JP2023183531A - Information processing device, information processing method and information processing program - Google Patents

Abstract

To provide information about a questionnaire respondent to a client in advance.SOLUTION: An information processing device related to the present application includes a reception part for receiving information about questionnaire contents of a questionnaire, an estimation part for estimating a prospective respondent estimated to answer the questionnaire on the basis of the questionnaire contents received by the reception part, and answer results about past questionnaires, and a provision part for providing information about the prospective respondent estimated by the estimation part.SELECTED DRAWING: Figure 2

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

2. Description of the Related Art Conventionally, there is an information processing apparatus that asks a user to respond to a questionnaire. In such an information processing apparatus, for example, a questionnaire is distributed until the number of responses specified by the client is reached (see, for example, Patent Document 1).

JP 2021-2251 Publication

However, with the conventional technology, the client cannot know in advance who will respond to the questionnaire. Therefore, there is a need for technology that provides clients with information about survey respondents in advance.

The present invention has been made in view of the above, and an object of the present invention is to provide an information processing device, an information processing method, and an information processing program that can provide a client with information on survey respondents in advance. do.

In order to solve the above-mentioned problems and achieve the purpose, an information processing device according to the present invention includes a reception section that receives information regarding the contents of a questionnaire, the contents of the questionnaire received by the reception section, and information about past questionnaires. an estimating unit that estimates prospective respondents who are expected to respond to the questionnaire based on the response history of the survey; and a providing unit that provides information regarding the prospective respondents estimated by the estimating unit. shall be.

According to the present invention, information regarding respondents to a questionnaire can be provided to a client in advance.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram showing an example of a display screen according to the embodiment. FIG. 3 is a block diagram illustrating a configuration example of an information processing apparatus according to an embodiment. FIG. 4 is a diagram illustrating an example of a questionnaire results storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of incentive-based processing according to the embodiment. FIG. 6 is a diagram illustrating an example of proposal information according to the embodiment. FIG. 7 is a flowchart illustrating an example of provision processing according to the embodiment. FIG. 8 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device according to the embodiment.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an embodiment of an information processing program (hereinafter referred to as "embodiments") according to the present application will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment.

[Embodiment]
[1. Information processing〕
First, an example of information processing according to the embodiment will be described using FIG. 1. FIG. 1 is a diagram illustrating an example of information processing according to an embodiment.

The information processing apparatus 100 according to the embodiment shown in FIG. 1 cooperates with each user's terminal device (not shown), and provides API (Application An information processing device that provides services such as Programming Interface (Programming Interface) and various data, and is realized by a server device, a cloud system, etc.

Further, the information processing device 100 may be an information processing device that provides some kind of web service online to each user's terminal device. For example, the information processing device 100 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce, electronic payment, online games, online banking, online trading, accommodation/ticket reservation, video/music distribution, etc. services may be provided. In reality, the information processing device 100 may cooperate with various servers that provide the above-mentioned Web services and may mediate the Web services.

Note that the information processing apparatus 100 can acquire user information regarding the user. For example, the information processing device 100 acquires information regarding user attributes such as the user's gender, age, and region of residence. Then, the information processing device 100 stores and manages information regarding user attributes as well as identification information indicating the user (user ID, etc.).

Further, the information processing device 100 acquires various types of history information (log data) indicating the user's actions from the user's terminal device or from various servers based on the user ID and the like. For example, the information processing device 100 acquires a location history, which is a history of a user's location, date and time, from a terminal device. The information processing device 100 also acquires a search history, which is a history of search queries input by the user, from a search server (search engine). The information processing apparatus 100 also acquires a viewing history, which is a history of content viewed by the user, from the content server. The information processing device 100 also acquires a purchase history, which is a history of a user's product purchases and payment processing, from an electronic commerce server or a payment processing server. Further, the information processing device 100 may acquire listing history and sales history, which are the user's listing history on the marketplace, from an electronic commerce server or a payment server.

Furthermore, the information processing apparatus 100 acquires information regarding the questionnaire from the client terminal 50 and implements a web service that requests responses from each user.

The client terminal 50 is a terminal operated by a client who is a questionnaire questioner. As will be described later, the client operates the client terminal 50, inputs information regarding the questionnaire, and requests the information processing apparatus 100 to conduct the questionnaire.

By the way, the client cannot grasp the number of responses for each user attribute until the questionnaire is actually conducted. Therefore, for example, depending on the questionnaire, it is possible that the number of questionnaire responses that meet the client's wishes may not be obtained.

Therefore, the information processing apparatus 100 according to the embodiment estimates the respondents based on the questionnaire input by the client, and provides the estimate to the client.

Specifically, as shown in FIG. 1, the information processing device 100 has a questionnaire history storage unit that stores information regarding past questionnaire response results, and stores the contents of the questionnaire and the responses to the questionnaire. A model that has learned the relationship between the two is generated (step S1). The model here is a model that outputs information about prospective respondents who are likely to respond to the questionnaire when the questionnaire contents are input.

Subsequently, when the client terminal 50 accesses the information processing apparatus 100, a questionnaire input screen G1 as shown in FIG. 1 is displayed on the client terminal 50. For example, the client operates the client terminal 50 and inputs each item. The example shown in FIG. 1 shows a case where the input screen G1 includes input items related to "category", "template selection", "task name", and "task description".

"Category" indicates the category of the survey to be conducted, and "Template Selection" indicates the template selection for the survey. “Task name” and “task description” indicate the questionnaire name and the questionnaire description, respectively. Note that the "task description" corresponds to an example of the contents of the questionnaire.

When the client finishes inputting each item on the input screen G1 on the client terminal 50, the client terminal 50 transmits questionnaire information to the information processing apparatus 100 (step S2).

Based on the questionnaire information received from the client terminal 50, the information processing apparatus 100 estimates prospective respondents who are likely to respond to the questionnaire input by the client (step S3).

In the estimation in step S3, the information processing device 100 estimates, for example, the distribution of prospective respondents, and provides the result to the client terminal 50 as respondent information (step S4).

The client terminal 50 then displays the respondent information received from the information processing device 100 on the screen. FIG. 2 is a diagram showing an example of a display screen according to the embodiment.

As shown in Figure 2, for example, the display screen related to respondent information displays information regarding the distribution of potential respondents by gender, age, and region, and allows you to specify the attributes of the respondents to whom the survey will be conducted. be.

The display screen related to respondent information displays a graph that visualizes the distribution of prospective respondents by gender, age, and region (area of residence). For example, for gender, a graph visualizing the proportion of prospective respondents by gender is displayed, and for age, a graph showing the proportion of prospective respondents by age is displayed. Note that although the example shown in FIG. 2 shows a case where these graphs are bar graphs, other graphs such as a pie chart may be used.

Further, as shown in FIG. 2, for the area of the prospective respondent, a graph showing the distribution of the residential areas of the prospective respondent on a map is displayed. For example, the size of a circle on a map corresponds to the expected number of respondents residing in that area, and the place name displayed inside the circle indicates the name of that area.

In other words, in this case, the client can visually recognize the number of prospective respondents by the size of the circle and the geographical distribution of the prospective respondents.

In this way, the information processing apparatus 100 according to the embodiment estimates potential respondents based on the questionnaire content input by the client, and provides information regarding the estimated potential respondents.

Thereby, according to the information processing apparatus 100 according to the embodiment, it is possible to provide the client with information regarding the respondents of the questionnaire in advance.

[2. Configuration example of information processing device]
Next, a configuration example of the information processing device 100 according to the embodiment will be described using FIG. 3. FIG. 3 is a block diagram showing a configuration example of the information processing device 100 according to the embodiment. As shown in FIG. 3, the information processing device 100 includes a communication section 110, a storage section 120, and a control section 130.

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). Further, the communication unit 110 is connected to a network by wire or wirelessly.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 3, the storage unit 120 includes a user information storage unit 121, a questionnaire performance storage unit 122, and a model storage unit 123.

(User information storage unit 121)
The user information storage unit 121 stores user information. The user information storage unit 121 stores various types of user information regarding respondents to the questionnaire. For example, the user information storage unit 121 stores information on items such as "user ID (identifier),""age,""gender,""home,""worklocation," and "interest."

(Questionnaire results storage unit 122)
The questionnaire results storage unit 122 stores information regarding past questionnaire results. FIG. 4 is a diagram illustrating an example of the questionnaire performance storage unit 122 according to the embodiment. As shown in FIG. 4, the questionnaire performance storage unit 122 has items such as "questionnaire ID", "client ID", "questionnaire content", "questionnaire period", and "respondent information".

"Questionnaire ID" is an identifier for identifying each questionnaire, and "client ID" is an identifier for identifying the client that has set each questionnaire. "Questionnaire content" indicates the content of the corresponding questionnaire, and "questionnaire period" indicates the period during which the questionnaire was conducted.

“Respondent information” indicates information regarding respondents (users) who actually responded to the corresponding questionnaire. For example, the answerer information item here stores information regarding the answerer's user ID and the date and time of the answer.

(Model storage unit 123)
The model storage unit 123 stores information regarding models. The model here is a model that has learned the relationship between the questionnaire content and the respondents. As described later, the model is generated by the generation unit 132.

(Control unit 130)
The control unit 130 is a controller, and controls the information processing device 100 using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array). This is achieved by executing various programs (corresponding to an example of an information processing program) stored in an internal storage device using a storage area such as a RAM as a work area. In the example shown in FIG. 3, the control unit 130 includes a receiving unit 131, a generating unit 132, an estimating unit 133, and a providing unit 134.

(Reception Department 131)
The reception unit 131 receives questionnaire information regarding the input results of the questionnaire from the client terminal 50 via the communication unit 110 . Upon receiving the questionnaire information, the reception unit 131 registers it in the questionnaire performance storage unit 122 and passes it to the estimation unit 133.

Further, the reception unit 131 receives various types of user information via the communication unit 110 and registers the user information in the user information storage unit 121.

(Generation unit 132)
The generation unit 132 generates a model that has learned the relationship between the contents of the questionnaire and the respondents who answered the questionnaire, based on past answers to questionnaires. The generation unit 132 generates a model that has learned the relationship between the questionnaire contents and the respondents of the questionnaire based on the questionnaire results registered in the questionnaire performance storage unit 122 , and registers it in the model storage unit 123 .

For example, the generation unit 132 generates a model for estimating the number of expected respondents for each attribute based on the contents of the questionnaire. The attributes here are demographic attributes such as the respondent's gender, age, and residential area (region), but may also include psychographic attributes such as interests.

Note that any type of model can be adopted as the model. For example, the generation unit 132 may employ SVM (Support Vector Machine) or DNN (Deep Neural Network) as a model. Here, the DNN may be a CNN (Convolutional Neural Network) or an RNN (Recurrent Neural Network). Further, the RNN may be LSTM (Long short-term memory) or the like. That is, any type of model can be adopted as the model. Further, the model may be a model realized by combining a plurality of models, such as a model combining CNN and RNN.

The learning is, for example, deep learning using a deep neural network (DNN). Data mining and other machine learning algorithms may also be used. The generation unit 132 performs model learning using the various learning methods described above.

Further, the generation unit 132 may perform model learning based on past questionnaire results, using incentives paid to questionnaire respondents as learning data in addition to the questionnaire contents. Note that the incentive here is, for example, points that can be used in a web service provided by the information processing device 100, as described later, but it may also be a coupon, an exchange ticket, or the like.

(Estimation unit 133)
The estimating unit 133 estimates prospective respondents who are expected to respond to the questionnaire based on the questionnaire content received by the receiving unit 131 and the response record regarding past questionnaires.

For example, the estimation unit 133 inputs the questionnaire contents into a model stored in the model storage unit 123, and estimates potential respondents based on the output value. For example, the estimation unit 133 estimates the number of respondents for each attribute (gender, age, region) of potential respondents.

The information regarding potential respondents estimated by the estimating unit 133 is sent to the client terminal 50 via the providing unit 134 and displayed on the client terminal 50, for example, as shown in FIG. 2.

Furthermore, the estimating unit 133 may estimate potential respondents based on incentives paid to respondents to the questionnaire. FIG. 5 is a diagram illustrating an example of incentive-based processing according to the embodiment.

For example, when the input screen G1 shown in FIG. 1 is scrolled down on the client terminal 50, a reward point input screen G2 is displayed. Note that reward points are an example of incentives paid to respondents to the questionnaire.

For example, the client can arbitrarily add reward points, and when reward points are added, this information is transmitted from the client terminal 50 to the information processing device 100, and the estimation unit 133 calculates information regarding the questionnaire contents and reward points. Estimate likely respondents by inputting information into a model.

Then, when the estimation unit 133 estimates the likely answerer, the answer prediction screen shown in FIG. 2 is updated, for example. Thereby, the client can approximate the distribution of prospective respondents to his/her desired distribution by appropriately changing the contents of the questionnaire and the reward points.

(Providing unit 134)
Returning to the explanation of FIG. 3, the providing unit 134 will be explained. The providing unit 134 provides the client terminal 50 with information regarding the prospective respondents estimated by the estimating unit 133. For example, as shown in FIG. 2, the providing unit 134 provides the client terminal 50 with information for displaying a graph showing the attribute distribution of prospective respondents.

Furthermore, the providing unit 134 may provide proposal information to the client terminal 50. FIG. 6 is a diagram illustrating an example of proposal information according to the embodiment. For example, as shown in FIG. 6, when the input screen G1 shown in FIG. 1 is scrolled down, an input screen G3 for setting the desired number of answers is displayed on the client terminal 50.

Here, the desired number of responses is the desired number of responses to the questionnaire. For example, as shown in FIG. 6, the client can input the attributes of the respondent and the desired number of responses. The example shown in the same figure indicates that the user wishes to respond ``1000 times'' to ``a man in his 20s''.

In this case, the providing unit 134 provides, as proposal information, prospective information regarding the total number of times the survey will be conducted to reach the desired number of responses, based on the estimation result of the estimating unit 133, for example. Note that the providing unit 134 may provide, for example, information regarding the implementation period of the questionnaire as the suggestion information, instead of being limited to the total number of times the survey has been conducted.

Furthermore, the providing unit 134 may, for example, provide suggestion information that suggests reward points for reaching the desired number of responses. In this case, for example, the providing unit 134 inputs information regarding a plurality of reward points into the model in the model storage unit 123, searches for reward points that reach the desired number of responses, and sends the information regarding the reward points to the client terminal 50 as proposal information. Provide to.

[3. Processing flow]
Next, a processing flow executed by the information processing apparatus 100 according to the embodiment will be described using FIG. 7. FIG. 7 is a flowchart illustrating an example of provision processing according to the embodiment.

As shown in FIG. 7, the information processing apparatus 100 receives questionnaire information from the client terminal 50 (step S101). Subsequently, the information processing apparatus 100 estimates potential respondents based on the questionnaire content of the questionnaire information received from the client terminal 50 (step S102).

Subsequently, the information processing device 100 provides respondent information regarding prospective respondents to the client terminal 50 (step S103). Then, the information processing device 100 ends the process.

[4. effect〕
As described above, the information processing device 100 according to the present application has a reception unit 131 that receives information regarding the contents of a questionnaire, and a survey based on the contents of the questionnaire accepted by the reception unit 131 and the response record regarding past questionnaires. The estimation unit 133 includes an estimating unit 133 that estimates potential respondents who are expected to respond to a question, and a providing unit 134 that provides information regarding the likely respondents estimated by the estimating unit 133.

Further, the providing unit 134 provides information that visualizes the distribution of prospective respondents. Further, the providing unit 134 provides a graph displaying the distribution of residential areas of prospective respondents on a map. Further, the providing unit 134 provides a graph visualizing the distribution of potential respondents by age.

Further, the receiving unit 131 receives information regarding the desired number of responses for each attribute of the respondent, and the providing unit 134 provides information regarding the expected number of responses to the questionnaire that is expected to achieve the desired number of responses.

Further, the reception unit 131 receives information regarding incentives to be paid to respondents to the questionnaire, and the estimation unit 133 estimates potential respondents based on the incentives. Further, the receiving unit 131 receives information regarding incentives to be paid to respondents to the questionnaire and the desired number of responses to the questionnaire, and the providing unit 134 receives proposal information regarding incentives to be paid to respondents according to the desired number of responses. provide.

The information processing device 100 according to the embodiment also includes a generation unit 132 that generates a model that has learned the relationship between questionnaire contents and respondents who answered the questionnaire, based on past response results regarding questionnaires, and an estimation unit 133. uses the model generated by the generation unit 132 to estimate potential respondents.

Through any one or a combination of the above-described processes, the information processing apparatus according to the present application can provide the client with information regarding the respondents to the questionnaire in advance.

[5. Hardware configuration]
Further, the information processing apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 8, for example. FIG. 8 is a diagram showing an example of the hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are connected to a bus. 1090.

The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and performs various processes. The arithmetic device 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the calculation device 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and includes a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid Disk Drive). This is realized using flash memory, etc. The secondary storage device 1050 may be a built-in storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface) and HDMI (registered trademark) (High Definition Multimedia Interface). Further, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, button, scanner, etc., and is realized by, for example, a USB or the like.

Further, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, output device 1010 and input device 1020 may be wireless devices.

Moreover, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

Note that the input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

Network I/F 1080 receives data from other devices via network N and sends it to computing device 1030, and also sends data generated by computing device 1030 to other devices via network N.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070. For example, the arithmetic device 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the information processing device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 by executing a program loaded onto the primary storage device 1040. Further, the arithmetic device 1030 of the computer 1000 may load a program obtained from another device via the network I/F 1080 onto the primary storage device 1040, and execute the loaded program. Furthermore, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I/F 1080, and may call and use program functions, data, etc. from other programs of other devices.

[6. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those that are in a so-called equivalent range. Furthermore, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the constituent elements can be made without departing from the gist of the embodiments described above.

Further, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed manually. All or part of this can also be performed automatically using known methods. In addition, information including the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed arbitrarily, unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Furthermore, each component of each device shown in the drawings is functionally conceptual, and does not necessarily need to be physically configured as shown in the drawings. In other words, the specific form of distributing and integrating each device is not limited to what is shown in the diagram, and all or part of the devices can be functionally or physically distributed or integrated in arbitrary units depending on various loads and usage conditions. Can be integrated and configured.

For example, the information processing device 100 described above may be realized by a plurality of server computers, or depending on the function, it may be realized by calling an external platform etc. using an API (Application Programming Interface), network computing, etc. can be changed flexibly.

Furthermore, the above-described embodiments and modifications can be combined as appropriate within a range that does not conflict with the processing contents.

Further, the above-mentioned "section, module, unit" can be read as "means", "circuit", etc. For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

50 Client terminal 100 Information processing device 110 Communication unit 120 Storage unit 121 User information storage unit 122 Questionnaire performance storage unit 123 Model storage unit 130 Control unit 131 Reception unit 132 Generation unit 133 Estimation unit 134 Provision unit

Claims (11)

A reception department that receives information regarding the contents of the questionnaire;
an estimating unit that estimates prospective respondents who are expected to respond to the questionnaire based on the questionnaire content received by the reception unit and response results regarding past questionnaires;
a providing unit that provides information regarding the prospective respondents estimated by the estimating unit;
An information processing device comprising: The provision department is
The information processing device according to claim 1, wherein the information processing device provides information that visualizes the distribution of the prospective respondents. The provision department is
The information processing device according to claim 2, further comprising: providing a graph displaying the distribution of residential areas of the prospective respondents on a map. The provision department is
The information processing device according to claim 2 or 3, further comprising: providing a graph that visualizes the distribution of the prospective respondents by gender. The provision department is
The information processing device according to claim 2 or 3, further comprising: providing a graph visualizing the distribution of the potential respondents by age. The reception department is
Receive information regarding the desired number of responses for each attribute of respondents to the questionnaire;
The provision department is
The information processing apparatus according to claim 1, further comprising: providing information regarding the expected number of responses to a questionnaire that is expected to achieve the desired number of responses. The reception department is
accept information regarding incentives to be paid to respondents of said survey;
The estimation unit is
The information processing device according to claim 1, wherein the likely responder is estimated based on the incentive. The reception department is
receiving information regarding the incentives to be paid to respondents to the survey and the desired number of responses to the survey;
The provision department is
The information processing device according to claim 1, further comprising: providing proposal information regarding incentives to be paid to the respondent in accordance with the number of desired responses. a generation unit that generates a model that has learned the relationship between the questionnaire contents and the respondents who answered the questionnaire, based on the response results regarding the past questionnaires;
The estimation unit is
The information processing device according to claim 1, wherein the likely answerer is estimated using the model generated by the generation unit. An information processing method performed by a computer, the method comprising:
a reception process for receiving information regarding the questionnaire content;
an estimating step of estimating prospective respondents who are expected to respond to the questionnaire based on the questionnaire contents received in the receiving step and response results regarding past questionnaires;
a providing step of providing information regarding the prospective respondents estimated by the estimation step;
An information processing method characterized by comprising: A reception procedure for receiving information regarding the survey content of the survey;
an estimation step of estimating prospective respondents who are expected to respond to the questionnaire based on the questionnaire contents received in the reception procedure and response results regarding past questionnaires;
a providing step of providing information about the prospective respondents estimated by the estimation step;
An information processing program that causes a computer to execute.

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