KR20210030146A - Method, system and non-transitory computer-readable recording medium for providing suggestion for location of franchise stores - Google Patents

Abstract

The present invention relates to a franchise store location recommendation method, system, and a non-transitory computer-readable recording medium. According to one aspect of the present invention, the franchise store location recommendation method comprises the steps of: receiving a location recommendation request from a user; obtaining location information of at least two top-selling stores from a franchise database according to the received location recommendation request; obtaining surrounding location information based on a location specified from the location information; deriving a common excellent location factor by comparing the location information around the at least two top-selling stores; selecting a recommended candidate location based on the similarity evaluation for the common excellent location factor; and reporting the selected recommended candidate location to the user.

Description

How to recommend franchise store locations, system and non-transitory computer-readable recording media {METHOD, SYSTEM AND NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM FOR PROVIDING SUGGESTION FOR LOCATION OF FRANCHISE STORES}

The present invention relates to a franchise store location recommendation method, system, and non-transitory computer-readable recording medium.

Both the preliminary franchise owner who wants to start a franchise store and the franchise head office looking to expand the franchise store make great efforts to select the optimal location. In the case of a franchise business in which the service provided is standard, it is no exaggeration to say that the choice of location is the biggest factor separating the success and failure of the store. In order to select an optimal location, information such as market conditions, population composition, surrounding industries, and competition conditions in the region where the store is to be established is acquired and analyzed, and the location is selected based on this analysis. Prospective franchisees and franchise headquarters obtain such location information and perform analysis with the help of entrepreneurship experts. However, it is very difficult to accurately collect the above-described information. Even if the information is properly collected, it is difficult to identify among the numerous pieces of information which information is valid information for choosing a favorable location and which information is invalid information. It can never be successful to make a location choice based on information that has not been accurately collected, or without an accurate analysis of the information collected. Even with the help of a start-up expert, there can be a problem of reliability. It is a publicly known fact that instead of selecting and recommending a location based on accurately collected and analyzed information, some startup experts share their interests with real estate agents in the region. .

In both the preliminary franchise owner who wants to establish a franchise store and the franchise head office that wants to expand the franchise store, a common location by collecting extensively information on the location of excellent franchisees among existing franchisees, that is, franchisees with high numbers of visitors and high sales Despite the need to select a store location with conditions, such a system is not currently established.

It is an object of the present invention to check common location-related conditions among affiliate stores with high sales in response to a user's location recommendation request, and to select another area that meets these conditions to provide information on the recommended area selected to the user's terminal. It is to provide a location recommendation method and system to be provided.

A typical configuration of the present invention for achieving the above object is as follows.

According to an aspect of the present invention, as a method for recommending a location of a franchise store, receiving a request for location recommendation from a user, obtaining location information of at least two stores with higher sales from a franchise database according to the received location recommendation request. Steps, obtaining surrounding location information based on a location specified from the location information, deriving a common excellent location factor by comparing surrounding location information of the at least two upper sales stores, and deriving a common excellent location factor. A method is provided that includes selecting a recommended candidate location based on similarity evaluation, and reporting the selected recommended candidate location to the user.

According to another aspect of the present invention, as a system for recommending a new location for a franchise, a recommendation for receiving a location recommendation request from a user and obtaining location information of at least two top sales stores from a franchise database according to the received location recommendation request Request management unit acquires surrounding location information based on the location specified from the location information, compares surrounding location information of the at least two upper sales stores to derive a common excellent location factor, and similarity to the common excellent location factor A system including an evaluation and recommendation unit for selecting a recommended candidate location based on an evaluation, and a reporting unit for reporting the selected recommended candidate location to the user is provided.

In addition to this, another method for implementing the present invention, another system, and a non-transitory computer-readable recording medium for recording a computer program for executing the method are further provided.

According to the present invention, according to the user's request for location recommendation, location-related conditions that are common among affiliate stores with high sales are checked, and information on the recommended area selected in the user's terminal is selected by selecting another area that meets these conditions. A method and system for recommending a location to be provided may be provided.

According to the present invention, the franchise headquarters can easily and accurately identify regions where high sales are expected without the need to directly visit various regions to expand affiliate stores, collect location-related information, and analyze the collected information individually. By establishing new stores in these identified areas, it is possible to achieve successful franchise expansion. Preliminary franchisees can select a location with high expected sales based on objectively reliable information, thereby increasing the chances of success in establishing a franchise store.

1 is a diagram showing a schematic configuration of an entire system for recommending a franchise store location according to an embodiment of the present invention.
2 is a diagram showing in detail the internal configuration of a location recommendation system according to an embodiment of the present invention.
3 is a diagram illustrating a situation in which location information is collected according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The detailed description of the present invention described below refers to the accompanying drawings, which illustrate specific embodiments in which the present invention may be practiced. These embodiments are described in detail sufficient to enable a person skilled in the art to practice the present invention. It should be understood that the various embodiments of the present invention are different from each other, but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described in the present specification may be changed and implemented from one embodiment to another without departing from the spirit and scope of the present invention. In addition, it should be understood that the position or arrangement of individual elements in each embodiment may be changed without departing from the spirit and scope of the present invention. Accordingly, the detailed description to be described below is not made in a limiting sense, and the scope of the present invention should be taken as encompassing the scope claimed by the claims of the claims and all scopes equivalent thereto. Like reference numerals in the drawings indicate the same or similar elements over several aspects.

Hereinafter, various preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings in order to enable those of ordinary skill in the art to easily implement the present invention.

Composition of the whole system

1 is a diagram showing a schematic configuration of an entire system for recommending a franchise store location according to an embodiment of the present invention.

As shown in FIG. 1, the entire system according to an embodiment of the present invention may include a communication network 100, a location recommendation system 200, a franchise database 300, and a user device 400.

First, the communication network 100 according to an embodiment of the present invention may be configured regardless of a communication mode such as wired communication or wireless communication, a local area network (LAN), a metropolitan area network (MAN). ), and a wide area network (WAN). Preferably, the communication network 100 referred to in the present specification may be a known Internet or World Wide Web (WWW). However, the communication network 100 is not necessarily limited thereto, and may include a known wired/wireless data communication network, a known telephone network, or a known wired/wireless television communication network in at least part thereof.

For example, the communication network 100 is a wireless data communication network, such as WiFi (WiFi) communication, WiFi Direct (WiFi-Direct) communication, Long Term Evolution (LTE) communication, Bluetooth communication (e.g., low-power Bluetooth ( BLE (Bluetooth Low Energy) communication), infrared communication, ultrasonic communication, and the like may be implemented in at least a part of a conventional communication method.

Next, the location recommendation system 200 according to an embodiment of the present invention may communicate with the franchise database 300 and the user device 400 to be described later through the communication network 100. The location recommendation system 200 receives a location recommendation request from the user device 400 and manages and stores it. Thereafter, the location recommendation system 200 calls the franchise database 300 through the communication network 100, and the franchise database 300 receives address information of at least two high-selling affiliated stores in response to the location recommendation system 200. ).

The location recommendation system 200 determines the location to be analyzed from address information of at least two stores with high sales obtained from the franchise database 300. The location recommendation system 200 holds information on the surrounding location of the location to be analyzed in its own database, and compares the information on a plurality of surrounding locations to derive an excellent location factor common thereto.

The location recommendation system 200 selects one or more recommended locations based on the common excellent location factor of the top sales stores within an area requested by the user device 400 or across the country, and this in the form of a report, the user device 400 To provide. Here, the location information around the location to be analyzed held by the location recommendation system 200 may include geographic information and information on characteristics of a floating population.

The configuration and function of the location recommendation system 200 according to the present invention will be described in more detail through the following detailed description. On the other hand, the location recommendation system 200 has been described as above, but this description is illustrative, and at least some of the functions or components required for the location recommendation system 200 are required by the user device 400 or the external device. It will be apparent to those skilled in the art that it may be realized within a system (not shown) or may be included within a user device 400 or an external system (not shown).

Next, the franchise database 300 according to an embodiment of the present invention stores and manages sales information and location information of each store across all affiliated stores. The franchise database 300 transmits, to the location recommendation system 200, the location information of stores with higher sales in response to a call of the location recommendation system 200. Store-specific sales information stored and managed in the franchise database 300 may be periodically updated through the communication network 100 according to an input of the user device 400.

Next, the user device 400 according to an embodiment of the present invention is a digital device that includes a function that enables a user to communicate after accessing the location recommendation system 200 through the communication network 100, and is a smart phone. Any portable digital device equipped with a memory unit such as a tablet PC and the like and equipped with a microprocessor can be adopted as the user device 400 according to the present invention. Meanwhile, according to an embodiment of the present invention, the user device 400 transmits information on the location recommendation request generated by the user to the location recommendation system 200, or at least provided from the location recommendation system 200. An application capable of providing one recommended location information to a user may be included. Such an application may be downloaded from the location recommendation system 200 or an external application distribution server (not shown).

In addition, the user device 400 may be used by the franchise headquarters to transmit the sales of each affiliated store to the franchise database 300. In addition, the user device 400 according to an embodiment of the present invention may further include a GPS module (not shown) for confirming the user's location. In this case, the sales of each affiliated store through the user device 400 The related input may be transmitted to the franchise database 300 in association with address information obtained through the GPS module.

Composition of the site recommendation system

Hereinafter, the internal configuration of the location recommendation system 200 that performs an important function for the implementation of the present invention and functions of each component will be described.

2 is a diagram showing in detail the internal configuration of a location recommendation system 200 according to an embodiment of the present invention.

As shown in Fig. 2, the location recommendation system 200 according to an embodiment of the present invention includes a recommendation request management unit 210, an evaluation recommendation unit 220, a reporting unit 230, a communication unit 240, and a control unit. It may be configured to include 250. According to an embodiment of the present invention, the recommendation request management unit 210, the evaluation recommendation unit 220, the reporting unit 230, the communication unit 240, and the control unit 250 are at least partially communicated with an external system. It can be a program module. Such a program module may be included in the location recommendation system 200 in the form of an operating system, an application program module, or other program module, and may be physically stored in various known storage devices. In addition, such a program module may be stored in a remote storage device capable of communicating with the location recommendation system 200. Meanwhile, such a program module includes routines, subroutines, programs, objects, components, data structures, etc. that perform specific tasks or execute specific abstract data types according to the present invention, but is not limited thereto.

First, the recommendation request management unit 210 according to an embodiment of the present invention receives information about a request for recommending a new store location of a specific franchise from the user device 400, and stores and manages the information. Another function of the recommendation request management unit 210 is to call the franchise database 300 and receive address information of one or more stores with higher sales stored therein. The recommendation request management unit 210 may store the received information and transmit it to the evaluation recommendation unit 220 to start analysis of the location to be recommended.

That is, information stored and managed in the recommendation request management unit 210 is largely obtained through two routes. The first is information from the user device 400, which includes information on a region in which a location recommendation request has been made. Requests for location recommendations may be made for a national scale. The second is information from the franchise database 300, which includes address information of stores with high sales and information on the sales point (that is, information on the point in time of sales). Since such information is maintained, the recommendation request management unit 210 may perform location analysis using information previously stored and managed even before the franchise database 300 provides the latest sales upper store address information.

In addition, the location recommendation system 200 according to an embodiment of the present invention may be connected to various franchise databases 300 to provide services. For example, the location recommendation system 200 according to an embodiment of the present invention may receive information provided from the male haircut specialty store franchise database when performing location recommendation for a male haircut specialty store. 210) can be maintained and managed. In another case, the location recommendation system 200 according to an embodiment of the present invention may receive information provided from the cosmetics sales franchise database when performing location recommendation for a cosmetic sales franchise, so that such information is requested for recommendation. The management unit 210 can be maintained and managed. Accordingly, the recommendation request management unit 210 of the location recommendation system 200 according to an embodiment of the present invention maintains a vast amount of information on sales information of various industries, distribution of top sales stores by industry, sales change trends by region/industry, etc. Can be managed. This can be used for various purposes in the future with the consent of the franchise company to be provided with the service. It goes without saying that the above-described various franchise industry-related information maintained and managed by the recommendation request management unit 210 may be maintained in a database outside the recommendation request management unit 210.

Next, the evaluation recommendation unit 220 according to an embodiment of the present invention plays the most essential function of the location recommendation system 200. The evaluation recommendation unit 220 initiates an evaluation and analysis of the location by receiving address information of stores with high sales from the recommendation request management unit 210.

The evaluation recommendation unit 220 may maintain various commercial district-related information including geographic information and floating population characteristic information around stores with high sales in its own database. Such a database may exist outside the evaluation recommendation unit 220 as long as it can be connected to the evaluation recommendation unit 220 through the communication network 100.

Geographic information among various commercial district-related information is literally information on what facilities exist around a specific address geographically, and encompasses all small and medium-sized stores as well as subway stations, government offices, and schools, which are often referred to as important facilities. For example, such geographic information includes where and how many billiards, beauty salons, and real estate agencies exist around a specific address. A more specific aspect of this geographic information held by the evaluation recommendation unit 220 in its internal database or in an external database connected through a communication network can be confirmed from FIG. 3.

Among the information related to various commercial districts, the floating population characteristic information may include information on the sex, age, and average payment amount of the floating population traveling around a specific address. Such floating population characteristic information may be collected and stored in various ways, such as obtained through card payment information through partnership with a card company, and may be periodically updated.

The above-described geographic information and floating population characteristic information are only examples of information that can be included in the database of the evaluation recommending unit 220, and the evaluation recommending unit 220 is Various time-varying location-related information, such as SNS-derived information, can be maintained and managed in a database.

Suppose that the addresses of existing stores with high sales received from the evaluation recommendation unit 220 are A, B, and C. The evaluation recommendation unit 220 grasps the geographical information and the floating population characteristic information as described above for all of the addresses A, B, and C, and finds common points therefrom. For example, when the addresses of three top sales stores of a male haircut franchise are delivered, the following geographic information may be identified for each address.

Address A (#1 in sales): 2 subway stations, 3 bus stops, 6 business buildings, 9 billiards rooms, 5 restaurants, 1 nail shop and 2 academies

Address B (2nd place in sales): 1 subway station, 3 bus stops, 5 office buildings, 7 billiard rooms, 10 restaurants, 2 nail shops and 30 academies

Address C (3rd place in sales): 1 subway station, 2 bus stops, 4 business buildings, 7 billiard rooms, 7 restaurants, 12 nail shops and 15 academies

Among the above geographic information, since the number of nail shops and academies is very jagged regardless of the sales ranking, the evaluation recommendation unit 220 may exclude stores of these industries from the common excellent location factor. On the other hand, the evaluation recommendation unit 220 may derive a subway station, a bus stop, a business building, and a billiard hall as factors affecting the ranking of sales, and may set the criteria for the number. For example, the evaluation recommendation unit 220 may derive, as a common excellent location factor, that there are at least one subway station, at least two bus stops, at least four business buildings, and at least seven billiards within a specific radius. The above example is for understanding the concept of deriving a common excellent location factor based on the address information of stores with high sales received from the evaluation and recommendation unit 220, and any known algorithm that finds common points among various conditions is common. It should be understood that it can be applied to the derivation of good location factors. The common excellent location factor can be derived in the same way for the information on the characteristics of the floating population.

The evaluation recommender 220 having derived the common excellent location factor may quantify the suitability of the target location by quantifying the degree of similarity to the common excellent location factor through the similarity evaluation model to select a recommended candidate location. In this case, it is possible to quantify the similarity through a known similarity determination method, for example, an artificial neural network-based multidimensional similarity measurement evaluation function model. The evaluation and recommendation unit 220 selects the top several location recommendation targets with a high ranking as a result of quantifying the degree of similarity.

Next, the reporting unit 230 according to an embodiment of the present invention determines in advance the derived common excellent location factor, the location of the selected location recommendation target, the location condition of the location, and a map of the selected location recommendation target location. It is produced in the form of a report according to the format and transmitted to the user device 400.

Next, the communication unit 240 according to an embodiment of the present invention may perform a function of enabling data transmission and reception from/to the recommendation request management unit 210, the evaluation recommendation unit 220, and the reporting unit 230. have.

Finally, the control unit 250 according to an embodiment of the present invention performs a function of controlling the flow of data between the recommendation request management unit 210, the evaluation recommendation unit 220, the reporting unit 230, and the communication unit 240. can do. That is, the control unit 250 according to the present invention controls the data flow from/to the outside of the location recommendation system 200 or the data flow between each component of the location recommendation system 200, so that the recommendation request management unit 210, Each of the evaluation recommendation unit 220, the reporting unit 230, and the communication unit 240 may be controlled to perform a unique function.

3 is a diagram illustrating a situation in which location information is collected according to an embodiment of the present invention.

Referring to FIG. 3, the distribution of various types of facilities is identified, centering on the location of stores with excellent sales among existing stores (green circles filled in in FIG. 3). In FIG. 3, apartments, academies, schools, reading rooms, real estate and universities are exemplarily displayed as types of facilities for determining the distribution situation, but the types of industries to be grasped are not limited thereto. Location information collection as illustrated in FIG. 3 is performed on all locations of at least two existing sales top stores, and a common excellent location factor may be derived through a comparison between these information. For example, as a result of collecting geographic information as shown in FIG. 3 with respect to the transmitted locations of all existing sales top stores and comparing them with each other, the number of apartment complexes of 2,000 households or more in common is 5 or more, and the number of academies and real estate When the result is jagged, and the number of schools and universities is 4 or more, it may be determined that the number of apartment complexes and the number of schools/universities are 5 and 4 or more, respectively.

One of the features of the present invention to be mentioned in connection with the embodiment shown in FIG. 3 is that, when analyzing the distribution of surrounding facilities centering on the location of stores with high sales, different distance criteria can be applied for each type of facility. . In this regard, referring to FIG. 3, it is specified that the collection conditions are within 600m for an apartment, 400m for academy, 400m for a school, 400m for a reading room, 400m for real estate, and 1000m for a university. For example, the existence of an apartment in a university and a large complex may be judged to have an effect on the commercial district to a greater distance than the existence of academies, schools, reading rooms, and real estate. Based on this judgment, the criteria for examining the distribution of facilities in which radius around the location of the top sales store may vary depending on the type of facility.

The embodiments according to the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded in a computer-readable recording medium. The computer-readable recording medium may include program instructions, data files, data structures, and the like alone or in combination. The program instructions recorded in the computer-readable recording medium may be specially designed and constructed for the present invention or may be known and usable to those skilled in the computer software field. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magnetic-optical media such as floptical disks. medium), and a hardware device specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware device can be changed to one or more software modules to perform the processing according to the present invention, and vice versa.

In the above, the present invention has been described by specific matters such as specific elements and limited embodiments and drawings, but this is provided only to help a more general understanding of the present invention, and the present invention is not limited to the above embodiments. Anyone with ordinary knowledge in the technical field to which the invention pertains can make various modifications and changes from these descriptions.

Therefore, the spirit of the present invention is limited to the above-described embodiments and should not be defined, and all ranges equivalent to or equivalently changed from the claims to be described later as well as the claims to be described later are the scope of the spirit of the present invention. It will be said to belong to.

100: communication network
200: location recommendation system
210: recommendation request management unit
220: evaluation recommendation unit
230: reporting department
240: communication department
250: control unit
300: franchise database
400: user device

Claims (6)

As a method for recommending a franchise store location,
Receiving a user's location recommendation request,
Acquiring location information of at least two top sales stores from a franchise database according to the received location recommendation request,
Acquiring surrounding location information based on a location specified from the location information,
Comparing the surrounding location information of the at least two high-selling stores to derive a common excellent location factor,
Selecting a recommended candidate location based on a similarity evaluation for the common excellent location factor, and
Including the step of reporting the selected candidate candidate location to the user,
Way. The method of claim 1,
In the step of deriving the common excellent location factor, at least geographic information and floating population characteristic information are compared when comparing the surrounding location information,
Way. The method of claim 2,
The geographic information is information on the distribution status of nearby facilities centered on the location of the upper sales store,
The floating population characteristic information is information on at least one of the sex, age, and average payment amount of the floating population in the surrounding area centered on the location of the upper sales store
Way. The method of claim 3,
Applying a different distance criterion for each type of facility in analyzing the distribution of surrounding facilities centered on the location of the upper sales store
Way. A non-transitory computer-readable recording medium storing a computer program for executing the method according to claim 1. As a system for recommending franchise locations,
A recommendation request management unit that receives a location recommendation request from a user and obtains location information of at least two top sales stores from a franchise database according to the received location recommendation request,
Acquires surrounding location information based on a location specified from the location information, compares the location information of the surrounding locations of the at least two high-selling stores to derive a common excellent location factor, based on similarity evaluation for the common excellent location factor An evaluation and recommendation unit that selects the position of the candidate for recommendation, and
Including a reporting unit for reporting the selected candidate candidate location to the user,
system.

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