WO2020202453A1

WO2020202453A1 - Customer insight analysis method, customer insight analysis device, information processing method using sense-of-value data, and information processing device using sense-of-value data

Info

Publication number: WO2020202453A1
Application number: PCT/JP2019/014560
Authority: WO
Inventors: 圭祐森島; 謙作磯部; 中尾　浩; 佑輔梅澤; 裕章木邨
Original assignee: ヤマハ発動機株式会社
Priority date: 2019-04-01
Filing date: 2019-04-01
Publication date: 2020-10-08
Also published as: WO2020204099A1; TWI762899B; JPWO2020204099A1; JP7210703B2; TW202040489A

Abstract

Provided is a customer insight analysis method capable of acquiring sense-of-value data while ensuring a degree of freedom in designing of hardware resources of an information processing device. This customer insight analysis method involves: acquiring, on the basis of data-conversion-use leaning vehicle traveling data including traveling data while a customer is on board a data conversion leaning vehicle and data-conversion-use evaluation data of a plurality of customers with respect to the boarding, sense-of-value conversion data generated by associating sense-of-value data indicating a sense of value, leaning vehicle traveling data, and evaluation data with one another; acquiring analysis-use leaning vehicle traveling data including traveling data in the case where the customer is on board a leaning vehicle to be analyzed and analysis-use evaluation data of the customer with respect to the boarding; converting the acquired analysis-use leaning vehicle traveling data and the acquired analysis-use evaluation data into conversion sense-of-value data relating to the sense of value of a customer to be analyzed by using the acquired sense-of-value conversion data; and generating and outputting output sense-of-value data by using the converted conversion sense-of-value data.

Description

Customer insight analysis method, customer insight analyzer, information processing method using value data, and information processing device using value data

The present invention relates to a customer insight analysis method for analyzing customer insights, a customer insight analysis device, an information processing method using value data, and an information processing device using value data.

An information processing system that processes information using customer preferences is known. As a configuration for performing information processing using the taste of a customer, for example, the configurations disclosed in Patent Documents 1 to 6 are known.

Patent Document 1 discloses a system that presents to the user supplementary information related to the advertisement that the user feels interested in.

Patent Document 2 discloses a system in which a set of drivers is presented to a user so that the user can select a driver.

Patent Document 3 discloses an electronic commerce system that introduces a seller who can sell a product by utilizing a user's preference and sends a purchase request to the seller.

Patent Document 4 discloses a system that proposes a recipe based on a user's taste and available materials stored in a storage such as a refrigerator.

Patent Document 5 discloses a system that analyzes hotel services based on user preferences.

Patent Document 6 discloses a system that analyzes a customer's preference based on the customer's product purchase history.

U.S. Patent Publication No. 2019/0005549 U.S. Patent Publication 2015/0206267 U.S. Pat. No. 10134078 U.S. Pat. No. 9821344 U.S. Patent Publication No. 2019026793 U.S. Patent Publication No. 2017/010403

By the way, there are as many user preference data as there are types of user behavior. The preference data is data showing superficial preference.

If there is highly versatile data indicating the preference of a potential user, that is, data indicating a sense of value, the preference is indicated by combining the data indicating the sense of value and the data indicating the superficial preference. The utilization of data can be further promoted.

Therefore, in order to obtain highly versatile data showing potential preference, that is, data showing so-called values, it is conceivable to use data showing preference for many types of user behavior. However, when such data showing preference for many types of user behavior is used, the types of data processed by the system become very large.

If the number of types of data processed by the system becomes very large, the load on the hardware of the system will increase. Therefore, since the hardware resources required by the system increase, the design of the hardware resources of the system is restricted. Therefore, the degree of freedom in designing the hardware resources of the system is reduced.

The present invention provides a customer insight analysis method capable of acquiring highly versatile data showing potential customer preferences, so-called values, while ensuring the degree of freedom in designing hardware resources of an information processing device. The purpose is to provide.

The customer insight analysis method according to the embodiment of the present invention is a customer insight analysis method for analyzing customer values. Lean vehicle driving data for data conversion including driving data when a customer is on a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left, and lean vehicle driving data for data conversion at that time. Based on the evaluation data for data conversion of a plurality of customers for the ride, the value conversion data generated by associating the value data indicating the values with the lean vehicle driving data and the evaluation data is acquired. Lean vehicle driving data for analysis, including driving data when the customer to be analyzed is in a lean vehicle to be analyzed that tilts to the right when turning right and tilts to the left when turning left, and its The evaluation data for the analysis of the customer for the time of boarding is acquired. The acquired lean vehicle running data for analysis and the acquired evaluation data for analysis are converted into conversion value data related to the values of the customer to be analyzed by using the value conversion data. Using the converted conversion value data, output value data for output is generated. The generated output value data is output.

The customer evaluation data is data that reflects the customer's preference with respect to the vehicle running data of the lean vehicle. Therefore, based on the lean vehicle traveling data and the evaluation data, it is possible to generate the value conversion data that associates the lean vehicle traveling data, the evaluation data, and the value data. Using this value conversion data, lean vehicle driving data and evaluation data can be converted into value data of an analysis target person who is a customer. In this way, the value data can be obtained from the lean vehicle driving data, the evaluation data, and the value conversion data. Therefore, the customer insight analysis is performed as compared with the case of using the data showing the preference for many types of user behavior. The amount of data processed by the device can be reduced. Therefore, while ensuring the degree of freedom in designing the hardware resources of the information processing device, it is possible to acquire highly versatile data showing the tastes of potential users, that is, data showing so-called values.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. Including many. The lean vehicle driving data for analysis includes more data in which changes in driver's operation with respect to the lean vehicle for analysis are reflected than data in which changes in operation with respect to the lean vehicle for analysis are not reflected.

With this configuration, the lean vehicle driving data strongly reflects the change in the operation of the lean vehicle after the driver makes a judgment. In other words, the lean vehicle driving data contains a lot of stimuli felt by the customer who is riding the lean vehicle. The stimulus felt by the customer affects the customer's evaluation. Moreover, in the case of a lean vehicle, there are many variations in the stimulus felt by the customer who is riding the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

The stimulus includes not only physical stimuli such as vibration received from the vehicle, but also psychological stimuli received during a series of boarding activities such as discomfort received from the boarding / alighting position and discomfort received from the waiting time.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is the lean vehicle operation input data for data conversion related to the operation input to the lean vehicle for data conversion, and the data conversion related to the behavior of the lean vehicle for data conversion. It includes at least one of the lean vehicle behavior data of the above and the lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis includes lean vehicle operation input data for analysis related to operation input to the lean vehicle for analysis, and lean vehicle behavior data for analysis related to the behavior of the lean vehicle for analysis. And include at least one of the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.

Since the lean vehicle operation input data is data related to the operation input by the driver, it more reflects the result of the driver's judgment. In lean vehicles, there are many types of driver's operations and they are complicatedly related, so there are many variations in operations. The result of the operation input is strongly reflected in the lean vehicle behavior data and the lean vehicle position data. With this configuration, the lean vehicle driving data more strongly reflects the change in the operation of the lean vehicle after the driver makes a judgment. In other words, the lean vehicle driving data contains more stimulus felt by the customer in the lean vehicle. Moreover, in the case of a lean vehicle, there are more variations in the stimulus felt by the customer riding the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle traveling data for analysis includes lean vehicle traveling environment data for analysis related to the traveling environment in which the lean vehicle for analysis is traveling.

Driving environment data is considered to be an example of external stress received by drivers and customers. The driving environment data influences the judgment of the customer's evaluation of the ride. Therefore, by using the driving environment data, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road. The lean vehicle traveling data for analysis includes more data when the lean vehicle for analysis travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.

When a driver traveling on a public road is operating a lean vehicle, the driver has more judgments, has more choices of judgment, and is easily exposed to external stress. The data contains more variations. In addition, while driving on public roads, customers are also easily exposed to external stress, which affects the evaluation of riding. Therefore, by using the lean vehicle driving data including a large amount of data when traveling on a public road, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left. The lean vehicle driving data for analysis includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for analysis.

By using lean vehicle driving data in a state where the driver's judgment options are limited but multiple are left, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle travel data for data conversion includes data in a state where the customer is not on board. The lean vehicle driving data for analysis includes data in a state where the customer is not on board.

By using lean vehicle driving data when the customer is not on board, for example, lean vehicle driving data before and after the customer is on board, the physical or psychological stimulus received by the customer from the driving data of the lean vehicle can be further analyzed. It will be easier to do. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle travel data for data conversion includes vehicle type-related data related to the vehicle type of the lean vehicle. The lean vehicle travel data for analysis includes vehicle type-related data related to the vehicle type of the lean vehicle.

Vehicle type-related data includes data related to lean vehicle manufacturers and vehicle types. The customer's preference manufacturer and / or vehicle type influences the customer's preference. For example, a customer who prefers a luxury car has a strong demand for status and has a preference for high status. As a result, the customer's sense of values data can be acquired in relation to the evaluation of the customer's status.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The converted conversion value data is stored. The output value value data is generated by using the plurality of stored conversion value value data.

By using multiple conversion value data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The output value data is generated as information processing value data used for further information processing.

As a result, the value data obtained by the customer insight analysis method using the lean vehicle driving data for analysis of the analysis target lean vehicle driven by the analysis target person can be used in a further information processing device.

Therefore, it is possible to acquire data showing values that can be used for further information processing while ensuring the degree of freedom in designing the hardware resources of the information processing device.

The customer insight analyzer according to the embodiment of the present invention is a customer insight analyzer that analyzes customer insights. This customer insight analyzer tilts to the right when turning right and leans to the left when turning left. Lean for data conversion Lean for data conversion including driving data when the customer is in a lean vehicle for data conversion. Value conversion generated by associating value data indicating values with lean vehicle driving data and evaluation data based on vehicle driving data and evaluation data for data conversion of a plurality of customers for riding at that time. The value conversion data acquisition unit that acquires data and the driving data when the customer to be analyzed is in a lean vehicle to be analyzed that tilts to the right when turning right and tilts to the left when turning left. Lean vehicle driving data acquisition unit for analysis that acquires lean vehicle driving data for analysis including, and the customer to be analyzed leans to the right when turning right and leans to the left when turning left. The analysis evaluation data acquisition unit that acquires the evaluation data for the analysis of the customer with respect to the ride while riding in the vehicle, the lean vehicle running data for the acquired analysis, and the acquired evaluation data for the analysis. Output using the value data conversion unit that converts the acquired value conversion data into conversion value data related to the value of the customer to be analyzed, and the converted conversion value data. It includes an output value value data generation unit that generates output value value data for the purpose, and an output unit that outputs the generated output value value data.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. Including many. The lean vehicle driving data for analysis includes more data in which changes in driver's operation with respect to the lean vehicle for analysis are reflected than data in which changes in operation with respect to the lean vehicle for analysis are not reflected.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is the lean vehicle operation input data for data conversion related to the operation input to the lean vehicle for data conversion, and the data conversion related to the behavior of the lean vehicle for data conversion. It includes at least one of the lean vehicle behavior data of the above and the lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis includes lean vehicle operation input data for analysis related to operation input to the lean vehicle for analysis, and lean vehicle behavior data for analysis related to the behavior of the lean vehicle for analysis. And include at least one of the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle travel data for analysis further includes lean vehicle travel environment data for analysis related to the travel environment in which the lean vehicle for analysis travels.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The output value data is generated as information processing value data used for further information processing.

The information processing method using the value data according to the embodiment of the present invention is an information processing method using the output value data generated as the value data for information processing by the above-mentioned customer insight analysis method. This information processing method acquires the output value data. The first data different from the output value data is acquired. Using the output value data and the first data, a second data different from the output value data and the first data is generated. The second data is output.

The value data showing the values is data showing the tastes of potential users with high versatility. The information processing method using this value value data includes an information processing method using preference data as described in the patent document described in the background technology. However, it is not limited to the information processing method described in the patent document described in the background technology. Any information processing method that uses preference data may be used. For example, the first data and the second data may be data related to finance, insurance, market, goods, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

As a result, the acquired output value data and the acquired output value data, which are highly versatile data indicating the preference of the potential user, and the first data different from the output value data are used. The second data different from the first data is generated and output. Therefore, it is possible to generate and output the second data with higher accuracy.

The information processing device according to the embodiment of the present invention is an information processing device that uses the output value value data generated as the information processing value value data by the customer insight analyzer described above. This information processing device includes an output value data acquisition unit that acquires the output value data, a first data acquisition unit that acquires first data different from the output value data, the output value data, and the above. It includes a second data generation unit that generates the output value data and a second data different from the first data using the first data, and a second data output unit that outputs the second data.

The technical terms used in the present specification are used for the purpose of defining only specific examples, and there is no intention of limiting the invention by the technical terms.

As used herein, "and / or" includes all combinations of one or more relatedly listed components.

As used herein, the use of "including, including," "comprising," or "having," and variations thereof, are described features, processes, elements, components, and / or. , Identifying the existence of their equivalents, but may include one or more of steps, actions, elements, components, and / or groups thereof.

In the present specification, "attached", "connected", "combined", and / or their equivalents are used in a broad sense and are "direct and indirect" attachments. Includes both connection and connection. Further, "connected" and "connected" are not limited to physical or mechanical connections or connections, but can include direct or indirect connections or connections.

Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

Terms defined in commonly used dictionaries should be construed to have meanings consistent with their meaning in the context of the relevant technology and disclosure, unless expressly defined herein. , Is not interpreted in an ideal or overly formal sense.

It is understood that a number of techniques and processes are disclosed in the description of the present invention. Each of these has its own interests and can be used with one or more of the other disclosed technologies, or in some cases all.

Therefore, for the sake of clarity, the description of the present invention refrains from unnecessarily repeating all possible combinations of individual steps. However, the specification and claims should be read with the understanding that all such combinations are within the scope of the present invention.

This specification describes a customer insight analysis method, a customer insight analysis device, an information processing method using value data, and an information processing device using value data according to the present invention.

In the following description, a number of specific examples will be given to provide a complete understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention can be practiced without these specific examples.

Therefore, the following disclosure should be considered as an example of the invention and is not intended to limit the invention to the particular embodiments set forth in the drawings or description below.

[Lean vehicle]
In the present specification, the lean vehicle is a vehicle that turns in an inclined posture. Specifically, a lean vehicle is a vehicle that inclines to the left when turning to the left and to the right when turning to the right in the left-right direction of the vehicle. The lean vehicle may be a single-seater vehicle or a vehicle that can accommodate a plurality of people. The lean vehicle includes not only a two-wheeled vehicle but also all vehicles that turn in an inclined posture, such as a three-wheeled vehicle or a four-wheeled vehicle.

[Value data]
In the present specification, the value data is data showing a customer's evaluation standard determined by the customer's tastes and desires. In other words, the value data is highly versatile data showing the preference of a potential customer. Specifically, the value data relates to data on the customer's evaluation criteria indicating the degree of satisfaction of taste, data on the customer's evaluation criteria indicating the degree of health desire, and customer evaluation criteria indicating the degree of labor saving desire. Includes data and data on customer metrics that indicate the degree of social life-related aspirations. Customers are basically individuals. The customer may be a group of a plurality of people.

[Evaluation data]
In the present specification, the evaluation data is data related to the evaluation of the driver and the vehicle when the customer gets on the vehicle. The evaluation data is, for example, an evaluation of the driver and / or the vehicle when the customer gets on the vehicle, and the comprehensive evaluation felt by the customer is given on a 5-point scale. The highest evaluation is 5, and the smaller the number, the lower the evaluation. Further, the evaluation data may include the degree of reliability, comfort, economic efficiency including speed, and the like. The evaluation axis in the evaluation data is not limited to one. The evaluation axis in the evaluation data may have a plurality of items.

[Vehicle driving data]
In the present specification, the vehicle traveling data is data related to the traveling of a lean vehicle. Specifically, the vehicle traveling data includes lean vehicle operation input data related to driving operation input to a lean vehicle by a driver, lean vehicle behavior data related to lean vehicle behavior, and a position where a lean vehicle is traveling. It includes at least one data such as lean vehicle position data related to, lean vehicle driving environment data related to the driving environment in which the lean vehicle travels, and vehicle type information data of the lean vehicle. Further, the vehicle traveling data may include processed data obtained by processing lean vehicle operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data, lean vehicle vehicle type information data, and the like. The vehicle driving data includes processing data processed using other data such as lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle driving environment data, and lean vehicle model information data. You may be.

[Lean vehicle driving operation input data]
In the present specification, the lean vehicle driving operation input data is data related to the driver's operation input performed when the driver drives and operates the lean vehicle. Specifically, it may include data related to accelerator operation, brake operation, steering, or change in the position of the center of gravity due to a change in the driver's posture. Specifically, the lean vehicle driving operation input data may include operations of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving operation input data is data related to the driving operation input by the driver, the result of the driver's judgment is more reflected. In lean vehicles, there are many types of driver's driving operations and they are complicatedly related, so there is a tendency for many variations. Further, the lean vehicle driving operation input data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle driving operation input data may include data acquired from a sensor or the like and processing data processed using other data.

[Lean vehicle behavior data]
In the present specification, the lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the operation input of the driver while operating the lean vehicle. Specifically, the lean vehicle behavior data includes, for example, the acceleration, speed, and angle of the lean vehicle that change when the driver who is the analysis target operates the driving operation. That is, the lean vehicle behavior data changes the posture including steering of the lean vehicle and changing the position of the center of gravity when the driver who is the analysis target operates the accelerator or the brake to accelerate or decelerate the lean vehicle. It is data showing the behavior of a lean vehicle that occurs in some cases.

Further, the lean vehicle behavior data includes not only data related to the acceleration, speed, and angle of the lean vehicle as described above, but also operations generated in the lean vehicle by a switch operation or the like performed by the driver on the lean vehicle. It may be. That is, the lean vehicle behavior data includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch. The lean vehicle behavior data strongly reflects the result of the driver's operation input. Therefore, the lean vehicle behavior data also tends to have many variations. Further, the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle behavior data may include data acquired from a sensor or the like and processing data processed using other data.

[Lean vehicle position data]
In the present specification, the lean vehicle position data is data related to the position of the lean vehicle. For example, it can be detected based on GPS and communication base station information of a communication mobile terminal. The lean vehicle position data can be calculated by various positioning techniques, SLAM, and the like. The lean vehicle position data strongly reflects the result of the driver's operation input. Therefore, the lean vehicle position data also tends to have many variations. Further, the lean vehicle position data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle position data may include data acquired from a sensor or the like and processing data processed using other data.

[Lean vehicle driving environment data]
In the present specification, the lean vehicle driving environment data includes, for example, map data. The map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The lean vehicle driving environment data can be used for analyzing customer values together with the lean vehicle driving operation input data, the lean vehicle behavior data, and the lean vehicle position data.

The information on the road conditions includes information on roads (regions) in a congested environment such as frequent traffic jams and many vehicles parked on the street. By combining this information with the time zone, the accuracy of the information is further improved. In addition, the information on the road condition includes information on a road that is easily flooded when there is a squall.

The lean vehicle driving environment data is considered to be an example of external stress received by the driver and the customer. The driving environment data influences the judgment of the driver. The lean vehicle driving environment data affects the driving operation of the driver. Therefore, by using the driving environment data, there are many variations of the driving data of the lean vehicle.

The lean vehicle driving environment data can be obtained from various means. The means for acquiring the lean vehicle driving environment data is not limited to a certain means. For example, the means for acquiring the lean vehicle traveling environment data is an external environment recognition device mounted on the lean vehicle. More specifically, the means for acquiring the lean vehicle driving environment data includes a camera, a radar, and the like. Further, the means for acquiring the lean vehicle traveling environment data is, for example, a communication device. More specifically, the means for acquiring the lean vehicle traveling environment data is a vehicle-to-vehicle communication device and a road-to-vehicle communication device. For example, the lean vehicle driving environment data can also be obtained via the Internet.

[Vehicle-related data]
In the present specification, the vehicle type-related data includes data related to the manufacturer of the lean vehicle and the vehicle type. The vehicle type-related data is used to distinguish between traveling lean vehicles. The customer's preference manufacturer and / or vehicle type influences the customer's preference. For example, a customer who prefers a luxury car has a strong demand for status and has a preference for high status.

[Public road]
In the present specification, the public road is not a simulation and circuit track, but a public road through which general vehicles can pass. The public roads also include private roads that general vehicles can pass through.

[Contains more B than A]
In the present specification, "containing more B than A" does not have to contain A at all. "Contains more B than A" may include a part of A.
For example, it is said that the data that reflects the change in the driver's operation on the lean vehicle for data conversion contains more data than the data that does not reflect the change in the operation on the lean vehicle for data conversion. It does not have to contain any data that does not reflect changes in operation on the vehicle. For example, it is said that the data that reflects the change in the driver's operation on the lean vehicle for data conversion contains more data than the data that does not reflect the change in the operation on the lean vehicle for data conversion. It may include some data that does not reflect changes in operation on the vehicle.

For example, it is said that the operation for the lean vehicle for analysis includes more data that reflects the change in the operation of the driver for the lean vehicle for analysis than the data that does not reflect the change in the operation for the lean vehicle for analysis. It is not necessary to include any data that does not reflect the change in. For example, it is said that the operation for the lean vehicle for analysis includes more data that reflects the change in the operation of the driver for the lean vehicle for analysis than the data that does not reflect the change in the operation for the lean vehicle for analysis. It may contain some data that does not reflect the change in.

For example, it is said that the lean vehicle running data for data conversion includes more data when the lean vehicle for data conversion runs on a public road than data when the lean vehicle for data conversion runs on a road other than a public road. , The data when the lean vehicle for data conversion travels on a road other than a public road may not be included at all. For example, the lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road. , The data when the lean vehicle for analysis travels on a road other than a public road may be partially included.

According to the customer insight analysis method according to the embodiment of the present invention, data showing a potential user's preference with high versatility while ensuring the degree of freedom in designing the hardware resource of the information processing device, so-called value. It is possible to provide a customer insight analysis method that can acquire data showing the view.

FIG. 1 is a diagram showing a schematic configuration of a customer insight analyzer according to the first embodiment of the present invention. FIG. 2 is a flowchart showing a customer insight data analysis method according to the first embodiment of the present invention. FIG. 3 is a diagram showing a schematic configuration of the customer insight analysis system according to the second embodiment. FIG. 4 is a flowchart showing an example of the operation of the information processing device.

While analyzing the running data of the lean vehicle, the present inventors noticed that the running data of the lean vehicle and the running data of the non-lean vehicle are significantly different. A lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left.

Lean vehicles are smaller in size than non-lean vehicles. Lean vehicles are smaller in the front-rear and / or left-right directions of the vehicle body than non-lean vehicles. In addition, the lean vehicle has a smaller amount of steering rotation operation than the non-lean vehicle. The amount of rotational operation of the steering of a lean vehicle is less than 360 degrees. Further, a lean vehicle is a rider-active vehicle that can be actively operated by the rider, unlike a non-lean vehicle. Therefore, the operation of a lean vehicle is different from the operation of a non-lean vehicle. The running data of a lean vehicle whose operation is different from that of a non-lean vehicle is significantly different from the running data of a non-lean vehicle.

When the present inventors examined the driving situation of the lean vehicle in more detail, they noticed that the lean vehicle had a much higher degree of freedom of driving by the driver's intention than the non-lean vehicle. ..

Therefore, when the driver is operating a lean vehicle, the number of judgments and judgment options of the driver tend to be larger than when the driver is operating a non-lean vehicle.

In addition, the driver is more likely to be exposed to external stress when operating a lean vehicle than when operating a non-lean vehicle. Moreover, the external stress exerted on the driver operating the lean vehicle is very diverse.

Therefore, it was found that the driving data of the lean vehicle has more variations than the driving data of the non-lean vehicle due to the difference in the driver who operates the lean vehicle, the difference in the lean vehicle, the difference in the driving environment, and the like.

In addition, when a lean vehicle is used as a business vehicle for carrying a customer, evaluation data for the customer's boarding may be collected.

Therefore, the present inventors examined in detail the relationship between the driving data of the lean vehicle and the evaluation data of the customer, and found that the evaluation data of the customer reflects the preference of the customer with respect to the driving data of the lean vehicle. I noticed that the data is being used.

In addition, since there are many variations in the driving data of lean vehicles, there are also many variations in the stimulus received by customers riding in lean vehicles. In addition, customers in lean vehicles are passive to stimuli.

For this reason, customer evaluations of lean vehicle rides are unknowingly performed very severely and tend to more strongly reflect palatability. From this, the present inventors have noticed that it is possible to obtain data indicating the customer's sense of values from the relationship between the driving data of the lean vehicle and the customer's evaluation data.

Therefore, the present inventors have considered a method of analyzing customer insights by obtaining data indicating customer values using lean vehicle driving data and customer evaluation data.

Hereinafter, each embodiment will be described with reference to the drawings. The dimensions of the constituent members in each drawing do not faithfully represent the actual dimensions of the constituent members and the dimensional ratio of each constituent member.

(Customer Insight Analyzer)
FIG. 1 shows a schematic configuration of the customer insight analyzer 1 according to the first embodiment of the present invention. The customer insight analysis device 1 is a device that analyzes the value data of the customer to be analyzed. The customer insight analyzer 1 of the present embodiment analyzes the lean vehicle driving data for analysis including the driving data when the customer to be analyzed is on the lean vehicle X, and the analysis of the customer for the riding at that time. Get the evaluation data for. Then, the customer insight analyzer 1 uses the value conversion data to convert the acquired lean vehicle driving data for analysis and the evaluation data for analysis into the conversion value related to the values of the customer to be analyzed. Convert to viewing data. The customer insight analyzer 1 generates output value data from the converted value data, and outputs the generated output value data.

The analysis of values in the present embodiment is to analyze the customer's evaluation criteria for satisfaction of tastes, health desires, labor saving desires, social life related desires, and the like. The value data is data showing the evaluation criteria of the customer's preference.

This value data is the value described later of the lean vehicle running data of the lean vehicle X obtained when the customer to be analyzed gets on the lean vehicle X as a passenger and the evaluation data for analysis of the customer for the ride at that time. It is included in the conversion value data obtained by converting by the view data conversion unit 40. This transformed value data includes data related to values related to the insights of the customer to be analyzed.

The lean vehicle running data in this embodiment is data related to the running of the lean vehicle. The lean vehicle driving data means data related to driving of a lean vehicle obtained when a driver drives and operates a lean vehicle, in which a highly versatile and potential customer preference appears. ..

Specifically, the lean vehicle driving data includes lean vehicle driving operation input data related to driving operation input to the lean vehicle by the driver, lean vehicle behavior data related to the behavior of the lean vehicle, and the traveling position of the lean vehicle. Includes relevant lean vehicle position data, lean vehicle vehicle-related data, and lean vehicle driving environment data related to the driving environment in which the lean vehicle travels. The lean vehicle traveling data may include data other than the lean vehicle driving operation input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle traveling environment data. Further, the lean vehicle driving data may include only one or a plurality of data among the lean vehicle driving operation input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle driving environment data. ..

For example, when the lean vehicle is a lean vehicle for data conversion, the lean vehicle driving data is lean vehicle driving data for data conversion, and the lean vehicle driving operation input data is lean vehicle driving operation input data for data conversion. The lean vehicle behavior data is lean vehicle behavior data for data conversion, the lean vehicle position data is lean vehicle position data for data conversion, and the vehicle-related data of the lean vehicle is for data conversion. It is vehicle-related data, and the lean vehicle traveling environment data is lean vehicle traveling environment data for data conversion.

For example, in the case of a lean vehicle X in which the lean vehicle is a lean vehicle for analysis, the lean vehicle driving data is lean vehicle driving data for analysis, and the lean vehicle driving operation input data is a lean vehicle driving operation input for analysis. The lean vehicle behavior data is data, the lean vehicle behavior data is lean vehicle behavior data for analysis, the lean vehicle position data is lean vehicle position data for analysis, and the vehicle-related data of the lean vehicle is a vehicle for data conversion. It is related data, and the lean vehicle driving environment data is lean vehicle driving environment data for analysis.

The lean vehicle driving data may include processed data obtained by processing lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle driving environment data, and the like. Further, the vehicle traveling data includes processing data processed by using lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data and other data and other data. May be good.

The lean vehicle driving operation input data is data related to the driver's operation input performed when the driver drives and operates the lean vehicle. Specifically, the lean vehicle driving operation input data may include data related to accelerator operation, braking operation, steering, or change of the center of gravity position due to a change in the driver's posture. Specifically, the lean vehicle driving operation input data may include operations of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving operation input data is data related to the driving operation input by the driver, the result of the driver's judgment is more reflected. Lean vehicles tend to strongly reflect the driver's personality because there are many types of driver's driving operations and they are intricately related. Further, the lean vehicle driving operation input data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle driving operation input data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the driver's operation input when the lean vehicle is driven and operated by the driver. Specifically, the lean vehicle behavior data includes, for example, the acceleration, speed, and angle of the lean vehicle that change when the driver operates the vehicle. That is, the lean vehicle behavior data is generated when the driver accelerates or decelerates the lean vehicle by operating the accelerator or the brake, or changes the posture including steering of the lean vehicle or changing the position of the center of gravity. Data showing the behavior of lean vehicles

As described above, the lean vehicle behavior data may include not only data on the acceleration, speed, and angle of the lean vehicle, but also movements that occur in the lean vehicle due to a switch operation or the like performed by the driver on the lean vehicle. That is, the lean vehicle behavior data includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch. The lean vehicle behavior data strongly reflects the result of input of the driver's driving operation. Therefore, the lean vehicle behavior data tends to strongly reflect the stimulus of the passengers on board. Further, the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle behavior data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle position data is data related to the running position of the lean vehicle. For example, the lean vehicle position data can be detected based on GPS and communication base station information of a communication mobile terminal. The lean vehicle position data can be calculated by various positioning techniques, SLAM, and the like. The lean vehicle position data strongly reflects the result of input of the driver's driving operation. Therefore, the lean vehicle position data also tends to strongly reflect the customer's stimulus. Further, the lean vehicle position data may include processed data obtained by processing data acquired from a sensor or the like. The lean vehicle position data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle driving environment data includes, for example, map data. This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The lean vehicle driving environment data can be used for analyzing the values of the customer who is the analysis target, together with the lean vehicle driving operation input data, the lean vehicle behavior data, and the lean vehicle position data.

The vehicle-related data includes, for example, information data related to a lean vehicle manufacturer and vehicle type. The vehicle-related data is used to distinguish between traveling lean vehicles. The customer's preference manufacturer and / or vehicle type influences the customer's preference.

The lean vehicle driving environment data is considered to be an example of external stress received by the driver and the customer. The lean vehicle driving environment data influences the judgment of the driver. Therefore, by using the lean vehicle driving environment data, the driving data of the lean vehicle is reflected in the stimulus given to the customer. Further, since the purpose and frequency of use of the lean vehicle are affected by using the lean vehicle driving environment data, it is reflected in the stimulus given to the customer in the driving data of the lean vehicle.

The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. Including many. The lean vehicle driving data for analysis includes more data that reflects changes in the driver's operation on the lean vehicle for analysis than data that does not reflect changes in operation on the lean vehicle for analysis. Good.

The lean vehicle driving data strongly reflects the change in operation of the lean vehicle after the driver makes a judgment. In other words, the lean vehicle driving data contains a lot of stimuli felt by the customer who is riding the lean vehicle. Moreover, in the case of a lean vehicle, there are many variations in the stimulus felt by the customer who is riding the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer 1.

As described above, the stimulus is not only a physical stimulus such as vibration received from the vehicle, but also a psychological stimulus received during a series of riding activities such as discomfort received from the boarding / alighting position and discomfort received from waiting time. including.

The customer insight analyzer 1 includes a value conversion data acquisition unit 10, a lean vehicle driving data acquisition unit 20 for analysis, an evaluation data acquisition unit 30 for analysis, a value data conversion unit 40, and an output value data generation. A unit 50, a data output unit 60, and a data storage unit 70 are provided. For example, the customer insight analyzer 1 of the present embodiment is a mobile terminal owned by the analysis target person. The customer insight analysis device 1 may be an arithmetic processing unit that acquires data via communication and performs arithmetic processing.

The analysis lean vehicle driving data acquisition unit 20 acquires lean vehicle driving data (lean vehicle driving data for analysis) when the driver drives the lean vehicle X on which the customer who is the analysis target is on board.

The analysis lean vehicle driving data acquisition unit 20 is the data included in the lean vehicle driving data of the lean vehicle X when the driver is driving the lean vehicle X on which the customer is riding, that is, the lean vehicle for analysis. Acquires vehicle driving operation input data, lean vehicle behavior data for analysis, lean vehicle position data for analysis, lean vehicle driving environment data for analysis, and the like.

The lean vehicle driving data acquisition unit 20 for analysis acquires the lean vehicle driving operation input data for analysis by, for example, acquiring the driving operation of the driver with respect to the lean vehicle X on which the customer is riding as an operation signal. You may. Specifically, the analysis lean vehicle driving data acquisition unit 20 changes the position of the center of gravity due to data related to the driver's operation input in the lean vehicle X, that is, accelerator operation, brake operation, steering, or change in the driver's posture. Data related to the above, data related to the operation of various switches such as a horn switch, a blinker switch, and a lighting switch may be acquired. These data are transmitted from the lean vehicle X.

The lean vehicle driving data acquisition unit 20 for analysis analyzes, for example, data including acceleration, speed, and angle of the lean vehicle X that changes when the driver of the lean vehicle X on which the customer rides operates the lean vehicle X. It may be acquired as lean vehicle behavior data for use. The analysis lean vehicle travel data acquisition unit 20 acquires the analysis lean vehicle behavior data by, for example, a gyro sensor. The lean vehicle behavior data for analysis is a posture change including steering of the lean vehicle X or a change in the position of the center of gravity when the driver of the lean vehicle X performs an accelerator operation or a brake operation to accelerate or decelerate the lean vehicle X. This is data showing the behavior of the lean vehicle X that occurs when the above is performed.

Further, the lean vehicle driving data acquisition unit 20 for analysis may acquire the operation generated in the lean vehicle X by the switch operation or the like performed by the driver of the lean vehicle X on the lean vehicle X as the lean vehicle behavior data. .. That is, the analysis lean vehicle travel data acquisition unit 20 acquires data related to the operation generated in the lean vehicle X by operating various switches such as the horn switch, the blinker switch, and the lighting switch as the analysis lean vehicle behavior data. You may. These data are sent from the lean vehicle X to the customer insight analyzer 1.

The analysis lean vehicle travel data acquisition unit 20 may acquire analysis lean vehicle position data related to the travel position of the lean vehicle X based on, for example, GPS and communication base station information of a communication mobile terminal. .. The lean vehicle position data for the analysis can be calculated by various positioning techniques, SLAM, and the like.

The analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving environment data from the map data, for example. This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The map data may include information in which road information and information on the road traffic environment (information incidental to the road such as a signal) are associated with rule information related to road travel.

The analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving environment data by, for example, an external environment recognition device mounted on the lean vehicle X. More specifically, the analysis lean vehicle travel data acquisition unit 20 may acquire the analysis lean vehicle travel environment data from a camera, radar, or the like. Further, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by, for example, a communication device. More specifically, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by the vehicle-to-vehicle communication device and the road-to-vehicle communication device. The analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data via the Internet, for example. As described above, the lean vehicle traveling environment data for the analysis can be obtained from various means. The means for acquiring the lean vehicle driving environment data for analysis is not limited to a certain means.

The evaluation data acquisition unit 30 for analysis receives the evaluation data evaluated by the customer from the mobile terminal such as a smartphone owned by the customer. The evaluation data is an evaluation of the driver and the vehicle when the customer gets on the vehicle. For example, a comprehensive evaluation felt by the customer is given on a five-point scale, for example. The highest evaluation is 5, and the smaller the number, the lower the evaluation. Further, as the evaluation data, the degree of reliability, comfort, speed, that is, economic efficiency including a short time to reach the destination may be included in the evaluation data.

The value conversion data acquisition unit 10 acquires the value conversion data for converting the lean vehicle running data and the evaluation evaluation data for analysis of the lean vehicle X on which the customer who is the analysis target is boarded into the value data.

The value conversion data indicates the values based on the lean vehicle driving data obtained when the customer is riding in the plurality of lean vehicles and the evaluation data of the multiple customers for the riding at that time. It is the data in which the value data, the lean vehicle driving data, and the evaluation data are associated with each other.

The value conversion data is generated by, for example, the following process. For example, the user's preference is analyzed from the driver's driving characteristics and evaluation analyzed from the lean vehicle driving data, and further, the relationship between the analyzed preference and the driving characteristics is analyzed to obtain the lean vehicle driving data. Value conversion data is generated as data that associates the evaluation data with the value data indicating the value.

Driving characteristics include the degree of reliability, comfort, and economy. For example, the degree of reliability is determined by analyzing the driver's skill and the frequency of legally compliant driving based on the driver's lean vehicle driving data. That is, the degree of reliability can be grasped by using, for example, the lean vehicle position data of the lean vehicle X, the lean vehicle driving environment data including the map data, and the lean vehicle behavior data among the lean vehicle traveling data. .. Then, the standard of the degree of trust of the driver is calculated based on the degree of trust of a plurality of drivers.

Comfort is obtained, for example, by calculating the level of body vibration and the vibration level from lean vehicle driving data of a plurality of drivers. The level of body swing is calculated based on the left-right behavior, up-down behavior, and front-back behavior calculated from the lean vehicle running data, and based on these calculation results. The vibration level is calculated, for example, by obtaining the acceleration in the vertical direction from the lean vehicle running data. Comfort criteria are calculated based on the level of body vibration and vibration.

Economic efficiency is calculated by, for example, the shortness of time to reach the destination obtained based on the lean vehicle driving data of a plurality of drivers.

The customer's preference can be estimated by analyzing the relationship between the customer's evaluation data and the driving characteristics of the driver of the vehicle on which the vehicle is boarded. For example, when a customer rides in a vehicle of a driver who has obtained driving characteristics that are highly evaluated for the degree of reliability, if the customer gives a high evaluation, it is estimated that the customer has a strong preference for the degree of reliability. Can be done. Similarly, when a customer gets into a vehicle of a driver who has obtained a driving characteristic that is highly evaluated for comfort, it can be estimated that the customer has a strong preference for comfort when the customer gives a high evaluation. When a customer gets into a vehicle of a driver who has obtained driving characteristics that are highly evaluated for economic efficiency, it can be estimated that the customer has a strong economic preference when the customer gives a high evaluation.

In this way, the customer's preference can be estimated from the relationship between the customer's evaluation and the driving characteristics based on the driving data. Then, by obtaining the customer's evaluation and driving data from a plurality of drivers and customers, it is possible to obtain a non-arbitrary and versatile relevance.

Then, the values that govern the customer's desire type can be associated with the customer's taste. For example, in the case of a customer who has a strong preference for the degree of trust, a relationship of a strong desire for health can be obtained, and in the case of a strong preference for economics, a relationship of a strong desire for labor saving can be obtained. In the case of a customer with strong comfort, a relationship of strong social life-related desire can be obtained. Based on these relationships, value conversion data for value analysis is obtained.

Status affects customer preference. Status is obtained, for example, based on the manufacturer and / or vehicle type preferred by the customer. That is, it can be presumed that customers who prefer luxury vehicles have a strong demand for status. The model information of the lean vehicle can be associated with the evaluation of the customer's status.

The value conversion data may be data created in advance and stored in the data storage unit 70, or may be data generated by the value conversion data acquisition unit 10. The value conversion data acquisition unit 10 may update the value conversion data by using the acquired lean vehicle traveling data and the value data.

The value data conversion unit 40 uses the above-mentioned value conversion data to acquire the lean vehicle travel data for analysis and the evaluation data acquisition unit 30 for analysis acquired by the lean vehicle travel data acquisition unit 20 for analysis. Convert the evaluation data for analysis into conversion value data. At this time, the value data conversion unit 40 ranks the customer who is the analysis target, for example, with respect to the above-mentioned elements of reliability, comfort, economy, and status. This leveling may be expressed as a continuous value for each of the above-mentioned elements, or may be expressed in a plurality of stages divided by a threshold value. Further, the value data conversion unit 40 may classify into a plurality of types by using the result of leveling by each of the above-mentioned elements, and the classification result may be used as the conversion value data.

The output value data generation unit 50 generates output value data using the converted value data converted by the value data conversion unit 40. This output value data is data output from the customer insight analyzer 1. The output value data may be the same data as the value data, or is data converted into data required as output data of the customer insight analyzer 1 using the value data. You may.

Further, the output value value data generation unit 50 may process the converted value value data to generate the output value value data. For example, the output value data generation unit 50 stores the conversion value data in the data storage unit 70, and uses the conversion value data extracted from the conversion value data stored in the data storage unit 70. Therefore, output value data may be generated. Specifically, for example, the output value data generation unit 50 may generate output value data from the converted value data within a certain period of time stored in the data storage unit 70.

The data output unit 60 outputs the output value value data generated by the output value value data generation unit 50 to the outside of the customer insight analyzer 1.

With the above configuration, the customer insight analyzer 1 analyzes the customer's sense of values by using the lean vehicle running data of the lean vehicle X on which the customer who is the analysis target is on board and the evaluation data at that time. The analysis result can be output as output value data. This output value data can be recognized as one piece of customer insight data.

(Customer insight data analysis method)
Next, the customer insight data analysis method performed by the customer insight analyzer 1 having the above-described configuration will be described with reference to FIG. FIG. 2 is a flowchart showing customer insight data analysis.

First, the analysis lean vehicle travel data acquisition unit 20 acquires the lean vehicle travel data of the lean vehicle X (step SA1). The lean vehicle driving data for analysis includes, for example, lean vehicle driving operation input data for analysis, lean vehicle behavior data for analysis, lean vehicle position data for analysis, lean vehicle driving environment data for analysis, and the like. Is done.

The lean vehicle driving data for analysis includes data other than lean vehicle driving operation input data for analysis, lean vehicle behavior data for analysis, lean vehicle position data for analysis, and lean vehicle driving environment data for analysis. It may be included. The lean vehicle driving data for the analysis includes the lean vehicle driving operation input data for the analysis, the lean vehicle behavior data for the analysis, the lean vehicle position data for the analysis, and the lean vehicle driving environment data for the analysis. Of these, only one or more data may be included.

Next, the analysis evaluation data acquisition unit 30 acquires the customer's evaluation data (step SA2). The evaluation data is evaluation data regarding the driver and the vehicle when the customer gets on the vehicle. For example, the comprehensive evaluation felt by the customer is given on a five-point scale, for example.

Subsequently, the value data conversion unit 40 converts the acquired lean vehicle driving data and evaluation data into conversion value data by the value conversion data (step SA3). This value conversion data is lean based on lean vehicle driving data including driving data of a plurality of riders operating a lean vehicle when the customer is on board and evaluation data of a plurality of customers for the riding at that time. It is data generated by associating vehicle running data and evaluation data with value data indicating values. For example, the converted value data is data showing the values of the customer who is the analysis target in terms of the degree of trust, comfort, economy, and status.

Next, the output value data generation unit 50 generates output value data using the converted value data (step SA4).

The data output unit 60 outputs the generated output value data (step SA5). After that, this flow ends (end).

The output value data output in this way is related to customer insights, and is considered when recommending to the customer who is the analysis target when performing arithmetic processing with an information processing device in fields such as finance and insurance. It may be used as palatability data which is one of the parameters to be processed. Specifically, in fields such as finance and insurance, information processing devices acquire output value value data as preference data, and use the acquired preference data to perform arithmetic processing to provide services suitable for customers. Output data about.

In fields such as finance and insurance, information processing methods output data related to services suitable for customers by a process of acquiring output value data as preference data and arithmetic processing using the acquired preference data. It may include a step of performing. In fields such as finance and insurance, information processing devices acquire data related to services suitable for customers by arithmetic processing using the acquisition unit that acquires the output value data as preference data and the acquired preference data. It may include an output unit to output. Using the data related to the output service, it is possible to propose a service that matches the customer's sense of values.

Further, the value data output as described above is one of the parameters to be considered when recommending to the customer who is the analysis target when the information processing device performs arithmetic processing in the field of sales or advertising, for example. It may be used as palatability data.

Specifically, in fields such as sales and advertising, the information processing method acquires the output value value data as preference data, and uses the acquired preference data to perform arithmetic processing to provide a service suitable for the customer. Output data about. In fields such as sales and advertising, information processing methods output data related to services suitable for customers by a process of acquiring output value data as preference data and arithmetic processing using the acquired preference data. It may include a step of performing. In fields such as sales and advertising, an information processing device has an acquisition unit that acquires output value value data as preference data, and data on services suitable for customers by arithmetic processing using the acquired preference data. It may include an output unit that outputs. Using the data related to the output service, it is possible to propose a service that matches the customer's sense of values. Goods and services may be recommended to the analysis target person according to the value data of the analysis target person.

Then, the value data obtained by using the lean vehicle driving data and the evaluation data can be used for the arithmetic processing of the information processing device using the customer's preference data such as finance, insurance, sales and advertisement.

Therefore, it is possible to acquire value data that can be used in the information processing device while increasing the degree of freedom in designing hardware resources.

The customer insight analysis method of this embodiment is an example of a customer insight analysis method for analyzing customer values. A lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left. The lean vehicle for data conversion means a lean vehicle operated by a plurality of drivers who are the targets of the lean vehicle driving data for data conversion. For example, the lean vehicle running data for data conversion may be acquired by various sensors supported by the lean vehicle for data conversion. Further, the lean vehicle traveling data for data conversion may be acquired by various sensors supported so as to be easily detachable from the lean vehicle for data conversion. Lean vehicle driving data for data conversion may be acquired by various sensors temporarily supported by the lean vehicle for data conversion for data collection.

The customer insight analysis method of the present embodiment obtains driving data when the customer to be analyzed is in a lean vehicle to be analyzed, which is tilted to the right when turning right and tilted to the left when turning left. The lean vehicle driving data for analysis including and the evaluation data for analysis of the customer for the ride at that time are acquired. The lean vehicle running data for analysis means the running data of the lean vehicle on which the customer to be analyzed is on board. The lean vehicle for analysis means the lean vehicle on which the customer to be analyzed is on board.

The lean vehicle data for analysis may be included in the lean vehicle data for data conversion. The lean vehicle data for analysis does not have to be included in the lean vehicle data for data conversion. For example, the lean vehicle driving data for analysis may be acquired by various sensors supported by the lean vehicle for analysis. Further, the lean vehicle running data for analysis may be acquired by various sensors supported so as to be easily detachable from the lean vehicle for analysis.

Lean vehicle driving data for analysis may be acquired by various sensors temporarily supported by the lean vehicle for analysis for data collection. It should be noted that the various sensors for collecting the lean vehicle running data for analysis may have lower detection accuracy than the various sensors for collecting the lean vehicle running data for data conversion.

The various sensors for collecting lean vehicle running data for analysis may be the same as the various sensors for collecting lean vehicle running data for data conversion. Further, the lean vehicle travel data for analysis may have fewer types of data than the lean vehicle travel data for data conversion. The lean vehicle running data for analysis may have the same data type as the lean vehicle running data for data conversion.

The driver of the lean vehicle recognizes the situation, makes a judgment, and performs the driving operation. At this time, there are cases where the driver changes the driving operation before and after the judgment and cases where the driving operation is not changed. In a lean vehicle, there are many variations in driving operation and there are many choices for the driver's judgment, so there are many variations in the scene in which the driver changes the driving operation. In other words, the lean vehicle driving data contains many variations of the stimulus felt by the customer riding the lean vehicle. Moreover, in the case of a lean vehicle, there are many variations in the stimulus felt by the customer who is riding the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

There are the following methods to separate lean vehicle driving data into data that does not reflect changes in driving operations for lean vehicles by drivers and data that reflects changes in driving operations for lean vehicles by drivers. To do.

For example, it is possible to directly see and separate the change in the driving operation of the lean vehicle by the driver from the lean vehicle driving data. For example, it is possible to separate from the lean vehicle driving data by directly observing the behavior of the lean vehicle in which the result due to the change in the driving operation of the lean vehicle by the driver appears. For example, it is possible to separate from the lean vehicle driving data by observing the position of the lean vehicle in which the result due to the change in the driving operation of the lean vehicle by the driver appears. For example, it is possible to separate from the lean vehicle driving data by observing the position of the lean vehicle indicating that the driver is traveling in a place where the driving operation for the lean vehicle is frequently changed. Specifically, the position data of the lean vehicle and the traveling environment data of the lean vehicle (for example, map data) can be used for separation. More specifically, the driving data in the suburbs and the driving data in the city may be separated. The driving data in the suburbs may be data that does not reflect the change in driving operation for the lean vehicle by the driver, and the driving data in the city may be data that reflects the change in driving operation for the lean vehicle by the driver.

Since the lean vehicle operation input data is data related to the operation input by the driver, it more reflects the result of the driver's judgment. In lean vehicles, there are many types of driver's operations and they are complicatedly related, so there are many variations in operations. The result of the operation input is strongly reflected in the lean vehicle behavior data and the lean vehicle position data. With this configuration, the lean vehicle driving data more strongly reflects the change in the operation of the lean vehicle after the driver makes a judgment. In other words, the lean vehicle driving data contains more stimulus felt by the customer in the lean vehicle. Moreover, in the case of a lean vehicle, there are more variations in the stimulus felt by the customer riding the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

Driving environment data is considered to be an example of external stress received by drivers and customers. The driving environment data influences the judgment of the driver. The driving environment data affects the operation of the driver. Therefore, by using the driving environment data, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

Lean vehicle driving environment data includes, for example, map data. For example, map data may be associated with information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. The lean vehicle driving environment data can be used for analyzing the values of the customer to be analyzed together with the lean vehicle operation input data, the lean vehicle behavior data, and the lean vehicle position data.

When a driver traveling on a public road is operating a lean vehicle, the driver has more judgments, has more choices of judgment, and is easily exposed to external stress. The data contains more variations. Therefore, by using the lean vehicle driving data including a large amount of data when traveling on a public road, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

By using lean vehicle driving data in a state where the driver's judgment options are limited but multiple are left, it becomes easier to analyze the stimulus received by the customer from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the information processing device.

For example, the driver's judgment options are limited by the vehicles around the lean vehicle, but a plurality of remaining states may be determined from the lean vehicle position data and the lean vehicle driving environment data. More specifically, the state may be estimated based on the date, time, and place where the lean vehicle is traveling. Lean vehicle driving data when traveling in an urban area includes data in a state where a plurality of driver's judgment options are restricted by vehicles around the lean vehicle, but a plurality of them are left. In addition, data on the actual surrounding conditions of the lean vehicle may be acquired to estimate the state. A combination of methods for estimating a plurality of states may be used.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle travel data for data conversion includes data in a state where the customer is not on board. The lean vehicle driving data for analysis includes data in a state where the customer is not on board. The lean vehicle driving data includes driving data before and after the customer boarding.

By using lean vehicle driving data when the customer is not on board, for example, lean vehicle driving data before and after the customer is on board, the physical or psychological stimulus received by the customer from the driving data of the lean vehicle can be further analyzed. It will be easier to do. By using such lean vehicle driving data, it is possible to acquire data showing more accurate values while ensuring the degree of freedom in designing the hardware resources of the customer insight analyzer.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes vehicle type-related data related to the vehicle type of the lean vehicle, and the lean vehicle traveling data for analysis includes vehicle type-related data related to the vehicle type of the lean vehicle.

From another point of view, the customer insight analysis method of the present invention preferably includes the following configurations. The converted conversion value data is stored. The output value value data is generated by using the plurality of stored conversion value value data. Note that the memory includes not only the memory for storage but also the temporary memory of the result. For example, the conversion value data stored in the storage and the conversion value data stored in the temporary memory may be used. These may be used to update the conversion value data stored in the storage. These may be used to generate new conversion value data. Statistical processing may be performed using these. These may be used to update the conversion value data stored in the storage.

By using a plurality of conversion value data, for example, statistical processing can be performed, and data showing more accurate values can be acquired while ensuring the degree of freedom in designing the hardware resources of the information processing device. .. More specifically, the old conversion value data and the new conversion value data can be used to analyze the customer's values more accurately.

For example, further information processing may be the processing of data related to finance, insurance, markets, products, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

The customer insight analyzer of the present invention is a customer insight analyzer that analyzes customer insights, and is a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. Value data showing values based on lean vehicle driving data for data conversion including driving data when the customer is on board and evaluation data for data conversion of multiple customers for riding at that time. The value conversion data acquisition unit that acquires the value conversion data generated by associating the lean vehicle driving data with the evaluation data, and the customer to be analyzed tilts to the right when turning right and left when turning left. When the lean vehicle driving data acquisition unit for analysis that acquires the lean vehicle driving data for analysis including the driving data when riding in the lean vehicle to be analyzed and the customer to be analyzed turn right The analysis evaluation data acquisition unit that acquires the evaluation data for the analysis of the customer for the ride when the lean vehicle to be analyzed that tilts to the right and tilts to the left when turning left, and the acquired The value that converts the lean vehicle driving data for analysis and the acquired evaluation data for analysis into the converted value data related to the value of the customer to be analyzed by using the acquired value conversion data. A data conversion unit, an output value data generation unit that generates output value data for output using the converted conversion value data, and an output unit that outputs the generated output value data. ,
To be equipped.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. The lean vehicle running data for analysis includes a large amount of data that reflects changes in the driver's operation on the lean vehicle for analysis rather than data that does not reflect changes in operation on the lean vehicle for analysis. Including many.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle running data for data conversion is the lean vehicle operation input data for data conversion related to the operation input to the lean vehicle for data conversion, and the data conversion related to the behavior of the lean vehicle for data conversion. The lean vehicle running data for analysis includes at least one of the lean vehicle behavior data and the lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. Lean vehicle operation input data for analysis related to operation input to the vehicle, lean vehicle behavior data for analysis related to the behavior of the lean vehicle for analysis, and analysis related to the position of the lean vehicle for analysis. Includes at least one of the lean vehicle position data.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels, and the lean vehicle traveling data for analysis is the analysis. Includes lean vehicle driving environment data for analysis related to the driving environment in which the lean vehicle is driven.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road, and is used for the analysis. The lean vehicle traveling data of the above includes more data when the lean vehicle for analysis travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle driving data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left for the analysis. The lean vehicle driving data includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for analysis, but a plurality of them are left.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle travel data for data conversion includes data in a state in which the customer is not on board, and the lean vehicle travel data for analysis includes data in a state in which the customer is not on board.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes vehicle type-related data related to the vehicle type of the lean vehicle, and the lean vehicle traveling data for analysis includes vehicle type-related data related to the vehicle type of the lean vehicle.

From another point of view, the customer insight analyzer of the present invention preferably includes the following configurations. The converted conversion value data is stored, and the output value data is generated by using the plurality of stored conversion value data.

<Embodiment 2>
FIG. 3 shows an example of the customer insight analysis system 100 including the customer insight analysis device 1 of the first embodiment. Hereinafter, the same components as those of the first embodiment are designated by the same reference numerals and the description thereof will be omitted, and only the configurations different from the first embodiment will be described.

The customer insight analysis system 100 includes a customer insight analysis device 1 and a value conversion data generation device 101 that generates value conversion data conversion data.

The value conversion data generation device 101 is, for example, an information processing calculation device capable of communicating with the customer insight analysis device 1 and having a processor. When the customer insight analysis device 1 is an information processing calculation device having a processor, the value conversion data generation device 101 may be the same information processing calculation device as the customer insight analysis device 1.

The value conversion data generation device 101 acquires lean vehicle traveling data, evaluation data, and value data, and generates value conversion data in which the lean vehicle traveling data, the evaluation data, and the value data are associated with each other. ..

Specifically, the value conversion data generation device 101 has a data storage unit 111 and a value conversion data generation unit 112. Although not particularly shown, the value conversion data generation device 101 has an acquisition unit for acquiring lean vehicle traveling data, evaluation data, and value data. Further, although not particularly shown, the value conversion data generation device 101 has an output unit that outputs the generated value conversion data.

The data storage unit 111 stores lean vehicle running data, evaluation data, value data, and value conversion data. Specifically, the data storage unit 111 stores lean vehicle driving data for data conversion obtained when a plurality of drivers are on the lean vehicle Y (lean vehicle for data conversion). Will be done. In addition, the data storage unit 111 stores evaluation data for data conversion of a plurality of customers for boarding at that time. Further, the data storage unit 111 stores the value conversion data generated by the value conversion data generation unit 112, which will be described later.

Note that the value data may be stored in the data storage unit 111 by input, or the value data may be stored in advance. Further, the evaluation data is stored in the data storage unit 111 by input. As this input method, various methods such as communication from a customer's mobile terminal and input based on a questionnaire are used.

The lean vehicle driving data for data conversion includes, for example, lean vehicle driving operation input data for data conversion, lean vehicle behavior data for data conversion, lean vehicle position data for data conversion, and lean vehicle driving environment for data conversion. Includes data etc.

The value conversion data generation unit 112 generates value conversion data in which the value data stored in the data storage unit 111, the lean vehicle running data for data conversion, and the evaluation data are associated with each other. The value conversion data generated by the value conversion data generation unit 112 is stored in the data storage unit 111.

The value conversion data stored in the data storage unit 111 is the lean vehicle running data (lean vehicle running data for analysis) and the evaluation data of the lean vehicle X (lean vehicle for analysis) in the customer insight analyzer 1. Is used when converting to value data. Since the method of converting the lean vehicle driving data and the evaluation data into the value data in the customer insight analyzer 1 is the same as that in the first embodiment, detailed description thereof will be omitted.

The customer insight analyzer 1 generates output value data using the converted value data, and outputs the output value data. Since the configuration of the customer insight analyzer 1 is the same as that of the first embodiment, detailed description of the customer insight analyzer 1 will be omitted.

The output value data output from the customer insight analysis device 1 may be input to the information processing device 102, for example. In this case, the output value data is generated in the customer insight analysis device 1 as information processing value data used for information processing in the information processing device 102.

The information processing device 102 may be, for example, a device that processes data related to finance, insurance, market, goods, services, environment, or customers used in businesses such as finance, insurance, sales, and advertising. When the customer insight analysis device 1 is an information processing calculation device, the information processing device 102 may be the same device as the customer insight analysis device 1. The information processing device 102 may be the same information processing calculation device as the value conversion data generation device 101.

The information processing device 102 includes, for example, an output value data acquisition unit 121, a first data acquisition unit 122, a second data generation unit 123, a second data output unit 124, and a data storage unit 125.

The output value data acquisition unit 121 acquires the output value data data output from the customer insight analyzer 1.

The first data acquisition unit 122 acquires the first data different from the output value data. This first data is data to be processed by the information processing apparatus 102. The first data is data related to finance, insurance, market, goods, services, environment or customers used in business such as finance, insurance, sales and advertising. The first data is stored in the data storage unit 125.

The second data generation unit 123 uses the output value data and the first data to generate second data different from the output value data and the first data. Similar to the first data, this second data is also data related to finance, insurance, market, goods, services, environment or customers used in business such as finance, insurance, sales and advertising.

The second data output unit 124 outputs the second data generated by the second data generation unit 123.

Next, an information processing method for performing information processing using output value data by the information processing device 102 having the above configuration will be described with reference to the flowchart shown in FIG. FIG. 4 is a flowchart showing the operation of information processing by the information processing device 102.

As shown in FIG. 4, first, the output value value data acquisition unit 121 of the information processing device 102 acquires the output value value data output from the customer insight analysis device 1 (step SB1).

Next, the first data acquisition unit 122 of the information processing device 102 acquires the first data stored in the data storage unit 125 (step SB2). This first data is different from the output value data.

After that, the second data generation unit 123 of the information processing apparatus 102 generates the second data by using the acquired output value data and the acquired first data (step SB3). This second data is different from the output value data and the first data.

Subsequently, the second data output unit 124 of the information processing device 102 outputs the generated second data (step SB4).

The output value data output from the customer insight analyzer 1 in this way is used, for example, in the field of finance or insurance, when the information processing device calculates and processes data related to services suitable for the customer. Can be done. That is, the value data obtained by using the lean vehicle driving data and the evaluation data can be used for the arithmetic processing of the information processing device in the fields of finance, insurance, sales, advertising, and the like.

Specifically, in fields such as finance or insurance, the information processing device acquires the output output value data, and uses the acquired output value data to acquire it as preference data by arithmetic processing. It is acquired, and the acquired preference data is used to output data related to a service suitable for the customer by arithmetic processing. Using the data related to the output service, it is possible to propose a service that matches the customer's sense of values.

In fields such as finance or insurance, the information processing method is suitable for the customer by a process of acquiring the output value value data output from the customer insight analyzer 1 and arithmetic processing using the acquired preference data. It may include a process of outputting data related to the service.

Further, as described above, the output value data output from the customer insight analyzer 1 is considered when recommending to the analysis target person when the information processing apparatus performs arithmetic processing in a field such as sales or advertisement. It can be used as a parameter to be processed. In fields such as sales or advertising, a product or service may be recommended to the analysis target person according to the value data of the analysis target person by performing arithmetic processing on the information processing device.

Specifically, in fields such as sales or advertising, the information processing device acquires output value data output from the customer insight analyzer 1 and uses the acquired output value data for arithmetic processing. Can output the products or services recommended to the analysis target person.

In fields such as sales or advertising, the information processing device uses the value data acquisition unit that acquires the output value data output from the customer insight analyzer 1 and the acquired output value data to be analyzed. It may include a product-related data output unit that outputs product-related data related to a product recommended to a person, or a service-related data output unit that outputs service-related data related to services.

In fields such as sales or advertising, the information processing method is the process of acquiring the value data output from the customer insight analyzer 1 and the product related to the product recommended to the analysis target person using the acquired value data. It may include a step of outputting related data or service related data related to a service.

From another point of view, it is preferable that the value data output by the customer insight analysis method of the present invention is used in the information processing method using the following value data. In this information processing method, the output value value data that has been output is acquired. In the information processing method, first data different from the output value data is acquired. In the information processing method, the output value data and the acquired first data are used to generate second data different from the output value data and the acquired first data. In the information processing method, the generated second data is output.

The information processing method using the value data includes the information processing method as described in the patent document described in the background technology. However, it is not limited to the information processing method described in the patent document described in the background technology. The information processing method may be any information processing method as long as it uses value data. For example, the first data and the second data may be data related to finance, insurance, market, goods, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

According to the configuration of this embodiment, the value data that can be used by the information processing device 102 can be acquired by the customer insight analysis device 1 and the customer insight analysis method using the customer insight analysis device 1. Further, as described in the first embodiment, by using the driving data of the lean vehicle for the analysis of the sense of values, the types of data processed by the system can be reduced, and the hardware load of the customer insight analyzer 1 can be reduced. it can.

The present invention can be used for a customer insight data analysis method and a customer insight data analysis system for analyzing customer insight data, and an information processing method and information using the value data obtained by these methods and devices. It can also be used for processing equipment.

1 Customer insight analyzer 10 Value conversion data acquisition unit 20 Analysis lean vehicle driving data acquisition unit 30 Analysis evaluation data acquisition unit 40 Value data conversion unit 50 Output value value data generation unit 60

Data output unit

70, 111 data Storage unit 100 Customer insight analysis system 101 Value conversion data generation device 102 Information processing device X Lean vehicle (lean vehicle to be analyzed)
Y lean vehicle (lean vehicle for data conversion)

Claims

A customer insight analysis method that analyzes customer insights.
Lean vehicle driving data for data conversion including driving data when a customer is on a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left, and lean vehicle driving data for data conversion at that time. Based on the evaluation data for data conversion of multiple customers for the ride, the value conversion data generated by associating the value data indicating the values with the lean vehicle driving data and the evaluation data is acquired.
Lean vehicle driving data for analysis, including driving data when the customer to be analyzed is in a lean vehicle to be analyzed that tilts to the right when turning right and tilts to the left when turning left, and its Obtain the evaluation data for the analysis of the customer regarding the ride at the time,
The acquired lean vehicle running data for analysis and the acquired evaluation data for analysis are converted into conversion value data related to the values of the customer to be analyzed by using the acquired value conversion data. And
Using the converted conversion value data, the output value data to be output is generated, and the output value data is generated.
Output the generated output value data,
Customer insight analysis method.
In the customer insight analysis method according to claim 1,
The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. Including a lot
The lean vehicle driving data for analysis includes more data that reflects changes in the driver's operation on the lean vehicle for analysis than data that does not reflect changes in operation on the lean vehicle for analysis. How to analyze customer insights.
In the customer insight analysis method according to claim 1 or 2.
The lean vehicle running data for data conversion is the lean vehicle operation input data for data conversion related to the operation input to the lean vehicle for data conversion, and the data conversion related to the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion.
The lean vehicle driving data for analysis includes lean vehicle operation input data for analysis related to operation input to the lean vehicle for analysis, and lean vehicle behavior data for analysis related to the behavior of the lean vehicle for analysis. And a customer insight analysis method comprising at least one of the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.
In the customer insight analysis method according to any one of claims 1 to 3.
The lean vehicle traveling data for data conversion includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels.
The lean vehicle driving data for analysis is a customer insight analysis method including lean vehicle driving environment data for analysis related to the driving environment in which the lean vehicle for analysis is traveling.
In the customer insight analysis method according to any one of claims 1 to 4.
The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road.
The lean vehicle traveling data for analysis is a customer insight analysis method including more data when the lean vehicle for analysis travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.
In the customer insight analysis method according to any one of claims 1 to 5,
The lean vehicle driving data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left.
The lean vehicle driving data for analysis is a customer insight analysis method including data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for analysis.
In the customer insight analysis method according to any one of claims 1 to 6.
The lean vehicle driving data for data conversion includes data in a state where the customer is not on board.
The lean vehicle driving data for analysis is a customer insight analysis method including data in a state where the customer is not on board.
In the customer insight analysis method according to any one of claims 1 to 7.
The lean vehicle driving data for data conversion includes vehicle type-related data related to the vehicle type of the lean vehicle.
The lean vehicle driving data for analysis is a customer insight analysis method including vehicle type-related data related to the vehicle type of the lean vehicle.
In the customer insight analysis method according to any one of claims 1 to 8.
The converted conversion value data is stored,
A customer insight analysis method for generating the output value data using the plurality of stored conversion value data.
In the customer insight analysis method according to any one of claims 1 to 9.
The output value data is a customer insight analysis method generated as information processing value data used for further information processing.
A customer insight analyzer that analyzes customer insights
Lean vehicle driving data for data conversion including driving data when a customer is on a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left, and at that time Value conversion data that acquires value conversion data generated by associating value data indicating values with lean vehicle driving data and evaluation data based on evaluation data for data conversion of multiple customers for boarding. Acquisition department and
Acquire lean vehicle driving data for analysis, including driving data when the customer to be analyzed is in a lean vehicle to be analyzed that tilts to the right when turning right and tilts to the left when turning left. Lean vehicle driving data acquisition unit for analysis and
Analysis to acquire evaluation data for analysis of the customer when the customer to be analyzed is in a lean vehicle to be analyzed, which is tilted to the right when turning right and tilted to the left when turning left. Evaluation data acquisition department and
The acquired lean vehicle driving data for analysis and the acquired evaluation data for analysis are converted into conversion value data related to the values of the customer to be analyzed by using the acquired value conversion data. Value data conversion department and
An output value data generation unit that generates output value data for output using the converted conversion value data,
An output unit that outputs the generated output value data and
With customer insight analyzer.
In the customer insight analyzer according to claim 11.
The lean vehicle running data for data conversion is data that reflects changes in the driver's operation on the lean vehicle for data conversion rather than data that does not reflect changes in the operation of the lean vehicle for data conversion. Including a lot
The lean vehicle driving data for analysis includes more data that reflects changes in the driver's operation on the lean vehicle for analysis than data that does not reflect changes in operation on the lean vehicle for analysis. Customer insight analyzer.
In the customer insight analyzer according to claim 11 or 12.
The lean vehicle running data for data conversion is the lean vehicle operation input data for data conversion related to the operation input to the lean vehicle for data conversion, and the data conversion related to the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion.
The lean vehicle driving data for analysis includes lean vehicle operation input data for analysis related to operation input to the lean vehicle for analysis, and lean vehicle behavior data for analysis related to the behavior of the lean vehicle for analysis. And a customer insight analyzer that includes at least one of the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.
In the customer insight analyzer according to any one of claims 11 to 13.
The lean vehicle traveling data for data conversion includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels.
The lean vehicle driving data for analysis is a customer insight analyzer including lean vehicle driving environment data for analysis related to the driving environment in which the lean vehicle for analysis is traveling.
In the customer insight analyzer according to any one of claims 11 to 14.
The output value data is a customer insight analyzer that is generated as information processing value data used for further information processing.
An information processing method using the output value data generated as the information processing value data by the customer insight analysis method of claim 10.
Acquire the output value data and
Acquire the first data different from the output value data,
Using the output value data and the first data, a second data different from the output value data and the first data is generated.
An information processing method using value data that outputs the second data.
An information processing device that uses the output value data generated as the information processing value data by the customer insight analyzer according to claim 15.
The output value data acquisition unit that acquires the output value data,
A first data acquisition unit that acquires first data different from the output value data,
A second data generation unit that uses the output value data and the first data to generate second data different from the output value data and the first data.
A second data output unit that outputs the second data, and
An information processing device that uses value data.