Data management system for franchise owner

Abstract

The invention discloses a data management system for franchise owners. The data management system comprises a unified master file management module, a customer feedback module, a service center module and a master file center module, the unified master file management module is used for classified storage of alliance provider master data; the customer feedback module is used for collecting evaluation information of the client to the store and supervising the store and the alliance owner to which the store belongs according to the evaluation information; the service center module is used for collecting order placing data information of the client, generating a work order according to the order placing data information of the client, and matching the work order with a store of a franchise owner to generate an order; the main file center module comprises a center selection system, a new store system, an ERP system and a B I system. According to the method, multi-label storage is carried out on the alliance owner information, the stores and store commodities of the alliance owners are analyzed from multiple aspects, and accurate guidance is provided for store operation of the alliance owners, so that the store operation risk of the alliance owners is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data management and processing, and more specifically, to a data management system for franchise owners. Background Art

[0002] With the rapid development of the chain operation model, the franchisee management system is facing severe challenges brought about by the explosion of data volume and the diversification of business scenarios; traditional data management systems are mostly built based on single functional modules, suffering from problems such as data islands and lack of integration, insufficient level of decision-making intelligence, weak real-time response capabilities, and overabundance of store resources. Summary of the Invention

[0003] In view of the above problems, the purpose of the present invention is to provide a data management system for franchise owners, which can store franchise owner information with multiple tags, comprehensively analyze the stores of franchise owners from multiple aspects, provide precise guidance for the store operation of franchise owners, and thus reduce the store operation risks of franchise owners.

[0004] The present invention provides a data management system for franchise owners, including: a unified master file management module, a customer feedback module, a service center module, and a master file center module;

[0005] The unified master file management module is used to collect franchise owner data, preprocess the collected franchise owner data to obtain standardized formatted franchise owner data, and then classify and store the standardized formatted franchise owner data;

[0006] The customer feedback module is used to collect evaluation information of the store from the client side, and supervise the store and the franchise owner to which the store belongs according to the evaluation information;

[0007] The service center module is used to collect order data information from the client side, generate a work order according to the order data information of the client side, and then match the work order with the store of the franchise owner to generate an order;

[0008] The master file center module includes a preferred selection system, a new store system, an ERP system, and a BI system; the preferred selection system is used for the franchise owner to select a cooperation model and optimize the products selected by the franchise owner; the new store system is used for the franchise owner to evaluate the selected store location; the ERP system is used for intelligent inventory monitoring and replenishment reminder of the store products of the franchise owner; the BI system is used for dynamically adjusting the indicators of the store products of the franchise owner and predicting the sales volume of the products.

[0009] In this solution, the unified master file management module includes a master file statistics unit, a store opening area unit, a store opening number unit, a franchisee level unit, a service team unit, an identity label unit, an operation portrait unit, and a franchisee master data collection unit;

[0010] The master file statistics unit is used to count the total number of stores operated by the franchisee master;

[0011] The store opening area unit is used to record the location area of each store and display the total number of stores in the current area on a preset map area;

[0012] The store opening number unit classifies the franchisee master according to the store opening quantity value for quick query;

[0013] The franchisee level unit is used to divide the levels of the franchisee master and provide franchisee level query;

[0014] The service team unit is used for the franchisee master to select the corresponding service team;

[0015] The identity label unit identifies the franchisee master and sets labels for the information query of the franchisee master;

[0016] The operation portrait unit is used to construct the operation portrait of each store;

[0017] The franchisee master data collection unit is used to collect franchisee master data.

[0018] In this solution, the steps for dividing the levels of the franchisee master specifically include:

[0019] Obtain the net profit of the monthly average profit of the stores of the franchisee master within a preset period;

[0020] Based on the amount range in which the net profit of the monthly average profit of the store falls within a preset period, obtain the corresponding wealth attribute level;

[0021] When the net profit of the monthly average profit of the store within a preset period is greater than zero, the current store is a profitable store, and record the value of the profitable store;

[0022] Divide the value of the profitable store by the total number of franchise stores of the corresponding franchisee master to obtain the profit rate;

[0023] Based on the preset profit range in which the profit rate falls, determine the corresponding operation ability level;

[0024] Obtain the number of stores opened by the franchisee master and the years of operation of the store;

[0025] According to the number of stores opened by the franchisee master and the years of operation of the store, obtain the brand loyalty level;

[0026] According to the financial attribute level, brand loyalty level, and business operation ability level, the corresponding judgment level of the franchisee owner is obtained.

[0027] In this solution, the customer feedback module is further configured to:

[0028] Extract the keywords from the evaluation information of the client side, classify the keywords, and obtain the positive keywords and negative keywords of the same store;

[0029] Extract the numerical values of the number of positive keywords and the number of negative keywords of the same store;

[0030] Subtract the numerical value of the number of negative keywords from the numerical value of the number of positive keywords to obtain a first numerical difference;

[0031] Add the numerical value of the number of positive keywords and the numerical value of the number of negative keywords to obtain the total numerical value;

[0032] According to the first numerical difference divided by the total numerical value, obtain the sentiment polarity value;

[0033] When the sentiment polarity value is less than or equal to a preset first threshold, trigger the negative warning information of the corresponding store.

[0034] In this solution, the selected system includes: a cooperation mode unit and a product optimization unit;

[0035] The cooperation mode unit is used for the franchisee to select the cooperation mode, and the cooperation mode includes the standard mode, the bidding mode, and the agent mode;

[0036] The product optimization unit is used to calculate the comprehensive score value S of the target product, and its formula is S i = w1 * S i―1 + w2 * S i―2 + w3 * S i―3 ; where S i represents the comprehensive score value of the target product i, w1, w2, and w3 respectively represent the corresponding weight coefficients, S i―1 , S i―2 and S i―3 respectively represent the standardized sales volume score value, gross profit margin score value, and trend score value of the target product i. When the comprehensive score value of the target product is less than the preset score threshold, the corresponding target product is excluded.

[0037] In this solution, the new store system is used to evaluate the store location selected by the franchisee owner to obtain the location evaluation score value. When the location evaluation score value is lower than the preset score threshold, trigger the location warning information.

[0038] In this solution, the ERP system includes an inventory warning unit and an intelligent replenishment unit;

[0039] The inventory warning unit is used to obtain the inventory quantity of goods in the store in real time, trigger the inventory warning information of the goods based on a preset inventory quantity threshold, and send the inventory warning information to the franchisee main terminal of the store for reminder;

[0040] The intelligent replenishment unit is used to calculate the replenishment quantity of goods for the corresponding store and send the replenishment quantity of goods to the franchisee main terminal of the store for reminder.

[0041] In this solution, the steps of calculating the replenishment quantity of goods for the corresponding store specifically include:

[0042] Obtain the sales volume of the corresponding goods within a preset time period and the maximum storage volume of the corresponding goods in the store;

[0043] Calculate the average daily sales volume of the corresponding goods by taking the average of the sales volume of the corresponding goods within a preset time period;

[0044] Subtract the inventory quantity threshold from the maximum storage volume of the corresponding goods in the store to obtain the maximum replenishment quantity of the corresponding goods;

[0045] Let the replenishment quantity of goods in the store be R and the yield rate of the corresponding replenishment goods be D. The formula is And the replenishment quantity of goods R in the store is less than or equal to the maximum replenishment quantity of the corresponding goods. f1 represents the profit value of selling a single corresponding replenishment good, f2 represents the purchase unit price of the corresponding goods, G represents the cost of purchasing the corresponding goods once, T represents the total time expected to sell the corresponding goods with the replenishment quantity R, t ∈ T, w4 represents the inventory cost coefficient of the replenishment goods in the corresponding store, and R represents the average daily sales volume of the replenishment goods;

[0046] Based on the fact that the replenishment quantity of goods R in the store is less than or equal to the maximum replenishment quantity of the corresponding goods, take any replenishment quantity R and substitute it into the yield rate formula of the corresponding goods to obtain a set of yield rates;

[0047] Extract the maximum yield rate from the set of yield rates and set the replenishment quantity of goods corresponding to the maximum yield rate as the replenishment quantity of goods in the current store.

[0048] In this solution, the BI system includes a dynamic index configuration unit and a prediction analysis and warning unit;

[0049] The dynamic index configuration unit is used to dynamically adjust commodity indexes;

[0050] The prediction analysis and warning unit is used to predict the sales volume of goods, obtain a prediction result, and make a judgment based on a preset sales volume threshold to trigger a sales volume warning information.

[0051] A data management system for franchise owners disclosed by the present invention includes: a unified master file management module, a customer feedback module, a service center module, and a master file center module; the unified master file management module is used for classifying and storing franchise owner data; the customer feedback module is used for collecting evaluation information of the store from the client side and supervising the store and the franchise owner to which the store belongs according to the evaluation information; the service center module is used for collecting order data information from the client side, generating a work order according to the order data information of the client side, and matching the work order with the store of the franchise owner to generate an order; the master file center module includes a heart selection system, a new store system, an ERP system, and a BI system. By storing franchise owner information with multiple tags and analyzing the stores and store products of the franchise owner from multiple aspects, the present invention provides precise guidance for the store operation of the franchise owner, thereby reducing the store operation risk of the franchise owner. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The flowchart of a data management system for franchise owners according to the present invention is shown. DETAILED DESCRIPTION OF THE INVENTION

[0053] In order to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0054] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0055] Figure 1 The flowchart of a data management system for franchise owners according to the present invention is shown.

[0056] As Figure 1 shown, the present invention discloses a data management system for franchise owners, including:

[0057] a unified master file management module, a customer feedback module, a service center module, and a master file center module;

[0058] The unified master file management module is used for collecting franchise owner data, preprocessing the collected franchise owner data to obtain standard formatted franchise owner data, and then classifying and storing the standard formatted franchise owner data;

[0059] The customer feedback module is used to collect evaluation information of the store by the client, and supervise the store and the franchise owner to which the store belongs according to the evaluation information;

[0060] The service center module is used to collect the order data information of the client, generate a work order according to the order data information of the client, and then match the work order with the store of the franchise owner to generate an order;

[0061] The master file center module includes a preferred selection system, a new store system, an ERP system, and a BI system; the preferred selection system is used for the franchise owner to select a cooperation model and optimize the products selected by the franchise owner; the new store system is used to evaluate the store location selected by the franchise owner; the ERP system is used for intelligent inventory monitoring and replenishment reminder of the store products of the franchise owner; the BI system is used for dynamically adjusting the indicators of the store products of the franchise owner and predicting the sales volume of the products.

[0062] According to an embodiment of the present invention, the customer feedback module sets multiple opinion feedback channels, and collects evaluation information of the store by the client through the opinion feedback channels; the service center module includes a client order placement unit, an intelligent work order allocation unit, and a work order coordination unit, collects the product data that the client needs to purchase, that is, the order data, through the client order placement unit, and then converts the corresponding order data into a work order in a set standard format, and then allocates it through the intelligent work order allocation unit, sets the allocation priority score of the store to P j , and its formula is where k1, k2, and k3 respectively represent the corresponding weight coefficients, C represents the matching degree of the store's corresponding work order requirements, L j represents the number of work orders currently processed by store j, L max represents the maximum load value that the corresponding store j can handle, d represents the distance value between the location where the work order is located and store j, d0 represents the set distance value, for example, d0 = 10 kilometers, and the corresponding work order is allocated to the store corresponding to the maximum priority score. When the store corresponding to the maximum priority score does not accept the order, the order can be entrusted to the store corresponding to the second highest priority score through the work order coordination unit; the ERP system is an Enterprise Resource Planning system, and the BI system is a Business Intelligence system; the unified master file management module stores the franchise owner data between multiple modules and classifies and summarizes them for query.

[0063] According to an embodiment of the present invention, the unified master file management module includes a master file statistics unit, a store opening area unit, a store opening number unit, a franchisee level unit, a service team unit, an identity label unit, an operation portrait unit, and a franchisee master data collection unit;

[0064] The master file statistics unit is used to count the total number of stores operated by the franchisee master;

[0065] The store opening area unit is used to record the location area of each store and display the total number of stores in the current area on a preset map area;

[0066] The store opening number unit classifies the franchisee master according to the store opening quantity value for quick query;

[0067] The franchisee level unit is used to divide the levels of the franchisee master and provide franchisee level query;

[0068] The service team unit is used for the franchisee master to select the corresponding service team;

[0069] The identity label unit identifies the franchisee master and sets labels for the information query of the franchisee master;

[0070] The operation portrait unit is used to construct the operation portrait of each store;

[0071] The franchisee master data collection unit is used to collect franchisee master data.

[0072] It should be noted that the master file statistics unit is also used to display the deduplication summary according to the unique ID card, distinguish between having a store and not having a store, that is, to count whether there is an effectively operating store under the master file; the store opening area unit supports area query. When there are multiple sub-file areas that are inconsistent, the first record address is defaulted as the area of the master file. Each franchisee master determines one master file according to the unique ID card, and the total number of master files in the area where the area needs to be displayed is supported for multiple selection and default full selection; the store opening number unit supports multiple selection and default empty selection. For example, the store opening quantity values are divided into 0, 1, 2...; in the service team unit, the names of the service team members will be displayed one by one, and the quantity value of the service stores will be displayed after the corresponding member names; the identity label unit displays the label screening conditions of the franchisee master, such as operation expert, potential rising star, etc.; the franchisee master data collection unit can directly obtain the franchisee master data from the data materials input by the franchisee master, or can also obtain the franchisee master data through the customer feedback module, the service center module, and the master file center module.

[0073] According to an embodiment of the present invention, the steps of dividing the levels of the franchisee master specifically include:

[0074] Obtain the monthly average net profit of the franchisee's main store within the preset period;

[0075] Based on the range of the monthly average net profit of the store falling within the preset period, obtain the corresponding wealth attribute level;

[0076] When the monthly average net profit of the store within the preset period is greater than zero, the current store is a profitable store, and record the value of the profitable store;

[0077] Divide the value of the profitable store by the total number of franchise stores of the corresponding franchisee owner to obtain the profit rate;

[0078] Based on the preset profit range that the profit rate falls into, determine the corresponding operation ability level;

[0079] Obtain the number of stores opened by the franchisee owner and the years of operation of the store;

[0080] Based on the number of stores opened by the franchisee owner and the years of operation of the store, obtain the brand loyalty level;

[0081] Based on the financial attribute level, brand loyalty level, and operation ability level, obtain the corresponding evaluation level of the franchisee owner.

[0082] It should be noted that the wealth attribute levels are divided into low - level wealth attributes, medium - level wealth attributes, and high - level wealth attributes, which are set according to the range of amounts. For example, the amount range is set into three intervals: within 10,000, greater than 10,000 and less than or equal to 50,000, and greater than 50,000. Among them, the low - level wealth attribute corresponds to within 10,000, the medium - level wealth attribute corresponds to greater than 10,000 and less than or equal to 50,000, and the high - level wealth attribute corresponds to greater than 50,000; the preset profit range is divided into three intervals, such as within 70%, greater than 70% and less than or equal to 90%, and greater than 90%. Among them, within 70% corresponds to low operating ability, greater than 70% and less than or equal to 90% corresponds to medium operating ability, and greater than 90% corresponds to high profit level; the brand loyalty level is determined according to the set scores. The more the number of stores opened and the longer the store - opening years, the higher the corresponding score. For example, opening 1 store corresponds to 1 point, opening 2 stores corresponds to 2 points, opening 3 or more stores corresponds to 3 points, opening within 1 year corresponds to 1 point, opening for 2 to 3 years corresponds to 2 points, and opening for more than 3 years corresponds to 3 points. Add up all the scores, and then determine the brand loyalty level according to the score range where the score falls. The brand loyalty level is divided into low loyalty, medium loyalty, and high loyalty. For example, the score range corresponding to low loyalty is within 1 point, the score range of medium loyalty is within 2 to 3 points, and the score range of high loyalty is 4 points and above; when all three of the financial attribute level, brand loyalty level, and operating ability level are low, or two are medium and one is low, or two are low and one is medium, the corresponding franchisee is judged as a low - level. When all three of the financial attribute level, brand loyalty level, and operating ability level are medium, or two are medium and one is high, or two are high and one is low, or one is high and two are medium, the corresponding franchisee is judged as a medium - level. When all three of the financial attribute level, brand loyalty level, and operating ability level are high, or two are high and one is medium, the corresponding franchisee is judged as a high - level.

[0083] According to an embodiment of the present invention, the customer feedback module is further configured to:

[0084] Extract keywords from the evaluation information of the client and classify the keywords to obtain positive keywords and negative keywords of the same store;

[0085] Extract the numerical value of the number of positive keywords and the numerical value of the number of negative keywords of the same store;

[0086] Subtract the numerical value of the number of negative keywords from the numerical value of the number of positive keywords to obtain a first quantity difference;

[0087] Add the numerical value of the number of positive keywords and the numerical value of the number of negative keywords to obtain a total quantity value;

[0088] According to the first quantity difference divided by the total quantity value, obtain an emotional polarity value;

[0089] When the emotional polarity value is less than or equal to a preset first threshold, the corresponding store negative warning information is triggered.

[0090] It should be noted that the positive keywords are positive review keywords, and the negative keywords are negative review keywords.

[0091] Further, when the emotional polarity value is greater than the preset first threshold and less than the preset second threshold, the assignment of work orders is adjusted according to the emotional acute value, and the adjusted formula is where Q j represents the emotional polarity value of the corresponding store j, and k4 represents the weight conversion coefficient of the corresponding emotional polarity value.

[0092] According to an embodiment of the present invention, the heart selection system includes: a cooperation mode unit and a product optimization unit;

[0093] The cooperation mode unit is used for the franchisee to select the cooperation mode, and the cooperation mode includes a standard mode, a bidding mode, and an agent mode;

[0094] The product optimization unit is used to calculate the comprehensive score value S of the target product, and its formula is S i = w1 * S i―1 + w2 * S i―2 + w3 * S i―3 ; where S i represents the comprehensive score value of the target product i, w1, w2, and w3 respectively represent the corresponding weight coefficients, and S i―1 、S i―2 and S i―3 respectively represent the standardized sales volume score value, gross profit margin score value, and trend score value of the target product i. When the comprehensive score value of the target product is less than the preset score threshold, the corresponding target product is excluded.

[0095] It should be noted that the standardized sales volume score value is the actual sales volume of the corresponding target product i divided by the highest sales volume of the same category, the gross profit margin score value is the actual gross profit of the corresponding target product i divided by the target gross profit, and the trend score value is the actual sales volume of this period minus the actual sales volume of the previous period, and the obtained difference is divided by the actual sales volume value of the previous period.

[0096] According to an embodiment of the present invention, the new store system is used to evaluate the store location selected by the franchisee to obtain a location evaluation score. When the location evaluation score is lower than the preset score threshold, a location warning information is triggered.

[0097] It should be noted that the location evaluation score is set as F, and its formula is where n represents the set of numbers of the normalized values of positive indicators, m represents the set of numbers of the normalized values of negative indicators, a x The weight of the x-th positive indicator, b y The weight of the y-th negative indicator, A x Represents the normalized value of the positive indicator, such as the score of the pedestrian flow in the business district, B y Represents the normalized value of the negative indicator, such as the score of the rental cost.

[0098] According to an embodiment of the present invention, the ERP system includes: an inventory warning unit and an intelligent replenishment unit;

[0099] The inventory warning unit is used to obtain the quantity of goods in stock of a store in real time, trigger the inventory warning information of the goods based on a preset inventory quantity threshold, and send the inventory warning information to the franchisee main terminal of the store for prompting;

[0100] The intelligent replenishment unit is used to calculate the quantity of goods to be replenished for the corresponding store and send the quantity of goods to be replenished to the franchisee main terminal of the store for prompting.

[0101] According to an embodiment of the present invention, the step of calculating the quantity of goods to be replenished for the corresponding store specifically includes:

[0102] Obtain the sales volume of the corresponding goods within a preset time period and the maximum storage capacity of the corresponding goods in the store;

[0103] Perform an average calculation on the sales volume of the corresponding goods within a preset time period to obtain the daily average sales volume of the corresponding goods;

[0104] Subtract the inventory quantity threshold from the maximum storage capacity of the corresponding goods in the store to obtain the maximum replenishment quantity of the corresponding goods;

[0105] Set the quantity of goods to be replenished for the store as R, and set the yield rate of the corresponding replenished goods as D. The formula is And the quantity of goods to be replenished R for the store is less than or equal to the maximum replenishment quantity of the corresponding goods. f1 represents the profit value of selling a single corresponding replenished good, f2 represents the purchase unit price of the corresponding goods, G represents the cost of a single purchase of the corresponding goods, T represents the total time for which the corresponding quantity of goods to be replenished R is expected to be sold, t ∈ T, and w4 represents the inventory cost coefficient of the replenished goods in the corresponding store. Represents the daily average sales volume of the replenished goods;

[0106] Based on the fact that the quantity of goods to be replenished R for the store is less than or equal to the maximum replenishment quantity of the corresponding goods, take any replenishment quantity R and substitute it into the yield rate formula of the corresponding goods to obtain a set of yield rates;

[0107] Extract the maximum yield rate from the set of yield rates and set the quantity of goods to be replenished corresponding to the maximum yield rate as the quantity of goods to be replenished for the current store.

[0108] It should be noted that, for example, if the preset time period is 30 days, then taking the current time as the reference point, the sales volume of the corresponding commodity within the previous 30 days is extracted. The maximum storage quantity of the commodity in the corresponding store is in a proportional relationship with the set storage repository size, and the set storage repository for each commodity is in a proportional relationship with the profit margin of the corresponding commodity.

[0109] Furthermore, obtain the working capital of the current franchisee. When only one commodity needs to be replenished, subtract the cost of the corresponding commodity for a single purchase from the corresponding working capital to obtain the remaining working capital, and then divide the remaining working capital by the unit price of the corresponding replenishment commodity to obtain the maximum replenishment quantity of the corresponding commodity. When the replenishment quantity R is greater than the maximum replenishment quantity of the corresponding commodity, delete the corresponding replenishment quantity R and the maximum rate of return in the rate of return set, and re-extract the replenishment quantity corresponding to the maximum rate of return in the earnings set for replacement.

[0110] Furthermore, when there are multiple commodities that need to be replenished, extract the maximum rate of return corresponding to the multiple commodities, and determine the distribution weight coefficient of the current working capital according to the maximum rate of return corresponding to the multiple commodities. The formula is where μ i represents the distribution weight coefficient of commodity i, D i―max represents the maximum rate of return of commodity i. When it comes to the replenishment quantity corresponding to the maximum rate of return, N represents the set of all types of commodities that currently need to be replenished. Multiply the distribution weight coefficient of the commodity by the working capital of the current franchisee to obtain the working capital corresponding to the commodity.

[0111] Furthermore, when there is surplus working capital for some commodities and shortage of working capital for some commodities, extract the surplus working capital, and extract the distribution weight coefficient of the commodity with the shortage of working capital, and re-confirm the secondary distribution weight coefficient according to the distribution weight coefficient of the commodity with the shortage of working capital. The formula is where μ ′ λ represents the secondary distribution weight coefficient of commodity λ, μ λ represents the distribution weight coefficient of commodity λ with the shortage of working capital, and M represents the set of distribution weight coefficients of the commodities with the shortage of working capital; redistribute the surplus working capital according to the secondary distribution weight coefficient until all the working capital is distributed or there is surplus working capital.

[0112] According to the embodiments of the present invention, the BI system includes: a dynamic index configuration unit and a prediction analysis and warning unit;

[0113] The dynamic index configuration unit is used to dynamically adjust commodity indexes;

[0114] The prediction analysis and warning unit is used to predict the sales volume of products, obtain the prediction results, and make a judgment based on a preset sales volume threshold to trigger a sales volume warning message.

[0115] It should be noted that the dynamic index configuration unit is used to set the indexes of various products in the store, such as product inventory indexes, expected product sales volume indexes, etc. The preset sales volume threshold is the expected product sales volume index.

[0116] A data management system for franchise owners disclosed by the present invention includes: a unified master file management module, a customer feedback module, a service center module, and a master file center module; the unified master file management module is used for classified storage of franchise owner data; the customer feedback module is used for collecting evaluation information of the store from the client side and supervising the store and the franchise owner to which the store belongs according to the evaluation information; the service center module is used for collecting order data information of the client side, generating a work order according to the order data information of the client side, and matching the work order with the store of the franchise owner to generate an order; the master file center module includes a preferred system, a new store system, an ERP system, and a BI system. By storing franchise owner information with multiple tags and analyzing the stores and store products of the franchise owner from multiple aspects, the present invention provides precise guidance for the store operation of the franchise owner, thereby reducing the store operation risk of the franchise owner.

[0117] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed with each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be electrical, mechanical, or other forms.

[0118] The units described as separate components above may or may not be physically separated. The components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in the embodiments of the present invention may be entirely integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the above-mentioned integrated unit may be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0120] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes: removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs and other various media that can store program codes.

[0121] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. And the foregoing storage medium includes: removable storage devices, ROM, RAM, magnetic disks, or optical discs and other various media that can store program codes.

Claims

1. A data management system for franchise owners, characterized in that, Including; a unified master file management module, a customer feedback module, a service center module, and a master file center module; The unified master file management module is used to collect franchisee master data, preprocess the collected franchisee master data to obtain standardized and formatted franchisee master data, and then classify and store the standardized and formatted franchisee master data; The customer feedback module is used to collect evaluation information of the store from the client side and supervise the store and the franchisee master to which the store belongs according to the evaluation information; The service center module is used to collect order data information from the client side, generate a work order according to the order data information of the client side, and then match the work order with the store of the franchisee master to generate an order; The master file center module includes a selected products system, a new store system, an ERP system, and a BI system; The selected products system is used for the franchisee master to select a cooperation mode and optimize the products selected by the franchisee master; The new store system is used to evaluate the store location selected by the franchisee master; The ERP system is used for intelligent inventory monitoring and replenishment reminder of the store products of the franchisee master; The BI system is used to dynamically adjust the indicators of the store products of the franchisee master and predict the sales volume of the products.

2. The data management system for franchise owners according to claim 1, characterized in that, The unified master file management module includes a master file statistics unit, a store opening area unit, a store opening number unit, a franchisee level unit, a service team unit, an identity label unit, an operation portrait unit, and a franchisee master data collection unit; The master file statistics unit is used to count the total number of stores operated by the franchisee master; The store opening area unit is used to record the location area of each store and display the total number of stores in the current area on a preset map area; The store opening number unit classifies the franchisee master according to the store opening quantity value for quick query; The franchisee level unit is used to divide the levels of the franchisee master and provide franchisee level query; The service team unit is used for the franchisee master to select the corresponding service team; The identity label unit identifies the franchisee master and sets labels for the information query of the franchisee master; The operation portrait unit is used to construct the operation portrait of each store; The franchisee master data collection unit is used to collect franchisee master data.

3. The data management system for franchise owners according to claim 2, characterized in that, The steps of dividing the levels of the franchisee master specifically include: Obtain the monthly average net profit of the store of the franchisee master within a preset period; Based on the range of the monthly average net profit of the store falling within a preset period, obtain the corresponding wealth attribute level; When the monthly average net profit of the store within a preset period is greater than zero, the current store is a profitable store, and record the value of the profitable store; Divide the value of the profitable store by the total number of franchise stores of the corresponding franchisee master to obtain the profit rate; Based on the preset profit range into which the profit rate falls, determine the corresponding operation ability level; Obtain the store opening quantity of the franchisee master and the store opening years of the store; According to the store opening quantity of the franchisee master and the store opening years of the store, obtain the brand loyalty level; According to the financial attribute level, the brand loyalty level, and the operation ability level, obtain the corresponding evaluation level of the franchisee master.

4. A data management system for franchise owners according to claim 1, characterized in that, The customer feedback module is also used for: Extract keywords from the evaluation information of the client, and classify the keywords to obtain positive keywords and negative keywords for the same store; Extract the numerical values of the positive keywords and the numerical values of the negative keywords for the same store; Subtract the numerical value of the negative keywords from the numerical value of the positive keywords to obtain the first quantity difference; Add the numerical value of the positive keywords and the numerical value of the negative keywords to obtain the total numerical value; Divide the first quantity difference by the total numerical value to obtain the sentiment polarity value; When the sentiment polarity value is less than or equal to a preset first threshold, trigger a negative warning message for the corresponding store.

5. A data management system for franchise owners according to claim 1, characterized in that, The selected system includes: a cooperation mode unit and a product optimization unit; The cooperation mode unit is used for the franchisee to select the cooperation mode, and the cooperation mode includes a standard mode, a bidding mode, and an agent mode; The target product optimization unit is used to calculate the comprehensive score value S of the target product, and its formula is S i = w1 * S i―1 + w2 * S i―2 + w3 * S i―3 ; where S i represents the comprehensive score value of the target product i, w1, w2, and w3 respectively represent the corresponding weight coefficients, S i―1 , S i―2 , and S i―3 respectively represent the standardized sales volume score value, gross profit margin score value, and trend score value of the target product i. When the comprehensive score value of the target product is less than the preset score threshold, the corresponding target product will be excluded.

6. The data management system for franchise owners according to claim 1, characterized in that The new store system is used to evaluate the store location selected by the franchisee to obtain a location evaluation score. When the location evaluation score is lower than a preset score threshold, trigger a location warning message.

7. A data management system for franchise owners according to claim 1, characterized in that, The ERP system includes: an inventory warning unit and an intelligent replenishment unit; The inventory warning unit is used to obtain the inventory quantity of the products in the store in real time, trigger the inventory warning message of the product based on a preset inventory quantity threshold, and send the inventory warning message to the main terminal of the franchisee of the store for reminder; The intelligent replenishment unit is used to calculate the product replenishment quantity of the corresponding store and send the product replenishment quantity to the main terminal of the franchisee of the store for reminder.

8. A data management system for franchise owners according to claim 7, characterized in that The step of calculating the product replenishment quantity of the corresponding store specifically includes: Obtain the sales volume of the corresponding product within a preset time period and the maximum storage volume of the product in the corresponding store; Perform an average calculation on the sales volume of the corresponding product within a preset time period to obtain the daily average sales volume of the corresponding product; Subtract the inventory quantity threshold from the maximum storage volume of the product in the corresponding store to obtain the maximum replenishment quantity of the corresponding product; Set the replenishment quantity of the products in the corresponding store as R, and set the yield rate of the replenished products as D. The formula is as follows And the replenishment quantity R of the products in the store is less than or equal to the maximum replenishment quantity of the corresponding products. f1 represents the profit value of selling a single replenished product, f2 represents the purchase unit price of the corresponding products, G represents the cost of purchasing the corresponding products once, T represents the total time expected for the sale of the replenishment quantity R of the corresponding products, t ∈ T, and w4 represents the inventory cost coefficient of the replenished products in the corresponding store represents the average daily sales volume of the replenished products Based on the product replenishment quantity R of the store being less than or equal to the maximum replenishment quantity of the corresponding product, take any replenishment quantity R and substitute it into the yield formula of the corresponding product to obtain a yield set; Extract the maximum yield from the yield set and set the product replenishment quantity corresponding to the maximum yield as the product replenishment quantity of the current store.

9. A data management system for franchise owners according to claim 1, characterized in that, The BI system includes: a dynamic index configuration unit and a prediction analysis and warning unit; The dynamic index configuration unit is used to dynamically adjust product indexes; The prediction analysis and warning unit is used to predict the sales volume of the product to obtain a prediction result, and make a determination based on a preset sales volume threshold to trigger a sales volume warning message.

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