Digital Baijiu industry internet platform

Abstract

The invention relates to a digital Baijiu industry Internet platform, and relates to the industrial Internet field, the method comprises an RFID management module used for determining identity information of Baijiu and tracing marketing data, and the identity information is a two-dimensional code of each bottle of Baijiu; the marketing activity management module is used for establishing personalized reward services based on the identity information of the white spirit, and the personalized reward services are different reward services formulated according to different application scenes and different code scanning channels; the member monitoring module is used for acquiring member registration information based on the personalized reward service, and monitoring based on the member information to obtain consumption data; and the data analysis module is used for receiving the consumption data and analyzing the consumption data to obtain a data report. The method has the effect of improving the digital management efficiency of the white spirit enterprise.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of industrial internet, in particular to a digital liquor industry internet platform. BACKGROUND

[0002] With the rapid development of internet technology, the traditional liquor industry has gradually transformed to digitalization, and the application of internet platforms in the liquor industry is becoming more and more widespread. The introduction of digital technology has brought many conveniences to the liquor industry, such as improving the marketing efficiency of liquor, optimizing the supply chain management, etc., so that liquor companies can better adapt to market changes and meet the increasingly diverse needs of consumers. Through the internet platform, liquor companies can establish closer contact with consumers, expand sales channels, enhance brand influence, and promote the upgrading and development of the entire liquor industry.

[0003] In the prior art, the digital management of the liquor industry uses a simple two-dimensional code management system to assign a unique two-dimensional code to each bottle of liquor. Consumers can obtain certain product information after scanning the code, but the system has relatively simple functions and is mainly limited to product traceability and basic information display However, the simple two-dimensional code management system has limited functions and cannot effectively trace and deeply analyze the marketing data of liquor. The basic marketing activity management software lacks personalized services and cannot develop appropriate reward services according to different application scenarios and scanning channels, resulting in poor marketing effect and difficulty in meeting the growing digital management needs of liquor companies. SUMMARY

[0004] In order to improve the digital management efficiency of liquor companies, the present application provides a digital liquor industry internet platform.

[0005] In the first aspect, the present application provides a digital liquor industry internet platform, which adopts the following technical solution: A digital liquor industry internet platform, comprising: An RFID management module for determining the identity information of liquor and tracing marketing data, the identity information being a two-dimensional code for each bottle of liquor; A marketing activity management module for establishing personalized reward services based on the identity information of the liquor, the personalized reward services being different reward services developed according to different application scenarios and different scanning channels; A member monitoring module for obtaining member registration information based on the personalized reward services and monitoring based on the member information to obtain consumption data; A data analysis module for receiving the consumption data and analyzing the consumption data to obtain a data report.

[0006] By adopting the technical scheme, the platform integrates an RFID management module, a marketing activity management module, a member monitoring module, and a data analysis module to build a comprehensive digital liquor industry Internet platform. The RFID management module allocates a unique identity information for each bottle of liquor by using RFID technology and two-dimensional code technology, and realizes product traceability and marketing data collection. The marketing activity management module provides personalized reward services based on user data and portraits, formulates differentiated reward strategies according to different application scenarios and code scanning channels, and effectively improves the participation and activity effect of users. The member monitoring module obtains member registration information and monitors consumption data, so that the enterprise can more deeply understand the consumption habits and preferences of members. This helps the enterprise optimize the member management system, improve the member satisfaction and loyalty, and provide data support for subsequent precision marketing and personalized services. The data analysis module analyzes the consumption data and generates data reports, so that the enterprise can more intuitively understand the market dynamics and sales situation.

[0007] In another possible implementation manner, the marketing activity management module comprises: A marketing preparation unit is configured to obtain user data, wherein the user data comprises a location of the user; An activity determination unit is configured to analyze the user data to obtain a user portrait, determine a matched activity category based on the user portrait, and push the matched activity category to the user to enable the user to participate in the activity; A marketing result determination unit is configured to record user data of the user participating in the activity.

[0008] By adopting the technical scheme, the marketing activity management module obtains user data including user location information through the marketing preparation unit, and provides a data basis for precision marketing. This helps the enterprise better understand the target user group and formulate more targeted marketing strategies. The activity determination unit analyzes the user data and generates a user portrait, so that the enterprise can more accurately grasp the user demand and preference. Based on the user portrait, the matched activity category is determined and pushed to the user, which effectively improves the participation and conversion rate of the activity. The marketing result determination unit records the user data of the user participating in the activity, so that the enterprise can more comprehensively understand the activity effect by recording the user data of the user participating in the activity.

[0009] In another possible implementation manner, the marketing activity management module further comprises: A marketing risk control unit is configured to filter the user participating in the activity to determine a risk user; A prize control unit is configured to obtain a number of times of drawing of the user and a number of times of winning, and control a frequency of winning of the user; An abnormality early warning unit is configured to monitor a prize collection state of the user in an activity process; The prize pool early warning unit is configured to monitor the prize of the activity and remind when the prize is lower than a preset prize threshold.

[0010] By adopting the above technical solutions, the marketing activity management module further screens the users participating in the activity and determines the risk users through the marketing risk control unit, effectively reducing the risk of the marketing activity. This helps the enterprise to protect its own interests and avoid the impact of malicious award brushing and other behaviors on the activity effect. The prize control unit controls the winning frequency of the users to ensure the fairness and sustainability of the activity. This helps to improve the user's participation experience and satisfaction, while avoiding excessive consumption of prize resources. The abnormal early warning unit monitors the prize collection status of the users during the activity process, discovers abnormal situations in time and handles them. This helps the enterprise to ensure the smooth progress of the activity and avoid the impact on the user experience and brand image. The prize pool early warning unit monitors the activity prize to ensure sufficient prizes and avoid the impact of insufficient prizes on the activity.

[0011] In another possible implementation manner, the member monitoring module comprises: A member system establishment unit is configured to obtain member information of a user and determine a member level of the user according to the member information; A member data unit is configured to analyze the member information and tag the user to obtain users in different groups; A member information pushing unit is configured to analyze the users in different groups to obtain group types and push messages based on the group types.

[0012] By adopting the above technical solutions, the member monitoring module obtains the member information of the user and determines the member level of the user, providing a clearer member management view for the enterprise. This helps the enterprise to optimize the member service system and improve the member satisfaction. The member data unit analyzes the member information and tags the user, enabling the enterprise to more deeply understand the consumption habits and preferences of the members. This helps the enterprise to develop more targeted marketing strategies and service solutions, improving the participation and conversion rates of the members. The member information pushing unit analyzes the users in different groups and pushes corresponding messages, enabling the enterprise to more accurately reach the target user group. This helps to improve the arrival rate and reading rate of the information, and further improves the marketing effect and user satisfaction.

[0013] In another possible implementation manner, the data analysis module comprises: A market dynamic monitoring unit is configured to determine logistics data according to the identity information of the liquor, the logistics data being data to channels, distributors, terminals and consumers; A dynamic sales situation analysis unit is configured to analyze the logistics data to obtain a number of product categories with sales and a ratio of sales in the current month to current inventory; A data visualization unit is configured to display the data analysis results in a graphical manner, including activity status, target achievement, prize distribution, and sales.

[0014] By adopting the above technical solutions, the data analysis module analyzes the logistics data and determines the logistics data, and the enterprise can more comprehensively understand the market dynamics and sales. This helps the enterprise to timely adjust the market strategy, optimize the product portfolio and supply chain management, and improve the market competitiveness. The dynamic sales situation analysis unit analyzes the logistics data and calculates the number of product categories with sales and the ratio of sales in the current month to current inventory, so that the enterprise can more accurately grasp the dynamic sales situation of the products. This helps the enterprise to timely adjust the production plan and inventory strategy, and avoid the occurrence of inventory accumulation and shortage. The data visualization unit displays the data analysis results in a graphical manner, so that the enterprise can more intuitively understand the activity status, target achievement, prize distribution, and sales information. This helps the enterprise to quickly grasp the overall business situation.

[0015] In another possible implementation manner, the system further includes: A code source data module is configured to integrate different code sources and centrally issue codes; A data middle platform application module is configured to collect data from various business systems, and perform verification, cleaning, and integration to form high-quality data assets; An early warning center sub-module is configured to monitor and warn abnormal data according to preset rules.

[0016] By adopting the above technical solutions, the code source data module integrates different code sources and centrally issues codes, ensuring the uniqueness and accuracy of the code sources. This helps the enterprise to realize the full life cycle tracking and management of products, and improves the accuracy of product traceability. The data middle platform application module collects data from various business systems and performs verification, cleaning, and integration to form high-quality data assets. This helps the enterprise to break down data silos, realize data sharing and reuse, and improve the value and utilization of data. The early warning center sub-module monitors and warns abnormal data according to preset rules, ensuring the stability and security of the system. This helps the enterprise to timely discover and handle potential problems, avoiding the impact on business operation and user experience.

[0017] In another possible implementation manner, the data middle platform application module includes: A channeling analysis unit is configured to obtain channeling quantity in a preset time period, and perform channeling quantity analysis to obtain channeling data; A channeling early warning unit is configured to analyze the channeling data, and trigger a warning mechanism when the channeling data is abnormal.

[0018] The channeling traceability unit determines a channeling code source through channeling data and traces the channeling code source.

[0019] By adopting the above technical solutions, the data center application module can obtain the channeling quantity in a preset time period and perform channeling quantity analysis, so that the enterprise can more accurately understand the situation and trend of channeling. This helps the enterprise to formulate targeted anti-channeling strategies and maintain market order. The channeling early warning unit analyzes based on channeling data and triggers the early warning mechanism when data is abnormal, ensuring that the enterprise can timely discover and handle channeling problems. This helps the enterprise to quickly respond to market changes and avoid the impact of channeling on business operations. The channeling traceability unit traces the channeling code source and traces the channeling code source, so that the enterprise can more accurately find the source and path of channeling. This helps the enterprise to solve the channeling problem and prevent the recurrence of channeling.

[0020] In another possible implementation manner, the RFID management module comprises: The RFID tag preparation unit receives the code package of the two-dimensional code platform, generates an RFID value according to an algorithm, and prints a two-dimensional code on the surface of the RFID tag while writing the RFID value into the RFID tag; The packaging workshop production unit, after associating the bottle box case code, pastes the RFID tag on the large box through an RFID tag pasting machine and performs verification of the two-dimensional code and the RFID value; The warehouse in-out unit sets an RFID gate or an RFID reading device at the warehouse entrance and exit to realize fast in-out operation of whole pallet or single box products and synchronizes the in-out data to the original two-dimensional code management platform.

[0021] By adopting the above technical solutions, the RFID management module receives the code package of the two-dimensional code platform through the RFID tag preparation unit, generates an RFID value according to an algorithm, and ensures the unique association of the RFID tag and the two-dimensional code. The packaging workshop production unit associates the bottle box case code through scanning and performs verification of the two-dimensional code and the RFID value, ensuring accurate identification and traceability of products in the production process. The warehouse in-out unit sets an RFID gate or an RFID reading device at the warehouse entrance and exit to realize fast in-out operation of whole pallet or single box products, improving the warehouse management efficiency and accuracy.

[0022] In summary, the present application has at least one of the following beneficial technical effects: 1. This platform integrates RFID management, marketing campaign management, membership monitoring, and data analysis modules to build a comprehensive digital internet platform for the liquor industry. The RFID management module uses RFID and QR code technologies to assign a unique identifier to each bottle of liquor, enabling product traceability and marketing data collection. The marketing campaign management module provides personalized reward services based on user data and profiles, developing differentiated reward strategies according to different application scenarios and scanning channels, effectively improving user engagement and campaign results. The membership monitoring module acquires member registration information and monitors consumption data, allowing businesses to gain a deeper understanding of members' consumption habits and preferences. This helps businesses optimize their membership management system, improve member satisfaction and loyalty, and provides data support for subsequent precision marketing and personalized services. The data analysis module analyzes consumption data and generates data reports, enabling businesses to more intuitively understand market dynamics and sales performance. 2. The code source data module integrates different code sources and centrally distributes them, ensuring the uniqueness and accuracy of the code sources. This helps enterprises achieve full lifecycle tracking and management of products, improving the accuracy of product traceability. The data platform application module collects data from various business systems and verifies, cleans, and integrates it, forming high-quality data assets. This helps enterprises break down data silos, achieve data sharing and reuse, and improve data value and utilization. The early warning center submodule monitors and issues early warnings for abnormal data according to preset rules, ensuring the stability and security of the system. This helps enterprises promptly identify and handle potential problems, avoiding impacts on business operations and user experience. Attached Figure Description

[0023] Figure 1 This is a structural block diagram of a digital liquor industry internet platform according to an embodiment of this application;

[0024] Figure 2 This is a structural block diagram of the marketing activity management module in the embodiments of this application;

[0025] Figure 3 This is a structural block diagram of the member monitoring module in the embodiments of this application; Figure 4 This is a structural block diagram of the data analysis module in an embodiment of this application; Figure 5 This is a structural block diagram of the RFID management module in the embodiments of this application. Detailed Implementation

[0026] The following is in conjunction with the appendix Figures 1-5 This application will be described in further detail.

[0027] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0030] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0031] This application provides a digital liquor industry internet platform, executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication. This application does not impose any limitations on this connection. Figure 1 As shown, the platform includes: The RFID management module 10 is used to determine the identity information of the liquor and trace marketing data, wherein the identity information is the QR code of each bottle of liquor; In this embodiment, the QR code is stored on a QR code platform, which sends the code packet to an RFID management platform. The RFID management platform generates a unique RFID value based on a specific algorithm. The QR code is then printed on the surface of an RFID tag, and the generated RFID value is written into the RFID tag, completing the association between the QR code and the RFID tag. The action of printing the QR code on the RFID tag surface is prior art, and this embodiment does not specifically limit its application. Based on the existing box-and-carton association station, the original functions are retained, and the tags are upgraded to RFID + QR code tags to adapt to new identification requirements. Products with RFID tags are verified and stacked to ensure product accuracy. The main equipment includes a stacking RFID reader, a stacking QR code reader, and a verification QR code reader.

[0032] When products leave the warehouse, an RFID collection area is set up in front of the warehouse gate. When a forklift carrying a whole stack of products passes through, the system can read the RFID information of the whole stack in real time to complete the fast outbound operation.

[0033] The marketing activity management module 20 establishes a personalized reward service based on the identity information of the liquor. The personalized reward service is to formulate different reward services according to different application scenarios and different scanning channels. In this embodiment of the application, the marketing preparation unit 201 is used to acquire user data, the user data including the user's location; the activity determination unit 202 is used to analyze the user data to obtain a user profile, determine a matching activity category based on the user profile, and push it to the user so that the user can participate in the activity; the marketing result determination unit 203 records the user data of the users who participated in the activity.

[0034] The member monitoring module 30 obtains member registration information based on the personalized reward service, monitors the member information, and obtains consumption data. In this embodiment of the application, the membership system establishment unit 301 is used to obtain the user's membership information and determine the user's membership level based on the membership information; the membership data unit 302 is used to analyze the membership information and tag the user to obtain users in different groups; the membership information push unit 303 is used to analyze the users in different groups to obtain the group type and push messages based on the group type.

[0035] The data analysis module 40 is used to receive the consumption data, analyze the consumption data, and obtain data reports.

[0036] In this embodiment, the market dynamic monitoring unit 401 is used to coordinate logistics status data and determine logistics data based on the identity information of the liquor, wherein the logistics data includes data on channels, distributors, terminals, and consumers; the sales performance analysis unit 402 is used to analyze the statistical indicators of the number of product categories with sales volume and the ratio of monthly sales volume to current inventory based on the logistics data; the data visualization unit 403 displays the data analysis results in a graphical manner, including activity status, target achievement status, prize distribution status, and sales volume.

[0037] like Figure 2 As shown, in one possible implementation of this application embodiment, the marketing activity management module 20 includes: Marketing preparation unit 201 is used to acquire user data, the user data including information about the user's location; The activity determination unit 202 is used to analyze the user data to obtain a user profile, determine the matching activity category based on the user profile, and push it to the user so that the user can participate in the activity. Marketing Results Determination Unit 203 records user data from the campaign.

[0038] In this embodiment, a map-based LBS service is integrated to obtain latitude and longitude coordinates through user authorization and combine them with a POI database to determine the user's location (e.g., supermarket / restaurant). User registration information is used to obtain age, gender, and mobile phone number location; RFID management module synchronizes scanning records (time, location, frequency); and the ERP system is integrated to obtain historical purchase categories, spending amounts, and frequencies. HBase column family database is used to store user data, with RowKey designed as user ID_timestamp, enabling efficient querying by user dimension; a GeoHash encoded index is established for geographic location data, supporting precise user filtering within a 5-kilometer radius. Apache Atlas is used to record data lineage, ensuring that location information comes from compliant channels.

[0039] Record users' historical behavior, spending power, and preference tags, such as the frequency of QR code scans in the past 90 days, the types of activities participated in (lottery / redeem / group purchase), and the duration of time spent on activity pages. Also record cumulative spending, average order value distribution, and the time of the most recent purchase. Analyze the QR code scan records using an LDA topic model to identify user preferences for categories such as "soy sauce flavor" and "gift boxes." Construct a GBDT classification model based on Spark MLlib, inputting the above features and outputting user stratification tags. This yields a complete user profile.

[0040] Use Drools to dynamically configure push strategies. For example, if a user's tag is "premium soy sauce flavor enthusiast" and their location is "premium restaurant," then push a Guojiao 1573 tasting event. If a user has been inactive for the past 30 days, trigger a "spend 500, get 100 off" coupon promotion to reactivate them. Record the user data who participated in the promotion.

[0041] In one possible implementation of this application embodiment, the marketing activity management module 20 further includes: Marketing risk control unit 204 screens the users participating in the activity and identifies high-risk users; The prize control unit 205 is used to acquire the number of times a user has participated in the lottery and the number of times a user has won a prize, and to control the frequency of the user's winnings. Anomaly warning unit 206 is used to monitor the prize collection status of the user during the activity; The prize pool early warning unit 207 is used to monitor the prizes of the activity and to issue a reminder when the prizes are below a preset prize threshold.

[0042] In this embodiment, a user behavior baseline is constructed: Flink is used to calculate historical user behavior data (such as scanning frequency and activity type) in real time to establish a normal behavior profile (e.g., ≤8 scans per device per day). An Isolation Forest algorithm is used to detect abnormal behavior, characterized by: a sudden increase in scanning frequency (month-on-month increase > 300%); abrupt changes in geographical location (e.g., scanning across provinces within one hour); and abnormal device fingerprint entropy (multiple accounts associated with the same device). Risk levels are then categorized as follows: Low risk: limiting daily lottery attempts (e.g., reducing from 10 to 3); Medium risk: requiring secondary verification via SMS; High risk: freezing the account and sending it to a manual review queue.

[0043] The initial winning rate is set based on the activity budget. Each time a user wins, the probability of winning subsequently decreases by P_new = P_base * (1 - 0.2 * N) (where N is the number of times a user has won). If a user fails to win for 10 consecutive times, a winning event is forcibly triggered. This award control algorithm improves the retention rate of active users.

[0044] By consuming prize claim logs from Kafka using Flink, abnormal patterns are identified (e.g., a single IP address claiming the same prize more than 20 times within 10 minutes); this is correlated with user profile data to flag "group cheating" behavior (e.g., multiple accounts associated with the same shipping address). When an anomaly is detected, a structured alert (including user ID and behavior history) is pushed within 30 seconds; serious violations (e.g., bulk theft of high-value prizes) trigger a voice call to notify the risk control specialist.

[0045] Multi-level threshold settings are available: a yellow alert is triggered when the remaining prize amount is less than 20%; a red alert is automatically pushed when the remaining amount is less than 10%. Near real-time synchronization of the prize pool inventory is achieved through Canal monitoring of the MySQL binlog. Prize data is stored in HBase wide tables, supporting queries by activity ID, prize type, and other dimensions. Integration with the supply chain system ensures that a purchase order is automatically generated and pushed to the purchasing department when the prize pool falls below the warning threshold; the prize pool warning mechanism guarantees no risk of interruption during the activity.

[0046] like Figure 3 As shown, in one possible implementation of this application embodiment, the member monitoring module 30 includes: The membership system establishment unit 301 is used to obtain the user's membership information and determine the user's membership level based on the membership information; Member data unit 302 is used to analyze the member information and tag users to obtain users in different groups; The member information push unit 303 is used to analyze users in different groups to obtain group types and push messages based on the group types.

[0047] In this embodiment, member data originates from user registration information: basic fields such as mobile phone number, name, and birthday, collected through a front-end form and transmitted to the back-end in encrypted form. Transaction data: integrated with the ERP system to obtain user spending amount, frequency, and category preferences (e.g., soy sauce-flavored / strong-flavored baijiu). Behavioral data: synchronously recorded via RFID management module (time, location, type of activity participated in). DataX is used to synchronize heterogeneous data sources, integrating MySQL (user basic data), Hive (transaction data), and Kafka (behavioral logs) into an HBase wide table. The RowKey is designed as user ID_timestamp, supporting efficient queries by user dimension. Membership level classification adopts the RFM model, defining the following metrics: R (last consumption time): number of days since the current date; F (consumption frequency): number of orders in the past 12 months; M (spending amount): cumulative spending amount in the past 12 months. Tier Classification: Bronze: R < 90 days, F < 3 times, M < 1000 yuan; Silver: R < 60 days, F 3-5 times, M 1000-5000 yuan; Gold: R < 30 days, F 5-10 times, M 5000-20000 yuan; Diamond: R < 15 days, F > 10 times, M > 20000 yuan. User spending data is calculated in real-time using Flink. When a user reaches a higher tier threshold, a tier upgrade is automatically triggered (e.g., from Silver to Gold), and the user is notified via SMS and app push notifications.

[0048] Cluster analysis is performed based on user attributes, behaviors, and value to determine user groups. Attributes include: basic attributes (age, gender, mobile phone number location), geographic tag (city of residence); behavioral tags (consumption behavior: category preference (using Apriori algorithm to mine association rules), price sensitivity (frequency of coupon usage); and interaction behavior (activity participation rate (e.g., "participating in at least one lucky draw per month"), content preference (e.g., "frequently browsing product review articles"). K-Means clustering is used: input features: RFM score, LTV prediction, activity participation frequency; output groups: potential customers (high LTV but low activity); loyal customers (high activity + high repurchase rate); dormant customers (low activity + low spending).

[0049] Drools is used to dynamically configure push strategies. For example, if a user is tagged as a "potential customer" and their birthday is approaching, a "spend 2000 and get 500 off" exclusive coupon is pushed; if a user is tagged as a "dormant customer," a "3-day inactivity wake-up" process is triggered, and a "free sample pack" promotion is pushed. Push content is dynamically generated using the FreeMarker template engine, supporting variable replacement (such as user name, exclusive discount code). A / B testing: different titles are pushed to the same user segment (e.g., "Your exclusive benefit has arrived" vs. "Don't miss it! Today only"), and click-through rates are tracked in real time using ClickHouse to optimize push copy.

[0050] like Figure 4 As shown, in one possible implementation of this application embodiment, the data analysis module 40 includes: The market dynamic monitoring unit 401 is used to coordinate logistics status data and determine logistics data based on the identity information of the liquor. The logistics data includes data on channels, distributors, terminals, and consumers. The sales performance analysis unit 402 is used to analyze the statistical indicators of the number of product categories with sales volume and the ratio of monthly sales volume to current inventory based on the logistics data. The data visualization unit 403 displays the data analysis results graphically, including activity status, goal achievement, prize distribution, and sales volume.

[0051] In this embodiment, the RFID tag data (including production batch, production date, and channel code) of each bottle of liquor is obtained through the RFID management module. Combined with QR code scanning records, a "one item, one code" end-to-end tracking system is established, covering four key nodes: channels, distributors, terminals, and consumers. IoT devices are deployed: RFID readers (such as ImpinjR700) and GPS locators are installed in warehouses, transport vehicles, and terminal stores to collect real-time data on location, temperature, humidity, vibration, etc. Third-party logistics systems are integrated: transportation trajectory data from carriers such as ZTO Express and SF Express is synchronized via API interfaces, with fields including waybill number, current status (in transit / received), and estimated arrival time. A dynamic trajectory map is built based on the Gaode Map JSAPI to display the entire chain path of liquor from production to consumption, supporting filtering by batch, distributor, and time range.

[0052] Key node marking: Mark the locations of warehouses, transit stations, and terminal stores on the map. Clicking on them will display detailed information (such as inbound time and inventory). This improves the transparency of the entire logistics chain.

[0053] Indicator Calculation: Category Sales Rate = Number of SKUs Sold in the Current Month / Total Number of SKUs on Sale × 100% (e.g., "Sales rate of Maotai-flavor liquor is 85%"). Inventory-to-Sales Ratio = Ending Inventory / Sales Volume in the Current Month (ideal range 1.5-2.0, warning will be issued if it exceeds this range).

[0054] By combining logistics and sales data (from the ERP system), we analyze sales performance differences across different regions, channels, and product categories. Using real-time Flink sales order data, we calculate minute-level sales turnover rate and inventory-to-sales ratio to support real-time replenishment decisions. Based on the Prophet time series algorithm, we predict sales volume for the next 7 days and generate replenishment recommendations by combining this data with inventory data.

[0055] Integrates with ClickHouse (logistics data), Redis (real-time metrics), and MySQL (business data), building a unified data view using Superset. Activity status: A funnel chart is used to display the activity participation process (browse → click → place order → repeat purchase), making the conversion rate at each stage clear at a glance.

[0056] The dashboard displays KPI achievement (such as "85% of sales target achieved"), with red / green indicators indicating progress.

[0057] Prize distribution details: A pie chart shows the distribution ratio of different prizes (e.g., "53-degree mini liquor accounts for 60% of the distribution"), and you can drill down to view the profiles of the prize-receiving users.

[0058] Sales Volume: A combination of line and bar charts displays time-series sales trends and category comparisons. Clicking on a map area allows you to drill down to the province, city, and store level to view detailed data (e.g., "Haidian District, Beijing: Terminal Sales Rate 92%"). Selecting "East China Region" automatically filters and displays relevant data such as activity results and prize distribution for that region.

[0059] One possible implementation of the embodiments of this application further includes: The code source data module is used to integrate different code sources and centrally distribute the code; The data platform application module collects data from various business systems and verifies, cleans, and integrates it to form high-quality data assets. The early warning center submodule monitors and issues early warnings for abnormal data based on preset rules.

[0060] In this embodiment, a general protocol adapter is constructed to support API integration with mainstream source code platforms, achieving interface compatibility through a dynamic proxy model. An Apache NiFi cluster is deployed, using processors such as TailFile and ExecuteSQL to collect data from MySQL (business data), Kafka (behavioral logs), and SFTP (third-party files). FlinkCDC is used to capture database changes, achieving near real-time synchronization. Over 400 validation rules are defined based on GreatExpectations. Missing values ​​are filled and outliers are corrected. A OneData system is constructed, defining a global data dictionary and fact table. Core metrics are registered through Apache Atlas to avoid redundant calculations. A rule engine is built using Drools, supporting hot deployment. Specific rule examples include: marketing campaigns: triggering an alert when a single user participates in more than 10 daily lottery draws; logistics monitoring: triggering an alert when the GPS trajectory of a transport vehicle deviates from the planned route by more than 10 kilometers.

[0061] One possible implementation of this application embodiment includes a data platform application module comprising: The cross-selling analysis unit is used to obtain the cross-selling volume within a preset time period, and then perform cross-selling volume analysis to obtain cross-selling data; The cross-selling early warning unit analyzes the cross-selling data and triggers an early warning mechanism when the cross-selling data is abnormal.

[0062] The cross-selling traceability unit determines the cross-selling code source through cross-selling data and traces the cross-selling code source.

[0063] In this embodiment, cross-regional scanning records (time, location, device ID) are obtained from the RFID management module, and a complete behavioral chain is constructed by combining them with logistics trajectory data (transport vehicle GPS, warehouse entry and exit records). Order information (distributor code, sales region, product batch) is obtained by connecting to the ERP system, and incremental synchronization with MySQL is achieved through DataX.

[0064] Calculate the cross-regional sales volume, i.e., Regional cross-regional sales volume = Σ (Number of scans in unauthorized areas - Number of scans in authorized areas), and the cross-regional sales rate = Cross-regional sales volume / Total sales volume × 100%. Construct a cross-regional sales heatmap based on the Gaode Map JSAPI, color-coding the severity of cross-regional sales by province / city (red > 10%, yellow 5%-10%, green < 5%). Clicking on a heatmap area allows you to view the flow of cross-regional products (e.g., "from East China warehouse to South China terminal").

[0065] Use Drools to build multi-level threshold rules, for example: Yellow alert: a single distributor's daily cross-regional sales volume > 50 bottles; Red alert: a single batch of products crosses more than 3 provincial regions. When a yellow alert is triggered: a push notification is sent to the company's WeChat group, requiring the regional manager to respond within 4 hours; when a red alert is triggered: a voice call is made to the legal department, and the distributor's account is suspended.

[0066] By binding RFID tags and QR codes, a full-chain traceability system is constructed, connecting production batches to warehouses, distributors, and end-users. A knowledge graph is built using Neo4j, with node types including "product," "batch," "distributor," and "region," and edge relationships representing "flow direction" and "cross-selling." Cross-selling paths are quickly located using Cypher statements.

[0067] like Figure 5 As shown, in one possible implementation of this application embodiment, the RFID management module 10 includes: The RFID tag preparation unit 101 receives the code packet from the QR code platform, generates the RFID value according to the algorithm, prints the QR code on the surface of the RFID tag, and writes the RFID value into the RFID tag. In production unit 102 of the packaging workshop, after scanning and associating the bottle, box and carton codes, RFID tags are affixed to the large boxes using an RFID tag labeling machine, and the QR code and RFID value are verified. Warehouse inbound / outbound unit 103 is equipped with RFID gates or RFID reading devices at the warehouse entrances and exits to enable rapid inbound / outbound operations for pallets or single boxes of products, and synchronizes the inbound / outbound data to the original QR code management platform.

[0068] In this embodiment, a code packet generated by a QR code platform (such as Alibaba Cloud CodeWin) is received, a unique RFID value is generated using the SHA-256 hash algorithm, and this value is written into the RFID tag via a chip. A variable data QR code, including the product batch number, production date, and verification code, is printed on the tag surface. A visual inspection system ensures that the QR code printing quality meets the ISO / IEC 15415 standard. A PLC control system is deployed to achieve a three-level code association between the bottle, box, and carton. The QR code on the bottle is captured by an industrial camera and logically bound to the RFID tag on the carton.

[0069] Labels are coded using a printer, and a custom verification protocol ensures the matching of QR codes and RFID values, increasing accuracy. An RFID reader array is deployed on the platform to achieve batch identification of RFID tags on the entire pallet (24 boxes / pallet), increasing reading distance and identification speed.

[0070] The MQTT protocol is used to synchronize inbound and outbound data to the existing QR code management platform in real time, reducing data latency.

[0071] The above embodiments describe a digital liquor industry internet platform from the perspective of method and process. The following embodiments describe a digital liquor industry internet platform device from the perspective of virtual modules or virtual units. For details, please refer to the following embodiments.

[0072] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0073] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A digital liquor industry internet platform, characterized in that, include: The RFID management module is used to determine the identity information of the liquor and trace marketing data. The identity information is the QR code of each bottle of liquor. The marketing campaign management module establishes personalized reward services based on the identity information of the liquor. The personalized reward services are designed according to different application scenarios and different scanning channels. The member monitoring module obtains member registration information based on the personalized reward service, monitors the members based on the member information, and obtains consumption data. The data analysis module is used to receive the consumption data, analyze the consumption data, and obtain data reports.

2. The digital liquor industry internet platform according to claim 1, characterized in that, The marketing campaign management module includes: A marketing preparation unit is used to acquire user data, including information about the user's location. The activity determination unit is used to analyze the user data to obtain a user profile, determine the matching activity category based on the user profile, and push it to the user so that the user can participate in the activity. The marketing results determination unit records user data related to the campaign.

3. The digital liquor industry internet platform according to claim 2, characterized in that, The marketing campaign management module also includes: The marketing risk control unit will screen the users participating in the activity and identify high-risk users. The prize-winning control unit is used to acquire the number of times a user has participated in the lottery and the number of times they have won, and to control the frequency of the user's winnings. An anomaly warning unit is used to monitor the prize collection status of the user during the activity; The prize pool early warning unit is used to monitor the prizes of the activity and issue a reminder when the prizes fall below a preset prize threshold.

4. The digital liquor industry internet platform according to claim 3, characterized in that, The member monitoring module includes: The membership system establishment unit is used to obtain users' membership information and determine users' membership levels based on the membership information. The member data unit is used to analyze the member information and tag users to obtain users in different groups. The member information push unit is used to analyze users in different groups to obtain group types and push messages based on the group types.

5. A digital liquor industry internet platform according to claim 4, characterized in that, The data analysis module includes: The market dynamic monitoring unit is used to coordinate logistics status data and determine logistics data based on the identity information of the liquor. The logistics data includes data on channels, distributors, terminals, and consumers. The sales performance analysis unit is used to analyze the statistical indicators of the number of product categories with sales volume and the ratio of monthly sales volume to current inventory based on the logistics data. The data visualization unit displays the data analysis results graphically, including activity status, goal achievement, prize distribution, and sales volume.

6. A digital liquor industry internet platform according to claim 5, characterized in that, Also includes: The code source data module is used to integrate different code sources and centrally distribute the code; The data platform application module collects data from various business systems and verifies, cleans, and integrates it to form high-quality data assets. The early warning center submodule monitors and issues early warnings for abnormal data based on preset rules.

7. A digital liquor industry internet platform according to claim 6, characterized in that, The data platform application modules include: The cross-selling analysis unit is used to obtain the cross-selling volume within a preset time period, and then perform cross-selling volume analysis to obtain cross-selling data; The cross-selling early warning unit analyzes the cross-selling data and triggers an early warning mechanism when the cross-selling data is abnormal.

8. A cross-border e-commerce traceability unit, which determines the cross-border e-commerce code source through cross-border e-commerce data and traces the cross-border e-commerce code source.

9. A digital liquor industry internet platform according to claim 7, characterized in that, The RFID management module includes: The RFID tag preparation unit receives the code packet from the QR code platform, generates the RFID value according to the algorithm, prints the QR code on the surface of the RFID tag, and writes the RFID value into the RFID tag. In the packaging workshop production unit, after scanning and associating the bottle, box and carton codes, RFID tags are affixed to the large cartons using an RFID tag labeling machine, and the QR code and RFID value are verified. The warehouse inbound / outbound unit is equipped with RFID gates or RFID reading devices at the warehouse entrances and exits to enable rapid inbound / outbound operations for pallets or single boxes of products, and synchronizes the inbound / outbound data to the existing QR code management platform.

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