A data analysis and processing system for franchisee platforms based on cloud computing

Abstract

The present invention discloses a franchisee data analysis and processing system of a franchise platform based on cloud computing, comprising a catering franchise project main body information extraction module, a franchisee online consumption port link module, a franchisee online catering consumption parameter collection module, a franchisee online catering consumption analysis module, a franchise database, a catering franchise project comprehensive franchise value evaluation module and a catering franchise project classification retrieval terminal. By extracting franchisee information corresponding to each franchise project from a catering franchise platform and obtaining an online consumption port corresponding to each franchisee, online catering consumption parameters are collected and supplemented to franchise project data, thereby greatly enriching the franchise project data. At the same time, the online catering consumption parameters of each franchisee corresponding to each catering franchise project are processed and analyzed, thereby evaluating the comprehensive franchise value coefficient corresponding to each catering franchise project, thereby providing a strong basis for users to join in screening franchise projects.

Description

Technical Field

[0001] The present invention belongs to the technical field of franchise platform information processing, and in particular, relates to a franchise platform franchisee data analysis and processing system based on cloud computing. Background Art

[0002] With the development of social economy, the traditional business self-operation model is changing to the chain operation model, and the franchise chain can combine the successful application model of the chain headquarters with the capital of the franchisees, and significantly increase the market share in a short period of time with lower capital investment and risk. This franchise chain operation model has become an important way for chain operation enterprises to expand rapidly at low cost and for investors to start businesses easily. In this case, in order to facilitate investors to join, the franchise platform was born. Franchise investors can choose the franchise projects they want to join according to the franchise projects displayed on the franchise platform, invest in the franchise, and become franchisees.

[0003] At present, with the expansion of the franchise business industry, franchise platforms are gradually classified into catering franchise platforms, clothing franchise platforms, maternal and child franchise platforms, etc. For catering franchise platforms, due to the wide range of audience users involved and not being restricted by specific age and gender, the demand for franchise investment is getting higher and higher, but the franchise project data displayed on the current catering franchise platform is too single and superficial. Specifically, most of the current catering franchise platforms only display the establishment time of each franchise project and the number of existing franchisees. The franchise project data displayed can only roughly indicate the franchise popularity corresponding to each franchise project, and cannot reflect the actual franchise value corresponding to each franchise project. As we all know, franchising requires pre-investment costs. In order to prove the investment effectiveness of the franchise investment costs, only the franchise value of the franchise project can arouse the franchise desire of the users to be franchised. It can be seen that the franchise project data displayed on the current catering franchise platform cannot provide a strong basis for the users to be franchised to screen franchise projects, resulting in a decline in the franchise experience of the users to be franchised. Summary of the invention

[0004] In view of the above problems, the purpose of this application is to propose a franchisee data analysis and processing system based on cloud computing for the franchise platform. By enriching the franchise project information existing on the catering franchise platform and supplementing the actual consumption data corresponding to the franchisees, the franchisee data is sorted and analyzed, and the comprehensive franchise value coefficient corresponding to each franchise project is evaluated, thereby providing users who are waiting to join with a strong basis for screening franchise projects.

[0005] The present invention is achieved through the following technical solutions:

[0006] A franchisee data analysis and processing system for a franchise platform based on cloud computing, comprising a catering franchise project main body information extraction module, a franchisee online consumption port link module, a franchisee online catering consumption parameter collection module, a franchisee online catering consumption analysis module, a franchise database, a catering franchise project comprehensive franchise value assessment module and a catering franchise project classification retrieval terminal;

[0007] The catering franchise project subject information extraction module is used to count the names of catering franchise projects existing on the catering franchise platform, and number the existing catering franchise projects in a set order, marking them as A, B, ..., I, ..., N in sequence, and extract the subject information corresponding to each catering franchise project;

[0008] The franchisee online consumption port link module is used to extract the number of franchisees and the franchisee name and franchise store location corresponding to each franchisee from the franchisee basic information corresponding to the subject information, and number each extracted franchisee in a predefined order, marked as 1, 2, ..., i, ..., n respectively, and then link to the online life service platform according to the franchisee name and franchise store location corresponding to each franchisee, and search for the consumption port of each franchisee on the online service platform corresponding to each catering franchise project, and then use it as the online consumption port of each franchisee corresponding to each catering franchise project;

[0009] The franchisee online catering consumption parameter collection module is used to extract the current franchise period from the franchisee basic information corresponding to the subject information, and divide and mark it according to the year, respectively marked as 1, 2, ..., j, ..., m, where j represents the jth year, thereby collecting the online catering consumption parameters corresponding to each year from the online consumption port of each franchisee corresponding to each catering franchise project;

[0010] The franchisee online catering consumption analysis module is used to analyze the online catering consumption parameters of each franchisee corresponding to each catering franchise project in each year, and obtain the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period, wherein the franchisee online catering consumption analysis module includes a franchisee popularity analysis module and a franchisee investment return analysis module;

[0011] The catering franchise project comprehensive franchise value evaluation module is used to evaluate the comprehensive franchise value coefficient corresponding to each catering franchise project by combining the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period;

[0012] The catering franchise project classification and retrieval terminal is used to classify the comprehensive franchise value coefficient corresponding to each catering franchise project and the popularity coefficient and franchise investment return coefficient of each franchisee within the current franchise period, forming a franchisee database corresponding to each catering franchise project, and then providing a retrieval port to users who are waiting to join to support the retrieval of franchisee data.

[0013] Based on the above improved technical solution, the subject information includes basic pricing information and franchisee basic information.

[0014] Based on the above improved technical solution, the basic pricing information includes the types of dishes and the basic pricing corresponding to various dishes, and the basic information of franchisees includes the number of franchisees and the franchisee names corresponding to each franchisee, the region where the franchise store is located, the current franchise period and the franchise investment costs.

[0015] Based on the above improved technical solution, the online catering consumption parameters include the frequent customer consumption rate, the overall rating value and the sales volume corresponding to various dishes.

[0016] Based on the above improved technical solution, the specific method for collecting the frequent customer consumption rate includes the following steps:

[0017] Step 1: crawl all online catering consumption records corresponding to each year from the online consumption portal of each franchisee of each catering franchise project, and count the total number of online catering consumption records crawled in each year;

[0018] Step 2: Extract the consumer customer account from each online catering consumption record crawled in each year, and then compare the consumer customer account corresponding to each online catering consumption record to determine whether there is an identical consumer customer account. If so, record the identical consumer customer as a regular consumer customer, record the different consumer customer as a new consumer customer, and summarize the online catering consumption records corresponding to the regular consumer customers;

[0019] Step 3: Count the number of regular customers and new customers respectively, and count the number of online catering consumption records corresponding to each regular customer;

[0020] Step 4: Calculate the frequent customer consumption rate of each franchisee in each year for each catering franchise project based on the number of frequent customers, the number of new customers, and the number of online catering consumption records corresponding to each frequent customer, denoted as σ Ii j.

[0021] Based on the above improved technical solution, the specific method for collecting the overall score value includes the following steps:

[0022] 1) Crawl all consumption evaluations corresponding to each year from the online consumption portals of each franchisee of each catering franchise project;

[0023] 2) Eliminate invalid consumption evaluations from each year, retain valid consumption evaluations, and count the number of valid consumption evaluations from each year;

[0024] 3) Calculate the score values ​​of all valid consumption evaluations corresponding to each year according to the set scoring model to obtain the score values ​​corresponding to each valid consumption evaluation in each year;

[0025] 4) Compare the score values ​​corresponding to each valid consumption evaluation in each year, select the maximum score value and the minimum score value and eliminate them, and then calculate the average of the other score values ​​corresponding to each year, and obtain the overall score value corresponding to each franchisee of each catering franchise project in each year.

[0026] Based on the above improved technical solution, the franchisee popularity analysis module is used to analyze the popularity coefficient of each franchisee of each catering franchise project within the current franchise period according to the frequent customer consumption rate and overall score value of each franchisee in the online catering consumption parameters of each year corresponding to each catering franchise project. The specific analysis method is as follows:

[0027] Step 1: Extract the overall score value from the online catering consumption parameters of each franchisee in each year corresponding to each catering franchise project, and match it with the overall score value range corresponding to various consumption score coefficients in the franchise database to obtain the consumption score coefficient of each franchisee in each year corresponding to each catering franchise project, denoted as η Ii j;

[0028] Step 2: According to the frequent customer consumption rate and consumption rating coefficient of each franchisee in each year, the popularity coefficient of each franchisee in each catering franchise project within the current franchise period is calculated. ξ Ii It is expressed as the popularity coefficient of the ith franchisee of the ith catering franchise project within the current franchise period.

[0029] Based on the above improved technical solution, the franchisee investment return analysis module is used to analyze the franchise investment return coefficient of each franchisee of each catering franchise project within the current franchise period according to the sales volume of various dishes corresponding to each franchisee in each annual online catering consumption parameter of each catering franchise project. The specific analysis method is as follows:

[0030] Step 1: Extract basic pricing information from the subject information corresponding to each catering franchise project;

[0031] Step 2: Extract the franchisee name from the franchisee basic information of the subject information corresponding to each catering franchise project, and obtain the menu pricing difference coefficient of each franchisee corresponding to each catering franchise project relative to the basic pricing from the franchise database;

[0032] Step 3: Extract the sales volume of various dishes from the online catering consumption parameters of each franchisee in each year corresponding to each catering franchise project, and substitute the sales volume, basic pricing and the coefficient of dish pricing difference relative to the basic pricing corresponding to each dish into the set operating income forecast calculation formula to predict the annual average operating income of each franchisee in each catering franchise project within the current franchise period;

[0033] Step 4: Extract the franchise investment fee from the franchisee basic information corresponding to the main information of each catering franchise project, and divide the annual average operating income of each franchisee corresponding to each catering franchise project within the current franchise period by the franchise investment fee to obtain the franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period, recorded as δ Ii .

[0034] Based on the above improved technical solution, the specific evaluation calculation formula for the comprehensive franchise value coefficient corresponding to each catering franchise project is: It is represented as the comprehensive franchise value coefficient corresponding to the I-th catering franchise project, and a and b represent the modified weight values ​​corresponding to popularity and franchise investment return respectively.

[0035] Based on the above improved technical solution, the specific retrieval method corresponding to the franchisee data is as follows:

[0036] When the user who wants to join enters the name of the designated catering franchise project in the search port, the comprehensive franchise value coefficient corresponding to the designated catering franchise project can be retrieved;

[0037] When the user who wants to join enters the name of the designated catering franchise project and the name of the designated franchisee in the search port, the popularity coefficient and franchise investment return coefficient of the designated franchisee corresponding to the designated catering franchise project can be retrieved.

[0038] The beneficial effects of the present invention are as follows:

[0039] (1) The present invention extracts the franchisee information corresponding to each franchise project from the catering franchise platform, and links it to the online consumption port according to the franchisee name and the location of the franchise store in the franchisee information, thereby collecting online catering consumption parameters from the online consumption port and adding them to the franchise project data, and then processing and analyzing the online catering consumption parameters of each franchisee corresponding to each catering franchise project, so as to evaluate the comprehensive franchise value coefficient corresponding to each catering franchise project. The present invention greatly enriches the franchise project data by supplementing the actual consumption data of each franchisee corresponding to the franchise project, and effectively makes up for the shortcomings of the franchise project data displayed on the current catering franchise platform being too single and superficial. The comprehensive franchise value coefficient evaluated by the invention can intuitively reflect the franchise value of the catering franchise project, and provide a strong basis for users to join in screening franchise projects, thereby improving the franchise experience of users to join.

[0040] (2) The comprehensive franchise value coefficient evaluated by the present invention integrates the franchisee's popularity coefficient and franchise investment return coefficient, making the evaluation index of the comprehensive franchise value coefficient more comprehensive, which is conducive to improving the accuracy of the evaluation results.

[0041] (3) The present invention sets up a classification and retrieval terminal for catering franchise projects to classify the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period and the comprehensive franchise value coefficient of each catering franchise project, thereby forming a franchisee database corresponding to each catering franchise project. This provides a retrieval port to support the retrieval of franchisee data for users who are waiting to join, improves the use function of the catering franchise platform, and provides a more convenient channel for users who are waiting to join to screen catering franchise projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0043] Figure 1 It is a schematic diagram of the module connection structure of the present invention;

[0044] Figure 2 It is a schematic diagram of the connection structure of the franchisee online catering consumption analysis module of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 A franchisee data analysis and processing system for a franchise platform based on cloud computing includes a catering franchise project main body information extraction module, a franchisee online consumption port link module, a franchisee online catering consumption parameter collection module, a franchisee online catering consumption analysis module, a franchise database, a catering franchise project comprehensive franchise value evaluation module and a catering franchise project classification retrieval terminal.

[0047] Among them, the catering franchise project main information extraction module is respectively connected to the franchisee online consumption port link module and the franchisee online catering consumption analysis module, the franchisee online consumption port link module is connected to the franchisee online catering consumption parameter collection module, the franchisee online catering consumption parameter collection module is connected to the franchisee online catering consumption analysis module, the franchisee online catering consumption analysis module is connected to the catering franchise project comprehensive franchise value assessment module, and the catering franchise project comprehensive franchise value assessment module is connected to the catering franchise project classification retrieval terminal.

[0048] The catering franchise project main information extraction module is used to count the names of catering franchise projects existing on the catering franchise platform. The catering franchise projects mentioned here include milk tea, braised chicken, Zhengxin chicken steak, etc., and number the existing catering franchise projects in a set order, marked as A, B,..., I,..., N in sequence, and extract the main information corresponding to each catering franchise project from the catering franchise platform, where the main information includes basic pricing information and franchisee basic information, and the basic pricing information includes the types of dishes and the basic pricing corresponding to various dishes. The franchisee basic information includes the number of franchisees and the franchisee name corresponding to each franchisee, the location of the franchise store, the current franchise period and the franchise investment cost. The basic pricing value mentioned here refers to the headquarters pricing of the catering franchise project.

[0049] In the above embodiment, the catering franchise projects are numbered according to a set order, wherein the set order is the order of establishment time of the headquarters corresponding to the catering franchise projects.

[0050] The franchisee online consumption port link module is used to extract the number of franchisees and the franchisee name and franchise store location corresponding to each franchisee from the franchisee basic information corresponding to the subject information, and number each extracted franchisee in a predefined order, marked as 1, 2, ..., i, ..., n respectively, where the predefined order is to obtain the joining time corresponding to each franchisee, and number them in chronological order of joining time. At this time, according to the franchisee name and franchise store location corresponding to each franchisee, it is linked to the online life service platform, where the online life service platform is a complex of various online life service platforms, specifically the corresponding complexes of Meituan, Dianping, Baidu Nuomi, etc., from which the consumption ports of each franchisee corresponding to each catering franchise project on the online service platform are searched, and then the corresponding consumption ports are used as the online consumption ports of each franchisee corresponding to each catering franchise project.

[0051] In a specific embodiment of the present invention, by obtaining the online consumption port corresponding to each franchisee according to the online life service platform, a reliable collection channel is provided for the subsequent collection of the online catering consumption parameters corresponding to each franchisee.

[0052] The franchise database is used to store the specific score value corresponding to each evaluation-related word, store the overall score value range corresponding to various consumption score coefficients, store the menu pricing difference coefficient of each franchisee relative to the basic pricing corresponding to each catering franchise project, and store the modified weight value corresponding to popularity and franchise investment return.

[0053] The franchisee online catering consumption parameter collection module is used to extract the current franchise duration from the franchisee basic information corresponding to the subject information. The franchise duration here is in years, and it is divided and marked according to years, marked as 1, 2, ..., j, ..., m, where j represents the jth year. The online catering consumption parameters corresponding to each year are collected from the online consumption port of each franchisee corresponding to each catering franchise project. The online catering consumption parameters include the frequent customer consumption rate, the overall score value and the sales volume of various dishes.

[0054] The specific method for collecting the frequent customer consumption rate includes the following steps:

[0055] Step 1: crawl all online catering consumption records corresponding to each year from the online consumption portal of each franchisee of each catering franchise project;

[0056] Step 2: Count the total number of online catering consumption records crawled in each year, recorded as Z Ii j. Number each online dining consumption record in the order of consumption time;

[0057] Step 3: extract the consumer customer account from each online catering consumption record, and compare the consumer customer account corresponding to each online catering consumption record to determine whether there is an identical consumer customer account. If so, record the identical consumer customer as a regular consumer customer, record the different consumer customer as a new consumer customer, and summarize the online catering consumption records corresponding to the regular consumer customers;

[0058] Step 4: Count the number of regular customers and new customers respectively, and count the number of online catering consumption records corresponding to each regular customer. Here, the number of regular customers and the number of new customers of each franchisee in each year corresponding to each catering franchise project are recorded as X Ii j.Y Ii j, and number the regular customers of each franchisee in each year corresponding to each catering franchise project, and mark them as 1, 2, ..., k, ..., u in sequence, and then record the number of online catering consumption records corresponding to the regular customers of each franchisee in each year corresponding to each catering franchise project as z Ii j k;

[0059] Step 5: Calculate the frequent customer consumption rate of each franchisee in each year for each catering franchise project based on the number of frequent customers, the number of new customers and the number of online catering consumption records corresponding to each frequent customer. σ Ii j represents the regular customer consumption rate of the i-th franchisee in the j-th year corresponding to the i-th catering franchise project, X Ii j.Y Ii j. Z Ii j represents the number of regular customers, the number of new customers, and the total number of online catering consumption records corresponding to the i-th franchisee of the i-th catering franchise project in the j-th year, and z Ii j k represents the number of online catering consumption records corresponding to the kth frequent consumer of the i-th franchisee in the j-th year of the i-th catering franchise project. The more frequent consumers there are, the more online catering consumption records corresponding to the frequent consumers and the higher the frequent customer consumption rate.

[0060] The specific method for collecting the overall score value includes the following steps:

[0061] 1) Crawl all consumption evaluations corresponding to each year from the online consumption portals of each franchisee of each catering franchise project;

[0062] 2) Eliminate invalid consumer evaluations from the corresponding consumer evaluations of each year, retain valid consumer evaluations, and count the number of valid consumer evaluations corresponding to each year. Invalid consumer evaluations refer to consumer evaluations without substantial evaluation content. The specific identification process of invalid consumer evaluations is as follows:

[0063] Extract evaluation-related words from each consumer evaluation content corresponding to each year. The evaluation-related words here include positive evaluation-related words, such as like, taste good, etc., and negative evaluation-related words, such as bad taste, not delicious, etc. If no evaluation-related words can be extracted from a consumer evaluation content, then the consumer evaluation is invalid. On the contrary, if one or more evaluation-related words can be extracted from a consumer evaluation, then the consumer evaluation is valid.

[0064] 3) Calculate the score values ​​of all valid consumer evaluations corresponding to each year according to the set scoring model to obtain the score values ​​corresponding to each valid consumer evaluation in each year. The specific operation process of the set scoring model includes:

[0065] All evaluation-related words corresponding to each valid consumer evaluation in each year constitute a valid consumer evaluation-related word set;

[0066] Extracting each evaluation-related word corresponding to each valid consumer evaluation from the set of valid consumer evaluation-related words in turn, and matching it with the specific score value corresponding to each evaluation-related word in the franchise database, wherein the specific score value may be a positive value or a negative value, and the specific score value of the evaluation-related word corresponding to the positive evaluation is a positive value, and the specific score value of the evaluation-related word corresponding to the negative evaluation is a negative value, so as to obtain the specific score value of each evaluation-related word corresponding to each valid consumer evaluation;

[0067] Accumulate the specific score values ​​of each evaluation-related word corresponding to each valid consumer evaluation to obtain the score value corresponding to each valid consumer evaluation in each year;

[0068] 4) Compare the score values ​​corresponding to each valid consumption evaluation in each year, select the maximum score value and the minimum score value and eliminate them, and then calculate the average of other score values ​​corresponding to each year, and obtain the overall score value corresponding to each franchisee of each catering franchise project in each year. The larger the overall score value, the higher the evaluation.

[0069] In a specific embodiment of the present invention, the purpose of removing the maximum score value and the minimum score value in the process of calculating the overall score value is to avoid the calculation interference of the maximum score value and the minimum score value on the overall score value, and the focus is to ensure the reliability of the calculation of the overall score value.

[0070] The specific method for collecting the sales volume of various dishes is to crawl the sales volume of various dishes corresponding to each year from the online consumption portal of each franchisee corresponding to each catering franchise project.

[0071] See also Figure 2The franchisee online catering consumption analysis module is used to analyze the online catering consumption parameters of each franchisee of each catering franchise project in each year, and obtain the popularity coefficient and franchise investment return coefficient of each franchisee of each catering franchise project within the current franchise period. The franchisee online catering consumption analysis module includes the franchisee popularity analysis module and the franchisee investment return analysis module.

[0072] The franchisee popularity analysis module is used to analyze the popularity coefficient of each franchisee in each catering franchise project within the current franchise period according to the frequent customer consumption rate and overall score value in the online catering consumption parameters of each year corresponding to each franchisee in each catering franchise project. The specific analysis method is as follows:

[0073] Step 1: Extract the overall score value from the online catering consumption parameters of each franchisee in each year corresponding to each catering franchise project, and match it with the overall score value range corresponding to various consumption score coefficients in the franchise database to obtain the consumption score coefficient of each franchisee in each year corresponding to each catering franchise project, denoted as η Ii j, where the overall rating value is directly proportional to the consumption rating coefficient;

[0074] Step 2: According to the frequent customer consumption rate and consumption rating coefficient of each franchisee in each year, the popularity coefficient of each franchisee in each catering franchise project within the current franchise period is calculated. ξ Ii It is represented as the popularity coefficient of the i-th franchisee of the i-th catering franchise project in the current franchise period, η Ii j represents the consumption score coefficient of the ith franchisee in the jth year corresponding to the ith catering franchise project. The larger the frequent customer consumption rate and the consumption score coefficient, the larger the popularity coefficient, indicating that it is more popular.

[0075] The franchisee investment return analysis module is used to analyze the franchise investment return coefficient of each franchisee in the current franchise period according to the sales volume of various dishes in the online catering consumption parameters of each franchisee in each catering franchise project. The specific analysis method is as follows:

[0076] Step 1: Extract basic pricing information from the subject information corresponding to each catering franchise project;

[0077] Step 2: Extract the franchisee name from the franchisee basic information of the main information corresponding to each catering franchise project, and compare it with the menu pricing difference coefficient of each franchisee corresponding to each catering franchise project in the franchise database relative to the basic pricing, and obtain the menu pricing difference coefficient of each franchisee corresponding to each catering franchise project relative to the basic pricing, denoted as χ Ii, the menu pricing difference coefficient mentioned here can be a number greater than zero or a number less than zero;

[0078] In this embodiment, the coefficient of difference in dish pricing of each franchisee corresponding to each catering franchise project in the franchise database relative to the basic pricing is obtained based on the difference between the consumption level in the area where the franchise store of each franchisee corresponding to each catering franchise project is located and the consumption level in the area where the headquarters is located.

[0079] Step 3: Number the various dishes in each restaurant franchise project, marking them as 1, 2, ..., d, ..., p, and the basic price of each dish corresponding to each restaurant franchise project is recorded as q I d, and extract the sales volume of various dishes from the online catering consumption parameters of each franchisee in each year, recorded as o Ii j d. By substituting the sales volume, basic pricing and the coefficient of pricing difference of various dishes into the set operating income forecast calculation formula, the annual average operating income of each franchisee in each catering franchise project within the current franchise period is predicted. Q Ii It is represented by the annual average operating income of the ith franchisee of the ith catering franchise project within the current franchise period, q I d represents the basic pricing of the d-th dish of the I-th catering franchise project, and x Ii It is expressed as the coefficient of the menu pricing difference of the ith franchisee in the ith catering franchise project relative to the basic pricing, o Ii j d represents the sales volume of the dth dish of the ith franchisee in the jth year of the ith catering franchise project;

[0080] Step 4: Extract the franchise investment fee from the franchisee basic information corresponding to the main information of each catering franchise project, and divide the annual average operating income of each franchisee corresponding to each catering franchise project within the current franchise period by the franchise investment fee to obtain the franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period, recorded as δ Ii Among them, the greater the annual average operating income, the smaller the franchise investment cost, and the greater the franchise investment return coefficient, indicating that the higher the franchise investment return rate.

[0081] In this embodiment, the types of dishes corresponding to each catering franchise project are consistent with the types of dishes corresponding to each franchisee of the catering franchise project.

[0082] The comprehensive franchise value assessment module for catering franchise projects is used to evaluate the comprehensive franchise value coefficient corresponding to each catering franchise project by combining the popularity coefficient and franchise investment return coefficient of each franchisee in the current franchise period. Expressed as the comprehensive franchise value coefficient corresponding to the I-th catering franchise project, ξ Ii , δ Ii They respectively represent the popularity coefficient and franchise investment return coefficient of the ith franchisee of the ith catering franchise project within the current franchise period. a and b respectively represent the modified weight values ​​corresponding to popularity and franchise investment return. The larger the popularity coefficient and franchise investment return coefficient are, the larger the comprehensive franchise value coefficient is, indicating that the comprehensive franchise value is higher.

[0083] The comprehensive franchise value coefficient evaluated by the embodiment of the present invention integrates the franchisee's popularity coefficient and the franchise investment return coefficient, making the evaluation index of the comprehensive franchise value coefficient more comprehensive, which is conducive to improving the accuracy of the evaluation result.

[0084] The catering franchise project classification retrieval terminal is used to classify the popularity coefficient and franchise investment return coefficient of each franchisee in the current franchise period of each catering franchise project and the comprehensive franchise value coefficient of each catering franchise project, so as to form a franchisee database corresponding to each catering franchise project, and then provide a retrieval port to support the retrieval of franchisee data for users to join. The specific retrieval method is as follows:

[0085] When the user who wants to join enters the name of the designated catering franchise project in the search port, the comprehensive franchise value coefficient corresponding to the designated catering franchise project can be retrieved;

[0086] When the user who wants to join enters the name of the designated catering franchise project and the name of the designated franchisee in the search port, the popularity coefficient and franchise investment return coefficient of the designated franchisee corresponding to the designated catering franchise project can be retrieved.

[0087] The embodiment of the present invention sets a classification and retrieval terminal for catering franchise projects, classifies the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period and the comprehensive franchise value coefficient of each catering franchise project, and forms a franchisee database corresponding to each catering franchise project. This provides a retrieval port to support the retrieval of franchisee data for users to join, improves the use function of the catering franchise platform, and provides a more convenient channel for users to join to screen catering franchise projects.

[0088] The present invention extracts the franchisee information corresponding to each franchise project from the catering franchise platform, and links to the online consumption port according to the franchisee name and the region where the franchise store is located in the franchisee information, thereby collecting online catering consumption parameters from the online consumption port, adding them to the franchise project data, and then processing and analyzing the online catering consumption parameters of each franchisee corresponding to each catering franchise project, so as to evaluate the comprehensive franchise value coefficient corresponding to each catering franchise project. The present invention greatly enriches the franchise project data by supplementing the actual consumption data of each franchisee corresponding to the franchise project, and effectively makes up for the shortcomings of the franchise project data displayed on the current catering franchise platform that are too single and superficial. The evaluated comprehensive franchise value coefficient can intuitively reflect the franchise value of the catering franchise project, and provide a powerful basis for users to join in screening franchise projects, thereby improving the franchise experience of users to join in.

[0089] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A franchisee data analysis and processing system based on cloud computing, characterized by: It includes a catering franchise project main body information extraction module, a franchisee online consumption port link module, a franchisee online catering consumption parameter collection module, a franchisee online catering consumption analysis module, a franchise database, a catering franchise project comprehensive franchise value assessment module and a catering franchise project classification retrieval terminal; The catering franchise project subject information extraction module is used to count the names of catering franchise projects existing on the catering franchise platform, and number the existing catering franchise projects in a set order, marking them as A, B, ..., I, ..., N in sequence, and extract the subject information corresponding to each catering franchise project; The franchisee online consumption port link module is used to extract the number of franchisees and the franchisee name and franchise store location corresponding to each franchisee from the franchisee basic information corresponding to the subject information, and number each extracted franchisee in a predefined order, marked as 1, 2, ..., i, ..., n respectively, and then link to the online life service platform according to the franchisee name and franchise store location corresponding to each franchisee, and search for the consumption port of each franchisee on the online service platform corresponding to each catering franchise project, and then use it as the online consumption port of each franchisee corresponding to each catering franchise project; The franchisee online catering consumption parameter collection module is used to extract the current franchise period from the franchisee basic information corresponding to the subject information, and divide and mark it according to the year, respectively marked as 1, 2, ..., j, ..., m, where j represents the jth year, thereby collecting the online catering consumption parameters corresponding to each year from the online consumption port of each franchisee corresponding to each catering franchise project; The franchisee online catering consumption analysis module is used to analyze the online catering consumption parameters of each franchisee corresponding to each catering franchise project in each year, and obtain the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period, wherein the franchisee online catering consumption analysis module includes a franchisee popularity analysis module and a franchisee investment return analysis module; The catering franchise project comprehensive franchise value evaluation module is used to evaluate the comprehensive franchise value coefficient corresponding to each catering franchise project by combining the popularity coefficient and franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period; The catering franchise project classification and retrieval terminal is used to classify the comprehensive franchise value coefficient corresponding to each catering franchise project and the popularity coefficient and franchise investment return coefficient of each franchisee within the current franchise period, so as to form a franchisee database corresponding to each catering franchise project, and then provide a retrieval port to support the retrieval of franchisee data for users who want to join; The specific evaluation calculation formula for the comprehensive franchise value coefficient corresponding to each catering franchise project is: , It is represented as the comprehensive franchise value coefficient corresponding to the I-th catering franchise project, a and b represent the modified weight values ​​corresponding to popularity and franchise investment return, respectively. It is expressed as the franchise investment return coefficient of each franchisee in the current franchise period for each catering franchise project. It is represented as the popularity coefficient of the i-th franchisee of the i-th catering franchise project within the current franchise period; The franchisee popularity analysis module is used to analyze the popularity coefficient of each franchisee of each catering franchise project within the current franchise period according to the frequent customer consumption rate and overall score value of each franchisee in the online catering consumption parameters of each year corresponding to each catering franchise project. The specific analysis method is as follows: Step 1: Extract the overall score value from the online catering consumption parameters of each franchisee in each year corresponding to each catering franchise project, and match it with the overall score value range corresponding to various consumption score coefficients in the franchise database to obtain the consumption score coefficient of each franchisee in each year corresponding to each catering franchise project, recorded as ; The specific method for collecting the overall score value includes the following steps: 1) Crawling all consumption evaluations corresponding to each year from the online consumption portals of each franchisee of each catering franchise project; 2) Eliminate invalid consumption evaluations from each year, retain valid consumption evaluations, and count the number of valid consumption evaluations from each year; 3) Calculate the score values ​​of all valid consumer evaluations corresponding to each year according to the set scoring model to obtain the score values ​​corresponding to each valid consumer evaluation in each year; 4) Compare the score values ​​corresponding to each valid consumption evaluation in each year, select the maximum score value and the minimum score value and eliminate them, and then calculate the average of the remaining score values ​​corresponding to each year to obtain the overall score value corresponding to each franchisee of each catering franchise project in each year; Step 2: According to the frequent customer consumption rate and consumption rating coefficient of each franchisee in each year, the popularity coefficient of each franchisee in each catering franchise project within the current franchise period is calculated. , It is represented as the popularity coefficient of the i-th franchisee of the i-th catering franchise project within the current franchise period. It is represented by the consumption score coefficient of the ith franchisee in the jth year corresponding to the ith catering franchise project; The specific collection method of the frequent customer consumption rate comprises the following steps: Step 1: crawl all online catering consumption records corresponding to each year from the online consumption portal of each franchisee of each catering franchise project, and count the total number of online catering consumption records crawled in each year; Step 2: Extract the consumer customer account from each online catering consumption record crawled in each year, and then compare the consumer customer account corresponding to each online catering consumption record to determine whether there is an identical consumer customer account. If so, record the identical consumer customer as a regular consumer customer, record the different consumer customer as a new consumer customer, and summarize the online catering consumption records corresponding to the regular consumer customers; Step 3: Count the number of regular customers and new customers respectively, and count the number of online catering consumption records corresponding to each regular customer, and number each regular customer of each franchisee in each year corresponding to each catering franchise project, and mark them as 1, 2, ..., k, ..., u in sequence; Step 4: Calculate the frequent customer consumption rate of each franchisee in each year for each catering franchise project based on the number of frequent customers, the number of new customers and the number of online catering consumption records corresponding to each frequent customer, recorded as ,in, , It is represented by the regular customer consumption rate of the i-th franchisee in the j-th year corresponding to the i-th catering franchise project, , , They are respectively represented as the number of regular customers, the number of new customers, and the total number of online catering consumption records corresponding to the i-th franchisee of the i-th catering franchise project in the j-th year, It is represented by the number of online catering consumption records corresponding to the kth frequent consumer of the i-th franchisee in the j-th year of the i-th catering franchise project; The franchisee investment return analysis module is used to analyze the franchise investment return coefficient of each franchisee of each catering franchise project within the current franchise period according to the sales volume of various dishes corresponding to each franchisee in each year's online catering consumption parameters. The specific analysis method is as follows: Step 1: Extract basic pricing information from the subject information corresponding to each catering franchise project; Step 2: Extract the franchisee name from the franchisee basic information of the subject information corresponding to each catering franchise project, and obtain the menu pricing difference coefficient of each franchisee corresponding to each catering franchise project relative to the basic pricing from the franchise database; Step 3: Number the various dishes in each restaurant franchise project, marking them as 1, 2, ..., d, ..., p, and the basic pricing of each dish in each restaurant franchise project is recorded as And extract the sales volume of various dishes from the online catering consumption parameters of each franchisee in each year, recorded as , the sales volume, basic pricing and the coefficient of pricing difference of dishes relative to the basic pricing of various dishes are substituted into the set operating income forecast calculation formula to predict the annual average operating income of each franchisee in each catering franchise project within the current franchise period. , It is represented by the annual average operating income of the ith franchisee of the ith catering franchise project within the current franchise period. It represents the basic pricing of the d-th dish of the I-th catering franchise project. It is expressed as the coefficient of the menu pricing difference of the ith franchisee in the ith catering franchise project relative to the basic pricing, It is represented by the sales volume of the d-th dish of the ith franchisee in the j-th year corresponding to the ith catering franchise project; Step 4: Extract the franchise investment fee from the franchisee basic information of each franchisee corresponding to the main information of each catering franchise project, and divide the annual average operating income of each franchisee corresponding to each catering franchise project within the current franchise period by the franchise investment fee to obtain the franchise investment return coefficient of each franchisee corresponding to each catering franchise project within the current franchise period, recorded as .

2. The cloud computing-based franchisee data analysis and processing system of the franchisee platform according to claim 1, characterized in that: The subject information includes basic pricing information and franchisee basic information.

3. The cloud computing-based franchisee data analysis and processing system of the franchisee platform according to claim 2, characterized in that: The basic pricing information includes the types of dishes and the basic pricing corresponding to various dishes. The basic information of franchisees includes the number of franchisees and the franchisee names corresponding to each franchisee, the region where the franchise store is located, the current franchise period and the franchise investment costs.

4. The cloud computing-based franchisee data analysis and processing system of the franchisee platform according to claim 1, characterized in that: The online catering consumption parameters include the frequent customer consumption rate, the overall rating value and the sales volume corresponding to various dishes.

5. The cloud computing-based franchisee data analysis and processing system of the franchisee platform according to claim 1, characterized in that: The specific retrieval method corresponding to the franchisee data is as follows: When the user who wants to join enters the name of the designated catering franchise project in the search port, the comprehensive franchise value coefficient corresponding to the designated catering franchise project can be retrieved; When the user who wants to join enters the name of the designated catering franchise project and the name of the designated franchisee in the search port, the popularity coefficient and franchise investment return coefficient of the designated franchisee corresponding to the designated catering franchise project can be retrieved.

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