KR20210075314A - customized menu recommending service system based on big data analysis - Google Patents

Abstract

Disclosed is technology relating to a customized menu recommendation service system based on bigdata analysis. The customized menu recommendation service system based on bigdata analysis includes a server system communicating with a customer terminal and a store terminal. The server system receives data from the customer terminal, and analyzes bigdata about a product purchase of a user of the customer terminal from the received data. The server system, when the customer visits a store in which the customer has previously made an order and payment, displays a menu product ordered by the customer in the store on the customer terminal, and displays whether the menu product ordered by the customer is in stock on the store terminal. In this case, if the menu product ordered by the customer is out of stock, the server system displays order disallowance information on the customer terminal or the store terminal, and displays another menu product different from the menu product ordered by the customer on the customer terminal or the store terminal.

Description

Customized menu recommending service system based on big data analysis

The technology disclosed herein generally relates to a recommended menu service system, and more specifically, to a customer-customized recommendation menu service system through big data analysis.

As a result of a preliminary survey through conversations with the representatives of the nationwide coffee chain headquarters (Mocambo, Coffee Myeongga) and franchise employees such as KFC, McDonald’s, and Lotteria, lunchtime (12 o’clock to 14:00) and work hours (18:00) ~ 20:00), there is a phenomenon that many customers' orders are rushing at the order payment counter during the peak hours, and the clerks are complaining that they have a lot of difficulties in preparing and ordering coffee, drinks, sandwiches, etc. ordered at the same time. There are times when they consider expanding the employment of part-time students, but they are complaining of difficulties due to the increase in the minimum wage.

When you train an employee who takes orders, 'They say that training to understand customers is quite difficult', 'Make the cafe latte less hot. For Iced Americano, add half ice. And if you say something like ‘Please give me two cheese buns’ in rapid-fire, people who are doing it for the first time often say that it will cause panic. And Ediya Members, a franchise coffee brand, is gaining popularity with a service that accumulates through the mobile app instead of the existing paper coupons, surpassing 700,000 cases within two months of its launch. When ordering, you can scan the barcode of the app to earn 1 stamp per cup. Various opinions are presented.

In addition, franchise companies such as KFC, McDonald's, and Lotteria are using the kiosk ordering method to solve this problem, but this method is also difficult to use because many customers are inexperienced and crowded during peak hours, so it is difficult to use the store in a line. Because of this, it is known that clerks have considerable difficulties with the attitude of sometimes nervous customers.

In larger stores, if automated ordering and payment services are activated with a voice-based application using smartphones used by almost all customers, labor costs can be reduced in a reality where the minimum wage increase is accelerating, and a free service for every 10 cups of coffee. It is expected that customers will increase their use of the store and see an effect of increasing sales when executing the double service, which is one free drink when downloading and collecting 10 AR icons.

The technology disclosed in this specification is derived to solve the problems of the prior art, and in order to solve these problems and requirements, a reservation order and payment are made at the same time regardless of location, and the customer can order menu at a desired time You can receive and take out, which eliminates the difficulty of waiting in line, and store owners can order and pay at the same time, thereby reducing loss of sales and loss of materials due to customers who do not come after ordering. It is to provide technology related to existing services.

In one embodiment, a technology related to a customer-customized recommendation menu service system through big data analysis is disclosed. The customer-customized recommendation menu service system through the big data analysis includes a customer terminal and a server system that communicates with the store terminal, wherein the server system receives data from the customer terminal, and the product of the customer terminal user from the received data Analyzes big data on purchase, and when the customer visits a store where he has ordered and paid for, the server system displays the menu items ordered by the customer at the store where he has ordered and paid for on the customer terminal, In order to display on the store terminal whether the menu product ordered by the customer is in stock, but when the stock of the menu product ordered by the customer is insufficient, the server system displays the order impossible to the customer terminal or the store terminal and a product menu different from the menu product ordered by the customer is displayed on the customer terminal or the store terminal.

The big data may include at least one selected from product information about the product purchase of the customer terminal user, product purchase place information, product purchase time information, product purchase season information, and a combination thereof.

The data received by the server system may include voice data of a user of the customer terminal received from the customer terminal, and the server system extracts a keyword by analyzing the voice data of the user of the customer terminal and extracts the extracted keyword. Through this, the big data can be analyzed.

The technology disclosed in this specification allows customers to know their location from any place, to know where nearby coffee shops are, along with store locations and information, and to order menus (coffee, drinks, chinos, muffins, cookies, Cakes, etc.) and menus that cannot be ordered due to the absence of ingredients can also be identified, and it has the effect of providing a voice ordering system that provides a comprehensive service that can identify each customer's menu preference through the payment menu notification of the store they have visited. Considering the reality of the advent of the 4th industrial age, the need for the development of an application that clearly transmits both the voice and the music of the surrounding people quickly and clearly is emerging, and the technology disclosed in this specification is a technology that meets this need. technology is presented.

In addition, in the reality that the sales increase is accelerating according to the visiting preference of young people in their 20s and 30s as games that can be easily enjoyed with an order in some pubs are popular, coffee shops provided by the technology disclosed in this specification The AR icon service after ordering and payment for My Menu (one free service after saving 10 icons) can contribute to an increase in users' sales, and its use is expected to increase in the future.

The foregoing provides only optional concepts in a simplified form for matters to be described in more detail later. It is not intended to limit key features or essential features of the claims, or to limit the scope of the claims.

1 is an overall system structure diagram of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification according to an embodiment.
2 is a view showing a server system of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification according to an embodiment.
3 is a diagram for explaining information transfer between a server system and a customer app of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification according to an embodiment.
4 is a view for explaining information transfer between a server system of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification and an application for a store according to an embodiment.

Hereinafter, embodiments disclosed herein will be described in detail with reference to the drawings. Unless otherwise specified in the text, like reference numbers in the drawings indicate like elements. Exemplary embodiments described above in the detailed description, drawings, and claims are not intended to be limiting, and other embodiments may be used, and other changes may be made without departing from the spirit or scope of the technology disclosed herein. A person skilled in the art may arrange, construct, combine, and design the elements of the present disclosure, i.e., the elements generally described herein and illustrated in the drawings, in variously different configurations, all of which are obviously It will be readily understood that the invention is intended to form a part of the present disclosure. In the drawings, in order to clearly express various layers (or films), regions, and shapes, the width, length, thickness, or shape of the components may be exaggerated.

When one component is referred to as “prepared” to another component, the case in which the one component is directly provided to the other component, as well as a case in which an additional component is interposed therebetween may be included.

When it is referred to as “providing” one component to another component, the case in which the component is directly provided to the other component, as well as a case in which an additional component is interposed therebetween may be included.

Since the description of the disclosed technology is merely an embodiment for structural or functional description, the scope of the disclosed technology should not be construed as being limited by the embodiment described in the text. That is, since the embodiment may have various changes and may have various forms, it should be understood that the scope of the disclosed technology includes equivalents capable of realizing the technical idea.

The singular expression is to be understood as including the plural expression unless the context clearly dictates otherwise, and terms such as “comprises” or “have” refer to the embodied feature, number, step, action, component, part or these It is to be understood that this is intended to indicate that a combination exists, and does not preclude the possibility of the presence or addition of one or more other features or numbers, steps, operations, components, parts, or combinations thereof.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosed technology belongs, unless defined otherwise. Terms defined in commonly used dictionaries should be interpreted as being consistent with the meanings in the context of the related art, and cannot be interpreted as having ideal or excessively formal meanings unless explicitly defined in the present application.

1 is an overall system structure diagram of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification according to an embodiment. 2 is a view showing a server system of a customer-customized recommendation menu service system through big data analysis disclosed herein according to an embodiment. FIG. 3 is a view for explaining information transfer between a server system and a customer app of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification according to an embodiment. 4 is a view for explaining information transfer between a server system of a customer-customized recommendation menu service system through big data analysis disclosed in the present specification and an application for a store according to an embodiment.

Hereinafter, a customer-customized recommendation menu service system through big data analysis disclosed in the present specification will be described with reference to the drawings.

In this specification, after analyzing data based on menu information previously ordered by customers in coffee shops and restaurant franchises, etc., customized recommended menus are provided for each customer for convenience and new menus, and for store owners, the company's menus are expanded and customers are immediately served. Develop and propose a service system that can maximize sales by promoting it. Such a system may be provided, for example, in the form of Android, iOS (including production of a web application in the store POS), or a kiosk order payment solution (including production of a web application in the store POS). Of course, simultaneous application is possible.

Through this, the customer can order/pay without worrying about the hustle and bustle of the order window at the coffee shop, and the coffee maker can focus on making and serving drinks and desserts. In addition, through this, the technology disclosed in this specification provides a convenient and fast voice reservation service in an environment where customers can preempt a comfortable free space (window or comfortable sofa, etc.) It provides a system differentiated from existing systems, such as providing services that customers can enjoy in their hobbies (SNS, mail, figure production) by receiving icons.

The figure above shows the effect that the technology disclosed in this specification can provide to store owners, reflecting the customer's needs for voice order payment service and customer needs.

The above figure is a figure showing the voice order payment service needs from the point of view of the store owner, and the technology disclosed in this specification can provide a system reflecting these needs of the store owner.

The problems of the existing technology and the originality of the technology disclosed in this specification will be described as follows.

Franchise stores that use the touch ordering method include cupping (membership limit function, customized order, payment system after order, discount and coupon provision), Coffee Bean Mall (membership function, prepayment system, payment system after order, custom order) , store search, promotion notification function, push and MMS function), Tom N Toms (membership function, pre-payment system, post-order payment system, customized order, store search, promotion notification function, push and MMS function), cafed (store search, store information), etc. Problems with the system used by these franchisees include that the app's operating method is complicated and there are frequent disputes when receiving the drinks ordered due to frequent typos during input.

In addition, looking at the usage status of voice ordering service by similar competitors, Starbucks (a service that identifies customer preferences) provides general membership functions, favorites and preferred menu recommendations, easy payment after ordering, customized orders, store search, and promotion notifications. Services, push and MMS functions, online order reservations, beacon functions, discounts and coupons are in operation. Ediya has the only function to earn points, and at first the app was opened including general ordering/payment, but due to the complexity of smart devices, communication networks and apps, only points are left. Problems with these systems include the fact that the barcode must be read when paying at the order counter to be credited, and the reception desk staff is busy and cumbersome to read the barcode, but instead induces most customers to enter their phone number instead.

The characteristics of the technology disclosed in the present specification for solving the problems of these existing methods are as follows. The technology disclosed in this specification developed a service including all services possessed by competitors' product services through nationwide franchise store analysis in order to present a solution for differentiated commercialization, and functions (stores) that have been pointed out as problems in the system. Recommendation, drink recommendation, siren order, store information, store search, voice amplification function _ SO GON SO GON, AR icon, and additional beverage free service) are developed and provided to provide a distinctly differentiated function from other products. A detailed comparison with the conventional method compared to the technology disclosed in this specification will be described using the figure below.

For your reference, when the technology disclosed in this specification is commercialized, it will provide higher functions compared to the existing service provided by this technology, provide AR icon, siren order (order according to the store on the app), store information, location-based store search additional function, etc. It is possible to provide users with a service system that has a significant functional difference from existing coffee specialty franchises.

The customer-customized recommendation menu service system through big data analysis disclosed in this specification provides a user-centered ordering/payment system using voice recognition technology and AR (augmented reality). The technology disclosed in this specification can be applied to a system through development of a program for a smart phone based on Android and iOS, and includes the following functions.

In stores where customers have pre-ordered and paid, the menu products they have ordered are displayed as a notification window, allowing customers to understand their preferred menu and to select new menu products. It can support customer's hobbies using AR (augmented reality) and customer-customized voice order payment service to order with words. It is possible to induce a phone call to select a different menu when selecting a menu by notifying a notification window that an order cannot be made due to a lack of ingredients for a store menu product. It can display the location of a GPS-based customer and also display nearby coffee shops so that they can choose. You can use the search bar to find out the location of specialty coffee shops, and make orders and payments possible. In addition to coffee, tea, and beverages, various menu options such as muffins, cookies, and cakes can be selected. When the ingredients are exhausted, the notification window can notify that the menu cannot be ordered. Pre-order service enables simultaneous ordering and payment regardless of location. In addition, it is possible to provide a function to display nearby coffee shops using the current location. The app can provide a technology that uses a sound amplification algorithm for data that has received speech recognition. It can provide a technology to remove noise with a noise filter algorithm for data that has received voice recognition through the app. After ordering and payment, AR icons are provided so that customers can enjoy their hobbies (SNS, mail, and figure production) (double service). In addition to the credit card payment function, Naver Pay, which is used a lot by the younger generation, and Kakao Pay, which has no commission for store owners, are also available to provide various payment services for customers. The service using voice recognition and AR icon provision service are collectively referred to as double service.

Small and medium-sized coffee specialty store chains that are difficult to pay high costs for order/payment management systems can use the functions provided by the technology disclosed in this specification at a low cost by utilizing the technology disclosed in this specification.

1 shows as an example the overall system structure of a user-centered ordering/payment system using voice recognition technology and AR (augmented reality), which are technologies disclosed in this specification.

2 shows a server system of the technology disclosed in this specification. In the server system, the store management system is a system that manages store information and events, and is a system in which customers can search for a registered store and select a store they want. The menu management system is a system that manages to register the menu of the store and expose the exposed menu to customers in the store. The customer management system is a system that stores and manages customer information, and is a system that can identify customers' tendencies and their desired or favorite menus. The order management system is a system in which customers order menus from the store and the store manages to check or produce the order details of the customers. The alarm system is a system that allows customers to confirm the order completion of the menu and stores to confirm the ordered menu with an alarm.

3 shows information transfer between the server system and the customer app disclosed in the present specification. This will be described in detail as follows.

The customer makes a voice request for the store they want ((1)), searches for the store requested by voice in the store management system ((2)), and transmits the store list to the customer ((3)). When a customer selects a store by voice from the searched list ((4)), the menu management system searches for the list in the menu provided in the store ((5)), transmits the menu list to the customer and displays it on the screen ((6)) do. When a customer places an order from the searched menu by voice ((7)), the order management registers the menu in which the order was placed by voice ((8)) and sends an alarm of the order history result to the customer ((9) ). In addition, membership registration and customer information modification and confirmation are handled in the customer system (<1>, <2>, <3>). When the store updates that the order production is complete ([1]), the alarm system sends the order production completion alarm ([2]) to the customer so that the customer can confirm that the ordered menu has been produced. A technology that can respond to small sounds loudly using voice amplification technology to protect customers' privacy by removing surrounding noise using noise filter technology by recognizing customers' desired stores and menus with voice. apply It is possible to implement and apply the technology to express the content that the searched customer wants by interworking with the recognized voice and the DB of the server system.

4 shows information transfer between the server system disclosed in this specification and the store application. This will be described in detail as follows.

When a customer requests an order, the store checks the order management system ([1]) to determine the current order status ([2]). When a customer places an order ((1)), the alarm system sends an alarm of the customer's order history to the store ((2)), and the store updates the order production completion in order management ((3)) when the order production is completed ((3)) After (4)), an alarm is sent to the customer that the order has been completed. Other than that, stores are registered by inputting store management information, and menus desired or provided by the store are registered in menu management. By composing an active screen on mobile and PC using HTML5, it is possible to implement and apply technology that links real-time stores and customers.

The figure below shows the process of extracting search keywords through natural language processing. Keyword extraction can be performed through recognizer training, character analysis algorithm construction, system training (using corpus and voice DB in related fields, and real-time reflection of changes in main server).

The figure below shows an example of the technical content disclosed in this specification.

From the above, various embodiments of the present disclosure have been described for purposes of illustration, and it will be understood that various modifications are possible without departing from the scope and spirit of the present disclosure. And the various embodiments disclosed above are not intended to limit the spirit of the present disclosure, the true spirit and scope will be presented from the following claims.

Claims (3)

It includes a server system that communicates with the customer terminal and the store terminal,
The server system receives data from the customer terminal, and analyzes big data on the product purchase of the customer terminal user from the received data,
When the customer visits a store where the customer has ordered and paid for, the server system displays the menu products ordered by the customer at the store where the customer has ordered and paid for on the customer terminal, and inventory of the menu products ordered by the customer is displayed on the customer terminal. Whether or not to be expressed on the store terminal,
When the stock of the menu product ordered by the customer is insufficient, the server system displays an order impossible to the customer terminal or the store terminal, and displays a product menu different from the menu product ordered by the customer to the customer terminal or the store terminal. Customer-tailored recommendation menu service system through big data analysis that is displayed on store terminals. According to claim 1,
The big data is customized to the customer through big data analysis including at least one selected from product information, product purchase place information, product purchase time information, product purchase season information, and a combination thereof for the customer terminal user's product purchase Recommended menu service system. 3. The method of claim 1 or 2,
The data received by the server system includes voice data of a user of the customer terminal received from the customer terminal,
The server system analyzes the voice data of the customer terminal user to extract a keyword, and a customer-tailored recommendation menu service system through big data analysis for analyzing the big data through the extracted keyword.

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