Sales negotiation evaluation method

Abstract

Improve negotiation evaluation techniques. [Solution] A business negotiation evaluation method performed by an information processing device, comprising: acquiring audio data related to the business negotiation; and inputting the audio data into a trained model to output evaluation information, wherein the trained model is a trained model that has been trained on training data to which labels based on predetermined evaluation indicators are associated.

Description

Technical Field

[0001] This disclosure relates to a negotiation evaluation method.

Background Art

[0002] Conventionally, a technique for analyzing the content of negotiations related to products has been known. For example, Patent Document 1 discloses a dialogue analysis system that checks whether a salesperson explains matters to be explained and does not mention matters that should not be mentioned in negotiations with customers.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Although Patent Document 1 shows a technique for analyzing the content of negotiations by machine learning, evaluation of the content of negotiations, pointing out improvements in the way of conducting negotiations, etc. have not been sufficiently studied so far. Thus, there has been room for improvement in negotiation evaluation techniques.

[0005] In view of such circumstances, an object of the present disclosure is to improve negotiation evaluation techniques.

Means for Solving the Problems

[0006] A negotiation evaluation method according to an embodiment of the present disclosure is a negotiation evaluation method executed by an information processing apparatus, acquiring voice data related to a negotiation, inputting the voice data into a learned model to output evaluation information, and including The aforementioned trained model is a trained model that has been trained on training data to which labels based on predetermined evaluation metrics are associated. [Effects of the Invention]

[0007] According to one embodiment of this disclosure, the business negotiation evaluation technology is improved. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing the schematic configuration of the system according to this embodiment. [Figure 2] This is a flowchart showing the operation of an information processing device. [Modes for carrying out the invention]

[0009] The embodiments of this disclosure will now be described. Referring to Figure 1, the overview and configuration of System 1 according to this embodiment will be described. System 1 according to this embodiment comprises an information processing device 10 and a terminal device 20. The information processing device 10 is a server device installed, for example, in a data center. The terminal device 20 is any device used by a user. These devices are connected to each other so as to be able to communicate via a network 30 such as the Internet. In Figure 1, one information processing device 10 and one terminal device 20 are shown, but System 1 may comprise multiple such devices.

[0010] First, an overview of this embodiment will be described, and details will be described later. In this embodiment, the business negotiation is, for example, a business negotiation related to the sale of a vehicle, and the offering related to the business negotiation is a vehicle, but is not limited to this. For example, the business negotiation may be a meeting aimed at concluding various types of contracts, such as the buying and selling of real estate, the contract of insurance products, or the sale of financial products. Furthermore, the offering related to the business negotiation in this embodiment may be goods, services, digital content, licenses, data / information, financial products, real estate, intangible assets, other tradable rights, etc. The business negotiation evaluation method according to this embodiment is performed by the information processing device 10. First, the information processing device 10 acquires audio data related to the business negotiation. The information processing device 10 also inputs the audio data into a trained model and outputs evaluation information. Here, the trained model is trained based on training data to which labels based on predetermined evaluation indicators are associated.

[0011] Thus, according to this embodiment, the information processing device 10 acquires audio data related to a business negotiation, inputs the audio data into a trained model, and outputs evaluation information. The trained model is trained based on training data to which labels based on predetermined evaluation indicators are associated. Therefore, since objective evaluation information related to the business negotiation is automatically obtained, the objectivity of the evaluation and the efficiency of feedback are improved, thus improving the business negotiation evaluation technology.

[0012] Next, the configurations of the information processing device 10 and the terminal device 20 will be described in detail.

[0013] As shown in Figure 1, the information processing device 10 comprises a control unit 11, a storage unit 12, an input unit 13, an output unit 14, and a communication unit 15. The control unit 11 includes at least one processor. The processor is a general-purpose processor such as a CPU, or a dedicated processor specialized for a specific process. The control unit 11 controls each part of the information processing device 10 and executes processes related to the operation of the information processing device 10. The storage unit 12 includes at least one semiconductor memory, such as RAM or ROM. The storage unit 12 functions as, for example, a main memory or an auxiliary memory. The storage unit 12 stores data used for the operation of the information processing device 10 and data obtained by the operation of the information processing device 10. For example, the storage unit 12 stores a trained model. The trained model is a model created by machine learning using a machine learning algorithm. The trained model may be, for example, a machine learning model built on a decision tree, a Convolutional Neural Network (CNN), a Recurrent Neural Network (RNN), or a model generated based on other machine learning algorithms such as deep learning. The input unit 13 includes at least one input interface. The input interface may be, for example, a physical key, a touchscreen, a sound sensor that accepts voice input, or a camera that accepts gesture input. The input unit 13 accepts operations to input data used for the operation of the information processing device 10. The output unit 14 includes at least one output interface. The output interface may be, for example, a display that outputs information as video, or a speaker that outputs information as audio. The output unit 14 outputs data obtained by the operation of the information processing device 10. The communication unit 15 includes at least one external communication interface. The communication interface may be either a wired communication interface or a wireless communication interface. In the case of wired communication, the communication interface may be, for example, a LAN or USB. In the case of wireless communication, the communication interface may be, for example, an interface compatible with a mobile communication standard such as 5G, or an interface compatible with short-range wireless communication.The communication unit 15 receives data used for the operation of the information processing device 10 and transmits data obtained through the operation of the information processing device 10.

[0014] As shown in Figure 1, the terminal device 20 comprises a control unit 21, a storage unit 22, an input unit 23, an output unit 24, and a communication unit 25. The control unit 21 includes at least one processor. The processor is a general-purpose processor such as a CPU, or a dedicated processor specialized for specific processing. The control unit 21 controls each part of the terminal device 20 and executes processing related to the operation of the terminal device 20. The storage unit 22 includes at least one semiconductor memory, etc. The semiconductor memory is, for example, RAM or ROM. The storage unit 22 functions, for example, as a main memory or auxiliary memory. The storage unit 22 stores data used for the operation of the terminal device 20 and data obtained by the operation of the terminal device 20. The input unit 23 includes at least one input interface. The input interface may be, for example, a physical key, a touchscreen, a sound sensor that accepts voice input, or a camera that accepts gesture input. The input unit 23 accepts operations to input data used for the operation of the terminal device 20. The output unit 24 includes at least one output interface. The output interface is, for example, a display that outputs information as video, or a speaker that outputs information as audio. The output unit 24 outputs data obtained by the operation of the terminal device 20. The communication unit 25 includes at least one external communication interface. The communication interface may be either a wired communication interface or a wireless communication interface. In the case of wired communication, the communication interface is, for example, a LAN or USB. In the case of wireless communication, the communication interface is, for example, an interface compatible with a mobile communication standard such as 5G, or an interface compatible with short-range wireless communication. The communication unit 25 receives data used in the operation of the terminal device 20 and transmits data obtained by the operation of the terminal device 20.

[0015] The functions of the information processing device 10 or terminal device 20 are realized by executing a program according to this embodiment on a processor corresponding to the control unit 11 or control unit 21. In other words, the functions of the information processing device 10 or terminal device 20 are realized by software. The program causes the computer to function as the information processing device 10 or terminal device 20 by having the computer execute the operations of the information processing device 10 or terminal device 20. In other words, the computer functions as the information processing device 10 or terminal device 20 by executing the operations of the information processing device 10 or terminal device 20 according to the program. In this embodiment, the program can be recorded on a computer-readable recording medium. The computer-readable recording medium includes non-temporary computer-readable media, such as magnetic recording devices and semiconductor memory. The program can be distributed, for example, by selling, transferring, or lending a portable recording medium such as a DVD on which the program is recorded. Alternatively, the program may be distributed by storing the program on the storage of an external server and transmitting the program from the external server to another computer. The program may also be provided as a program product. Some or all of the functions of the information processing device 10 or the terminal device 20 may be implemented by a dedicated circuit corresponding to the control unit 11 or the control unit 21. In other words, some or all of the functions of the information processing device 10 or the terminal device 20 may be implemented by hardware.

[0016] Referring to Figure 2, the operation of the information processing device 10 according to this embodiment will be described. Here, the example mainly describes a business negotiation, for example, a business negotiation related to the sale of a vehicle, and the offering related to the business negotiation is a vehicle. First, the control unit 11 of the information processing device 10 acquires audio data related to the business negotiation (S10). Any method can be used for the acquisition of audio data related to the business negotiation. For example, the control unit 11 may acquire audio data related to the business negotiation from an external device, including a terminal device 20, via the communication unit 15 and the network 30. Alternatively, for example, the control unit 11 may acquire audio data related to the business negotiation via the input unit 13.

[0017] Next, the control unit 11 inputs the audio data into the trained model and outputs evaluation information (S20). The evaluation information may include an evaluation score and comments. The evaluation score may be a numerical value representing the staff's response in a sales negotiation on a 5-point scale, for example. The comments may be text information including specific points for improvement and strengths of the staff's response. This provides specific feedback on the staff's response in a sales negotiation, in addition to a numerical evaluation, which can be used for further improvement and training. Here, the trained model is trained based on training data to which labels based on predetermined evaluation indicators are associated. The predetermined evaluation indicators include at least one of the following: the content of the staff's explanation, the stability of their speaking speed, the staff's emotions, the amount of information obtained from the customer, the customer's reaction, the customer's tone of voice, the customer's emotions, and the intonation of their voice. The content of the staff's explanation includes product descriptions, explanations of necessary information, and explanations of advantages compared to competitors. The stability of the speaking speed can be evaluated by the average value, variance, etc., of the speed of the staff's conversation. For example, such stability can be used to evaluate whether the staff can converse smoothly. Staff emotions include the emotions of the staff when they are explaining key points in their explanation. For example, whether they can speak calmly at such key points should be evaluated. The amount of information obtained from the customer includes the amount of personal information obtained from the customer (hereinafter also referred to as personal information). Personal information includes information such as family structure, hobbies, daily lifestyle, information on currently owned vehicles, income and expenditure trends, and customer values. Family structure information includes whether they have a spouse or children, and the age range of family members. Hobby information includes information on preferences such as driving, outdoor activities, sports, and music. Daily lifestyle information includes information on commuting methods, frequency, and purpose of using the car. Information on currently owned vehicles includes information such as the type of vehicle owned, years of use, and reasons for replacement. Income and expenditure trend information includes information on budget and whether or not loans are used. Customer values ​​information includes information on priorities such as safety, fuel efficiency, and brand preference. Customer reactions include the frequency of positive and negative words.

[0018] By using such a predetermined evaluation index, the learned model can comprehensively evaluate the conversation content between the staff and the customer in the negotiation. For example, it is possible to judge the stability of the speaking speed, the calmness and persuasiveness of the staff from the intonation of the voice, and to infer the degree of interest, satisfaction, etc. from the changes in the customer's reaction and emotion. Based on this, high-precision evaluation information can be obtained, and effective feedback is possible in improving negotiations, staff education, etc.

[0019] For the output process of the evaluation information, any method can be adopted. For example, the control unit 11 may transmit data to the terminal device 20 via the communication unit 15, and the output unit 24 of the terminal device 20 may output the evaluation information through the user interface for display output. Alternatively, the control unit 11 may output the evaluation information through the user interface for display output by the output unit 14.

[0020] As described above, the information processing apparatus 10 according to the present embodiment acquires voice data related to the negotiation, inputs the voice data into the learned model, and outputs evaluation information. The learned model is trained based on teacher data associated with labels based on a predetermined evaluation index. Therefore, the negotiation evaluation technology is improved in that objective evaluation information related to the negotiation can be automatically obtained, thereby improving the objectivity of evaluation, the efficiency of feedback, etc.

[0021] Although the present disclosure has been described based on the drawings and examples, it should be noted that those skilled in the art may make various modifications and alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included in the scope of the present disclosure. For example, the functions included in each component or each step, etc. can be rearranged so as not to be logically contradictory, and it is possible to combine or divide a plurality of components or steps, etc. into one.

[0022] For example, the control unit 11 of the information processing apparatus 10 may further acquire still images and moving images related to the negotiation (hereinafter, these are also collectively referred to as image data). The images related to the negotiation include the expressions of at least one of the customer and the staff. Any method can be adopted for the acquisition process of the image data related to the negotiation. For example, the control unit 11 may acquire the image data related to the negotiation from an external device including the terminal device 20 via the communication unit 15 and the network 30. Also, for example, the control unit 11 may acquire the image data related to the negotiation via the input unit 13. Then, the control unit 11 may input the voice data and the image data into the learned model and output evaluation information. By doing so, a comprehensive evaluation using both the voice data and the image data becomes possible, and the interaction between the staff and the customer in the negotiation can be analyzed more precisely.

[0023] Also, for example, the evaluation information may be publicly disclosed via social media, review sites, word-of-mouth sites, etc. In this case, the control unit 11 of the information processing apparatus 10 may perform anonymization processing on the evaluation information to be publicly disclosed. For example, detailed information such as price setting, details of the negotiation process, required time, information of specific top performers, etc. may be anonymized or abstracted. This is because anonymization or abstraction is preferable from the perspective of privacy or the perspective that it may be advantageous for competing companies. Also, for example, the control unit 11 may process the evaluation information in a manner that emphasizes positive evaluations. Also, for example, a process of obtaining the consent of at least one of the staff, supervisor, or customer before the public disclosure may be executed for the evaluation information to be publicly disclosed.

[0024] Also, for example, in the above-described embodiment, an embodiment in which the configuration and operation of the information processing apparatus 10 are distributed to a plurality of computers capable of communicating with each other is also possible.

Explanation of Reference Numerals

[0025] 1: System, 10: Information processing device, 11: Control unit, 12: Storage unit, 13: Input unit, 14: Output unit, 15: Communication unit, 20: Terminal device, 21: Control unit, 22: Storage unit, 23: Input unit, 24: Output unit, 25: Communication unit, 30: Network

Claims

1. A business negotiation evaluation method performed by an information processing device, To acquire audio data related to business negotiations, The process involves inputting the aforementioned audio data into a trained model and outputting evaluation information. Includes, A business opportunity evaluation method, wherein the pre-trained model is a pre-trained model trained on training data to which labels based on predetermined evaluation metrics are associated.

2. A negotiation evaluation method according to claim 1, The aforementioned evaluation information includes a sales negotiation evaluation method, which includes evaluation scores and comments.

3. A negotiation evaluation method according to claim 1, A sales negotiation evaluation method in which the predetermined evaluation indicators include at least one of the following: the content of the explanation given by the staff, the consistency of the speaking speed, the staff's emotions, the amount of information obtained from the customer, the customer's reaction, the customer's tone of voice, the customer's emotions, and the intonation of the voice.

4. A negotiation evaluation method according to claim 1, further This includes obtaining image data related to the aforementioned business negotiation, A business negotiation evaluation method that inputs the aforementioned audio data and image data into a trained model and outputs evaluation information.

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