KR102455030B1 - Rental car contract management system - Google Patents

Abstract

The present invention relates to a rental car contract management system. More specifically, the present invention relates to a rental car contract management system capable of matching customer inquiry information flowing through various routes to a customized salesperson. To this end, the rental car contract management system includes: an information acquisition unit that acquires car rental inquiry information input from a customer terminal through the car rental web service; an analyzer registering at least two or more filtering identifiers for filtering a pre-registered car rental history list based on access information on the car rental inquiry information; a derivation unit filtering at least two or more sample lists from the pre-registered rental car rental history list according to the at least two or more filtering identifiers and deriving metadata for each of the at least two or more sample lists; a determination unit for determining a propensity grade for the rental car inquiry information based on the average contract rate for each of the metadata; and a matching unit that selects a first customized salesperson and matches the same to the rental car inquiry information based on the difference between the propensity grade and the performance grade evaluated for each salesperson from the previously registered salesperson list.

Description

RENTAL CAR CONTRACT MANAGEMENT SYSTEM

The present invention relates to a rental car contract management system, and more particularly, to a rental car contract management system capable of matching customer inquiry information flowing in through various channels to a customized salesperson.

Recently, in case of a car accident, there is an increasing demand for rental services that want to use a rental car during the repair period, but also for office workers who frequently travel on business trips or travelers who do not own a vehicle to rent a vehicle from a foreign country and use it conveniently. is being activated.

In addition to the rapid increase in the use of car rental services, large-scale car rental companies have established their own car rental management programs to efficiently manage car rentals. There is this.

In particular, various customer management tasks related to car rental management, from car rental inquiries to contract conclusion and follow-up management, are customized to salespeople to increase the possibility of contract signing, and support for efficient car rental management tasks service is needed

The present invention is to solve the above problems, and an object of the present invention is to provide a rental car contract management system that can increase the possibility of concluding a contract according to customer inquiry information by matching customer inquiry information flowing in through various channels to a customized salesperson is to provide

These and other objects and advantages of the present invention will become apparent from the following description of preferred embodiments.

In order to achieve the above object, the rental car contract management system according to an embodiment of the present invention includes an information acquisition unit that acquires rental car inquiry information input from a customer terminal through a rental car web service, and access information for the rental car inquiry information. Based on the analysis unit for registering at least two or more filtering identifiers for filtering the pre-registered rental car rental history list, filtering at least two or more sample lists from the registered rental car rental history list according to the at least two filtering identifiers and a derivation unit for deriving each metadata for the at least two or more sample lists, a determining unit for determining a propensity grade for the rental car inquiry information based on an average contract rate for each metadata, and the propensity grade and group and a matching unit that selects a first customized salesperson based on a difference value between performance grades evaluated for each salesperson among the registered salesperson list and matches the rental car inquiry information, wherein the at least two filtering identifiers are selected from the rental car web site. It includes information on an inflow path and consultation time of any one of a site converted into a service page, an advertisement medium linked to the car rental web service, and a search engine site using keyword search.

In an embodiment, the matching unit is a list generator that generates the salesperson list on the basis of customer management information that is received from each of the plurality of salesperson terminals at predetermined times, and a process calculated for each salesperson from the customer management information A list management unit that integrates and manages the impossible rate and the contract rate into the salesperson list, based on a first weight weighted according to the contract rate and a second weight weighted according to the non-progression rate, for each salesperson of the salesperson list Based on the average daily work time received from the rating evaluation unit for evaluating the performance grade and the salesperson terminal of any one of the plurality of salesperson terminals, the rental car inquiry information added within a certain period of time, the performance grade is preset Includes reassignment units that reassign to salespeople who are undervalued.

In an embodiment, when the list management unit matches the car rental inquiry information with the first customized salesperson, a video service that enables non-face-to-face consultation with the customer terminal through the car rental web service may be performed. Authorization is given to the first customized salesperson.

In an embodiment, when the rental fee information confirmed from the rental car inquiry information is equal to or greater than a preset amount, the list management unit based on an approval signal received by inquiring whether to support a substitute driver to the customer terminal, the proxy Personal information about the article is provided to the customer terminal.

In an embodiment, when the reassignment unit matches the first customized salesperson with the rental car inquiry information, when the total number of customer management information of the first customized salesperson is equal to or greater than a preset number, the first customized The salesperson is changed to a second customized salesperson corresponding to an approximation of the difference value, and when there are at least two second customized salespersons, the second customized salesperson is selected in the order of the highest performance grade.

In an embodiment, when the vehicle information detected from the rental car inquiry information is an electric vehicle, the analysis unit includes an image requesting unit for requesting the driving flow map images to the customer terminal, and each driving route map image received in response through the customer terminal Based on the location information of the center point identified from An algorithm application unit for diagnosing risk information for each accident type based on an output value for each accident type derived by inputting objects, traffic elements, and weather information for the corresponding period into an AI-based diagnosis algorithm for each accident type; The image has a pixel area that is larger than or equal to that of each of the map images.

In an embodiment, the analysis unit is based on whether the accident history confirmed from the rental car inquiry information and the diagnosis information for each accident type are the same, from the operating flow suggestion unit and the customer terminal for proposing a new operating flow to replace the operating flow The method further includes a reward providing unit for providing a reward point for providing a discount for a rental car to the customer terminal when the customer's movement route received through the rental car web service corresponds to the new operation route.

In an embodiment, the determiner calculates the propensity grade from the average contract rate of each metadata by using a first weight weighted according to the inflow path information and a second weight weighted according to the consultation time information.

According to an embodiment of the present invention, the possibility of concluding a contract according to the customer inquiry information can be increased by matching customer inquiry information flowing in through various channels to a customized salesperson.

1 is a diagram schematically showing a rental car contract management system 100 according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating an embodiment of the matching unit 150 of FIG. 1 .
3 is a diagram illustrating an embodiment of the analysis unit 120 of FIG. 1 .

Hereinafter, the present invention will be described in detail with reference to embodiments and drawings of the present invention. It will be apparent to those of ordinary skill in the art that these examples are only presented as examples to explain the present invention in more detail, and that the scope of the present invention is not limited by these examples. .

Further, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and in case of conflict, this specification, including definitions description will take precedence.

In order to clearly explain the invention proposed in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification. And, when a part "includes" a certain component, this means that other components may be further included, rather than excluding other components, unless otherwise stated. In addition, the "unit" described in the specification means one unit or block that performs a specific function.

In each step, the identification code (first, second, etc.) is used for convenience of description, and the identification code does not describe the order of each step, and each step does not clearly describe a specific order in context. It may be performed differently from the order specified above. That is, each step may be performed in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

1 is a diagram schematically showing a rental car contract management system 100 according to an embodiment of the present invention.

Referring to FIG. 1 , the rental car contract management system 100 may include an information acquisition unit 110 , an analysis unit 120 , a derivation unit 130 , a determination unit 140 , and a matching unit 150 . have.

First, the information acquisition unit 110 may acquire rental car inquiry information received from the customer terminal 10 through the rental car web service.

Here, the rental car inquiry information may include any one of vehicle information about the rental car, rental information, rental fee information, and customer information. For example, vehicle information for a rental car includes keywords related to the type of vehicle, usage age, accumulated mileage, fuel amount and battery capacity, and rental information for a rental car includes keywords related to rental location, period of use, and operation flow. , substitute fee information may include keywords related to usage fee, and customer information may include keywords related to driver's license number, number of rental car history and accident history.

At this time, the car rental web service is an app or program installed in the customer terminal 10, and the rental car inquiry information is inputted and selected through at least one method of text, image shooting, image-based touch input, and image upload as a graphic user interface. can be implemented.

Next, the analysis unit 120, based on the access information for the rental car inquiry information obtained through the information acquisition unit 110, at least two or more for filtering the rental car rental history list previously registered in the storage DB (200) A filtering identifier can be registered.

Here, at least two or more filtering identifiers are the inflow path of any one of a site converted to a rental car web service, such as a community or blog, an advertisement medium linked to a rental car web service, and a search engine site using keyword search, such as Naver or Google. It may include information and consultation time information.

Next, the derivation unit 130 filters at least two or more sample lists from the rental car rental history list previously registered in the storage DB 200 according to at least two or more filtering identifiers, and extracts metadata for at least two or more sample lists. can be derived

Here, as shown in Table 1, the metadata is DB information on a sample list extracted from the rental car rental history list according to the filtering identifier, and the total number of customers, the number of unproblematic cases, the total number of contracts, the average impossible rate and average contract rate. may include

All DB Unable to proceed in full whole contract Average no progress rate average contract rate 2173 536 91 24.67% 4.19%

Next, the determination unit 140 may determine the propensity grade for the rental car inquiry information obtained through the information obtaining unit 110 based on the average contract rate confirmed in each metadata derived through the deriving unit 130 . have.

According to an embodiment, the determining unit 140 determines the propensity grade from the average contract rate of each metadata by using a first weight weighted according to the inflow path information and a second weight weighted according to the consultation time information among each metadata. can be calculated.

Next, the matching unit 150 determines the rental car inquiry information based on the difference between the propensity grade for the rental car inquiry information determined through the determining unit 140 and the performance grades evaluated for each salesperson among the pre-registered salesperson list. Accordingly, it is possible to select the first customized salesperson who will be in charge of contract signing and follow-up management and match it with the rental car inquiry information.

Hereinafter, the configuration of the present invention and its effects will be described in more detail through specific examples and comparative examples. However, these examples are for explaining the present invention in more detail, and the scope of the present invention is not limited to these examples.

FIG. 2 is a diagram illustrating an embodiment of the matching unit 150 of FIG. 1 .

1 and 2 , the matching unit 150 may include a list generation unit 151 , a list management unit 152 , a rating evaluation unit 153 , and a reassignment unit 154 .

First, the list generator 151 may generate a salesperson list based on customer management information that is respectively transmitted from the plurality of salesperson terminals 20_1 to 20_N at a predetermined time through the sales management service.

Here, the sales management service includes a customer consultation management service for managing customer information, an examination management service for managing the examination status on rental status, a contract management service for managing contract-related information, and display settlement information according to rental. It may include a settlement management service for, a member management service for managing customers and salespeople, a vehicle management service for managing vehicle information of a rental car, a statistics management service for managing metadata, and a bulletin board service.

For example, the list management unit 152 may list and manage customer management information including vehicle rental, reservation status, dispatch status, rental fee, sales according to a rental car contract, and payment through a sales management service. .

At this time, as shown in Table 2, the customer management information includes the total number of customers handled by each salesperson, the number of non-progressable cases, the number of valid progress cases, and contract cases, and the salesperson list lists customer management information for each salesperson. It can be a table.

Next, the list management unit 152 may manage the non-progression rate and the contract rate calculated for each customer management information by integrating them into the salesperson list.

For example, the non-progress rate may be calculated by the list management unit 152 through the number of non-progressable cases/total number of customers, and the contract rate may be calculated by the list management unit 152 through the number of contracts/valid progress.

According to an exemplary embodiment, the list management unit 152 may integrate and manage the number of customer inquiry information newly matched to the salesperson in the salesperson list.

According to another embodiment, when the list management unit 152 matches the first customized salesperson with the rental car inquiry information, a video service that enables non-face-to-face consultation with the customer terminal 10 through the rental car web service is performed. The right to do this may be granted to the first customized salesperson.

According to another embodiment, when the rental fee information confirmed from the rental car inquiry information is greater than or equal to a preset amount, the list management unit 152 is based on an approval signal received by inquiring whether to support a proxy driver to the customer terminal 10 . Thus, it is possible to provide personal information about the agent to the customer terminal (10).

Next, the rating evaluation unit 153 may evaluate the performance rating for each salesperson in the salesperson list by using the third weight weighted according to the contract rate and the fourth weight weighted according to the non-progression rate.

Next, the reassignment unit 154 is based on the average daily work time received from any one of the salesperson terminals (eg, 20_1) among the plurality of salesperson terminals 20_1 to 20_N, the rental car inquiry added within a certain period of time The information may be reassigned to a salesperson whose performance rating is rated below a predetermined rating.

According to an embodiment, when the reassignment unit 154 matches the first customized salesperson with the rental car inquiry information, if the total number of customer management information of the first customized salesperson is equal to or greater than a preset number, the first customized salesperson can be changed to a second customized salesperson corresponding to an approximation of the difference value. In this case, when there are at least two second customized salespersons, the reassignment unit 154 may select any one of the at least two or more second customized salespersons in the order of highest performance grade.

3 is a diagram illustrating an embodiment of the analysis unit 120 of FIG. 1 .

1 and 3 , the analyzing unit 120 may include an image requesting unit 121 , a charging station information providing unit 122 , and an algorithm applying unit 123 .

First, the image request unit 121 may request the customer terminal 10 for a map image of the operation route when the vehicle information confirmed from the rental car inquiry information obtained through the information acquisition unit 110 is an electric vehicle capable of autonomous driving. have.

Next, the charging station information providing unit 122 is based on the location information on the center point detected from the map image of the operation route received through the customer terminal 10, a modified map displaying the charging station information located within a certain distance from the center point The image may be provided to the customer terminal 10 through the rental car web service.

Here, the corrected map image may have a pixel area greater than or equal to that of the map image.

Next, the algorithm application unit 123 performs risk diagnosis by accident type based on the output value for each accident type derived by inputting road element objects related to traffic impact assessment detected from the corrected map image into the AI-based accident type diagnosis algorithm. information can be predicted.

Here, road element objects related to traffic impact assessment are road objects such as general intersections, non-intersections, roundabouts, straight roads, one-way roads, two-lane roads, and four-lane roads, traffic lights, crosswalks, medians, and road construction sites. It may include a facility object for At this time, the accident type may include the type of vehicle collision caused by rear-end collision and vehicle door opening, lane change accident type such as two-wheeled vehicle overtaking and center line violation, type of intersection violation, pedestrian collision accident type such as entering a crosswalk. have.

On the other hand, the AI-based diagnosis algorithm for each accident type is an artificial neural network algorithm that receives a plurality of map images in advance and outputs an output value for each accident type. The algorithm may be any one of a decision tree and a random forest.

Specifically, the algorithm application unit 123 collects a plurality of map images in advance, classifies the plurality of map images by thought type, and learns through machine learning. can create

For example, the AI-based diagnosis algorithm for each type of thinking is mainly used in deep learning and is a statistical learning algorithm inspired by neural networks in machine learning and biology. It is a convolutional neural network including feature extraction neural networks and classification neural networks. can At this time, the convolutional neural network is a kind of deep, feed-forward artificial neural network used to analyze visual images. Images can be recognized based on the acquired features.

Specifically, the feature extraction neural network proceeds by sequentially stacking a convolutional layer and a pooling layer on an input signal. The convolution layer contains convolution operations, convolution filters, and activation functions. The calculation of the convolution filter is adjusted according to the matrix size of the target input, but a 9X9 matrix is generally used. The activation function may generally use a ReLU function, a sigmoid function, a tanh function, and the like, but is not limited thereto. The pooling layer is a layer that reduces the size of the input matrix, and uses a method of extracting representative values by tying pixels in a specific area. In general, the average value or the maximum value is often used for the calculation of the pooling layer, but is not limited thereto. The operation is performed using a square matrix, which is usually a 9x9 matrix. The convolutional layer and the pooling layer are iterated alternately until the corresponding input becomes small enough while maintaining the difference.

Also, the classification neural network has a hidden layer and an output layer. The classification neural network 520 generally includes five or more hidden layers, and 80 nodes of each hidden layer can be designated, but it is also possible to set more than one in some cases. The activation function of the hidden layer uses a ReLU function, a sigmoid function, a tanh function, and the like, but is not limited thereto.

According to an embodiment, the analysis unit 120 may further include a travel route suggestion unit 124 and a reward providing unit 125 .

Specifically, the operating flow suggestion unit 124 is a new operating flow that has changed the operating flow based on whether the accident history confirmed from the rental car inquiry information and the risk diagnosis information for each accident type derived through the algorithm application unit 123 are the same. can be proposed to the customer terminal 10 .

At this time, when the location information received from the customer terminal 10 through the rental car web service corresponds to the new operation route proposed through the operation route suggestion unit 124, the reward providing unit 125 provides a discount for the rental car. The reward points for providing may be provided to the customer terminal 10 through the rental car web service.

In this specification, only a few examples among the various embodiments performed by the present inventors will be described, but the technical spirit of the present invention is not limited or limited thereto, and it is of course that it may be modified and variously implemented by those skilled in the art.

100: rental car contract management system
110: Information Acquisition Department
120: analysis unit
130: derivation part
140: decision unit
150: matching unit

Claims (8)

an information acquisition unit that acquires rental car inquiry information received from a customer terminal through a rental car web service;
an analysis unit that registers at least two filtering identifiers for filtering a pre-registered rental car rental history list based on access information for the rental car inquiry information;
a derivation unit for filtering at least two or more sample lists from the registered car rental history list according to the at least two or more filtering identifiers, and deriving respective metadata for the at least two or more sample lists;
a determination unit for determining a propensity level for the rental car inquiry information based on the average contract rate for each of the metadata; and
A matching unit that selects a first customized salesperson based on the difference between the propensity grade and the performance grade evaluated for each salesperson among the pre-registered salesperson list and matches the rental car inquiry information,
The at least two filtering identifiers include inflow path information and consultation time information of any one of a site converted to the car rental web service, an advertisement medium linked to the car rental web service, and a search engine site using a keyword search,
Each of the metadata is DB information for the at least two or more sample lists, and includes the total number of customers, the number of non-progressable cases, the total number of contracts, the average impossible rate, and the average contract rate,
The rental car inquiry information includes any one of vehicle information about the rental car, rental information, rental fee information, and customer information,
The determination unit calculates the propensity grade from the average contract rate of each metadata by using a first weight weighted according to the inflow path information and a second weight weighted according to the consultation time information,
The matching unit may include: a list generator configured to generate the salesperson list based on customer management information received from a plurality of salesperson terminals every predetermined time through the sales management service;
a list management unit for integrating and managing the non-progression rate and the contract rate calculated for each salesperson from the customer management information into the salesperson list;
a rating evaluation unit for evaluating performance grades for each salesperson in the salesperson list based on a third weight weighted according to the contract rate and a fourth weight weighted according to the non-progression rate; and
Based on the average daily work time received from any one of the salesperson terminals among the plurality of salesperson terminals, the rental car inquiry information added within a certain period is reassigned to the salesperson whose performance grade is evaluated to be less than a preset grade including reassignment to
The list management unit, when the rental fee information confirmed from the rental car inquiry information is greater than or equal to a preset amount,
In order to selectively provide the support service of a surrogate driver who will drive a rental car on behalf of the customer, an approval signal is received by inquiring whether the surrogate driver supports the customer terminal, and based on the approval signal, personal information about the surrogate driver to the customer terminal, a rental car contract management system. delete According to claim 1,
When the list management unit matches the car rental inquiry information with the first customized salesperson, the list management unit gives the right to perform a video service that enables non-face-to-face consultation with the customer terminal through the car rental web service through a video call method. 1 A rental car contract management system for a customized salesperson. delete According to claim 1,
When the reassignment unit matches the first customized salesperson with the rental car inquiry information, when the total number of customer management information of the first customized salesperson is equal to or greater than a preset number, the first customized salesperson is assigned the difference change to a second custom salesperson who approximates the value;
When the second customized salesperson is at least two or more, selecting the second customized salesperson in order of highest performance grade, a rental car contract management system. According to claim 1,
When the vehicle information detected from the rental car inquiry information is an electric vehicle, the analysis unit may include: an image request unit for requesting a map image of a travel route to the customer terminal;
a charging station information providing unit that provides a modified map image displaying charging station information located within a certain distance from the central point based on the location information of the central point identified from the operating route map image that is answered through the customer terminal; and
An algorithm application unit for diagnosing risk information for each accident type based on an output value for each accident type derived by inputting road element objects related to traffic impact assessment derived from the modified map image into an AI-based accident type diagnosis algorithm,
Each modified map image has a pixel area greater than or equal to that of the operation route map image, a rental car contract management system. 7. The method of claim 6,
The analysis unit, based on whether the accident history confirmed from the rental car inquiry information and the diagnosis information for each type of accident is the same, the operation flow proposal unit for proposing a new operation route to replace the operation flow; and
When the customer's movement route received through the rental car web service from the customer terminal corresponds to the new operation route, a reward providing unit that provides reward points for providing a discount for a rental car to the customer terminal , car rental contract management system. delete

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