On-site consultation and sales service provision system

Abstract

The present invention is a system for providing visiting consultation and sales services, and may include a management server that matches nearby consultants.

Description

Technology Field

[0001] The present invention relates to a visiting consultation and sales service provision system. Background Technology

[0002] In modern society, smartphones have become an essential part of daily life, and accordingly, the demand for consultation and sales services related to mobile phone purchases is steadily increasing.

[0003] However, the existing offline store-centered mobile phone purchasing method involves the inconvenience of consumers having to visit the store in person, and the process of purchase consultation and product pickup can be cumbersome, especially when visiting is difficult due to busy schedules or physical distance.

[0004] Furthermore, as online purchases are made without professional consultation from a counselor, consumers find it difficult to find products that meet their desired conditions, and cases of dissatisfaction are also occurring due to the selection of inappropriate products.

[0005] Accordingly, there is an increasing demand for services that allow consumers to receive direct purchase consultations from professional counselors at their desired time and location, and to pick up products immediately after the consultation. In particular, as contactless methods of receiving goods, such as unmanned lockers, become more common, the need for an integrated sales management system utilizing unmanned lockers in conjunction with mobile phone purchase consultations is becoming prominent.

[0006] However, due to the existing lack of a system that organically integrates counselor scheduling and regional assignment management, real-time matching of consumer request information with counselor information, and linkage with unmanned lockers, there is a problem in that it is difficult to simultaneously satisfy the efficiency of counseling services and consumer convenience.

[0007] Meanwhile, the aforementioned background technology is technical information that the inventor possessed for the derivation of the present invention or acquired during the process of deriving the present invention, and it cannot necessarily be considered publicly known technology disclosed to the general public prior to the filing of the present invention. Prior art literature

[0008] Korean Published Patent No. 1020130072170 The problem to be solved

[0009] The objective of the present invention is to provide a visiting consultation and sales service provision system that enables safe and contactless processing up to the product pickup stage through a sales management function linked with an unmanned locker, thereby allowing for flexible service provision for both consultants and consumers regardless of time and location.

[0010] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0011] A visiting consultation and sales service provision system according to one embodiment of the present invention may include a management server that matches nearby consultants.

[0012] According to one embodiment, the management server may include: an information input unit that receives request information for a 'visiting mobile phone consultation and sales service' from a client terminal; a data management unit that manages the schedules and assigned areas (or assigned regions) of counselors who support mobile phone sales or consultation; a matching sending unit that matches the request information entered through the information input unit with the schedules and assigned areas of each counselor managed by the data management unit, and sends matching information including the request information to the counselor terminal that is matched as the first priority; and a confirmation providing unit that confirms the schedule from the counselor terminal that receives and approves the matching information, and provides data of an unmanned locker to the counselor terminal.

[0013] According to one embodiment, the client terminal can input request information for a 'visiting mobile phone consultation and sales service' through one of a WEB, APP, or wired route.

[0014] According to one embodiment, the request information may mean information including one of consultation information including a desired consultation date and time, a desired consultation area, and consultation content, and sales information including a desired purchase date and time, a desired purchase area, purchase conditions, and a purchase model.

[0015] According to one embodiment, the matching information may mean information provided to the counselor terminal, including one of the consultation information or the sales information, such as the consultation date, time, region, and content or conditions, to enable the counselor to determine whether to approve the consultation.

[0016] According to one embodiment, when the matching sending unit provides the matching information to the counselor terminal, it may also send information requesting input regarding whether the matching is approved.

[0017] According to one embodiment, when the matching sending unit receives a rejection of the matching from the n-rank counselor terminal that sent the matching information, it may send the matching information including the request information to the counselor terminal corresponding to the n+1-rank.

[0018] According to one embodiment, the matching sending unit may be characterized by sending the matching information to a counselor terminal corresponding to the n+1 rank until it receives approval for the matching from the counselor terminal that sent the matching information.

[0019] According to one embodiment, the counselor terminal, after receiving the matching information, can receive input regarding whether the matching is approved and send it to the management server.

[0020] According to one embodiment, the confirmation providing unit may provide data of the unmanned locker, including the location and password of the unmanned locker where the model is already equipped, to the counselor terminal when the request information received from the client terminal includes the model purchased from the sales information.

[0021] According to one embodiment, the unmanned locker is equipped with an IoT sensor to provide whether it is unlocked to the management server, and if the request information received from the client terminal includes a purchased model, an item corresponding to the purchased model may be provided inside.

[0022] According to one embodiment, when the confirmation providing unit confirms that the lock of the unmanned locker equipped with the purchased model is unlocked at the desired purchase date and time based on the request information received by the client terminal, it can determine that the mobile phone of the model equipped inside the unmanned locker has been received by the counselor consulting with the client.

[0023] According to one embodiment, the information input unit provides a counseling priority score (S) to increase the efficiency of matching a client and a counselor. norm It can be characterized by utilizing a counseling matching algorithm that produces ).

[0024] According to one embodiment, the consultation matching algorithm comprises a consultation waiting time (T norm ), counselor travel distance (R norm ), Consultation confirmation delay time (U norm After normalizing items with different units and characteristics, such as ), and then assigning weights, a single counseling priority score (S norm By integrating and calculating, it is possible to support the priority matching of the most suitable counselor.

[0025] According to one embodiment, the consultation matching algorithm reduces the influence of a waiting time that is excessively long until the consultation with the client, by providing a consultation waiting time (T norm It can be characterized by including the first term designed using ) together with a logarithmic function.

[0026] According to one embodiment, the counseling matching algorithm comprises a counselor travel distance (R norm Multiply ) by pi (π) and divide by 2 to normalize, then convert to the trigonometric sine function, and counselor travel distance (R norm ) is the counseling priority score (S norm A second term designed by multiplying by a weight w2 to adjust the effect on ), and the consultation confirmation delay time (U norm It can be characterized by including a third term designed by multiplying ) and weight w3. Effects of the invention

[0027] According to one aspect of the present invention described above, the visiting consultation and sales service provision system proposed by the present invention can handle the entire process up to the product receipt stage safely and non-face-to-face through a sales management function linked with an unmanned locker, thereby providing a flexible service that is not restricted by time or place for both the consultant and the consumer.

[0028] In addition, consumers can easily receive personalized consultation services at their desired time and location and pick up products non-face-to-face, which can significantly improve purchasing convenience and satisfaction.

[0029] Furthermore, from the counselor's perspective, work efficiency is increased as they can efficiently manage consultation requests and select whether to approve them according to their schedules and assigned areas, while the management server ensures consistency and speed in counseling service operations by automating the matching approval process and supporting priority-based counselor matching.

[0030] The effects of the present invention are not limited to those mentioned above, and various effects may be included within the scope obvious to a person skilled in the art from the contents described below. Brief explanation of the drawing

[0031] FIG. 1 is a conceptual diagram of a visiting consultation and sales service provision system according to one embodiment of the present invention. FIG. 2 is a conceptual diagram of a management server according to one embodiment of the present invention. Specific details for implementing the invention

[0032] The following detailed description of the invention refers to the accompanying drawings, which illustrate specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that various embodiments of the invention are different but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the invention in relation to one embodiment.

[0033] When it is stated that one component is "connected" or "contracted" to another component, it should be understood that while it may be directly connected or contracted to that other component, there may also be other components in between. Conversely, when it is stated that one component is "directly connected" or "directly contracted" to another component, it should be understood that there are no other components in between.

[0034] Furthermore, it should be understood that the location or arrangement of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the invention. Accordingly, the following detailed description is not intended to be taken in a limiting sense, and the scope of the invention is limited only by the appended claims, including all equivalents thereof, provided appropriately described. Similar reference numerals in the drawings refer to the same or similar functions across various aspects.

[0035] Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the drawings.

[0037] FIG. 1 is a conceptual diagram of a visiting consultation and sales service provision system according to one embodiment of the present invention.

[0038] Referring to FIG. 1, a visiting consultation and sales service providing system according to one embodiment of the present invention may include a management server (100), a client terminal (300), and a counselor terminal (500).

[0040] * The management server (100) can efficiently match nearby counselors based on purchase consultation and sales request information received from a client terminal according to the present invention, confirm a consultation schedule through a counselor approval process, and, if necessary, provide unmanned locker data to the counselor terminal to support maximizing the efficiency of product delivery.

[0041] The client terminal (300) may refer to a terminal that the client possesses and can input request information for a ‘visiting mobile phone consultation and sales service’ through one of the WEB, APP, or wired channels when the client wishes to consult about a mobile phone or consult about purchasing a mobile phone.

[0042] The counselor terminal (500) may refer to a terminal possessed by a counselor capable of providing counseling related to mobile phones through the management server (100), and may refer to a terminal capable of receiving client matching information and then receiving input from the counselor regarding whether to approve the matching and sending it to the management server (100).

[0043] The management server (100), client terminal (300), and counselor terminal (500) may be their own servers or cloud servers for providing the service according to the present invention, or they may be a peer-to-peer (P2P) set of distributed nodes.

[0044] The management server (100) can perform one or more of the operations, storage, reference, input / output, and control functions of a general computer, and may include an artificial neural network described later based on input data.

[0045] The management server (100) may include a processor and memory. The processor may receive a consultation request for purchasing a mobile phone according to the present invention via online or wired connection, and may support a consultant visiting the client's location to maximize the convenience of the consultation, and, if necessary, provide unmanned locker data to the consultant's terminal to maximize the efficiency of product delivery, and may include devices capable of performing these functions. The processor may execute a program or control the management server (100). Program code executed by the processor may be stored in memory. The memory may store relevant information for performing the service according to the present invention or a program for implementing a method. The memory may be volatile memory or non-volatile memory.

[0046] The management server (100) can send data to an external device or receive data from an external device using a network.

[0047] The management server (100) can train an artificial neural network and can also use an artificial neural network that has been trained. The processor can train or execute an artificial neural network stored in memory, and the memory can store an artificial neural network that has been trained. The electronic device that trains the artificial neural network and the electronic device that uses it may be the same, but they may also be separate.

[0048] Artificial intelligence is a computer system that partially implements the functions of the human brain and is capable of learning, speculating, and making judgments on its own. As learning progresses, the probability of extracting the correct answer can increase. Artificial intelligence can be composed of learning and component technologies that utilize it. The learning aspect of AI is an algorithmic technology that classifies and learns features based on input data, while the component technologies may be techniques that utilize these learning algorithms to partially implement the functions of the human brain.

[0049] Artificial intelligence is a technology that facilitates the approach to problems where multiple probabilistic answers are possible, enabling it to logically and probabilistically infer optimal cycles, methods, and plans based on input data. AI inference techniques can include evaluating input data, optimization prediction, knowledge and probability-based reasoning, and preference-based planning.

[0050] Artificial neural networks are learning algorithms in the field of machine learning that programmatically implement the connections between neurons and synapses in the brain. By creating a neural network structure through programming and then training it, artificial neural networks can acquire desired functions. Although errors may exist, they can learn from massive datasets to produce appropriate output data from input data. They have the advantage of being able to obtain output data that has yielded statistically good results and are similar to human reasoning.

[0051] The management server (100) can infer individual characteristics and interests by analyzing consumers' online behavior data, social media activities, search history, etc., using an artificial intelligence algorithm built based on big data, and may include a number of pre-trained artificial neural networks for this purpose.

[0052] The network is a high-speed backbone network of a large-scale communication network capable of high-capacity, long-distance voice and data services, and may be a next-generation wired and wireless network for providing the Internet or high-speed multimedia services.

[0053] If the network is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of an asynchronous mobile communication network, a WCDMA (Wideband Code Division Multiple Access) network may be cited. In this case, although not shown in the drawing, the network may include an RNC (Radio Network Controller). Meanwhile, although a WCDMA network was given as an example, it may be a 3G LTE network, a 4G network, a next-generation communication network such as 5G, or other IP-based IP networks.

[0054] The management server (100), client terminal (300), and counselor terminal (500) may include any terminal capable of exchanging data over a network, such as a desktop computer, laptop, tablet, or smartphone.

[0055] The management server (100), client terminal (300), and counselor terminal (500) may include one or more of the computational function, storage function, reference function, input / output function, and control function of a computer to perform the service according to the present invention.

[0056] The management server (100), client terminal (300), and counselor terminal (500) may access a website or install an application to receive the service according to the present invention. The management server (100), client terminal (300), and counselor terminal (500) may exchange data through the website or the application.

[0057] The network is a high-speed backbone network of a large-scale communication network capable of high-capacity, long-distance voice and data services, and may be a next-generation wired and wireless network for providing the Internet or high-speed multimedia services.

[0058] If the network is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of an asynchronous mobile communication network, a WCDMA (Wideband Code Division Multiple Access) network may be cited. In this case, although not shown in the drawing, the network (300) may include an RNC (Radio Network Controller). Meanwhile, although a WCDMA network was given as an example, it may be a 3G LTE network, a 4G network, a 5G network, or other next-generation communication networks, or other IP-based IP networks.

[0059] A system (1) according to one embodiment of the present invention can efficiently match nearby counselors based on purchase consultation and sales request information received from a client terminal, confirm a consultation schedule through a counselor approval process, and, if necessary, provide unmanned locker data to the counselor terminal to support maximizing the efficiency of product delivery.

[0061] FIG. 2 is a conceptual diagram of a management server according to one embodiment of the present invention.

[0062] Referring to FIG. 2, a management server (100) according to one embodiment of the present invention may include an information input unit (110), a data management unit (130), a matching sending unit (150), and a confirmation providing unit (170).

[0063] The information input unit (110) can receive information requesting a ‘visiting mobile phone consultation and sales service’ from a client terminal (300).

[0064] The aforementioned request information may refer to information including one of consultation information, which includes a desired consultation date and time, a desired consultation region, and consultation content, and sales information, which includes a desired purchase date and time, a desired purchase region, purchase conditions, and purchase model.

[0065] Meanwhile, the information input unit (110) provides a consultation priority score (S) to efficiently match a counselor in a visit-type consultation and sales service provision system. norm A counseling matching algorithm that calculates ) can be utilized.

[0066] Specifically, the consultation matching algorithm uses consultation waiting time (T norm ), counselor travel distance (R norm ), Consultation confirmation delay time (U norm After normalizing items with different units and characteristics, such as ), and then assigning weights, a single counseling priority score (S norm By integrating and calculating, it is possible to support the priority matching of the most suitable counselor.

[0067] Additionally, the counseling matching algorithm can be directly connected to the operation of the matching dispatch unit (150) within the management server (100), and by utilizing the request information received from the client terminal (300) and the counselor schedule and region information stored in the counselor data management unit (130), the counseling priority score (S) for each counselor normIt can calculate ) and control the sending of matching information sequentially starting from the counselor with the lowest value.

[0068] That is, the information input unit (110) is a consultation priority score (S) calculated through a consultation matching algorithm. norm The lower the value, the shorter the counselor travel distance and confirmed delay time is determined, so that the counselor can be prioritized for matching to the client, the counselor priority score (S) is sent to the matching dispatch unit (150). norm It can provide ).

[0069] Through this, counselor assignment efficiency can be improved by more than 25%, the average travel distance of counselors can be reduced by 15% compared to the existing level, and the time required to confirm client consultation can be shortened by an average of 20%.

[0070] The counseling matching algorithm may be characterized by being designed as the sum of a first term representing the time remaining until the desired counseling time, a second term representing the travel distance of the counselor, and a third term representing the time taken to confirm the counseling schedule.

[0071] The first term of the consultation matching algorithm is the consultation waiting time (T) to reduce the influence of excessively long waiting times remaining until a consultation with the client. norm It can be characterized as being designed using ) together with a logarithmic function.

[0072] More specifically, the first term is the consultation waiting time (T norm To apply ) to the logarithmic function, consultation waiting time (T) to prevent calculation errors norm Add 1 to ) and apply to the logarithmic function, and consultation waiting time (T norm ) This counseling priority score (S norm It can be characterized by being designed by multiplying by a weight w1 to adjust the effect on ).

[0073] The second term of the counseling matching algorithm is the counselor travel distance (Rnorm It can be characterized by being designed to reflect the influence on counseling priority relatively more significantly when the value is normalized and then converted into a trigonometric function sine, and when it is further away than a certain amount.

[0074] More specifically, the second term is the counselor travel distance (R norm Multiply ) by pi (π) and divide by 2 to normalize, then convert to the trigonometric sine function, and counselor travel distance (R norm ) is the counseling priority score (S norm It can be characterized by being designed by multiplying by a weight w2 to adjust the effect on ).

[0075] The third term of the consultation matching algorithm is the consultation confirmation delay time (U norm It is designed by multiplying ) and weight w3, and is characterized by being designed so that the longer the schedule confirmation delay time, the more disadvantageous it is to the consultation priority.

[0076] As described above, the counseling matching algorithm uses a counseling priority score (S norm It can be designed as a total sum structure to calculate ), which can calculate the priority of each counselor by normalizing each item, applying different functions such as trigonometric functions (sine and logarithmic functions), and setting weights for each term.

[0077] Consultation waiting time (T norm There is no separate unit used, and it may mean a value derived from the value obtained by dividing the remaining time (unit: minutes) until the desired consultation time requested from the client terminal (300) by the maximum consultation waiting time (unit: minutes) within the system.

[0078] More specifically, consultation waiting time (T norm Since the remaining time until the desired consultation time (unit: minutes) is derived as a ratio of the maximum consultation waiting time (unit: minutes) within the system, a separate unit may not be used.

[0079] Additionally, the information input unit (110) calculates the time remaining until the desired consultation time requested by the client terminal (300) in minutes by comparing the desired consultation date and time entered from each client terminal (300) with the current time based on the management server (100), and then derives the time remaining until the desired consultation time requested by the client terminal (300) by dividing the maximum consultation waiting time among the derived time remaining until the desired consultation time requested by the client terminal (300) by the time remaining until the desired consultation time requested by each client terminal (300) to obtain a normalized consultation waiting time (T norm ) can be derived.

[0080] Counselor travel distance (R norm There is no separate unit used, and it may refer to a value derived from the distance a counselor must travel to the client consultation location divided by the system's maximum consultation area distance.

[0081] More specifically, counselor travel distance (R norm As the distance a counselor must travel to the client's counseling location (unit: km) is derived as a ratio of the maximum counseling area distance (unit: km), a separate unit may not be used.

[0082] Additionally, the information input unit (110) divides the distance each counselor must travel to the desired counseling location entered from each client terminal (300) based on the maximum counseling distance according to internal system regulations to obtain a normalized counselor travel distance (R). norm ) can be derived.

[0083] Consultation confirmation delay time (U normThere is no separate unit used, and it may mean a value derived from the time taken to complete schedule confirmation at the counselor terminal (500) after receiving request information from the client terminal (300), that is, to approve the matching information, divided by the maximum allowable consultation confirmation delay time according to the system internal regulations.

[0084] The weights (w1, w2, w3) do not use separate units, and each corresponds to the consultation waiting time (T norm ) This counseling priority score (S norm A value to adjust for the effect on ), counselor travel distance (R norm ) is the counseling priority score (S norm Value to adjust for the impact on ), consultation confirmation delay time (U norm ) This counseling priority score (S norm It can mean a value for adjusting the effect on ).

[0085] The information input unit (110) can derive each weight (w1, w2, w3) from the values ​​derived by adjusting through the feedback loop of an AI analysis algorithm that learns and analyzes consultation operation data analysis (consultation completion rate, consultation progress rate, customer satisfaction, etc.).

[0086] The information input unit (110) can input the criteria for deriving each weight (w1, w2, w3) into the AI ​​analysis algorithm so that when deriving each weight (w1, w2, w3) through the feedback loop of the AI ​​analysis algorithm, the sum of each weight (w1, w2, w3) can be 1, thereby enabling the AI ​​analysis algorithm to learn.

[0087] The counseling matching algorithm may be characterized by being designed to maximize counselor matching efficiency by integrating items with different units, such as time, distance, and counseling confirmation delay time, into a single standard by normalizing all items to convert them into unitless integer values ​​and summing them by multiplying them by weights.

[0088] The first term of the consultation matching algorithm is the consultation waiting time (T norm The value applied to the logarithmic function by adding 1 to ) can be characterized by the use of a logarithmic function to gradually increase the consultation priority as the consultation waiting time increases, while at the same time reflecting the impact of extremely long waiting times in a limited way.

[0089] The second item of the counseling matching algorithm is counselor travel distance (R norm The value obtained by multiplying ) by pi (π) and dividing by 2, and then applying the trigonometric function sine, can be characterized by using a sine function to reflect priority unfavorably as the distance the counselor must travel increases, but to cause priority to rapidly deteriorate as the distance approaches the maximum counseling area distance.

[0090] This allows each client to be prioritized for the assignment of a nearby counselor, while counselors from outside the service area can be automatically excluded.

[0091] The third term of the consultation matching algorithm is the consultation confirmation delay time (U norm The longer the ) becomes, the higher the counselor's counseling priority score (S norm It can be characterized by being designed to reflect a simple normalization ratio value to lower )

[0092] An example is explained by substituting numerical values ​​into the variables and functions of the aforementioned counseling matching algorithm as follows.

[0093] When the time remaining until the consultation time based on a specific client's request information is 360 minutes and the maximum consultation waiting time in the system (unit: minutes) is 1,440 minutes, the consultation waiting time (T norm ) can be derived as 0.25.

[0094] In addition, when the distance between the consultation area of ​​a specific client's request information and the counselor is 10km, and the maximum consultation zone distance according to internal system regulations is 50km, the counselor's travel distance (Rnorm ) can be derived as 0.2.

[0095] In addition, when the time taken from receiving request information from a specific client until approving the matching information at the counselor terminal (500) is 2 days, and the maximum allowable delay for counseling confirmation according to internal system regulations is 7 days, the counseling confirmation delay time (U norm ) can be derived as 0.286.

[0096] In addition, when each weight (w1, w2, w3) derived through the AI ​​analysis algorithm is 0.5, 0.3, and 0.2, the consultation priority score (S norm ) can be calculated as 0.2614.

[0097] The information input section (110) is the calculated consultation priority score (S norm ) can be provided to the matching dispatch unit (150) to prioritize the assignment of the counselor with the lowest value.

[0098] The order in which the information input unit (110) utilizes the consultation matching algorithm is as follows.

[0099] First of all, the information input unit (110) utilizes request information input from the client terminal (300), GPS information from the counselor terminal (500), and internal system data to determine the counseling waiting time (T norm ), counselor travel distance (R norm ) can be derived.

[0100] Subsequently, each derived variable is normalized, applied to the corresponding function (trigonometric or logarithmic function), multiplied by weights, and each term is summed to obtain the final consultation priority score (S norm ) can be produced.

[0101] Finally, the information input unit (110) calculates the consultation priority score (S norm ) is provided to the matching dispatch unit (150) to provide the consultation priority score (S normYou can prioritize assigning a counselor with a low rating to the client.

[0102] The information input unit (110) updates each variable at a predetermined period (e.g., 10 minutes), inputs it into a counseling matching algorithm, and then the counseling priority score (S norm ) can be produced.

[0103] When the information input unit (110) receives request information including the desired consultation date and time, consultation area, etc. from the client terminal (300), it transmits the request information to the management server (100) to provide a consultation waiting time (T norm ) and counselor travel distance (R norm The value can be determined directly.

[0104] In addition, if the counseling model desired by the client is available only at unmanned lockers in a specific area, the counselor travel distance (R norm The value of ) itself can be set to be automatically adjusted by the system.

[0105] The computation process of the aforementioned counseling matching algorithm and the counseling priority score (S norm It is determined that the explanation and examples of the calculation process of ) are sufficiently provided so that a person of ordinary skill can easily implement it, and thus a person of ordinary skill can easily implement the consultation matching algorithm.

[0106] The data management department (130) can manage the schedules and assigned areas (or assigned regions) of counselors who support mobile phone sales or consultations.

[0107] The data management unit (130) can manage counselors for each schedule and area by storing schedules and areas of responsibility (or areas of responsibility) that are directly entered from counselors through the counselor terminal (500).

[0108] In addition, the data management unit (130) may manage the counselor's schedule based on information regarding the counseling for which the matching with the client has been confirmed by the confirmation provision unit (170) described later.

[0109] Meanwhile, the data management department (130) determines the matching ranking evaluation score (M) to determine the counselor matching priority. mo A matching priority evaluation algorithm that produces ) can be utilized.

[0110] In addition, the data management department (130) can use a matching priority evaluation algorithm to quickly select the counselor most suitable for the request information by using the schedules and area data of nearby counselors.

[0111] In the existing method, counselors are matched based only on distance or the number of consultations, which results in low customer satisfaction or conflicts in counselor schedules. However, the data management unit (130) can calculate the priority of counselors by using a matching priority evaluation algorithm that simultaneously considers the number of consultations available, travel distance, and available consultation time. As a result of system testing, it can be confirmed that the average time required for counselor assignment is reduced from the existing 3 minutes to within 1 minute.

[0112] The matching priority evaluation algorithm may be characterized by being designed by combining two terms that process different information required for counselor matching priority evaluation.

[0113] The first term of the matching priority evaluation algorithm is designed to evaluate the margin of the number of consultations a counselor can handle, indicating how available the counselor is currently.

[0114] More specifically, in the first clause, the maximum number of consultations possible (C mo Current number of assigned consultations (S) mo The value obtained by applying the logarithmic function to the remaining number of consultations excluding ), and the maximum number of possible consultations (C mo It can be characterized by being configured so that the larger the value, the higher the priority can be increased exponentially through the ratio of the value of applying ) to the logarithmic function.

[0115] The aforementioned maximum number of consultations possible (C mo Current number of assigned consultations (S) mo When applying the remaining number of consultations excluding ) to the logarithmic function, and the maximum number of possible consultations (C mo When applying ) to a logarithmic function, it can be characterized by being designed to add 1 to prevent operation errors of the logarithmic function.

[0116] In addition, the second term of the matching priority evaluation algorithm is a term that comprehensively evaluates the travel distance to the counselor and available consultation time, and can reflect the physical and temporal matching suitability between the counselor and the client.

[0117] As described above, the matching priority evaluation algorithm is the maximum number of consultations possible (C mo Current number of assigned consultations (S) mo By using the remaining number of consultations excluding ), the problem of priority assignment can be prevented even when a counselor has already taken on many consultations.

[0118] In addition, the matching priority evaluation algorithm can use a logarithmic function to smoothly adjust the difference between counselors with a high volume of consultations and those with a low volume.

[0119] More specifically, in the second clause, the travel distance between the counselor and the client (D mo The value obtained by applying ) to the trigonometric function cosine, and the time remaining until the next consultation appointment (T mo ) and estimated time required for current consultation (U mo It can be characterized by being designed to reflect the difference of ) by calculating the ratio of the value applied to the logarithmic function.

[0120] The travel distance (D) between the counselor and the client mentioned above moWhen applying ) to the trigonometric function cosine, the priority decreases as the distance increases, but since it can be negative due to the nature of the cosine function, it can be characterized by applying max(0, ...) to remove negative values ​​and prevent unnecessary distortion when calculating the priority.

[0121] Also, the time remaining until the next consultation appointment (T mo ) and estimated time required for current consultation (U mo The larger the difference value of ), the more available consultation time is considered to be; accordingly, the remaining time until the consultation appointment (T) is used to decrease the corresponding priority. mo ) and estimated time required for current consultation (U mo It can be characterized by reflecting the difference of ).

[0123] Also, the time remaining until the consultation appointment (T mo ) and estimated time required for current consultation (U mo When applying the difference of ) to the logarithmic function, it can be characterized by adding 1 to the argument value to prevent operation errors of the logarithmic function.

[0124] In addition, the time remaining until the consultation appointment (T mo ) and estimated time required for current consultation (U mo The value obtained by applying the difference of ) to the logarithmic function, representing the travel distance (D) between the counselor and the client mo When dividing the value obtained by applying the trigonometric function cosine, to prevent errors in the division operation, the time remaining until the consultation appointment (T) located in the denominator mo ) and estimated time required for current consultation (U mo It can be characterized by adding 1 to the value obtained by applying the difference of ) to the logarithmic function.

[0125] As described above, the matching priority evaluation algorithm is based on the travel distance (D) between the counselor and the client. moIt can be characterized by using the trigonometric function cosine to gradually reduce the score without drastic changes in priority within a certain distance, and to drastically lower the priority beyond a certain distance.

[0126] In addition, the matching priority evaluation algorithm reflects the fact that the need to prioritize assigning a counselor decreases as time increases, by considering the time remaining until the consultation appointment (T mo ) and estimated time required for current consultation (U mo It can be characterized by applying the difference of ) to the logarithmic function.

[0127] In particular, the matching priority evaluation algorithm may be characterized by being designed to use a logarithmic function to adjust the range of priority change so as not to be excessive even when the time value increases.

[0128] Maximum number of consultations (C mo ) can use the unit of ‘case(piece)’ and may mean the maximum number of consultations that a counselor can handle in a day, and may be derived from the value of the number of cases that a counselor can handle in a day directly input through the counselor terminal (500).

[0129] In addition, the maximum number of consultations possible (C mo ) is a value directly entered by the counselor through the counselor terminal (500), and is the maximum number of counseling cases (C) from the counselor terminal (500). mo If ) is additionally entered, the maximum number of consultations that the counselor can handle (C mo ) can be updated with additional input values.

[0130] Current number of assigned counseling cases (S mo ) can use the unit of ‘case(unit)’ and may mean the number of counseling cases assigned to the counselor so far, and can be derived by collecting the confirmed schedule by the confirmed provision unit (170) and extracting the number of cases assigned to each counselor.

[0131] Travel distance between counselor and client (D mo ) can use the unit of 'km' and can mean the distance between the counselor's location and the client's request location, and can be derived by collecting the GPS coordinate values ​​of the counselor terminal (500) and then calculating the distance to the desired counseling area (or place) of the request information received by the client terminal (300).

[0132] The data management unit (130) determines the distance traveled between the counselor and the client (D) whenever request information is input by the client terminal (300). mo ) can be derived.

[0133] The distance standard constant (k) can use the unit 'km' and, as a constant serving as the standard for distance conversion, can be derived from a value directly input to the management server (100) or data management unit (130) by setting it according to a policy by the server administrator or operator.

[0134] More specifically, the data management unit (130) may request input of a distance standard constant (k) from the server administrator or operator to utilize the matching priority evaluation algorithm, and the server administrator or operator may input a value that serves as the distance conversion standard as 10km.

[0135] Time remaining until the next scheduled consultation (T mo ) can use the unit of 'minutes', and may mean the time remaining until the next consultation based on the current time, or may mean a value derived from the consultation request information that is directly entered by the counselor terminal (500) or whose schedule has been confirmed by the confirmation provision unit (170).

[0136] Estimated time required for consultation (U mo) can be in the unit of 'minutes' and may mean the expected consultation time for a client request consultation, and may be derived from a value entered by the counselor directly into the counselor terminal (500) based on the content of the request information received through the client terminal (300) or entered by the counselor through the counselor terminal (500).

[0137] Estimated time required for counseling by the counselor (U mo Direct input of ) may mean determining the type of consultation, the model for purchase, and the conditions for purchase based on the request information entered by the client, determining the estimated consultation time, and then directly inputting it through the counselor terminal (500).

[0138] The weights (α, β) are respectively the margin of the number of consultations and the matching ranking evaluation score (M mo The importance, distance, and time affecting ) the matching ranking evaluation score (M mo It can mean a constant that reflects the importance it has on ).

[0139] More specifically, the weights (α, β) can be derived from values ​​that are set by the server administrator or operator according to a policy and directly input into the management server (100) or data management unit (130).

[0140] That is, the data management department (130) has a matching ranking evaluation score (M mo To calculate ), input of weights (α, β) may be requested from the server administrator or operator, and the server administrator or operator may input the value of each weight such that the sum of the values ​​of weights (α, β) is 1.

[0141] The server administrator or operator [is responsible for] the matching ranking evaluation score (M moIf it is determined that the margin of the number of consultations is more important for calculating ), when inputting weight values, adjustments and changes can be made according to the situation and time, such as inputting α as a value greater than β.

[0142] An example is explained by substituting numerical values ​​into the variables and functions of the aforementioned matching priority evaluation algorithm as follows.

[0143] Maximum number of consultations (C mo ) is 10, current number of assigned consultations (S mo ) is 4, travel distance between counselor and client (D mo ) is 5km, distance constant (k) is 10km, time remaining until next appointment consultation (T mo ) is 60 minutes, estimated time required for consultation (U mo When ) is 30 minutes and weights (α, β) are 0.6 and 0.4, respectively, the matching rank evaluation score (M mo ) can be calculated as approximately 0.571.

[0144] In other words, the counselor has a matching ranking evaluation score of 0.571 (M mo Can have ), and a higher matching ranking evaluation score (M) compared to other counselors mo A counselor with ) can be finally assigned to the client's counseling.

[0145] The data management department (130) retrieves the list of counselors already registered on the server, and for each counselor, the maximum number of counseling cases (C mo ), current number of assigned consultations (S mo ), travel distance between counselor and client (D mo ), Time remaining until next scheduled consultation (T mo ), Estimated time required for consultation (U mo ) can be derived.

[0146] Each derived variable and the distance-based constant (k) and weights (α, β) previously entered by the server administrator or operator are reflected in the matching priority evaluation algorithm to obtain a matching ranking evaluation score (M mo ) can be produced.

[0147] The data management department (130) calculates the matching ranking evaluation score (M) for each counselor. mo After sorting in order, the matching ranking evaluation score (M mo Counselor information can be provided to the matching dispatch unit (150) so that the counselor with the highest value can be selected as the first priority.

[0148] The data management department (130) checks whether the matching information is approved, and if it is rejected, the next ranking matching ranking evaluation score (M mo Counselor information having ) can be provided to the matching sending unit (150).

[0149] The data management unit (130) automatically recalculates the matching priority evaluation algorithm at the time a real-time consultation request occurs at a predetermined interval (e.g., 5 minutes) and the matching priority evaluation score (M) based on the latest information of the counselor mo ) can be produced.

[0150] Current number of assigned consultations (S) over time mo ) and time remaining until the next scheduled consultation (T mo Since ) changes in real time, the data management unit (130) periodically or in an event-triggered manner, the matching ranking evaluation score (M mo The value can be updated.

[0151] In addition, if the client enters purchase conditions and desired models, the estimated time required for consultation (U mo ) value is entered, matching ranking evaluation score (M mo This can be reflected in ), and if a client requests a long consultation time, behavioral variability can be applied so that a counselor with sufficient time is assigned first.

[0152] The aforementioned matching priority evaluation algorithm involves a computation process and a matching priority evaluation score (M mo It is determined that the explanation and examples of the calculation process of ) are sufficiently provided so that a person skilled in the art can easily implement it, and thus a person skilled in the art can easily implement the matching priority evaluation algorithm.

[0153] The matching sending unit (150) can match the request information entered through the information input unit (110) with the schedule and assigned area of ​​each counselor managed by the data management unit (130), and send matching information including the request information to the counselor terminal matched as the first priority.

[0154] The aforementioned matching information may refer to information provided to the counselor terminal (500), including one of the above-mentioned counseling information or the above-mentioned sales information, such as the counseling date, time, region, and content or conditions, to enable the counselor to determine whether to approve the counseling.

[0155] When the matching sending unit (150) provides the matching information to the counselor terminal (500), it may also send information requesting input regarding whether the matching is approved.

[0156] The matching sending unit (150) may be characterized by sending the matching information to the counselor terminal (500) corresponding to the n+1 rank until it receives approval for the matching from the counselor terminal (500) that sent the matching information.

[0157] When the matching sending unit (150) receives a rejection of the matching from the n-rank counselor terminal (500) that sent the matching information, it may send the matching information including the request information to the counselor terminal (500) corresponding to the n+1 rank.

[0158] The confirmation providing unit (170) can confirm the schedule from the counselor terminal (500) that received and approved the matching information, and provide the data of the unmanned locker to the counselor terminal (500).

[0159] If the request information received from the client terminal (300) includes a model purchased from the sales information, the confirmation providing unit (170) can provide the data of the unmanned locker, including the location and password of the unmanned locker where the model is already equipped, to the counselor terminal (500).

[0160] Here, the unmanned locker is equipped with an IoT sensor to provide the unlock status to the management server (100), and if the requested information received from the client terminal includes a purchased model, an item corresponding to the purchased model may be provided inside.

[0161] That is, the unmanned locker may be characterized by being equipped with a door lock, capable of communicating with a management server (100), and equipped with an IoT sensor that detects whether the door lock is unlocked.

[0162] Based on the characteristics of the unmanned locker described above, if the confirmation providing unit (170) confirms that the lock of the unmanned locker equipped with the purchased model is unlocked at the desired date and time of purchase based on the request information received by the client terminal (300), it can determine that the mobile phone of the model equipped inside the unmanned locker has been received by the counselor consulting with the client.

[0163] Meanwhile, the management server (100) quantitatively evaluates the efficiency of counselor matching and forms a satisfaction index (S) to form technical judgment criteria for counselor management and counselor selection optimization. m A counselor matching satisfaction calculation algorithm that calculates ) can be utilized.

[0164] Specifically, the management server (100) utilizes a counselor matching satisfaction calculation algorithm by comprehensively considering the counselor's matching ranking, approval time, success of counseling and unmanned locker use, and end-user satisfaction, to calculate a counselor-specific satisfaction index (S m ) can be produced.

[0165] Through this, the efficiency of counselor management can be improved by more than 25% by evaluating using comprehensive indicators, whereas previously it was judged solely on whether approval or consultation success was determined. Additionally, objectivity in counselor management and consultation assignment logic can be ensured through a structure that comprehensively evaluates faster approval and consultation success rates compared to the existing method.

[0166] The counselor matching satisfaction calculation algorithm may be characterized by being designed as the sum of a first term that comprehensively reflects the counselor's matching priority, approval time, and success of counseling and unmanned locker usage, and a second term that reflects the end-user satisfaction evaluation score.

[0167] The first term of the counselor matching satisfaction calculation algorithm is the counselor's priority (N s The design can be characterized by dividing the value obtained by applying the trigonometric function sine to the value obtained by dividing by 1 and multiplying by pi (π) / 2 so that the smaller the value, the higher the value, and dividing the product of the sum of the consultation success status (B1) and the unmanned locker usage success status (B2) by the value obtained by applying the logarithmic function to the time required for consultation approval (T1).

[0168] The counselor matching satisfaction calculation algorithm may be characterized by being designed to apply the time required for counseling approval (T1) to the logarithmic function by adding 1 to the time required for counseling approval (T1) to prevent calculation errors in the logarithmic function when applying the time required for counseling approval (T1) to the logarithmic function.

[0169] The second client satisfaction (S) of the counselor matching satisfaction calculation algorithm sIt can be characterized by being designed to convert ) into a range between 0 and 100 and reflect it in the form of a ratio.

[0170] The counselor matching satisfaction calculation algorithm assigns weights (w) to the first and second terms, respectively. a , w b Multiply by ) and sum to obtain each counselor's satisfaction index (S m ) can be produced.

[0171] Counselor's priority (N s ) is a dimensionless value and may represent the matching priority of each counselor when a matching request is made by receiving request information from the client terminal (300).

[0172] The management server (100) obtains a consultation priority score (S) calculated from a database by a consultation matching algorithm or a matching priority evaluation algorithm. norm ) and matching ranking evaluation score (M mo Sort counselors from ) and counselor priority(N s ) can be derived.

[0173] The time required for consultation approval (T1) may be in 'seconds' and may refer to the time taken from sending matching information to the counselor until receiving confirmation of approval.

[0174] More specifically, the management server (100) can derive the time required until counseling approval (T1) by comparing the time of sending matching information and the time of receiving matching approval through the counselor terminal (500).

[0175] The success of the consultation (B1) is a dimensionless value that can be either 0 or 1, and can mean whether the consultant succeeded in the consultation with the client and completed the transaction of the mobile phone.

[0176] More specifically, if the counselor has successfully completed a mobile phone transaction with the client who conducted the previous consultation, the management server (100) can determine that the consultation was successful and the consultation success status (B1) is 1.

[0177] In the opposite case, the management server (100) can determine the consultation success status (B1) as 0.

[0178] The success of using the unmanned locker (B2) may be a dimensionless value, which may mean one of 0 or 1, and may mean whether the counselor who received the data from the unmanned locker successfully performed the item dispatch.

[0179] More specifically, the management server (100) can check whether the lock is unlocked through an IoT sensor already equipped in the unmanned locker.

[0180] For example, if the unmanned locker provided data of the unmanned locker is unlocked, the management server (100) can determine that the counselor has taken out the mobile phone model already provided in the unmanned locker and determine the success of using the unmanned locker (B2) as 1.

[0181] In the opposite case, the management server (100) can determine the success or failure of using the unmanned locker (B2) as 0.

[0182] Client satisfaction (S s ) may mean the counselor's feedback score directly entered by the final client through the client terminal (300) after the consultation and purchase are completed.

[0183] The management server (100) may provide a survey UI to receive a counselor's feedback score through a client terminal (300), and the survey UI may provide a standard for entering a feedback score as a value between 0 and 100.

[0184] weight(w a , w bThere is no separate unit used for ), and each counselor's priority (N s ), time taken to consultation approval (T1), consultation success status (B1), and unmanned locker usage success status (B2) are the satisfaction index (S m A value to adjust for the impact on ), client satisfaction (S s ) satisfaction index (S m It can mean a value for adjusting the effect on ).

[0185] weight(w a , w b ) can be derived from a value that is directly input to the management server (100) by the server administrator or operator according to the policy.

[0186] That is, weights (w a , w b ) is the satisfaction index (S m To calculate ) weights (w from the server administrator or operator a , w b ) input may be requested, and the server administrator or operator may request weights (w a , w b You can input the value of each weight so that the sum of the values ​​of ) becomes 1.

[0187] The server administrator or operator is the satisfaction index (S m If it is determined that the success of the consultation (B1) is more important to calculate ), when inputting the weight value, w a ul w b It can be adjusted and changed according to the situation and time, such as by entering a larger value.

[0188] An example is explained by substituting numerical values ​​into the variables and functions of the counselor matching satisfaction calculation algorithm described above.

[0189] Counselor's priority (N s) is 2, time to consultation approval (T1) is 60 seconds, consultation success status (B1) is 1, unmanned locker usage success status (B2) is 1, client satisfaction (S s ) is 80 points, weight(w a , w b When ) are 0.7 and 0.3 respectively, the satisfaction index (S m ) can be calculated as approximately 0.481.

[0190] Through this, the management server (100) can use 0.481 for the counselor's evaluation.

[0191] When a counseling request occurs, the management server (100) checks the counselor's priority (N) in the counselor database. s It can be derived by verifying ), and the time required until consultation approval (T1) can be derived by calculating the time of sending matching information and the time of receiving approval, and the consultation success status (B1) and unmanned locker usage success status (B2) can be derived through success status reports from the counselor terminal and the IoT locker after the consultation ends, and client satisfaction (S) through the client terminal s ) can be derived.

[0192] Subsequently, the management server (100) derives each variable and a weight (w) previously set by the server administrator or operator. a , w b The value of ) is reflected in the counselor matching satisfaction calculation algorithm to calculate the satisfaction index (S m After calculating ), it can be stored in each counselor's evaluation table.

[0193] Counseling success status (B1), unmanned locker usage success status (B2), and client satisfaction (S) of the counselor matching satisfaction calculation algorithm s ) can each be derived independently within the range of 0 to 100, and the weights (w a , w b The sum of ) can be managed to satisfy 1.

[0194] In addition, the management server (100) has a satisfaction index (S m You can set a threshold value for ), for example, the satisfaction index (S m When the threshold value of ) is 0.6, the satisfaction index (S m If ) is calculated to be greater than 0.6, the counselor may be classified as an excellent counselor, etc.

[0195] In addition, the time required until counseling approval (T1) of the counselor matching satisfaction calculation algorithm is measured in real time, and when waiting for approval, the management server (100) can check the elapsed time in 1-second intervals.

[0196] In addition, the success of the consultation (B1) and the success of using the unmanned locker (B2) can be recorded in the database immediately after the consultation ends, and the satisfaction index (S m ) can be calculated based on the time of counseling termination.

[0197] The aforementioned counselor matching satisfaction calculation algorithm involves a computation process and a satisfaction index (S m It is determined that the explanation and examples of the calculation process of ) are sufficiently provided so that a person of ordinary skill can easily implement it, and thus a person of ordinary skill can easily implement the counselor matching satisfaction calculation algorithm.

[0199] The embodiments described above are for illustrative purposes only, and those skilled in the art will understand that the embodiments described above can be easily modified into other specific forms without altering the technical concept or essential features of the embodiments described above. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single unit may be implemented in a distributed manner, and components described as distributed may likewise be implemented in a combined form.

[0201] The scope of protection sought through this specification is defined by the claims set forth below rather than by the detailed description, and should be interpreted to include all modifications or variations derived from the meaning and scope of the claims and the concept of equivalents. Explanation of the symbols

[0202] 100: Management Server

Claims

Claim 1 In a system for providing visiting consultation and sales services, a client terminal that inputs request information for a 'visiting mobile phone consultation and sales service' through one of a WEB, APP, or wired connection; a counselor terminal that receives matching information, inputs whether the matching is approved, and sends it to a management server; and an unmanned locker equipped with an IoT sensor to provide a locking status to the management server, and which contains an item corresponding to the purchased model if the request information includes the purchased model. A visiting consultation and sales service provision system comprising: a management server communicating with the client terminal, the counselor terminal, and the unmanned locker; wherein the management server sends the matching information to the counselor terminal based on the request information received from the client terminal, and confirms the schedule from the counselor terminal that has received and approved the matching information; wherein the management server, when the request information includes a model to be purchased from sales information, provides the counselor terminal with data of the unmanned locker including the location and password of the unmanned locker in which the model to be purchased is already provided; and wherein the management server determines that the mobile phone of the model to be purchased provided inside the unmanned locker has been received by the counselor consulting the client when it is confirmed that the lock of the unmanned locker in which the model to be purchased is provided is unlocked at the desired date and time of purchase. Claim 2 A visiting consultation and sales service providing system according to claim 1, wherein the unmanned locker is equipped with a door lock, capable of communicating with the management server, and equipped with an IoT sensor that detects whether the door lock is unlocked; wherein the management server determines that the counselor has taken out a mobile phone model already equipped in the unmanned locker when the unmanned locker that provided data of the unmanned locker is unlocked, and derives the unmanned locker usage success status (B2) as 1, and derives the unmanned locker usage success status (B2) as 0 when the unmanned locker is not unlocked.

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