an acquisition unit and a persona identification unit that specifies the nature of the customer based on the feature amount of the use.

In the data management method according to one aspect, the usage history information, which is the information related to the usage history of the product provided to the customer, is stored in the storage unit, the feature amount of the usage is acquired based on the usage history information, and the above-mentioned The nature of the customer is specified based on the feature amount of use.

According to the present invention, it is possible to obtain information on the nature of the customer that appears in the usage history of the product by the customer.

It is a figure which shows an example of the service system which concerns on this embodiment. It is a figure which shows an example of the service flow which concerns on this embodiment. It is a figure which shows an example of the relationship between the customer tag, the product tag, the usage tag, the customer persona, and the product persona which concerns on this Embodiment. It is a figure which shows the configuration example of the data management system which concerns on this embodiment. It is a figure which shows an example of the customer information which concerns on this embodiment. It is a figure which shows an example of the product information which concerns on this embodiment. It is a figure which shows an example of the use history information which concerns on this embodiment. It is a figure which shows an example of the customer feature amount addition rule which concerns on this embodiment. It is a figure which shows an example of the product feature amount addition rule which concerns on this embodiment. It is a figure which shows an example of the use feature amount addition rule which concerns on this embodiment. It is a figure which shows an example of the customer feature amount information which concerns on this embodiment. It is a figure which shows an example of the product feature quantity information which concerns on this embodiment. It is a figure which shows an example of the utilization feature amount information which concerns on this embodiment. It is a figure which shows an example of the customer persona information which concerns on this embodiment. It is a figure which shows an example of the product persona information which concerns on this embodiment. It is a flowchart which shows an example of the tag addition processing which concerns on this embodiment. It is a flowchart which shows an example of the recommendation generation processing which concerns on this embodiment. It is a figure which shows the example of the list screen for a dealer. It is a figure which shows the example of the vehicle information screen for a dealer. It is a figure which shows the example of the maintenance recommendation screen for a dealer. It is a figure which shows the example of the warehousing promotion screen for a customer. It is a figure which shows the hardware configuration example of a data management system.

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

FIG. 1 shows an example of the service system 1 according to the present embodiment.

The service system 1 according to the present embodiment analyzes information about the customer and the product purchased by the customer, and the service provider makes a recommendation (recommendation, recommendation) suitable for the customer and the nature of the product at an appropriate time. Support what you do. In the present embodiment, an example in which the product is a vehicle (automobile) and the service provider is a dealer will be described. However, the product and service providers of this embodiment are not limited to vehicles and dealers.

The service system 1 includes a data collection system 2, a data management system 3, and an information providing system 4.

The data collection system 2 collects information about the customer (hereinafter referred to as "customer information") 200 (see FIG. 5) and information about the vehicle (hereinafter referred to as "product information") 300 (see FIG. 6). The customer information 200 and the product information 300 may be input from the control terminal of the dealer and / or the operator via the intra-network, or may be acquired from another business system via the intra-network. In addition, the data collection system 2 collects 400 (see FIG. 7) history information (hereinafter referred to as "usage history information") of the use of the vehicle by the customer. The usage history information 400 may be transmitted from the customer's vehicle and / or terminal. The customer information 200 and the product information 300 may be referred to as attribute information.

The data management system 3 uses various information collected by the data collection system 2 to generate recommendation information for the customer. The details of the data management system 3 will be described later.

The information providing system 4 transmits the recommendation information generated by the data management system 3 to the customer's terminal 5 and / or the dealer's control terminal via the external network.

By using the recommendation information provided by the service system 1, the dealer can make an appropriate recommendation at an appropriate time for each customer. For example, the dealer can appropriately provide warehousing guidance for vehicle maintenance, test drive guidance for new vehicles, and transfer guidance.

FIG. 2 shows an example of a service flow according to the present embodiment.

The customer purchases the vehicle from the dealer. The dealer inputs the customer information 200 and the product information 300 of the customer and the vehicle into the data collection system 2. In addition, information regarding the daily use of the vehicle by the customer (usage history information 400) is collected in the data collection system 2.

The data management system 3 is a customer feature amount information 800 indicating a customer feature amount based on at least one of the customer information 200, the product information 300, and the usage history information 400 collected in the data collection system 2 (see FIG. 11). , Product feature amount information 900 (see FIG. 12) indicating the feature amount of the product, and utilization feature amount information 1000 (see FIG. 13) indicating the feature amount of the use of the product are generated. In the present embodiment, the customer feature amount is expressed by the customer tag, the product feature amount is expressed by the product tag, and the use feature amount is expressed by the use tag. The tag is a title of the feature quantity so that it is easy for people to understand. The data management system 3 executes a tagging process (see FIG. 16), assigns a customer tag to each customer, and assigns a product tag to each product. This tagging process may be executed periodically.

Further, the data management system 3 generates customer persona information 1100 (see FIG. 14) indicating the property of the customer and product persona information 1200 (see FIG. 15) indicating the property of the product based on the usage tag. Then, the data management system 3 determines the customer persona to be given to the customer's relationship with the product based on the customer tag given to the customer and the usage history information of the product by the customer. Further, the data management system 3 determines the product persona to be assigned to the product based on the product tag attached to the product. Then, the data management system 3 executes a recommendation generation process (see FIG. 17) to generate recommendation information suitable for the customer. This recommendation generation process may be executed periodically.

The dealer formulates a contact plan for the customer based on the recommendation information generated by the data management system 3. Then, the dealer contacts the customer according to the contact plan that has been devised. In addition, the dealer registers the result of contacting the customer in the data management system 3.

The customer decides to receive the vehicle at the dealer in response to the contact from the dealer. Then, when the customer stores the vehicle, the customer decides the maintenance content based on the content of the recommendation information. The customer then stocks the vehicle at the dealer.

The dealer will carry out the determined maintenance contents for the warehousing vehicle. In addition, the dealer inputs information related to the maintenance (hereinafter referred to as "maintenance information") into the data collection system. This maintenance information is used in the data management system 3 for the next tagging process, recommendation process, and the like.

By repeating the above service flow, the accuracy of recommendations to customers is improved.

FIG. 3 shows an example of the relationship between the customer tag, the product tag, the usage tag, the customer persona, and the product persona.

The data management system 3 applies the usage feature amount assignment rule 700 (see FIG. 10) to the usage history information 400, and uses the usage tags "commuting time", "acceleration smoothness", "urban area", "residential area", and " Generate "weekday evening", "bad weather", "short time", etc.

The data management system 3 applies a predetermined customer persona assignment rule to the customer tag and the usage tag, and generates the customer persona. As an example, the customer persona granting rule is for a combination of one or more customer tags given to a customer and one or more usage tags given to the customer's use of a product (vehicle). It is the table information associated with the customer persona. The customer persona is information indicating the nature of the customer, and is given a name indicating the nature. A customer persona indicates the nature of an individual customer that reflects the attributes and preferences of the customer and the purpose and method of use of the customer's product. In this embodiment, customer personas such as "experienced margin", "convenient daily life", "cospa first", "fun family drive", and "attacking runner" are exemplified.

Further, the data management system 3 applies a predetermined product persona assignment rule to the product tag and the usage tag to generate the product persona. As an example, the product persona assignment rule associates a product persona with a combination of one or more product tags attached to a product and a usage tag attached to the customer's use of the product. Table information. A product persona is information that indicates the properties of a product, and is given a name that indicates the properties. A product persona indicates the properties of an individual product that reflects the attributes and performance of the product, the purpose for which the product is used, and how it is used. In this embodiment, product personas such as "heavy sedan", "city riding compact", "family outing", and "outdoor sporty" are exemplified.

In addition, the data management system 3 applies the product feature amount addition rule 600 (see FIG. 9) to the product information 300 of the vehicle type W, and sets the product tags "luxury-oriented", "large displacement" and "livability". Give.

For example, it is assumed that the customer A and the customer B shown in FIG. 3 are a married couple, purchase a vehicle of vehicle type W, and use it jointly. In this case, the data management system 3 assigns the following customer tags to the customer A and the customer B.

The data management system 3 applies the customer feature amount assignment rule 500 (see FIG. 8) to the customer information 200 of the customer A, and applies the customer tags "senior male", "rich", and "luxury-oriented" to the customer A. And "long-term customers" are granted. Further, the data management system 3 applies the customer feature amount giving rule 500 to the customer information 200 of the customer B, and gives the customer tags "housewife" and "health-oriented" to the customer B.

The data management system 3 is based on the customer tag given to the customer A and the usage tag determined from the usage history information 400 of the customer A, with respect to the customer A's relationship with the vehicle type W, the customer persona "Veteran". "Margin" is given. Further, the data management system 3 is a customer persona for the relationship of the customer B with respect to the vehicle type W based on the customer tag given to the customer B and the usage tag determined from the usage history information 400 of the customer B. Give "convenient everyday life".

Further, the data management system 3 assigns a product persona "heavy sedan" to the vehicle type W based on the product tag attached to the vehicle type W and the usage tag determined from the usage history information 400 of the vehicle type W. ..

By the above processing, the customer persona "Veteran's margin" indicating the relationship of the customer A with the vehicle type W and the customer persona "Convenient daily life" indicating the relationship of the customer B with the vehicle type W are generated. In addition, a product persona "heavy sedan" for vehicle type W is generated. The data management system 3 can generate recommendation information for customer A and / or customer B by using this customer persona and product persona. In addition, the dealer can formulate a recommendation plan for customer A and / or customer B with reference to the customer persona and the product persona.

FIG. 4 shows a configuration example of the data management system 3. The data management system 3 has a storage unit 101, a feature amount acquisition unit 102, a persona identification unit 103, and a recommendation unit 104.

The storage unit 101 includes customer information 200, product information 300, usage history information 400, customer feature amount giving rule 500, product feature amount giving rule 600, usage feature amount rule, customer feature amount information 800, product feature amount information 900, and usage. The feature amount information 1000, the customer persona information 1100, the product persona information 1200, and the like are stored. The storage unit 101 may be configured as a DB (DataBase).

The feature amount acquisition unit 102 applies the customer feature amount addition rule 500 to the customer information 200 of the customer, and determines the customer tag to be given to the customer. The feature amount acquisition unit 102 applies the product feature amount assigning rule 600 to the product information 300 of the product, and determines the product tag to be attached to the product. Further, the feature amount acquisition unit 102 generates a usage tag based on the usage history information 400 of the product. It should be noted that the feature amount acquisition unit 102 does not necessarily have to generate these tags. For example, the feature amount acquisition unit 102 may acquire a tag generated by another functional block.

The persona specifying unit 103 applies the customer persona assigning rule to a plurality of usage tags and generates the customer persona information 1100. Further, the persona specifying unit 103 applies the product persona assigning rule to a plurality of usage tags to generate the product persona information 1200. The persona specifying unit 103 identifies the product persona to be given to the product based on the product tag given to the product and the usage tag related to the product. Further, the persona identification unit 103 assigns the customer persona to the relationship between the product and the customer based on the customer tag given to the customer and the usage tag determined from the usage history information 400 of the customer's product. To identify.

The recommendation unit 104 generates recommendation information for the customer based on the customer persona and / or the product persona given to the customer's product by the persona identification unit 103.

FIG. 5 shows an example of customer information 200. The customer information 200 has information about the customer. The customer information 200 includes basic customer information, vehicle purchase information, and contact information.

The customer basic information has basic information about the customer. For example, basic customer information includes customer ID, store ID (dealer ID), person in charge ID, customer's first and last name, gender, age, occupation, address, customer registration date, customer's driver's license acquisition date, and cumulative possession as data items. It has the number of units, telephone number, e-mail address, membership type, contact information, etc.

Vehicle purchase information has information regarding the purchase of a vehicle. For example, vehicle purchase information includes vehicle ID, store ID (dealer ID) of sale, vehicle delivery date, main unit list price, main unit selling price, total accessory selling price, total expenses, total payment, discount rate, accessory ratio as data items. , Purchase classification, payment method, and opportunity for business negotiations.

The contact information has information about the contact from the dealer to the customer. For example, the contact information has, as data items, a contact ID, a person in charge ID, a contact customer ID, a corresponding customer ID, a contact date and time, a contact purpose, recommended contents, a contact result, a related warehousing ID, a comment, and the like.

Here, the contact customer ID is the ID of the customer with whom the dealer has contacted, and the corresponding customer ID is the ID of the customer who actually responded to the contact from the dealer. For example, when the dealer contacts the husband (representative of the family) and the wife responds, the contact customer ID becomes the husband's ID and the corresponding customer ID becomes the wife's ID.

FIG. 6 shows an example of product information 300. Product information 300 has information about the product. The product information 300 includes vehicle basic information, vehicle accessory information, warehousing history information, and maintenance detailed information.

The vehicle basic information has basic information about the vehicle. For example, the vehicle basic information includes the vehicle ID, the store ID (dealer ID) of the person in charge, the person in charge ID, the owned customer ID, the customer ID, the delivery date, the vehicle name, the color, the displacement, and the vehicle as data items. Has a type, etc.

Vehicle accessory information has information about vehicle accessories. For example, the vehicle accessory information has accessory ID, vehicle ID, parts and work ID, accessory name, list price, selling price, and the like as data items.

The warehousing history information has information on warehousing to the dealer. For example, the warehousing history information includes warehousing ID, vehicle ID, warehousing date, warehousing date, store ID, customer ID, person in charge ID, warehousing purpose, number of maintenance details, total amount before discount, payment amount, and warehousing. Has mileage, etc.

The maintenance detailed information has detailed information regarding the maintenance of the vehicle. For example, the maintenance detailed information has maintenance detail ID, vehicle ID, warehousing ID, warehousing purpose, maintenance person ID, parts and work ID, maintenance name, amount of money, and the like as data items.

FIG. 7 shows an example of the usage history information 400. The usage history information 400 has information regarding the usage history of the vehicle. For example, the usage history information 400 includes trip ID, vehicle ID, driving date, start time, end time, weather, time zone type, departure place, destination, driving time, mileage, average speed, and data items. It has a vehicle type, etc.

Here, the trip ID is assigned to each movable unit of the product. For example, one trip ID is assigned to the period from the start of the vehicle engine to the stop.

FIG. 8 shows an example of the customer feature amount giving rule 500. The customer feature amount giving rule 500 has a rule used for determining a customer tag to be given to a customer.

For example, when the customer information 200 meets the condition of the purchase category "replacement trade-in", the customer tag "trust" may be given to the customer. Further, when the customer information 200 meets the conditions of the payment means "cash", the customer tag "rich" may be attached to the customer. Further, when the customer information 200 meets the condition of the family "with infant", the customer tag "safe driving" and / or "family" may be attached to the customer.

FIG. 9 shows an example of the product feature amount giving rule 600. The product feature amount giving rule 600 has a rule used for determining a product tag to be given to a product.

For example, when the product information 300 meets the condition of the main body price "more than 5 million", the product tag "luxury-oriented" may be attached to the product. If the product information 300 meets the purpose of warehousing "free inspection of new car" and the timing of warehousing "6 months", the product tag "free" and / or "reliability" for the product (model). May be given. In addition, when the product information 300 conforms to the parts and work name "additive ABC" and the warehousing timing "every year", the product tag "fuel efficiency improvement" and / or "improvement of fuel consumption" and / or " "Running performance" may be given. Further, when the product information 300 conforms to the part name "Dashcam xxxx", the product tag "safety" and / or "high functionality" may be added to the product (vehicle model).

FIG. 10 shows an example of the usage feature amount giving rule 700. The usage feature amount assigning rule 700 has a rule used for determining a usage tag to be assigned to the customer's use of the product.

For example, if one trip ID of the usage history information 400 meets the conditions of the time zone type "weekday morning", the departure place "residential area", and the destination "office district", the usage tag is applied to the trip ID. "Commuting" may be granted.

Further, the conditions (for example, the threshold value) in the usage feature amount granting rule 700 may change according to the product tag attached to the product to which the usage feature amount granting rule 700 is applied. For example, when determining whether or not a utility feature amount of "rapid acceleration" is applicable based on the numerical value of acceleration, it may be determined with a different threshold value depending on the vehicle type. For example, if the vehicle type is a high-performance sports car, the threshold value may be set higher, and if the vehicle type is a family car, the threshold value may be set lower.

FIG. 11 shows an example of customer feature amount information 800. The customer feature amount information 800 is information indicating a customer feature amount (customer tag).

In the first line of the customer feature amount information 800 shown in FIG. 11, the weighting of the customer ID “C0001” of the vehicle ID “V0001” is “70%”, and the customer IDs include the customer tags “luxury oriented” and “ Indicates that "safety", "commuting" and "trust" are given. The weighting value indicates the weighting ratio of each customer when one vehicle is shared by a plurality of customers.

Further, the value in parentheses of the customer feature amount information 800 shown in FIG. 11 indicates the frequency of the customer tag. The higher the frequency, the stronger the tendency (weight) of the customer tag. For example, "luxury-oriented (80)" indicates that the frequency of the customer tag "luxury-oriented" is "80".

FIG. 12 shows an example of product feature quantity information 900. The product feature amount information 900 is information indicating the feature amount (product tag) of the product.

The first line of the product feature amount information 900 shown in FIG. 12 is that the vehicle ID "V0001" is given the product tags "luxury-oriented", "looks beautiful", "driving performance", and "multipurpose". Is shown. The value in parentheses of the product feature amount information 900 shown in FIG. 12 indicates the frequency of the product tag, as in FIG.

FIG. 13 shows an example of the utilization feature amount information 1000. The usage feature amount information 1000 is information indicating a feature amount (usage tag) related to the use of the product (vehicle).

The first line of the usage feature amount information 1000 shown in FIG. 13 indicates that the usage tag “commuting” is attached to the vehicle ID “V0001” of the trip ID “TR0001”.

FIG. 14 shows an example of customer persona information 1100. The customer persona information 1100 is information indicating the nature (persona) of the customer in relation to the product.

The first line of the customer persona information 1100 shown in FIG. 14 indicates that the customer persona "experienced margin" is given to the relationship of the customer ID "C0001" with respect to the vehicle ID "V0001". Further, the second line of the customer persona information 1100 indicates that the customer persona "safety first" is given to the relationship of the customer ID "C0002" with respect to the vehicle ID "V0001". In this way, the customer persona may differ depending on the usage mode of the customer even if the vehicle is the same.

FIG. 15 shows an example of product persona information 1200. The product persona information 1200 is information indicating the property (persona) of the product.

The first line of the product persona information 1200 shown in FIG. 15 indicates that the vehicle ID "V0001" is held by the owned customer ID "C0001" and the product personas "heavy" and "sedan" are given. ..

FIG. 16 is a flowchart showing an example of the tag addition process. The feature amount acquisition unit 102 executes the following tagging process for each vehicle.

The feature amount acquisition unit 102 applies the customer feature amount addition rule 500 to the customer basic information and the vehicle purchase information included in the customer information 200, and determines the customer tag to be given to the customer indicated by the customer information 200. Further, the feature amount acquisition unit 102 applies the product feature amount addition rule 600 to the vehicle basic information included in the product information 300, and determines the product tag to be given to the vehicle indicated by the product information 300 (S201).

When the assigned customer tag and the customer tag determined in S201 are different, the feature amount acquisition unit 102 updates the assigned customer tag with the customer tag determined in S201. Further, when the added product tag and the product tag determined in S201 are different from each other, the feature amount acquisition unit 102 updates the assigned product tag with the product tag determined in S201 (S202).

The feature amount acquisition unit 102 divides the travel history information included in the usage history information 400 corresponding to the vehicle into trip information units (S203). Then, the feature amount acquisition unit 102 applies the usage feature amount assigning rule 700 to the trip information, and determines the usage tag to be assigned to the trip information (S204).

The feature amount acquisition unit 102 aggregates the usage tags attached to each trip information, and identifies the characteristic usage tags from the aggregation result. Then, the feature amount acquisition unit 102 attaches the specified characteristic usage tag to the vehicle as a product tag. Further, when the trip information can be classified for each driver (customer), the feature amount acquisition unit 102 attaches the specified characteristic usage tag to the customer as a customer tag (S205).

The feature amount acquisition unit 102 applies a predetermined feature amount addition rule to the contact information included in the customer information 200, and determines a tag to be attached to the contact information (S206). For example, a feature amount addition rule may be set so that the tag "long-term customer" is given if the contact continues for a predetermined number of years or more.

The feature amount acquisition unit 102 aggregates the tags attached to the contact information for each customer, and identifies the characteristic tags from the aggregation result. Then, the feature amount acquisition unit 102 attaches the specified characteristic tag to the customer as a customer tag (S207).

The feature amount acquisition unit 102 applies a predetermined feature amount addition rule to the warehousing history information and / or maintenance detailed information included in the product information 300, and determines a tag to be given to the warehousing history information and / or maintenance detailed information. (S208).

The feature amount acquisition unit 102 aggregates the tags attached to the warehousing history information and / or the maintenance detailed information for each vehicle, and identifies the characteristic tags from the aggregation result. Then, the feature amount acquisition unit 102 attaches the specified characteristic tag to the vehicle as a product tag. Further, the feature amount acquisition unit 102 adds the specified characteristic tag to the customer as a customer tag, if necessary (S209).

By the above processing, a customer tag is given to each customer, and a product tag is given to each product.

FIG. 17 is a flowchart showing an example of the recommendation generation process. The recommendation unit 104 executes the following processing for each vehicle.

The recommendation unit 104 acquires the next milestone (S301). Milestones are timings that trigger warehousing, such as various regular inspections and store visit campaigns. If the vehicle does not correspond to a milestone, the recommendation unit 104 ends this process, and if the vehicle corresponds to a milestone, proceeds to the next S302.

The recommendation unit 104 acquires detailed maintenance information having a track record of being implemented at milestones, including other vehicles (S302). Then, the recommendation unit 104 repeats the following processes from S303 to S306 for each maintenance detailed information acquired in S302.

If the maintenance item (consumables, etc.) for which detailed maintenance information is essential, the recommendation unit 104 adds the maintenance item to the recommendation information (S303).

When the tag attached to the maintenance item of the maintenance detailed information and the product tag attached to the vehicle match, the recommendation unit 104 determines the maintenance item and the priority (recommendation degree) of the maintenance item. It is added to the recommendation information (S304).

When the tag attached to the maintenance item of the maintenance detailed information and the customer tag attached to the customer of the vehicle match, the recommendation unit 104 indicates the maintenance item, the customer name, and the priority of the maintenance item. (Recommendation level) is added to the recommendation information (S305).

The recommendation unit 104 outputs the maintenance product included in the recommendation information. At that time, the recommendation unit 104 outputs the maintenance implementation status of the vehicle, and if the target customer is clear, the customer name is also written (S306).

By the above processing, it is possible to make a recommendation suitable for each customer. For example, if the maintenance item "air purifier" is given the tag "clean lover" and the customer "customer B" is given the customer tag "clean lover", these tags match. Recommend the air purifier to customer B.

FIG. 18 shows an example of a list screen for dealers.

On the list screen, the contents of contact information for each customer are displayed in a list. As the contact information, for example, the importance, the contact customer, the possessed customer, the response deadline, the contact content, the contact means, the vehicle, and the warehousing guideline are displayed. From this list screen, the dealer can know the appropriate timing of contact with the customer, the content of the contact, the means of contact, and the like.

FIG. 19 shows an example of a vehicle information screen for a dealer.

On the vehicle information screen, the customer information 200 of the customer and the product information 300 of the vehicle owned by the customer are displayed. In addition, a customer tag, a product tag, and a usage tag are displayed on the vehicle information screen. In addition, the product persona assigned to the vehicle and the customer persona assigned to each customer who uses the vehicle are displayed on the vehicle information screen. The dealer can refer to this vehicle information screen to make an appropriate recommendation plan for the customer.

FIG. 20 shows an example of a maintenance recommendation screen for dealers.

On the maintenance recommendation screen, maintenance items included in the recommendation information for the customer are displayed. In addition, the tag attached to the maintenance item is displayed on the maintenance recommendation screen. The dealer can refer to this maintenance recommendation screen and recommend appropriate maintenance items to the customer who has received the vehicle.

FIG. 21 shows an example of a warehousing promotion screen for customers. The warehousing promotion screen may be the screen of the customer's smartphone application.

Information that prompts the customer to receive the goods is displayed on the goods receipt promotion screen. In addition, a button for contacting the dealer is displayed on the warehousing promotion screen. As a result, the customer becomes aware of the need for warehousing and can easily contact the dealer. Therefore, the possibility of warehousing at the dealer is improved.

FIG. 22 shows a hardware configuration example of the data management system 3.

The data management system 3 includes a processor 2001, a main memory 2002, a storage device 2003, a communication device 2004, an input device 2005, and a display device 2006. These components 2001 to 2006 are connected by an internal bus 2007 so as to be able to communicate in both directions.

The processor 2001 is, for example, a CPU (Central Processing Unit). The main memory 2002 is, for example, a DRAM (Dynamic Random Access Memory). The storage device 2003 is, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The input device 2005 is, for example, a keyboard and a mouse. The display device 2006 is, for example, a display device.

The feature amount acquisition unit 102, the persona identification unit 103, and the recommendation unit 104 described above are realized by reading the computer program recorded in the storage device 2003 into the main memory 2002 and executing the computer program in the processor 2001. You can. Further, the computer program may be acquired from an external device via the communication device 2004. Further, the storage unit 101 may be realized by the main memory 2002 and / or the storage device 2003 shown in FIG.

<Summary of the present embodiment>
The data management system 3 according to the present embodiment has a storage unit 101 that stores usage history information 400, which is information related to the usage history of the product provided to the customer, and a usage feature amount (usage) based on the usage history information 400. It has a feature amount acquisition unit 102 for acquiring a tag) and a persona specifying unit 103 for specifying a customer property (customer persona) based on a used feature amount (used tag).

As a result, the data management system 3 generates the usage feature amount based on the usage history information 400 and identifies the customer property (customer persona) based on the usage feature amount. Therefore, the customer property (customer) appearing in the usage history. Persona) can be known.

The storage unit 101 stores the product information 300, which is information about the product, the feature quantity acquisition unit 102 acquires the product feature quantity based on the product information 300, and the persona identification unit 103 acquires the product feature quantity and the product feature quantity. The nature of the product (product persona) may be specified based on.

As a result, the data management system 3 identifies the properties of each product (product persona) based on the usage feature amount and the product feature amount, so that the property of each product including the use by the customer can be known. Can be done.

The use of the product includes the quantified use in which the mode is quantified, and the feature amount acquisition unit 102 determines whether or not the quantified use shown in the usage history information 400 corresponds to the used feature amount. The determination may be made using a threshold value at which the value is determined according to the information 300.

As a result, the data management system 3 can change the threshold value for determining the usage feature amount according to the product, and therefore obtains an appropriate usage feature amount even when the usage feature amount changes due to the relative relationship with the product. can do. For example, when determining whether or not a utility feature amount of "rapid acceleration" is applicable based on the numerical value of acceleration, the determination may be made with a different threshold value depending on the vehicle type. For example, a high-performance sports car may have a higher threshold, and a family car may have a lower threshold.

The storage unit 101 stores customer information 200, which is information about the customer, the feature amount acquisition unit 102 acquires the customer feature amount based on the customer information 200, and the persona identification unit 103 acquires the customer feature amount and the usage feature amount. The nature of the customer (customer persona) may be specified based on.

As a result, the data management system 3 identifies the customer characteristics (customer persona) based on the usage feature amount and the customer feature amount, so that the customer characteristics including the usage method can be acquired.

A tag indicating a condition for determining whether or not a product, a customer, or the use of a product is applicable, and a feature amount to be given to the product, the customer, or the use of the product when the condition is met for the product, the customer, or the use of the product. The feature amount giving rule corresponding to the above is set in advance, and the feature amount acquisition unit 102 is associated with the product, the customer, or the use of the product according to the corresponding condition in the feature amount giving rule. Tags may be attached to the product, the customer, or the use of the product.

As a result, the data management system 3 predetermines a tag for indicating the feature amount of the product, the customer, or the use of the product, and sets the tag corresponding to the product, the customer, or the use of the product as the product, the customer, or the product. Since it is given to the use of the product, the tag indicating the product or the customer and the tag indicating the characteristic amount of the use of the product by the customer can be shown more concisely and appropriately.

The persona identification unit 103 identifies a customer persona indicating the nature of the customer based on the tag given to the customer and the tag given to the use, and is based on the tag given to the product and the tag given to the use. You may specify a product persona that indicates the nature of the product.

As a result, the data management system 3 identifies the product persona indicating the property of the product and the customer persona indicating the property of the customer by using the tag indicating the feature quantity to be used. It can reflect and show the nature of customers and products concisely and appropriately.

The recommendation unit 104 may recommend at least one of additional services related to the product or additional products related to the product or a new product replacing the product based on the product information 300 and the nature of the customer.

As a result, the data management system 3 determines the recommended product or service based on the product information 300 and the property of the customer, so that the service or product that reflects the property of the customer appearing in the usage history can be recommended.

The persona identification unit 103 identifies the nature of at least one customer who uses the product for one said product, and the recommendation unit 104 recommends additional services or services based on the nature of the product and the nature of the customer. You may identify at least one of the additional products or new products and the approached customer who recommends at least one of the additional services or additional products or new products.

As a result, the data management system 3 sets one or more customers who use the product for the product, and identifies the person who recommends the service or the product from the customers set in the product. It will be possible to recommend services and products to the right people. For example, when a husband and wife share a vehicle, it is possible to present to the wife products and services that are more effective in approaching the wife than the husband.

The product is an automobile, the usage history information 400 includes travel history information indicating the state of driving from the departure place to the arrival point, and the product information 300 includes information on the vehicle type of the automobile, and customer information. The 200 contains information on the attributes of the customer, and when notifying when the maintenance should be performed, the recommendation unit 104 recommends a part or implementation that recommends replacement in the maintenance based on the customer persona and the product persona. At least one of the maintenance items may be extracted and notified.

As a result, for example, when a car dealer notifies a customer who has purchased a car when to carry out regular maintenance, in addition to the car and the customer's information, the history of the customer's driving of the car is also taken into consideration. It is possible to propose parts that are recommended for replacement and maintenance items that are recommended for implementation.

In the data management method according to the present embodiment, the usage history information 400, which is information on the usage history of the product provided to the customer, is stored in the storage unit 101, and the processor uses the usage feature amount based on the usage history information 400. And identify the nature of the customer based on the feature quantity used.

The above-described embodiments are examples for the purpose of explaining the present invention, and the scope of the present invention is not limited to the embodiments. One of ordinary skill in the art can practice the present invention in various other aspects without departing from the gist of the present invention.

1 ... Service system 2 ... Data collection system 3 ... Data management system 4 ... Information provision system 5 ... Terminal 101 ... Storage unit 102 ... Feature quantity acquisition unit 103 ... Persona specific unit 104 ... Recommendation unit 200 ... Customer information 300 ... Product information 400 … Usage history information 500… Customer feature amount granting rule 600… Product feature amount granting rule 700… Usage feature amount granting rule 800… Customer feature amount information 900… Product feature amount information 1000… Usage feature amount information 1100… Customer persona information 1200… Product persona information

Claims (7)

A storage unit that stores usage history information that is information about the usage history of the product provided to the customer, product information that is information about the product, and customer information that is information about the customer .
With a feature amount acquisition unit that acquires the feature amount of the use based on the usage history information, acquires the feature amount of the product based on the product information, and acquires the feature amount of the customer based on the customer information. ,
A persona specifying unit that specifies the property of the customer based on the feature amount of the customer and the feature amount of the use, and specifies the property of the product based on the feature amount of the use and the feature amount of the product .
A recommendation section that recommends at least one of an additional service related to the product, an additional product related to the product, or a new product replacing the product based on the product information and the nature of the customer.
Have,
The persona identification unit identifies the nature of at least one customer who uses the product for one product.
The recommendation unit includes at least one of the additional service or the additional product or the new product recommended based on the property of the product and the property of the customer, and the additional service or the additional product or the new product. Identify at least one of the recommended customers to approach,
Data management system. The storage unit further stores product information, which is information about the product, and stores the product information.
The use includes a quantified use in which the aspect is quantified.
The feature amount acquisition unit determines whether or not the digitized use shown in the usage history information corresponds to the feature amount of the use, using a threshold value whose value is determined according to the product information.
The data management system according to claim 1. The storage unit further stores product information, which is information about the product, and stores the product information.
The use includes a quantified use in which the aspect is quantified.
The feature amount acquisition unit determines whether or not the digitized use shown in the usage history information corresponds to the feature amount of the use, using a threshold value whose value is determined according to the product information.
The data management system according to claim 1 . Conditions for determining whether or not the product, the customer, or the use is applicable, and features imparted to the product, the customer, or the use when the product, the customer, or the use meets the above conditions. A feature amount assignment rule that associates with a tag indicating the amount is set in advance.
The feature amount acquisition unit attaches a tag associated with the product, the customer, or the use to the applicable condition to the product, the customer, or the use according to the feature amount granting rule. Grant,
The data management system according to claim 1. The persona specific part is
A customer persona indicating the nature of the customer is identified based on the tag given to the customer and the tag given to the use.
Identify a product persona that indicates the properties of the product based on the tag attached to the product and the tag attached to the use.
The data management system according to claim 4 . The product is an automobile
The usage history information includes travel history information indicating the state of driving from the departure place to the arrival place.
The product information includes information on the vehicle type of the automobile.
The customer information includes information on the attributes of the customer.
When notifying when maintenance should be performed, the recommendation section extracts at least one of the parts recommended for replacement or the maintenance items recommended for maintenance in the maintenance based on the customer persona and the product persona. Notice,
The data management system according to claim 5 . The usage history information, which is information about the usage history of the product provided to the customer, the product information, which is the information about the product, and the customer information, which is the information about the customer, are stored in the storage unit.
The feature amount of the use is acquired based on the usage history information, the feature amount of the product is acquired based on the product information, and the feature amount of the customer is acquired based on the customer information .
The property of the customer is specified based on the feature amount of the customer and the feature amount of the use , and the property of the product is specified based on the feature amount of the use and the feature amount of the product.
Based on the product information and the nature of the customer, at least one of the additional services related to the product, the additional products related to the product, or the new product replacing the product is recommended .
That's what the computer does,
For one said product, identify the nature of at least one customer who uses the product.
At least one of the additional services or the additional products or the new products recommended and at least one of the additional services or the additional products or the new products based on the nature of the product and the nature of the customer. Identify the recommended approach to the customer,
A data management method that a computer does.

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