Method for increasing client stickiness based on artificial intelligence

Abstract

The invention discloses a method for increasing client stickiness based on artificial intelligence. The method comprises the following steps: collecting and sorting data; customer grading and service matching; deploying an AI service quality inspection point; personalized service pushing is carried out; and social sharing and incentive. And according to accumulation of customer arrival times, the VIP level of the customer is automatically adjusted, and gradual upgrading from basic service to advanced customized service is provided. AI monitoring and analysis are deployed at three key service nodes of welcome, dish ordering and cashier, the service attitude, efficiency and customer feedback are evaluated in real time, and problems in the service are found and corrected in time.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence management, and in particular to an artificial intelligence-based method for increasing customer stickiness, which combines customer store visit frequency data to dynamically adjust and provide personalized VIP services, aiming to cultivate customer loyalty, promote the proportion of repeat customers, and enhance the sense of belonging and satisfaction of employees and customers. Background Art

[0002] The ultimate goal of marketing is returning customers:

[0003] Indeed, repeat customers are the key to business success. Not only do they bring continuous revenue to businesses, they also attract more new customers through word-of-mouth. Therefore, cultivating loyal customers is an important marketing goal.

[0004] Customers who want to take advantage are not quality customers:

[0005] This statement is somewhat controversial. Although long-term, stable customers are more valuable to businesses, customers who "want to take advantage" can also be converted into loyal customers. The key lies in how businesses guide them to consume correctly and give them appropriate discounts and care. Therefore, this type of customer cannot be excluded from the category of high-quality customers.

[0006] In traditional marketing, companies often focus too much on maximizing profits from a single transaction and ignore the importance of establishing long-term relationships with customers. This approach leads companies to focus more on immediate benefits and ignore the importance of repeat customers for the company's sustainable development. Repeat customers, that is, those customers who make repeated purchases and have a high degree of recognition and loyalty to the company's products or services, are the cornerstone of a company's stable revenue and sustainable growth.

[0007] However, how to effectively identify and motivate truly valuable customers has become a major challenge facing the current service industry. Valuable customers not only refer to those who purchase frequently and spend a large amount of money, but also include those who have a positive impact on the company's word-of-mouth communication and brand loyalty. Companies need to establish a complete customer value assessment system to accurately identify these valuable customers through data analysis, customer feedback, etc., and take corresponding incentives, such as providing personalized services, discounts, membership privileges, etc., to enhance their loyalty and satisfaction.

[0008] At the same time, companies also need to avoid over-reliance on customers who seek short-term discounts. These customers are often price-sensitive and tend to flock in during promotions, but quickly leave after the promotions are over. They have low loyalty and make limited contributions to the long-term development of the company. Therefore, when formulating marketing strategies, companies should pay more attention to the long-term maintenance of customer relationships rather than just pursuing short-term sales growth.

[0009] In addition, with the development of artificial intelligence technology, how to use AI to improve service quality and enhance customer experience has become an urgent problem to be solved. AI technology can deeply understand customer needs and preferences through data analysis, machine learning and other methods, and provide more accurate services for enterprises. For example, AI customer service can answer customer questions online 24 hours a day to improve service efficiency; intelligent recommendation systems can recommend suitable products or services to customers based on their purchase history and behavior data, thereby improving customer satisfaction.

[0010] In summary, the traditional marketing approach of focusing too much on the profit of a single transaction is no longer suitable for the current market environment. Enterprises need to change their marketing concepts, attach importance to establishing long-term relationships with customers, effectively identify and motivate valuable customers, and use AI technology to improve service quality and enhance customer experience in order to achieve sustainable development of the enterprise. Summary of the invention

[0011] The present invention provides a method for increasing customer stickiness based on artificial intelligence.

[0012] The present invention provides a method for increasing customer stickiness based on artificial intelligence, comprising:

[0013] A. Data collection and organization;

[0014] B. Customer classification and service matching;

[0015] C. Deployment of AI service quality inspection points;

[0016] D. Personalized service push;

[0017] E. Social sharing and incentives.

[0018] Furthermore, a dynamic VIP service system is adopted to automatically adjust the customer's VIP level according to the cumulative number of customer visits to the store, providing a gradual upgrade from basic services to advanced customized services, allowing customers to experience the consumption experience of "the more you come, the more distinguished you are".

[0019] Furthermore, by utilizing AI service quality inspection, AI monitoring and analysis are deployed at the three key service nodes of welcoming guests, ordering food, and cashiering to evaluate service attitude, efficiency, and customer feedback in real time, promptly discover and correct problems in the service, and improve the overall service quality.

[0020] Furthermore, by leveraging social trust communication, customers are encouraged to share their VIP experience through social media or in-store interactions, leveraging trust relationships among acquaintances to expand the brand's positive influence, attract more potential customers, and enhance the sense of belonging of existing customers.

[0021] Furthermore, in order to motivate and empower employees, the system also includes an employee performance evaluation system, which rewards employees based on customer satisfaction and service quality inspection results, thereby enhancing their work enthusiasm and sense of team belonging.

[0022] Furthermore, data such as the number of customer visits to stores and consumption records are collected through channels such as membership systems and POS systems.

[0023] Furthermore, according to preset rules, customers are divided into different VIP levels, and each level corresponds to different service packages and discounts.

[0024] Furthermore, intelligent monitoring equipment is installed in the reception, ordering and checkout links, combined with natural language processing and image recognition technology to achieve real-time monitoring and evaluation of service quality.

[0025] Furthermore, based on customer preferences and historical data, personalized service recommendations and discount information are pushed to customers through APP, text messages, etc.

[0026] Furthermore, a customer sharing reward mechanism is established to encourage customers to share their experiences on social platforms, while providing employees with rewards for customer praise, forming a positive cycle.

[0027] Furthermore, improving VIP service content through store visits is an effective customer incentive strategy. By recording the number of store visits by customers, merchants can provide more personalized services and discounts to regular customers, thereby enhancing their loyalty and sense of belonging.

[0028] Furthermore, the consumer concept of "the more you come, the more distinguished you are" is established, which helps to cultivate customer loyalty and consumption habits. When customers feel their distinguished status, they are more willing to visit frequently and recommend it to others.

[0029] Furthermore, through communication and trust between acquaintances, both employees and customers can achieve a sense of belonging. Social interaction is an important means to enhance customer loyalty. When customers and employees establish a trusting relationship, they will not only become repeat customers, but also become brand evangelists. At the same time, employees will also gain a sense of accomplishment from a good relationship with customers, thereby enhancing their sense of belonging.

[0030] Furthermore, AI service quality inspection points are set up for the three positions of welcoming guests, ordering dishes, and cashiering. The introduction of AI technology for service quality inspection can ensure service quality and consistency. By monitoring the service performance of these three key positions, merchants can promptly discover and correct problems and improve customer satisfaction.

[0031] Furthermore, customers receive a separate commission for bookings with waiters: this is an incentive mechanism designed to encourage waiters to be more proactive in establishing contact with customers and increase booking rates. However, this mechanism needs to be carefully designed to ensure that it does not induce over-sales or damage the customer experience.

[0032] Beneficial Effects

[0033] The present invention can not only effectively improve customer loyalty and increase the proportion of repeat customers through an intelligent and personalized VIP service system, but also attract more new customers through high-quality services and positive word-of-mouth communication. At the same time, through AI service quality inspection and employee incentive mechanism, it can significantly improve service quality and employee satisfaction, create a harmonious and efficient business environment, and bring long-term competitive advantages and economic benefits to enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flowchart of a method for increasing customer stickiness based on artificial intelligence provided by an embodiment of the present invention; DETAILED DESCRIPTION

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0036] Figure 1 A flowchart of a method for increasing customer stickiness based on artificial intelligence provided by an embodiment of the present invention. The method can be performed by a method for increasing customer stickiness based on artificial intelligence, which specifically includes the following steps:

[0037] S110, data collection and collation;

[0038] 1. Data Collection Channels

[0039] Membership system:

[0040] The membership system is an important tool for merchants to record and manage member information. Through the membership system, merchants can collect basic information of customers, such as name, contact information, birthday, etc.

[0041] More importantly, the membership system can record detailed information such as the number of times a customer visits the store, consumption records, points, etc. These data are crucial for analyzing customer consumption habits, preferences, and loyalty.

[0042] POS System:

[0043] As a sales terminal, the POS (Point of Sale) system not only completes the transaction process, but is also a key channel for collecting customer consumption data.

[0044] The POS system can record every sales transaction in detail, including product name, quantity, price, purchase time, and customer information.

[0045] These data provide merchants with rich information on customer consumption behavior, helping them to gain a deeper understanding of customers' consumption habits and preferences.

[0046] Internet of Things system: Smartphones conduct quality inspection on the waiter’s voice service and the camera can obtain smile recognition during checkout to detect problems immediately, feedback customer emotions and improve service quality.

[0047] 2. Data Collection Methods

[0048] Ensure data interoperability:

[0049] In order to achieve efficient data collection and analysis, merchants need to ensure data interoperability between the membership system and the POS system. This can be achieved through technical means such as API interfaces to ensure that transaction information can be updated in real time to the membership card management system.

[0050] Automatically identify members:

[0051] When members check out, the POS system should be able to automatically identify the member's identity and automatically apply the corresponding member benefits, such as discounts, points, etc. This not only improves checkout efficiency, but also facilitates subsequent data analysis.

[0052] Comprehensive record of consumption data:

[0053] Merchants should make full use of the functions of the POS system to comprehensively record customers' consumption data, including the purchased goods, quantity, price, purchase time, and customer information, etc., to provide a solid foundation for subsequent data analysis.

[0054] 3. The significance of data collection

[0055] Understand customer consumption habits:

[0056] By collecting and analyzing customer consumption data, merchants can gain a deeper understanding of their consumption habits and preferences, which helps them develop more precise marketing strategies and improve customer satisfaction and loyalty.

[0057] Optimize inventory management:

[0058] Merchants can grasp the sales status of goods in real time based on customer consumption data, which is of great significance for optimizing inventory management and avoiding out-of-stock or overstocking.

[0059] Improve personalized marketing effectiveness:

[0060] Based on customers' consumption data, merchants can conduct accurate member segmentation and personalized recommendations, which can not only improve customers' shopping experience, but also effectively promote sales growth.

[0061] S120, customer classification and service matching;

[0062] 1. VIP Level Classification

[0063] Merchants first need to segment customers based on multiple dimensions such as their consumption behavior, purchase frequency, consumption amount, brand loyalty, etc., and set different VIP levels accordingly. Common VIP level classification methods are:

[0064] Basic Membership: For light consumers or new customers, it provides basic membership benefits and services, such as discounts on some products, limited free delivery times, etc. The membership threshold for this level is relatively low, aiming to attract customers to try membership services.

[0065] Premium Membership (or Silver / Gold Membership): Targeting moderate consumers, it provides more benefits and services than Basic Membership. This may include more discounts on products, more free deliveries, priority delivery, invitations to exclusive events, etc. Members at this level need to meet certain spending amount or frequency requirements.

[0066] Exclusive members (or diamond cards / VIP members): provide a full range of high-end services and discounts for heavy consumers or high-value customers. This may include unlimited free delivery, the biggest discount on all products, member-exclusive customer service, customized services, etc. Exclusive members usually enjoy the highest discounts and service treatment, and need to meet higher consumption thresholds or brand loyalty requirements.

[0067] 2. Service packages and discount design

[0068] For different VIP levels, merchants need to design attractive service packages and discounts to ensure that membership benefits match customer needs and reflect the level differences. Specifically:

[0069] Basic membership: The service package may include basic discounts, points accumulation and the right to participate in member activities. For example, 1 point is accumulated for every 1 yuan spent, and the points can be used to redeem small gifts or deduct cash; participate in member-exclusive shopping day activities and enjoy additional discounts, etc.

[0070] Premium Membership: Based on the basic membership service package, more benefits and privileges are added. For example, more points are accumulated for every RMB spent, and discounts are offered throughout the year or during a specific period of time; priority delivery service is provided to ensure fast delivery of goods; more member-exclusive activities are offered, and more exclusive benefits are enjoyed.

[0071] Exclusive membership: Provides a full range of high-end services and benefits. For example, unlimited free delivery service ensures that customers can enjoy convenient shopping at any time; the maximum discount on all products allows customers to buy their favorite products at the lowest price; a member-exclusive customer service team provides 24-hour attentive service; customized services, such as exclusive gift customization, personalized shopping recommendations, etc.

[0072] Through this hierarchical VIP level division and service package design, merchants can more effectively meet the needs and expectations of different customers and improve customer satisfaction and loyalty. At the same time, this can also encourage customers to continuously upgrade their membership levels, thereby increasing consumption frequency and amount, bringing greater commercial value to merchants.

[0073] S130, AI service quality inspection point deployment;

[0074] 1. Application of intelligent monitoring equipment

[0075] Welcoming session:

[0076] Install high-definition cameras and microphones to capture the movements and sounds of customers as they enter the store.

[0077] Use image recognition technology to identify customers’ expressions, movements, etc., and determine their initial needs or emotional state.

[0078] Combined with natural language processing technology, the conversation between customers and receptionists is analyzed to evaluate the receptionists’ polite language, service attitude, etc.

[0079] Ordering

[0080] The customer's ordering process is monitored through cameras, and the customer's browsing of the menu, ordering speed, etc. are recorded.

[0081] Use natural language processing technology to analyze conversations between customers and waiters, identify customers' inquiries about dishes, special needs, etc., as well as the speed and accuracy of waiters' responses.

[0082] Combined with image recognition technology, it can detect whether the waiter's operations during the ordering process are standardized, such as whether the correct ordering equipment is used, whether the customer's ordering information is accurately recorded, etc.

[0083] Cashiering process:

[0084] Install high-definition cameras to monitor the cash register and record customers' waiting time, payment methods, etc. when checking out.

[0085] Use natural language processing technology to analyze conversations between customers and cashiers, and evaluate cashiers' politeness, checkout efficiency, etc.

[0086] Through image recognition technology, it is possible to detect whether the cashier’s operations during the checkout process are accurate and quick, such as whether the product barcode is scanned correctly and whether the change is given accurately.

[0087] 2. Implementation of Real-time Monitoring and Evaluation

[0088] Data Collection and Processing:

[0089] Intelligent monitoring equipment collects video and audio data of the welcoming, ordering and checkout processes in real time.

[0090] Use advanced algorithms and models to process and analyze the collected data to extract key information.

[0091] Service quality assessment:

[0092] Based on the processed data, the service quality of the welcoming, ordering and cashiering links is evaluated in real time.

[0093] Evaluation indicators may include customer waiting time, waiter attitude, operational accuracy, etc.

[0094] By setting thresholds or standard values, service quality can be quantitatively scored to facilitate subsequent management and improvement.

[0095] Real-time feedback and improvement:

[0096] Provide real-time feedback of service quality evaluation results to relevant managers and waiters.

[0097] Based on the evaluation results, managers can promptly identify problems and deficiencies in services and formulate corresponding improvement measures.

[0098] Waiters can also adjust their service methods and attitudes based on the feedback results to improve service quality.

[0099] 3. Technical support and advantages

[0100] Natural language processing and image recognition technology:

[0101] These two technologies are the key to achieving real-time monitoring and evaluation of service quality.

[0102] Natural language processing technology can accurately identify and analyze conversation content, providing strong support for service quality assessment.

[0103] Image recognition technology can capture and analyze the movements and expressions of customers and waiters, providing an intuitive basis for evaluating service quality.

[0104] Data-driven management and decision-making:

[0105] By collecting and analyzing data in real time, businesses can understand customer needs and service status more accurately.

[0106] Data-driven management and decision-making methods can improve management efficiency and decision-making accuracy, bringing greater business value to businesses.

[0107] Improve customer experience and loyalty:

[0108] Real-time monitoring and evaluation of service quality can promptly identify and improve problems in the service.

[0109] High-quality service can improve customer satisfaction and loyalty, bringing more repeat customers and word-of-mouth communication to businesses.

[0110] In summary, installing intelligent monitoring equipment in the reception, ordering, and cashiering stages, combined with natural language processing and image recognition technology, can achieve real-time monitoring and evaluation of service quality. This can not only improve the merchant's operational efficiency and management level, but also greatly enhance customer experience and loyalty.

[0111] S140, personalized service push;

[0112] First, businesses need to collect and organize customer preferences and historical data. This includes customer browsing history, purchase history, evaluation feedback, interactive behavior, etc. on the APP, as well as customer information collected through other channels (such as social media, questionnaires, etc.). These data provide businesses with a basis for in-depth understanding of customer needs and behaviors.

[0113] Next, the collected data is deeply mined and analyzed using data analysis tools and techniques. Through machine learning algorithms, collaborative filtering, content filtering and other methods, merchants can build user portraits and predict customer preferences and purchase intentions. For example, for customers who often dine on weekends, the system can identify that they may prefer family packages or specific types of dishes.

[0114] Based on these analysis results, merchants can formulate personalized service suggestions and preferential information. These suggestions and information should be closely centered on the preferences and needs of customers, such as recommending dishes that customers like, providing package discounts for specific occasions, and giving gifts that customers are interested in. Through channels such as APP and SMS, merchants can push these personalized service suggestions and preferential information to customers in a timely manner to ensure the relevance and timeliness of the information.

[0115] During the push process, merchants also need to pay attention to the rationality of the push frequency and method. Too frequent pushes may make customers feel harassed, while too sparse pushes may cause customers to miss important information. Therefore, merchants should adjust the push frequency and method according to customer activity and feedback to ensure that customers can feel the merchant's care and respect while receiving information.

[0116] Finally, merchants need to continuously track and evaluate the effectiveness of push notifications. By monitoring customer feedback, purchasing behavior and other data, merchants can understand the actual effects of personalized service suggestions and preferential information, and optimize and adjust push notification strategies based on the evaluation results. This continuous optimization process helps merchants continuously improve customer experience, enhance customer loyalty, and ultimately achieve increased sales conversions.

[0117] In summary, based on customer preferences and historical data, pushing personalized service suggestions and preferential information to customers through APP, SMS, etc. is an important strategy for merchants to improve customer experience and promote sales conversion. By carefully designing and implementing this process, merchants can stand out in the fierce market competition and win more favor and support from customers.

[0118] S150, social sharing and incentives.

[0119] Establish a customer sharing reward mechanism:

[0120] Clarify the reward criteria: First, you need to set clear reward criteria, such as points, discounts or gifts that customers can get after sharing their experiences on social platforms. This can directly stimulate customers' motivation to share.

[0121] Diversified reward forms: Reward forms can be diversified, including but not limited to points accumulation redemption prizes, direct discounts, gifts for next consumption, etc., to meet the needs and preferences of different customers.

[0122] Public ranking mechanism: You can consider introducing a public ranking mechanism. After registering through a QR code or a superior mobile phone number, the system will automatically arrange it under this mobile phone number to encourage customers to actively share and attract more new customers to join.

[0123] Encourage customers to share their experiences on social platforms:

[0124] Provide sharing channels: Set up obvious sharing buttons or links in the restaurant or APP to facilitate customers to share to major social platforms with one click.

[0125] Guide customers to share: Employees can actively remind customers to share their experiences during the service process and inform them of the rewards they can get after sharing, so as to increase customers' willingness to share.

[0126] Leverage social media marketing: Actively post restaurant updates, new product recommendations, and other content on social media, and encourage customers to interact and share to expand the restaurant’s exposure and word-of-mouth communication.

[0127] Provide employees with customer praise rewards:

[0128] Set employee reward standards: According to the effectiveness of employees in guiding customers to give positive reviews, set corresponding reward standards, such as points, bonuses or promotion opportunities.

[0129] Timely cashing of rewards: When employees reach the reward criteria, rewards should be paid in a timely manner to enhance their enthusiasm and sense of belonging.

[0130] Encourage employee participation: Through training, meetings, etc., convey to employees the importance of the praise reward mechanism, and encourage employees to actively participate in order to jointly improve the restaurant's praise and reputation.

[0131] Forming a positive cycle:

[0132] Continuously optimize services: Through customer sharing and positive feedback, restaurants can promptly understand customer needs and opinions, thereby continuously optimizing service quality and food quality and improving customer satisfaction.

[0133] Enhance customer loyalty: After receiving good experiences and rewards, customers are more likely to come back and actively share their experiences, thereby attracting more new customers and forming a positive cycle.

[0134] Enhance brand influence: With the continuous accumulation of customer sharing and positive reviews, the restaurant's brand influence will gradually increase, thereby attracting more customers to consume.

[0135] Example 2

[0136] Application of AI-based methods to increase customer stickiness in “Food Cloud” restaurants

[0137] Background

[0138] "Food Cloud" is a mid-to-high-end restaurant chain. In order to improve customer satisfaction, enhance customer loyalty, and optimize internal management efficiency, it decided to implement a comprehensive intelligent customer service and management system. The system covers data collection and organization, customer classification and service matching, AI service quality inspection point deployment, personalized service push, social sharing and incentives, and many other aspects.

[0139] 1. Data collection and organization

[0140] Membership system upgrade:

[0141] "Food Cloud" first upgraded its membership system to ensure that it can record in detail each member's basic information (such as name, gender, age, contact information, etc.) as well as consumption records of each visit to the store (including dish selection, consumption amount, dining time, etc.).

[0142] The membership system is also seamlessly connected to the restaurant's POS system (point of sale system) to ensure that all transaction data can be synchronized to the membership database in real time.

[0143] Data Integration and Analysis:

[0144] Restaurants integrate and analyze the collected data regularly (such as daily or weekly) to understand key information such as customers' consumption habits, preferences, and frequency of visits.

[0145] Through data analysis, restaurants can identify high-value customer groups and provide data support for subsequent customer grading and service matching.

[0146] 2. Customer grading and service matching

[0147] Customer rating:

[0148] Based on multi-dimensional data such as customers' consumption frequency, consumption amount, dining evaluations, etc., the restaurant divides customers into four levels: ordinary members, silver card members, gold card members and diamond card members.

[0149] Each level has clear upgrade and maintenance standards to ensure the dynamic and accurate customer grading.

[0150] Service matching:

[0151] The restaurant provides different service packages and discounts for different levels of customers. For example, gold card members can enjoy free birthday meals, priority reservations, exclusive waiters and other advanced services; while ordinary members may only enjoy basic discounts and points accumulation.

[0152] The restaurant also provides a consistent and high-quality service experience by training its employees to ensure that they understand and are proficient in the service standards for customers of all levels.

[0153] 3. Deployment of AI Service Quality Inspection Points

[0154] Intelligent monitoring equipment installation:

[0155] The restaurant has installed high-definition intelligent monitoring equipment in key service areas such as the reception area, ordering area, and cashier area. These devices can not only record video images, but also use built-in natural language processing and image recognition technology to perform real-time analysis of voice conversations and customer expressions during the service process.

[0156] Service quality monitoring and evaluation:

[0157] Through AI technology, restaurants can monitor key indicators of the service process in real time, such as the enthusiasm of welcoming guests, the accuracy of ordering, the efficiency of cashiering, etc.

[0158] When service quality issues or customer dissatisfaction are found, the system will immediately trigger an alarm and notify relevant managers to intervene. At the same time, the system will also conduct regular evaluations of service quality and provide improvement suggestions for restaurants.

[0159] 4. Personalized service push

[0160] Customer preference analysis:

[0161] Based on the customer's historical consumption data and preference information, the restaurant can build a personalized portrait of each customer. For example, a customer may prefer Sichuan cuisine, like a quiet dining environment, and be more sensitive to price.

[0162] Service suggestions and preferential information push:

[0163] Based on the personalized portrait of customers, the restaurant pushes customized service suggestions and preferential information to customers through its official APP, SMS and other channels. For example, when a customer's birthday is approaching, the restaurant will send birthday wishes and attach exclusive birthday coupons; or when the restaurant launches new dishes, it will push tasting invitations to customers who like to try new things.

[0164] 5. Social Sharing and Incentives

[0165] Customer sharing reward mechanism:

[0166] The restaurant encourages customers to share their dining experiences on social platforms (such as WeChat, Weibo, Douyin, etc.). In order to motivate customers to share, the restaurant has set up a sharing reward mechanism, such as points, coupons or discounts for next consumption after sharing.

[0167] Employee praise rewards:

[0168] At the same time, the restaurant has also established an employee praise reward system. When customers give a positive review to an employee on social platforms or in the restaurant's internal reviews, the employee will receive corresponding rewards, such as bonuses, promotion opportunities or extra vacations.

[0169] This mechanism not only motivates employees to provide better services, but also promotes positive interactions between customers and employees, forming a positive service ecosystem.

[0170] By implementing this intelligent customer service and management system, the "Food Cloud" restaurant has successfully improved customer satisfaction and loyalty, optimized internal management efficiency, and achieved sustained business growth.

[0171] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0172] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0173] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0174] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0175] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0176] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0177] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0178] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for increasing customer stickiness based on artificial intelligence, characterized in that: include: A. Data collection and organization; B. Customer classification and service matching; C. Deployment of AI service quality inspection points; D. Personalized service push; E. Social sharing and incentives.

2. The method according to claim 1, characterized in that include: Based on the cumulative number of times customers visit the store and the amount of consumption, the customer's VIP level is automatically adjusted, providing a gradual upgrade from basic services to advanced customized services. The data also includes the customer's dining information and dining habits, which are automatically split into multiple labels using artificial intelligence to form a customer portrait.

3. The method according to claim 1, characterized in that include: Deploy AI monitoring and analysis at the three key service nodes of welcoming guests, ordering food, and cashiering to evaluate service attitude, efficiency, and customer feedback in real time, and promptly identify and correct problems in the service.

4. The method according to claim 1, characterized in that include: Install intelligent monitoring equipment during the reception, ordering and checkout process, and combine natural language processing and image recognition technology to achieve real-time monitoring and evaluation of service quality.

5. The method according to claim 1, characterized in that include: Establish a customer sharing reward mechanism to encourage customers to share their experiences on social platforms, and at the same time provide employees with rewards for customer praise to form a positive cycle.

6. The method according to claim 1, characterized in that include: When members check out, the POS system should be able to automatically identify the member's identity and automatically apply the corresponding member benefits.

7. The method according to claim 1, characterized in that include: According to preset rules, customers are divided into different VIP levels, and each level corresponds to different service packages and discounts.

8. The method according to claim 1, characterized in that include: Based on customer preferences and historical data, personalized service recommendations and discount information are pushed to customers through APP, text messages, etc.

9. The method according to claim 1, characterized in that: include: By recording the number of times customers visit a store, merchants can provide more personalized services and offers to regular customers, thereby enhancing their loyalty and sense of belonging.

10. The method according to claim 1, characterized in that include: When members check out, the POS system should be able to automatically identify the member's identity and automatically apply the corresponding member benefits.

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