Digital catering intelligent management system

Abstract

The invention relates to the technical field of catering management, in particular to a digital catering intelligent management system, which is used for solving the problems in the prior art that sales data and customer behaviors cannot be analyzed in detail, product performance cannot be accurately evaluated, accurate customer portraits cannot be constructed, decision support driven by data cannot be provided, and the customer performance cannot be accurately evaluated. And a merchant cannot be helped to optimize operation and improve customer experience. Through the data analysis module, the sales trend is tracked in real time, the product performance is evaluated, hot dishes are identified, the promotion activity effect is optimized, an accurate customer portrait is constructed, personalized marketing, customer loyalty analysis, lost customer identification and feedback collection are realized to improve customer satisfaction, and data-driven decision support is provided; therefore, merchants are helped to optimize operation and improve customer experience.

Description

Technical Field

[0001] The present invention relates to the technical field of catering management, and more specifically, to a digital catering intelligent management system. Background Art

[0002] With the rapid development of the catering industry, the traditional catering industry is gradually entering the era of smart catering. The era of smart catering is to use Internet technology, products and data capabilities to help traditional businesses innovate new business methods, transforming traditional paper menu ordering into online menu ordering, transforming manual checkout into terminal checkout, transforming offline marketing into online event marketing, etc. This series of changes have brought tremendous changes and impacts to the traditional catering industry, enabling it to adapt to the development of the times.

[0003] The patent application with reference publication number CN115619487A discloses an intelligent catering management system, including a management end, a cashier end and a data middle platform, the cashier end and the management end are connected to the data middle platform through the Internet for data communication, the management end and the cashier end are used to aggregate the merchant order management data and cashier data within a preset area; in the data middle platform, the data acquisition module is used to acquire the order management data of the management end and the cashier data of the cashier end, generate summary data, and store it in the database module; the data processing module is used to perform data preprocessing on the summary data and generate preprocessing results; the data analysis module is used to generate report data by preprocessing the results according to preset category information; the data modeling module is used to perform digital modeling according to the report data; the present invention can solve the problem that the existing management technology has barriers to data circulation between industries, resulting in reduced data authenticity;

[0004] However, existing technologies cannot automatically schedule production according to orders, which reduces the efficiency of order processing, cannot monitor raw material inventory in real time and promptly warn of low inventory items, cannot automatically generate procurement plans based on sales data and inventory status, which reduces procurement efficiency, cannot provide detailed analysis reports on inventory turnover rate and out-of-stock rate, and cannot help merchants optimize inventory management; at the same time, they cannot perform detailed analysis of sales data and customer behavior, cannot accurately evaluate product performance, cannot build accurate customer portraits, cannot provide data-driven decision support, and cannot help merchants optimize operations and improve customer experience.

[0005] To this end, we propose a digital catering intelligent management system to address the above issues. Summary of the invention

[0006] The purpose of the present invention is to provide a digital catering intelligent management system, which solves the problems that the prior art cannot automatically schedule production according to orders, reduces the order processing efficiency, cannot monitor the raw material inventory in real time and timely warn of low inventory goods, cannot automatically generate procurement plans according to sales data and inventory status, reduces procurement efficiency, cannot provide detailed analysis reports on inventory turnover rate and out-of-stock rate, and cannot help merchants optimize inventory management; at the same time, it cannot perform detailed analysis of sales data and customer behavior, cannot accurately evaluate product performance, cannot build accurate customer portraits, cannot provide data-driven decision support, and cannot help merchants optimize operations and improve customer experience.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A digital catering intelligent management system, including a management platform, a front desk ordering module, a back kitchen management module, an inventory management module, a member management module and a data analysis module;

[0009] The front desk ordering module is used to support customers to quickly browse the menu and place orders through the touch screen, APP or mini program. The system intelligently recommends dishes based on the customer's history and preferences. It also supports multiple payment methods such as WeChat Pay, Alipay and bank cards to achieve fast payment and order confirmation.

[0010] The back kitchen management module is used to synchronize front-end orders to the back kitchen in real time. The system automatically schedules the production process according to the order content and priority, monitors the inventory of raw materials in real time, and warns of low inventory products;

[0011] The inventory management module automatically generates a purchase plan based on historical sales data and inventory status, realizes the scanning of raw materials and goods in and out of the warehouse, and provides analysis reports on inventory turnover rate and out-of-stock rate;

[0012] The member management module is used to support customers to self-register as members, enjoy member-exclusive discounts and services, and automatically accumulate consumption points, which can be used to redeem dishes and coupons. Based on the consumption behavior and preferences of members, personalized marketing information is pushed;

[0013] The data analysis module is used to analyze sales data and customer behavior, track sales trends, evaluate product performance and promotion effects, build customer portraits, and evaluate customer loyalty and satisfaction.

[0014] As a preferred embodiment of the present invention, the specific process of ordering food through the front desk ordering module is as follows:

[0015] Menu browsing: Customers enter the ordering interface through the touch screen, APP or mini program, and the system displays a classified menu. Each dish is accompanied by a picture, name, price and a brief description to help customers make choices. Customers can also use the search box to quickly find specific dishes, and the system displays matching results in real time;

[0016] Intelligent recommendation: The system analyzes the customer's historical order data and preferences to generate a personalized recommendation list. On the menu page or in a dedicated recommendation area, the system displays intelligently recommended dishes, and customers can add them to the shopping cart with one click.

[0017] Place an order: The customer clicks on the desired dish and enters the detail page to view more detailed information. The customer can select the quantity and flavor options. After the customer confirms the selection, click the "Add to Cart" button, and the system updates the shopping cart content. The customer can view the shopping cart at any time, modify the quantity or delete unnecessary dishes;

[0018] Payment method selection: Customers confirm the order content on the shopping cart page, including dishes, quantity and total price. The system provides multiple payment options such as WeChat Pay, Alipay and bank card. After the customer selects the payment method, the system guides the customer to the payment interface;

[0019] Quick payment: Customers enter the necessary payment information according to the selected payment method, and the system processes the transaction through a secure payment interface. After the payment is completed, the system instantly receives the payment result and generates order confirmation information;

[0020] Order confirmation: Customers receive order confirmation information, including order number, dish details, total amount and estimated delivery time. Customers can check the order status in the APP or mini program.

[0021] As a preferred embodiment of the present invention, the specific process of the back kitchen management module processing the front desk order is as follows:

[0022] The system receives front-end order information in real time through the message queue. The order information includes order number, timestamp, dish name, quantity and priority;

[0023] Convert the received order data into a processable format and sort the orders according to priority using the sorting formula:

[0024]

[0025] Among them, w e For each dish, the priority weight, p e is the number of dishes, n is the total number of dishes in the order;

[0026] Define the required quantity of raw materials for each dish. If a dish requires R j , then it is expressed as:

[0027]

[0028] Among them, r jk is the demand for the kth raw material corresponding to dish j, q k is the number of dishes k, and m is the total number of dishes;

[0029] Check the inventory status of each raw material to ensure the current inventory S j Satisfy the needs j :

[0030] S j ≥R j；

[0031] Once it is confirmed that all raw materials are in sufficient stock, the system starts to produce dishes in sequence. The production of each dish can be expressed as:

[0032] P j =r j1 ×t1+r j2 ×t2+…+r jm ×t m ;

[0033] Among them, P j is the total production time of dish j, r jk is the amount of raw material required, t k is the processing time for each raw material.

[0034] As a preferred implementation of the present invention, the specific process of early warning for low inventory goods is as follows:

[0035] Set a low inventory threshold T for each raw material j , real-time inventory tracking j , if the inventory is below the threshold, trigger a warning: If S j <T j , triggering a low inventory warning;

[0036] Once production is completed, update the order status to "Completed" and record the specific time of production and any abnormalities;

[0037] After all production and inventory adjustments are completed, the system should be analyzed for performance, including:

[0038]

[0039] Generate comprehensive reports regularly, including inventory status, production efficiency and low-stock goods information.

[0040] As a preferred implementation of the present invention, the specific steps of managing inventory goods by the inventory management module are as follows:

[0041] The system first collects and organizes sales data over a period of time, including sales volume, sales amount and sales trend, and then obtains the current inventory status in real time, including the inventory quantity, type and storage location of raw materials and commodities;

[0042] Using historical sales data, combined with market trends and seasonal changes, machine learning algorithms are used to predict sales demand in the future. Based on the current inventory situation and predicted sales demand, it is assessed whether the inventory can meet future sales demand and whether there is a risk of out-of-stock or overstocking.

[0043] Based on the sales forecast and inventory assessment results, the system calculates the quantity of raw materials and goods that need to be purchased. The calculation formula is as follows:

[0044] Purchase quantity = forecast sales + safety stock - current inventory;

[0045] Among them, safety stock is the additional inventory set up to deal with uncertain factors;

[0046] Based on the calculation results, the system automatically generates a detailed purchase plan, which includes the purchased items, quantity, supplier and estimated arrival time;

[0047] Enter the warehousing management unit, use a barcode scanner or mobile phone APP to scan the barcode or QR code of the raw materials or goods, the system automatically recognizes and enters the goods information, after verifying that the scanned information is correct, click "Save" or "Submit" to complete the update of the warehousing record;

[0048] Enter the outbound management unit, scan the barcode or QR code of the goods to be shipped, the system will automatically check the inventory and reduce the quantity. After confirming that the outbound information is correct, click "Save" or "Submit" to complete the update of the outbound record.

[0049] As a preferred embodiment of the present invention, the specific process of the inventory management module evaluating inventory supply and demand and warning of shortage and surplus is as follows:

[0050] Before starting the assessment, prepare the following necessary data:

[0051] Current stock: marked as I c , represents the current available inventory;

[0052] Forecast sales demand: marked as D f , represents the predicted sales volume in the future period;

[0053] Safety stock: marked as S, additional inventory set aside to cope with demand fluctuations and supply uncertainties;

[0054] Past sales data: historical data used to estimate future demand changes;

[0055] The following formula is used to calculate the future inventory required:

[0056] Total demand = D f +S;

[0057] Compare the current inventory and total demand and use the following formula to evaluate:

[0058] If the current inventory is insufficient to meet future sales demand, there is a risk of out-of-stock:

[0059]

[0060] Calculate whether there is excess inventory, and define excess inventory as current inventory minus demand plus safety stock:

[0061]

[0062] Based on the above calculated out-of-stock and excess inventory, the following evaluation conclusions are drawn:

[0063] Out of stock risk: When I c <D f +S means insufficient inventory;

[0064] Excess risk: When I c >D f +S means excess inventory.

[0065] As a preferred implementation of the present invention, the specific process of calculating the inventory turnover rate and the out-of-stock rate is as follows:

[0066] The system automatically calculates the inventory turnover rate based on historical sales data and inventory data, and generates an inventory turnover rate analysis report. The inventory turnover rate calculation formula is as follows:

[0067]

[0068] Among them, cost of sales refers to the total cost of goods sold in a certain period, and average inventory cost refers to the average of the inventory at the beginning of the period and the inventory at the end of the period;

[0069] The system records and analyzes out-of-stock situations, automatically calculates the out-of-stock rate, and generates an out-of-stock rate analysis report. The out-of-stock rate calculation formula is as follows:

[0070]

[0071] As a preferred implementation of the present invention, the specific steps of the member management module for managing members are as follows:

[0072] Customers can register by themselves through various channels, fill in basic information, and the system will generate a unique member account. Customers can choose to set a password or bind a third-party login;

[0073] The system divides members into different levels according to the amount or number of times the customer spends, and provides corresponding exclusive discounts and benefits for different levels. Members can enjoy specific discounts, free shipping and priority activity services when consuming. The system automatically matches the corresponding discounts when the customer places an order;

[0074] After each purchase, the system will accumulate corresponding points according to the amount of consumption. The points rules can be flexibly configured, including double points on birthdays and doubling points for specific products during events. The points accumulation status can be viewed in real time in the member center.

[0075] Members can choose the goods or coupons they want to redeem in the Points Mall. The system will check whether the member has enough points. If so, the corresponding points will be deducted and the redemption will be completed. After successful redemption, the coupon will be issued to the member's account and can be used when making purchases.

[0076] The system collects and analyzes members' consumption data to generate customer behavior and preference models. Based on the analysis results, the system pushes personalized marketing information, which can be pushed in a variety of ways.

[0077] Member benefits include birthday privileges, exclusive customer service and priority event participation. The system provides members with corresponding benefits based on their membership level. Members can view all available benefits in the member center and automatically apply the corresponding benefits when making purchases.

[0078] As a preferred implementation of the present invention, the specific process of the data analysis module analyzing the sales data is as follows:

[0079] The system collects daily sales data from POS machines and online shopping channels. The sales data includes sales volume, sales quantity, product category and customer information. It compares sales changes in different time periods, observes seasonal trends, monthly or annual growth rates, and the sales trend calculation formula is as follows:

[0080]

[0081] Draw a time series graph to observe sales peaks and valleys and discover potential influencing factors;

[0082] The sales contribution rate is calculated as follows:

[0083]

[0084] The sales contribution rate calculation formula is used to evaluate the contribution of a product to the overall sales. Based on the sales data, the products are sorted by sales volume to find out the best-selling and slow-selling products;

[0085] The formula for calculating promotion conversion rate is as follows:

[0086]

[0087] Evaluate the effectiveness of promotions by comparing sales and conversion rates before and after promotions;

[0088] The formula for calculating the promotion lift rate is as follows:

[0089]

[0090] Use tools to generate visual reports to display sales trends and product performance, and generate sales data analysis reports regularly.

[0091] As a preferred embodiment of the present invention, the specific process of the data analysis module analyzing customer behavior is as follows:

[0092] Collect the basic information of customers, consumption frequency, consumption categories, preferred products and average customer unit price, use K-means clustering algorithm to group customers according to different characteristics, and use RFM model to evaluate customer value:

[0093] RFM=W R ·R+W F ·F+W M M;

[0094] Where R is the time interval of the most recent consumption, F is the consumption frequency, M is the consumption amount, and W is the consumption amount. R , W F , W M is the weight;

[0095] Build customer profiles based on customer behavior data, including age group, preferred product type, and consumption habits;

[0096] The customer loyalty and satisfaction evaluation formula is as follows:

[0097]

[0098] The customer satisfaction score is obtained through the customer questionnaire, and the net recommendation value (NPS) is calculated by the following formula:

[0099]

[0100] Based on customers' ratings of brands, they are divided into promoters, neutrals and critics to assess customer satisfaction and brand influence;

[0101] Use tools to generate visual reports to display customer behavior and generate customer behavior analysis reports regularly.

[0102] Compared with the prior art, the advantages of the present invention are:

[0103] (1) In the present invention, the back kitchen management module can synchronize orders in real time, improve response speed, automatically schedule production, improve work efficiency, monitor raw material inventory in real time to ensure sufficient stock, and promptly warn of low inventory products to prevent out-of-stock situations and ensure that orders are completed normally;

[0104] (2) In the present invention, the inventory management module can automatically generate a procurement plan to ensure that raw materials are sufficient, realize the scanning of raw materials and goods in and out of the warehouse, improve the efficiency of in and out of the warehouse and reduce human errors, provide detailed analysis reports on inventory turnover rate and out-of-stock rate, help merchants optimize inventory management, reduce expiration and waste through accurate inventory management, and improve overall profitability;

[0105] (3) In the present invention, the data analysis module is used to track sales trends in real time, evaluate product performance, identify popular dishes, optimize the effectiveness of promotional activities, build accurate customer portraits, achieve personalized marketing, analyze customer loyalty, identify lost customers, collect feedback to improve customer satisfaction, and provide data-driven decision support, thereby helping merchants optimize operations and improve customer experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0106] Figure 1 is a system block diagram of the present invention;

[0107] Figure 2 This is a system block diagram of Embodiment 1 of the present invention;

[0108] Figure 3 It is a logical flow diagram of the present invention. DETAILED DESCRIPTION

[0109] The following will combine 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 the embodiments. All other embodiments obtained by ordinary technicians in this field without creative work based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0110] Embodiment 1: Figure 1 As shown, a digital catering intelligent management system proposed by the present invention includes a management platform, a front desk ordering module, a back kitchen management module, an inventory management module, a member management module and a data analysis module;

[0111] The management platform is connected to the member management module and the kitchen management module in a one-way communication manner. The management platform is connected to the data analysis module, the inventory management module and the front desk ordering module in a two-way communication manner. The kitchen management module is connected to the inventory management module in a one-way communication manner.

[0112] The back kitchen management module is used to synchronize the front desk order to the back kitchen in real time. The system automatically schedules the production process according to the order content and priority, monitors the raw material inventory in real time, and warns of low inventory products. The back kitchen management module can automatically schedule production according to orders, improve the order processing efficiency, monitor the raw material inventory in real time, and warn of low inventory products in time.

[0113] The specific process of the back kitchen management module processing the front desk order is as follows:

[0114] The system receives front-end order information in real time through the message queue. The order information includes order number, timestamp, dish name, quantity and priority;

[0115] Convert the received order data into a processable format and sort the orders according to priority using the sorting formula:

[0116]

[0117] Among them, w e For each dish, the priority weight, p e is the number of dishes, n is the total number of dishes in the order, and the higher the priority score, the earlier the order will be processed;

[0118] Define the required quantity of raw materials for each dish. If a dish requires R j , then it is expressed as:

[0119]

[0120] Among them, r jk is the demand for the kth raw material corresponding to dish j, q k is the number of dishes k, and m is the total number of dishes;

[0121] Check the inventory status of each raw material to ensure the current inventory S j Satisfy the needs j :

[0122] S j ≥R j；

[0123] Once it is confirmed that all raw materials are in sufficient stock, the system starts to produce dishes in sequence. The production of each dish can be expressed as:

[0124] Pj =r j1 ×t1+r j2 ×t2+…+r jm ×t m ;

[0125] Among them, P j is the total production time of dish j, r jk is the amount of raw material required, t k is the processing time for each raw material.

[0126] As a preferred implementation of the present invention, the specific process of early warning for low inventory goods is as follows:

[0127] Set a low inventory threshold T for each raw material j , real-time inventory tracking j , if the inventory is below the threshold, trigger a warning: If S j <T j , triggering a low inventory warning;

[0128] Once production is completed, update the order status to "Completed" and record the specific time of production and any abnormalities;

[0129] After all production and inventory adjustments are completed, the system should be analyzed for performance, including:

[0130]

[0131] Generate comprehensive reports regularly, including inventory status, production efficiency and low inventory goods information;

[0132] The inventory management module automatically generates purchase plans based on historical sales data and inventory status, realizes the scanning of raw materials and goods in and out of the warehouse, and provides analysis reports on inventory turnover rate and out-of-stock rate. The inventory management module can automatically generate purchase plans based on sales data and inventory status, improve procurement efficiency, and provide detailed analysis reports on inventory turnover rate and out-of-stock rate, thereby helping merchants optimize inventory management.

[0133] The specific steps for the inventory management module to manage inventory goods are as follows:

[0134] The system first collects and organizes sales data over a period of time, including sales volume, sales amount and sales trend, and then obtains the current inventory status in real time, including the inventory quantity, type and storage location of raw materials and commodities;

[0135] Using historical sales data, combined with market trends and seasonal changes, machine learning algorithms are used to predict sales demand in the future. Based on the current inventory situation and predicted sales demand, it is assessed whether the inventory can meet future sales demand and whether there is a risk of out-of-stock or overstocking.

[0136] Based on the sales forecast and inventory assessment results, the system calculates the quantity of raw materials and goods that need to be purchased. The calculation formula is as follows:

[0137] Purchase quantity = forecast sales + safety stock - current inventory;

[0138] Among them, safety stock is the additional inventory set up to cope with uncertainties (such as supplier delays and demand fluctuations);

[0139] Based on the calculation results, the system automatically generates a detailed purchase plan, which includes the purchased items, quantity, supplier and estimated arrival time;

[0140] Enter the warehousing management unit, use a barcode scanner or mobile phone APP to scan the barcode or QR code of the raw materials or goods, the system automatically recognizes and enters the goods information, after verifying that the scanned information is correct, click "Save" or "Submit" to complete the update of the warehousing record;

[0141] Enter the outbound management unit, scan the barcode or QR code of the goods to be outbound, the system will automatically check the inventory and reduce the quantity, after confirming that the outbound information is correct, click "Save" or "Submit" to complete the update of the outbound record;

[0142] The specific process of the inventory management module to evaluate inventory supply and demand and warn of shortages and surpluses is as follows:

[0143] Before starting the assessment, prepare the following necessary data:

[0144] Current stock: marked as I c , represents the current available inventory;

[0145] Forecast sales demand: marked as D f , represents the predicted sales volume in the future (e.g., the next month);

[0146] Safety stock: marked as S, additional inventory set aside to cope with demand fluctuations and supply uncertainties;

[0147] Past sales data: historical data used to estimate future demand changes;

[0148] The following formula is used to calculate the future inventory required:

[0149] Total demand = D f +S;

[0150] Compare the current inventory and total demand and use the following formula to evaluate:

[0151] If the current inventory is insufficient to meet future sales demand, there is a risk of out-of-stock:

[0152]

[0153] Calculate whether there is excess inventory, and define excess inventory as current inventory minus demand plus safety stock:

[0154]

[0155] Based on the above calculated out-of-stock and excess inventory, the following evaluation conclusions are drawn:

[0156] Out of stock risk: When I c <D f +S means insufficient inventory. When insufficient inventory is detected, the corresponding out-of-stock products will be replenished immediately.

[0157] Excess risk: When I c >D f +S means excess inventory. When excess inventory is detected, the excess goods will be processed immediately and given priority.

[0158] The specific process of calculating inventory turnover rate and out-of-stock rate is as follows:

[0159] The system automatically calculates the inventory turnover rate based on historical sales data and inventory data, and generates an inventory turnover rate analysis report. The inventory turnover rate calculation formula is as follows:

[0160]

[0161] Among them, cost of sales refers to the total cost of goods sold in a certain period, and average inventory cost refers to the average of the inventory at the beginning of the period and the inventory at the end of the period;

[0162] The system records and analyzes out-of-stock situations, automatically calculates the out-of-stock rate, and generates an out-of-stock rate analysis report. The out-of-stock rate calculation formula is as follows:

[0163]

[0164] The data analysis module is used to analyze sales data and customer behavior, track sales trends, evaluate product performance and promotion effects, build customer portraits, and evaluate customer loyalty and satisfaction. The data analysis module can conduct detailed analysis of sales data and customer behavior, accurately evaluate product performance, build accurate customer portraits, and provide data-driven decision support, thereby helping merchants optimize operations and improve customer experience.

[0165] The specific process of the data analysis module analyzing sales data is as follows:

[0166] The system collects daily sales data from POS machines and online shopping channels. The sales data includes sales volume, sales quantity, product category and customer information. It compares sales changes in different time periods, observes seasonal trends, monthly or annual growth rates, and the sales trend calculation formula is as follows:

[0167]

[0168] Draw time series graphs to observe sales peaks and valleys and identify potential influencing factors (such as holiday promotions);

[0169] The sales contribution rate is calculated as follows:

[0170]

[0171] The sales contribution rate calculation formula is used to evaluate the contribution of a product to the overall sales. Based on the sales data, the products are sorted by sales volume to find out the best-selling and slow-selling products;

[0172] The formula for calculating promotion conversion rate is as follows:

[0173]

[0174] Evaluate the effectiveness of promotions by comparing sales and conversion rates before and after promotions;

[0175] The formula for calculating the promotion lift rate is as follows:

[0176]

[0177] Use tools (such as Power BI, Tableau, etc.) to generate visual reports to display sales trends and product performance, and generate sales data analysis reports regularly;

[0178] According to the sales data analysis report, we can adjust the purchase quantity of raw materials, optimize the food preparation, and formulate a product marketing plan to increase profits while taking care of the customer's dining experience, so as to increase the restaurant's operating profit;

[0179] The specific process of the data analysis module to analyze customer behavior is as follows:

[0180] Collect the basic information of customers, consumption frequency, consumption categories, preferred products and average customer unit price, use K-means clustering algorithm to group customers according to different characteristics (such as consumption amount, consumption frequency, etc.), and use RFM model to evaluate customer value:

[0181] RFM=W R·R+W F ·F+W M M;

[0182] Where R is the time interval of the most recent consumption, F is the consumption frequency, M is the consumption amount, and W is the consumption amount. R , W F , W M is the weight;

[0183] Build customer profiles based on customer behavior data, including age group, preferred product type, and consumption habits;

[0184] The customer loyalty and satisfaction evaluation formula is as follows:

[0185]

[0186] The customer satisfaction score is obtained through the customer questionnaire, and the net recommendation value (NPS) is calculated by the following formula:

[0187]

[0188] Based on customers' ratings of brands, they are divided into promoters, neutrals and critics to assess customer satisfaction and brand influence;

[0189] Use tools (such as Power BI, Tableau, etc.) to generate visual reports to display customer behavior and regularly generate customer behavior analysis reports; based on the customer behavior analysis reports, formulate a series of business measures to cater to customers and improve their dining experience.

[0190] Embodiment 2: The technical solution of the embodiment of the present invention is different from that of embodiment 1 in that:

[0191] like Figure 2 As shown in the figure, the front desk ordering module is used to support customers to quickly browse the menu and place orders through the touch screen, APP or mini program. The system intelligently recommends dishes based on the customer's history and preferences. It also supports multiple payment methods such as WeChat Pay, Alipay and bank cards to achieve fast payment and order confirmation.

[0192] The specific process of ordering through the front-end ordering module is as follows:

[0193] Menu browsing: Customers enter the ordering interface through the touch screen, APP or mini program, and the system displays the classified menu (such as appetizers, main dishes, drinks, desserts, etc.). Each dish is accompanied by a picture, name, price and a brief description to help customers make choices. Customers can also use the search box to quickly find specific dishes, and the system displays matching results in real time;

[0194] Intelligent recommendation: The system analyzes the customer's historical order data and preferences (such as frequently ordered dishes, taste preferences, etc.) to generate a personalized recommendation list. On the menu page or in a dedicated recommendation area, the system displays intelligently recommended dishes, and customers can add them to the shopping cart with one click.

[0195] Ordering: Customers click on the desired dish and enter the detail page to view more detailed information (such as ingredients, allergens, etc.). Customers can select quantity and flavor (such as spiciness, doneness) options. After the customer confirms the selection, click the "Add to Cart" button, and the system updates the shopping cart content. Customers can view the shopping cart at any time, modify the quantity or delete unnecessary dishes;

[0196] Payment method selection: Customers confirm the order content on the shopping cart page, including dishes, quantity and total price. The system provides multiple payment options such as WeChat Pay, Alipay and bank card. After the customer selects the payment method, the system guides the customer to the payment interface;

[0197] Quick payment: Customers enter necessary payment information (such as password, verification code, etc.) according to the selected payment method. The system processes the transaction through a secure payment interface. After the payment is completed, the system instantly receives the payment result and generates order confirmation information.

[0198] Order confirmation: The customer receives order confirmation information, including the order number, dish details, total amount and estimated serving time. The customer can check the order status (such as "preparing", "served", etc.) in the APP or mini program;

[0199] The ordering module allows customers to quickly browse the menu and get smart recommendations, saving waiting time. It also supports WeChat payment, Alipay and bank cards for quick checkout. The automated process reduces dependence on waiters and reduces manual errors. The module also reduces contact between customers and waiters and improves safety.

[0200] The member management module is used to support customers to self-register as members, enjoy member-exclusive discounts and services, and automatically accumulate consumption points, which can be used to redeem dishes and coupons. Based on the consumption behavior and preferences of members, personalized marketing information is pushed;

[0201] The specific steps for member management module to manage members are as follows:

[0202] Customers can register through various channels (such as APP, mini-programs, websites, offline self-service devices, etc.), fill in basic information (such as name, mobile phone number, email, etc.), and the system will generate a unique member account. Customers can choose to set a password or bind a third-party login (such as WeChat, Alipay, etc.);

[0203] The system divides members into different levels (such as ordinary members, gold members, platinum members, etc.) according to the amount or number of customers' consumption, and provides corresponding exclusive discounts and benefits for different levels. Members can enjoy specific discounts, free shipping and priority activity services when consuming. The system automatically matches the corresponding discounts when customers place orders;

[0204] After each purchase, the system will accumulate corresponding points according to the amount of consumption (for example, 1 point for every 1 yuan spent). The points rules can be flexibly configured, including double points on birthdays and doubling points for specific products during events. The points accumulation status can be viewed in real time in the member center.

[0205] Members can choose the goods or coupons they want to redeem in the Points Mall. The system will check whether the member has enough points. If so, the corresponding points will be deducted and the redemption will be completed. After successful redemption, the coupon will be issued to the member's account and can be used when making purchases.

[0206] The system collects and analyzes members' consumption data (such as consumption frequency, consumption amount, preferred dishes, etc.) to generate customer behavior and preference models. Based on the analysis results, the system pushes personalized marketing information, which can be pushed in a variety of ways (such as SMS, APP notifications, emails, etc.);

[0207] Member benefits include birthday privileges, exclusive customer service and priority event participation. The system provides members with corresponding benefits based on their membership level. Members can view all available benefits in the member center and automatically apply the corresponding benefits when making purchases.

[0208] The member management module allows customers to easily register as members and improve their user experience. Members can enjoy exclusive discounts and enhance customer loyalty. Member consumption points can be accumulated and redeemed for dishes and coupons to encourage customers to consume. Customized marketing information is pushed based on member consumption behavior to increase customer consumption probability, provide value-added services, and improve customer satisfaction and stickiness.

[0209] Working principle of the present invention: When in use, in the present invention, the back-kitchen management module can synchronize orders in real time, improve response speed, automatically schedule production, improve work efficiency, monitor raw material inventory in real time, ensure sufficient preparation, and timely warn of low inventory goods to prevent out-of-stock situations, ensure that orders are completed normally, and automatically generate procurement plans through the inventory management module to ensure sufficient raw materials, realize the scanning of raw materials and goods in and out of the warehouse, improve the efficiency of in and out of the warehouse and reduce human errors, provide detailed analysis reports on inventory turnover rate and out-of-stock rate, help merchants optimize inventory management, reduce expiration and waste through precise inventory management, and improve overall profitability, as well as track sales trends in real time through the data analysis module, evaluate product performance, identify popular dishes, optimize the effectiveness of promotional activities, build accurate customer portraits, realize personalized marketing, analyze customer loyalty, identify lost customers, collect feedback to improve customer satisfaction, and provide data-driven decision support, thereby helping merchants optimize operations and improve customer experience.

[0210] The above are only preferred specific implementation modes of the present invention; however, the protection scope of the present invention is not limited thereto; any technician familiar with the technical field within the technical scope disclosed by the present invention; any equivalent replacement or change based on the technical solution and improved concept of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A digital catering intelligent management system, characterized in that: Including management platform, front desk ordering module, kitchen management module, inventory management module, membership management module and data analysis module; The front desk ordering module is used to support customers to quickly browse the menu and place orders through the touch screen, APP or mini program. The system intelligently recommends dishes based on the customer's history and preferences. It also supports multiple payment methods such as WeChat Pay, Alipay and bank cards to achieve fast payment and order confirmation. The back kitchen management module is used to synchronize front-end orders to the back kitchen in real time. The system automatically schedules the production process according to the order content and priority, monitors the inventory of raw materials in real time, and warns of low inventory products; The inventory management module automatically generates a purchase plan based on historical sales data and inventory status, realizes the scanning of raw materials and goods in and out of the warehouse, and provides analysis reports on inventory turnover rate and out-of-stock rate; The member management module is used to support customers to self-register as members, enjoy member-exclusive discounts and services, and automatically accumulate consumption points, which can be used to redeem dishes and coupons. Based on the consumption behavior and preferences of members, personalized marketing information is pushed; The data analysis module is used to analyze sales data and customer behavior, track sales trends, evaluate product performance and promotion effects, build customer portraits, and evaluate customer loyalty and satisfaction.

2. According to claim 1, a digital catering intelligent management system is characterized in that: The specific process of ordering through the front-end ordering module is as follows: Menu browsing: Customers enter the ordering interface through the touch screen, APP or mini program, and the system displays a classified menu. Each dish is accompanied by a picture, name, price and a brief description to help customers make choices. Customers can also use the search box to quickly find specific dishes, and the system displays matching results in real time; Intelligent recommendation: The system analyzes the customer's historical order data and preferences to generate a personalized recommendation list. On the menu page or in a dedicated recommendation area, the system displays intelligently recommended dishes, and customers can add them to the shopping cart with one click. Place an order: The customer clicks on the desired dish and enters the detail page to view more detailed information. The customer can select the quantity and flavor options. After the customer confirms the selection, click the "Add to Cart" button, and the system updates the shopping cart content. The customer can view the shopping cart at any time, modify the quantity or delete unnecessary dishes; Payment method selection: Customers confirm the order content on the shopping cart page, including dishes, quantity and total price. The system provides multiple payment options such as WeChat Pay, Alipay and bank card. After the customer selects the payment method, the system guides the customer to the payment interface; Quick payment: Customers enter the necessary payment information according to the selected payment method, and the system processes the transaction through a secure payment interface. After the payment is completed, the system instantly receives the payment result and generates order confirmation information; Order confirmation: Customers receive order confirmation information, including order number, dish details, total amount and estimated delivery time. Customers can check the order status in the APP or mini program.

3. According to claim 1, a digital catering intelligent management system is characterized in that: The specific process of the back kitchen management module processing the front desk order is as follows: The system receives front-end order information in real time through the message queue. The order information includes order number, timestamp, dish name, quantity and priority; Convert the received order data into a processable format and sort the orders according to priority using the sorting formula: Among them, w e For each dish, the priority weight, p e is the number of dishes, n is the total number of dishes in the order; Define the required quantity of raw materials for each dish. If a dish requires R j , then it is expressed as: Among them, r jk is the demand for the kth raw material corresponding to dish j, q k is the number of dishes k, and m is the total number of dishes; Check the inventory status of each raw material to ensure the current inventory S j Satisfy the needs j : S j ≥R j； Once it is confirmed that all raw materials are in sufficient stock, the system starts to produce dishes in sequence. The production of each dish can be expressed as: P j =r j1 ×t1+r j2 ×t2+…+r jm ×t m ; Among them, P j is the total production time of dish j, r jk is the amount of raw material required, t k is the processing time for each raw material.

4. A digital catering intelligent management system according to claim 3, characterized in that: The specific process of early warning for low inventory goods is as follows: Set a low inventory threshold T for each raw material j , real-time inventory tracking j , if the inventory is below the threshold, trigger a warning: If S j <T j , triggering a low inventory warning; Once production is completed, update the order status to "Completed" and record the specific time of production and any abnormalities; After all production and inventory adjustments are completed, the system should be analyzed for performance, including: Generate comprehensive reports regularly, including inventory status, production efficiency and low-stock goods information.

5. According to claim 1, a digital catering intelligent management system is characterized in that: The specific steps of managing inventory goods by the inventory management module are as follows: The system first collects and organizes sales data over a period of time, including sales volume, sales amount and sales trend, and then obtains the current inventory status in real time, including the inventory quantity, type and storage location of raw materials and commodities; Using historical sales data, combined with market trends and seasonal changes, machine learning algorithms are used to predict sales demand in the future. Based on the current inventory situation and predicted sales demand, it is assessed whether the inventory can meet future sales demand and whether there is a risk of out-of-stock or overstocking. Based on the sales forecast and inventory assessment results, the system calculates the quantity of raw materials and goods that need to be purchased. The calculation formula is as follows: Purchase quantity = forecast sales + safety stock - current inventory; Among them, safety stock is the additional inventory set up to deal with uncertain factors; Based on the calculation results, the system automatically generates a detailed purchase plan, which includes the purchased items, quantity, supplier and estimated arrival time; Enter the warehousing management unit, use a barcode scanner or mobile phone APP to scan the barcode or QR code of the raw materials or goods, the system automatically recognizes and enters the goods information, after verifying that the scanned information is correct, click "Save" or "Submit" to complete the update of the warehousing record; Enter the outbound management unit, scan the barcode or QR code of the goods to be shipped, the system will automatically check the inventory and reduce the quantity. After confirming that the outbound information is correct, click "Save" or "Submit" to complete the update of the outbound record.

6. A digital catering intelligent management system according to claim 5, characterized in that: The specific process of the inventory management module evaluating inventory supply and demand and warning of shortages and surpluses is as follows: Before starting the assessment, prepare the following necessary data: Current stock: marked as I c , represents the current available inventory; Forecast sales demand: marked as D f , represents the predicted sales volume in the future period; Safety stock: marked as S, additional inventory set aside to cope with demand fluctuations and supply uncertainties; Past sales data: historical data used to estimate future demand changes; The following formula is used to calculate the future inventory required: Total demand = D f +S; Compare the current inventory and total demand and use the following formula to evaluate: If the current inventory is insufficient to meet future sales demand, there is a risk of out-of-stock: Calculate whether there is excess inventory, defining excess inventory as current inventory minus demand plus safety stock: Based on the above calculated out-of-stock and excess inventory, the following evaluation conclusions are drawn: Out of stock risk: When I c <D f +S means insufficient inventory; Excess risk: When I c >D f +S means excess inventory.

7. A digital catering intelligent management system according to claim 6, characterized in that: The specific process of calculating inventory turnover rate and out-of-stock rate is as follows: The system automatically calculates the inventory turnover rate based on historical sales data and inventory data, and generates an inventory turnover rate analysis report. The inventory turnover rate calculation formula is as follows: Among them, cost of sales refers to the total cost of goods sold in a certain period, and average inventory cost refers to the average of the inventory at the beginning of the period and the inventory at the end of the period; The system records and analyzes out-of-stock situations, automatically calculates the out-of-stock rate, and generates an out-of-stock rate analysis report. The out-of-stock rate calculation formula is as follows:

8. According to claim 1, a digital catering intelligent management system is characterized in that: The specific steps of the member management module to manage members are as follows: Customers can register by themselves through various channels, fill in basic information, and the system will generate a unique member account. Customers can choose to set a password or bind a third-party login; The system divides members into different levels according to the amount or number of times the customer spends, and provides corresponding exclusive discounts and benefits for different levels. Members can enjoy specific discounts, free shipping and priority activity services when consuming. The system automatically matches the corresponding discounts when the customer places an order; After each purchase, the system will accumulate corresponding points according to the amount of consumption. The points rules can be flexibly configured, including double points on birthdays and doubling points for specific products during events. The points accumulation status can be viewed in real time in the member center. Members can choose the goods or coupons they want to redeem in the Points Mall. The system will check whether the member has enough points. If so, the corresponding points will be deducted and the redemption will be completed. After successful redemption, the coupon will be issued to the member's account and can be used when making purchases. The system collects and analyzes members' consumption data to generate customer behavior and preference models. Based on the analysis results, the system pushes personalized marketing information, which can be pushed in a variety of ways. Member benefits include birthday privileges, exclusive customer service and priority event participation. The system provides members with corresponding benefits based on their membership level. Members can view all available benefits in the member center and automatically apply the corresponding benefits when making purchases.

9. A digital catering intelligent management system according to claim 1, characterized in that: The specific process of the data analysis module analyzing the sales data is as follows: The system collects daily sales data from POS machines and online shopping channels. The sales data includes sales volume, sales quantity, product category and customer information. It compares sales changes in different time periods, observes seasonal trends, monthly or annual growth rates, and the sales trend calculation formula is as follows: Draw a time series graph to observe sales peaks and valleys and discover potential influencing factors; The sales contribution rate is calculated as follows: The sales contribution rate calculation formula is used to evaluate the contribution of a product to the overall sales. Based on the sales data, the products are sorted by sales volume to find out the best-selling and slow-selling products; The formula for calculating promotion conversion rate is as follows: Evaluate the effectiveness of promotions by comparing sales and conversion rates before and after promotions; The formula for calculating the promotion lift rate is as follows: Use tools to generate visual reports to display sales trends and product performance, and generate sales data analysis reports regularly.

10. A digital catering intelligent management system according to claim 9, characterized in that: The specific process of analyzing customer behavior by the data analysis module is as follows: Collect the basic information of customers, consumption frequency, consumption categories, preferred products and average customer unit price, use K-means clustering algorithm to group customers according to different characteristics, and use RFM model to evaluate customer value: RFM=W R ·R+W F ·F+W M ·M; Where R is the time interval of the most recent consumption, F is the consumption frequency, M is the consumption amount, and W is the consumption amount. R , W F , W M is the weight; Build customer profiles based on customer behavior data, including age group, preferred product type, and consumption habits; The customer loyalty and satisfaction evaluation formula is as follows: The customer satisfaction score is obtained through the customer questionnaire, and the net recommendation value (NPS) is calculated by the following formula: Based on customers' ratings of brands, they are divided into recommenders, neutrals and critics to assess customer satisfaction and brand influence; Use tools to generate visual reports to display customer behavior and generate customer behavior analysis reports regularly.

Images