A smart vending system and method for direct-to-consumer sales of branded goods.

Abstract

This invention relates to the field of smart vending technology, specifically a smart vending system and method for directly delivering branded goods to consumption scenarios. The system includes receiving marketing activity configuration data sent by a brand management platform and generating marketing activity task data; matching corresponding smart vending terminal identification data with target consumption scenario identification data to generate terminal-issued task data; the smart vending terminal generating product display control data and user interaction control data based on the terminal-issued task data; generating user access session data, user behavior data, and scenario transaction data; generating marketing analysis data; and feeding it back to the brand management platform. This solution establishes a full-link data association mechanism for branded goods, from marketing activity configuration, scenario terminal deployment, user behavior tracking to transaction conversion analysis, improving the accuracy of marketing activity delivery, user behavior analysis capabilities, and marketing effectiveness evaluation capabilities, thereby achieving intelligent marketing management in consumption scenarios.

Description

Technical Field

[0001] This invention relates to the field of smart vending, specifically a smart vending system and method for directly delivering branded goods to consumer scenarios. Background Technology

[0002] With the development of IoT, cloud computing, mobile internet, and smart terminal technologies, new retail systems based on online-offline integration are gradually becoming important technological carriers for commodity circulation and digital marketing. These systems typically construct data interaction networks through cloud service platforms, smart terminal devices, and user terminals to realize functions such as commodity information dissemination, terminal control, user interaction, and transaction processing. Within this technological framework, commodity information, scenario information, terminal operation information, and user interaction information can all be collected, transmitted, and processed in digital form, thereby forming a data-driven commodity service model tailored to specific consumption scenarios.

[0003] Currently, in the field of digital marketing for branded goods, brand management platforms are typically used to configure marketing campaigns, and product information is displayed to users through terminal devices such as vending machines, smart display cabinets, and self-service experience devices. These systems generally distribute product display tasks to terminal devices via a cloud platform, allowing the devices to complete product display, advertising content playback, QR code display, or product sales operations. Users access the corresponding product or transaction page after identifying the terminal device via their mobile devices. The system further records user access and transaction behavior and uploads the relevant data to the backend platform for statistical analysis, thus forming an integrated business process encompassing product display, user interaction, and transaction processing.

[0004] The inventors of this application have discovered that the above-mentioned technical solutions have at least the following technical problems: In the prior art, marketing activity data, consumption scenario data, terminal deployment data, user interaction data, and transaction data are usually processed by multiple independent modules, lacking a unified data association mechanism. This makes it difficult to establish a stable data mapping relationship between marketing activities and terminal execution results in different consumption scenarios. At the same time, the behavioral link data formed by users from terminal identification, access to marketing content to transaction completion suffers from scattered storage and insufficient correlation, making it difficult to construct complete user access session data and scenario transaction data. Furthermore, there is a lack of a unified data collection and analysis mechanism among the terminal interaction data, user behavior data, and transaction data generated by different smart vending terminals, making it difficult to form full-link data analysis results based on consumption scenarios. Summary of the Invention

[0005] This application provides an intelligent sales system and method for branded goods to directly reach consumption scenarios, solving the problem that branded goods marketing activities cannot accurately reach consumption scenarios and lack full-link effect tracking.

[0006] To achieve the above objectives, the embodiments of this application disclose the following technical solutions:

[0007] On the one hand, this solution discloses an intelligent sales method for branded goods to directly reach consumer scenarios, including:

[0008] S1. The central cloud service platform receives marketing campaign configuration data sent by the brand's management platform. This data includes brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data. The platform performs structured parsing on this data to generate marketing campaign task data. This structured parsing is not simply a data format conversion; rather, it establishes the relationships between brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data through a unified data organization method. This transforms the originally scattered marketing configuration content into marketing campaign task data that can be directly accessed by subsequent smart vending terminals, ensuring data consistency and traceability throughout the marketing campaign deployment process from the source.

[0009] S2. Based on the target consumption scenario identification data, query the terminal deployment database to obtain the smart vending terminal identification data corresponding to the target consumption scenario identification data, and establish a correlation between marketing activity task data and smart vending terminal identification data to generate terminal-issued task data. The introduction of this correlation mechanism between target consumption scenario identification data and smart vending terminal identification data aims to address the low utilization rate of terminal resources and insufficient adaptability of marketing content to consumption scenarios caused by traditional marketing activities relying on manual deployment. By establishing a data mapping relationship between marketing activity task data and smart vending terminal identification data, marketing activities can be deployed in a targeted manner based on actual consumption scenarios, thereby improving the accuracy of brand products reaching the target user group.

[0010] S3. The terminal sends the task data to the corresponding smart vending terminal. The smart vending terminal parses the task data and generates product display control data and user interaction control data. Based on the product display control data, the smart vending terminal controls the display interface to output marketing content. The product display control data and user interaction control data adopt a separate control structure, which can manage the display logic and interaction logic independently. This avoids the impact of updating the display content on the interaction process, while ensuring that different smart vending terminals can execute consistent marketing activities based on unified task data.

[0011] S4. Receive terminal identification data uploaded by the user terminal, obtain the corresponding marketing activity task data based on the terminal identification data, and generate user access session data corresponding to the marketing activity task data; wherein, by constructing user access session data, a unique correspondence is established between the user terminal and the marketing activity task data, thereby forming a data link that runs through the access, interaction and transaction process, providing a unified data foundation for subsequent correlation analysis of user behavior data and scenario transaction data.

[0012] S5. Based on user access session data, send marketing content data and purchase path data to the user terminal, and receive user interaction data returned by the user terminal. Associate the user interaction data with the user access session data to generate user behavior data. In this application, it is not only to count isolated access records generated by the user terminal, but to use user access session data to associate and map user interaction data, so that each behavioral event has a unified session context, thereby truly reflecting the continuous behavioral characteristics of users in marketing activities.

[0013] S6. Receive transaction data generated based on purchase path data, associate and store the transaction data with user behavior data, and generate scenario transaction data. By associating and storing the transaction data with user behavior data, the transaction results can be traced back to the corresponding user access process and marketing activity process, thereby solving the problem that traditional marketing systems cannot accurately identify the source of transactions and realizing a closed-loop association between marketing behavior and transaction behavior.

[0014] S7 collects terminal interaction data uploaded from smart vending terminals and user behavior data uploaded from user terminals. It then aggregates and analyzes this terminal interaction data, user behavior data, and scenario transaction data to generate marketing analysis data, which is then sent to the brand management platform. By unifying and analyzing terminal interaction data, user behavior data, and scenario transaction data, a full-link analysis system covering marketing content display, user behavior conversion, and transaction result feedback is formed. This allows the brand management platform to not only obtain marketing results but also the key influencing factors in the formation of marketing results, thereby improving the accuracy of marketing campaign optimization decisions.

[0015] To avoid deployment failures due to discrepancies in data structures uploaded to the brand management platform, this application first performs field parsing and format validation on the marketing campaign configuration data, and then establishes a relationship between the marketing campaign identifier and the brand product identifier data. Compared to directly storing the original configuration data, this solution ensures that the data structure called during the generation of task data issued by the subsequent terminals remains consistent, thereby improving the stability of the entire marketing campaign deployment process.

[0016] This application does not simply retrieve smart vending terminals based on target consumption scenario identification data. Instead, it further incorporates terminal attribute data for filtering after obtaining the smart vending terminal identification data. By matching marketing campaign needs with terminal resource capabilities, it avoids deploying marketing campaigns to smart vending terminals with insufficient functionality or abnormal operation, thereby improving the success rate of marketing campaign execution.

[0017] To ensure seamless coordination between the marketing content display and user interaction processes, this application converts terminal-issued task data into product display control data and user interaction control data, respectively. This approach creates a unified business chain for the displayed content and the interaction flow, guaranteeing both accurate presentation of marketing content and seamless user follow-up actions along the pre-defined purchase path.

[0018] This application establishes a correspondence between user terminals and marketing campaign identifiers through access session identifiers. Its purpose is not merely to record access behavior, but to construct a data tracking mechanism covering the entire marketing campaign cycle. The introduction of access session identifiers effectively solves the data confusion problem caused by multiple user visits or the parallel execution of different marketing campaigns.

[0019] This application describes the evolution of user behavior during marketing campaigns by constructing user behavior trajectory data, rather than relying solely on single clicks or visits for analysis. By establishing correlations between behavioral events in chronological order, it can more accurately reflect the process of changing user interests and the formation of purchase intentions, providing continuous behavioral evidence for subsequent transaction correlation analysis.

[0020] This application associates and aggregates transaction data with user behavior data, enabling transaction results to be mapped to specific marketing campaigns and specific user behavior processes. This approach not only allows for the tracking of transaction sources but also identifies the actual contribution of different marketing activities to transaction results, thereby improving the accuracy of marketing effectiveness evaluation.

[0021] In order to eliminate the interference of abnormal data in the terminal operation data on the analysis results, this application first performs outlier filtering on the terminal operation data and generates standardized terminal interaction data, and then establishes a unified data analysis object.

[0022] This application does not directly statistically analyze marketing campaign results. Instead, it first generates campaign interaction statistics, campaign visit statistics, and campaign transaction statistics, and then correlates and aggregates these statistics to form a marketing campaign analysis record. By constructing this marketing campaign analysis record, a unified analysis of marketing process data and marketing result data is achieved, thereby providing more comprehensive data support for optimizing brand product operation strategies.

[0023] On the other hand, this solution discloses an intelligent vending system for branded goods to directly reach consumer scenarios, including an activity task generation module, a scenario matching module, a terminal control module, a session management module, a behavior analysis module, a transaction association module, and a marketing analysis module. These modules do not operate independently but rather establish a continuous data transmission link around marketing activity task data. After generating marketing activity task data, the activity task generation module transmits it to the scenario matching module. The scenario matching module then generates terminal-issued task data and transmits it to the terminal control module. The session management module, behavior analysis module, and transaction association module further construct data associations between user behavior and transaction behavior. Finally, the marketing analysis module completes the full-link data analysis. Through this collaborative mechanism, closed-loop management of branded goods is achieved, encompassing marketing deployment, terminal display, user interaction, transaction conversion, and marketing analysis.

[0024] This invention establishes a full-link correlation mechanism between marketing campaign configuration data, smart vending terminal identification data, user access session data, user behavior data, and scenario transaction data. This enables closed-loop management of branded products from marketing campaign launch, terminal deployment, user outreach, behavior collection, to transaction conversion analysis, improving the precision and efficiency of marketing campaigns across different consumption scenarios. By matching target consumption scenario identification data with smart vending terminal identification data, targeted deployment of marketing campaigns can be automatically completed based on terminal attribute data, reducing manual configuration workload and improving terminal resource utilization. By establishing user access session data and user behavior trajectory data, continuous tracking of user access paths, interaction processes, and purchasing behavior during marketing campaigns can be achieved, realizing a precise correlation between user behavior and transaction results. Furthermore, by unifying and analyzing terminal interaction data, user behavior data, and scenario transaction data to form marketing analysis data, the marketing effectiveness of different marketing campaigns, different consumption scenarios, and different smart vending terminals can be accurately evaluated, providing quantifiable data-driven decision-making support for brand management platforms. This achieves digital, traceable, and intelligent management of the branded product marketing process, improving marketing conversion efficiency, scenario operation capabilities, and marketing resource allocation efficiency. Attached Figure Description

[0025] Figure 1 This is an overall flowchart of the method according to Embodiment 1 of the present invention;

[0026] Figure 2 This is a system structure diagram of Embodiment 2 of the present invention;

[0027] Figure 3 This is a system interaction timing diagram of Embodiment 2 of the present invention;

[0028] Figure 4 This is a flowchart illustrating the marketing activity task data generation and terminal distribution process according to Embodiment 1 of the present invention.

[0029] Figure 5 This is a flowchart illustrating the process of generating user access session and behavior data according to Embodiment 1 of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In the following description, numerous specific details are set forth to provide a comprehensive understanding of the present invention. The present invention may be practiced without some or all of these specific details. In other instances, well-known processes have not been described in detail to avoid unnecessarily obscuring the present invention.

[0031] When used in conjunction with the terms "comprising," "method comprising," or similar language in this specification and appended claims, the singular forms "a," "some," and "the" include plural references unless the context clearly indicates otherwise. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0032] Example 1

[0033] This embodiment provides an intelligent sales method for branded goods directly reaching consumer scenarios, including:

[0034] Step 1: Receive marketing campaign configuration data and generate marketing campaign task data

[0035] In this embodiment, the central cloud service platform first receives marketing campaign configuration data sent by the brand's management platform via an application programming interface (API). The marketing campaign configuration data is encapsulated using a predefined data structure, such as JSON, XML, or a database object structure. Upon receiving the marketing campaign configuration data, the central cloud service platform invokes a parsing engine to perform field-level parsing of the brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data.

[0036] In the specific implementation process, the system first performs field validity checks, including field length checks, field format checks, and field integrity checks. After the checks are completed, the system writes the parsed fields into the corresponding database table structure according to preset mapping rules, forming the basic data for the marketing campaign.

[0037] Subsequently, the central cloud service platform generates a marketing campaign identifier based on the basic data of the marketing campaign and establishes a mapping relationship between the marketing campaign identifier and the brand product identifier data.

[0038] The generated marketing campaign task data is written into the campaign task database, serving as the data source for subsequent terminal deployment and task scheduling.

[0039] The principle is to convert the original marketing activity configuration data into a unified data object through a structured parsing process, thereby ensuring that the subsequent smart vending terminals can execute marketing tasks according to unified rules.

[0040] Step 2: Establish the correlation between marketing campaign task data and smart vending terminal identification data.

[0041] In this embodiment, the central cloud service platform reads the target consumption scenario identification data from the marketing activity task data and accesses the terminal deployment database to obtain the smart vending terminal identification data in the corresponding scenario. The terminal deployment database stores the smart vending terminal identification data and the terminal attribute data corresponding to the smart vending terminals. The terminal attribute data includes terminal type, terminal location, terminal status, and terminal functional capabilities information.

[0042] The terminal deployment database records terminal attribute data for smart vending terminals, including terminal type, location, status, and functional capabilities. The system performs filtering based on this terminal attribute data, such as filtering for smart experience cabinets that support sample mode or smart vending machines that support vending machine mode.

[0043] Subsequently, the system performs a matching operation between the filtered smart vending terminal identification data and the marketing campaign task data.

[0044] In this embodiment, the system filters and sorts smart vending terminals that meet the deployment conditions based on the target consumption scenario identification data and terminal attribute data in the marketing activity task data.

[0045] When a smart vending terminal meets preset deployment conditions, the corresponding smart vending terminal identification data is written into the terminal's task data. Meeting the preset deployment conditions includes one or more of the following: terminal location matching with the target consumption scenario, terminal online status, and terminal functional capability adaptation.

[0046] After matching is completed, terminal-issued task data is generated, and a data index relationship is established between the terminal-issued task data and the marketing activity task data.

[0047] Its principle lies in achieving targeted deployment of marketing activities through a data mapping mechanism between consumption scenarios and terminal resources.

[0048] Step 3: Generate product display control data and user interaction control data

[0049] In this embodiment, after receiving the task data issued by the terminal, the smart vending terminal parses and processes the marketing content data and purchase path configuration data therein.

[0050] Marketing content data is processed by the display template engine to generate product display control data. This data is used to control the image assets, video assets, text content, and their display order on the terminal display interface.

[0051] The purchase path configuration data is processed by the interaction flow engine to generate user interaction control data. This user interaction control data is used to control QR code generation, page navigation, and interactive event responses.

[0052] In a preferred embodiment, the smart vending terminal includes a terminal display module and a terminal interaction module. Product display control data is loaded into the terminal display module, and user interaction control data is loaded into the terminal interaction module.

[0053] In this embodiment, while performing product display control and user interaction control, the smart vending terminal can also simultaneously output terminal identification information for user identification. Terminal identification information can be presented through dynamic QR codes, near-field communication (NFC) identification information, or image recognition identification information. After reading the terminal identification information, the user terminal generates terminal identification data and sends it to the central cloud service platform to trigger the creation of subsequent user access session data.

[0054] Its principle lies in converting marketing campaign content into terminal-executable control commands, thereby achieving a unified drive for display logic and interaction logic.

[0055] Step 4: Generate user access session data

[0056] In this embodiment, the user terminal obtains terminal recognition data through dynamic QR code recognition, near-field communication recognition, or image recognition.

[0057] After receiving the terminal identification data, the central cloud service platform analyzes the smart vending terminal identification data and the user's smart vending terminal identification data, and queries the corresponding marketing activity task data based on the smart vending terminal identification data.

[0058] The system extracts marketing campaign identifiers and combines them with smart vending terminal identifier data and user smart vending terminal identifier data to generate user access request data.

[0059] After generating the access session identifier, an association is established between the access session identifier and the marketing campaign identifier, thereby forming user access session data.

[0060] The principle behind this is to establish a unique data link for each user visit in order to enable subsequent behavior tracking.

[0061] Step 5: Generate user behavior data

[0062] In this embodiment, the central cloud service platform pushes marketing content data and purchase path data to the user terminal based on the user access session data.

[0063] After user terminals generate page visit data, marketing content click data, and purchase path access data, they upload them to the central cloud service platform. The system then categorizes user interaction data into display behavior, browsing behavior, click behavior, and purchase behavior based on preset behavior classification rules.

[0064] In this embodiment, preset behavior classification rules are used to determine behavior categories based on the interaction type corresponding to user interaction data; wherein, page access data corresponds to browsing behavior, marketing content click data corresponds to click behavior, and purchase path access data corresponds to purchase behavior; when the user terminal receives marketing content display, a display behavior is generated accordingly.

[0065] Subsequently, the system establishes the correlation between user behavior event data based on the timestamp order, forming user behavior trajectory data.

[0066] User behavior trajectory data is used to record the user's access process, interaction process, and purchase path access process during marketing activities.

[0067] The system associates and stores user behavior event data with user access session data to generate user behavior data.

[0068] Step 6: Generate scenario transaction data

[0069] In this embodiment, the purchase path data is used to guide the user terminal to the corresponding transaction system to complete the purchase operation. The transaction system can be a brand merchant's online store system, an e-commerce platform system, a mini-program transaction system, or a smart vending terminal with a built-in payment system. After the user completes the order, payment, or order confirmation in the transaction system, the transaction system generates the corresponding transaction data and sends it to the central cloud service platform through an application programming interface, message queue, or data synchronization interface.

[0070] Subsequently, the central cloud service platform receives the transaction data returned by the transaction system and parses the order identification data, product identification data, and transaction time data.

[0071] In this embodiment, the central cloud service platform receives transaction data returned by the transaction system and parses order identification data, product identification data, and transaction time data.

[0072] The system queries the corresponding user access session data based on the order identifier data and establishes a correlation between transaction data and user behavior data.

[0073] Subsequently, the data is aggregated according to the marketing campaign identifier, generating scenario transaction records and writing them into the scenario transaction database to form scenario transaction data.

[0074] The principle behind this is to establish a data mapping relationship between marketing activities and transaction activities, thereby enabling the tracking of transaction origins.

[0075] Step 7: Generate marketing analytics data

[0076] In this embodiment, the central cloud service platform receives terminal operation data uploaded by smart vending terminals and user behavior data uploaded by user terminals.

[0077] Terminal operation data includes terminal display count data, terminal interaction count data, and terminal identification trigger data. The system first performs outlier filtering and standardization processing to generate standardized terminal interaction data.

[0078] The standardized terminal interaction data is correlated with user behavior data and scenario transaction data; a data analysis object containing standardized terminal interaction data, user behavior data and scenario transaction data is established.

[0079] The system performs correlation analysis on terminal interaction data, user behavior data, and scenario transaction data to generate marketing analysis data.

[0080] The principle behind this is to use the relationships between data across the entire value chain to build contextualized analysis results for marketing campaigns.

[0081] Example 2

[0082] This embodiment discloses an intelligent vending system for direct-to-consumer scenarios of branded goods, including an activity task generation module, a scenario matching module, a terminal control module, a session management module, a behavior analysis module, a transaction association module, and a marketing analysis module. Each module establishes a unified data interaction link through a central cloud service platform. The activity task generation module communicates with the brand management platform, as does the marketing analysis module. The remaining modules are connected sequentially according to the flow order of marketing activity task data, terminal-issued task data, user access session data, user behavior data, and scenario transaction data, thus forming a closed-loop business architecture covering marketing activity creation, terminal deployment, user interaction, transaction association, and effect analysis.

[0083] In this embodiment, the activity task generation module receives marketing activity configuration data sent by the brand management platform, parses and processes brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data to generate marketing activity task data, which is then sent to the scenario matching module. The scenario matching module queries the terminal deployment database based on the target consumption scenario identification data, combines it with terminal attribute data to complete terminal filtering and matching calculations, generates terminal-issued task data, and sends it to the terminal control module, thereby achieving precise mapping between marketing activities and target terminal resources.

[0084] The terminal control module receives task data from the terminal, generates product display control data and user interaction control data, and drives the smart vending terminal to perform product display and user interaction. When the user terminal recognizes the smart vending terminal, the session management module receives the terminal identification data, queries the corresponding marketing activity task data based on the smart vending terminal identification data, establishes user access session data, and transmits the user access session data to the behavior analysis module. The behavior analysis module further receives user interaction data, generates user behavior data through behavior correlation analysis, and sends it to the transaction correlation module.

[0085] The transaction association module receives transaction data returned by the transaction system, associates and processes this transaction data with user behavior data, and generates scenario-based transaction data. The marketing analysis module simultaneously receives terminal interaction data, user behavior data, and scenario-based transaction data, performs aggregated analysis through a unified data analysis object, generates marketing analysis data, and feeds it back to the brand management platform.

[0086] The innovation of this embodiment lies in integrating target consumption scenario identification data throughout the entire data chain, ensuring a unified and correlated identification for marketing campaign task data, terminal-issued task data, user access session data, user behavior data, and scenario transaction data. Based on this, a scenario matching module enables dynamic adaptation between marketing campaigns and smart vending terminals, a session management module tracks the entire user access process, a transaction association module maps and correlates user behavior with transaction behavior, and finally, a marketing analysis module performs closed-loop analysis of the entire data chain. This achieves precise targeting, reach, and evaluation of branded products within the target consumption scenario.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation methods of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A smart sales method for branded goods directly reaching consumer scenarios, characterized in that, include: S1. The central cloud service platform receives marketing activity configuration data sent by the brand management platform. The marketing activity configuration data includes brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data. The platform performs structured parsing on the marketing activity configuration data to generate marketing activity task data. S2. Based on the target consumption scenario identification data, query the terminal deployment database, obtain the smart vending terminal identification data corresponding to the target consumption scenario identification data, establish the association between marketing activity task data and smart vending terminal identification data, and generate terminal-issued task data; S3. Send the task data from the terminal to the corresponding smart vending terminal. The smart vending terminal parses the task data from the terminal, generates product display control data and user interaction control data, and controls the smart vending terminal to output marketing content based on the product display control data. S4. Receive terminal identification data uploaded by the user terminal, obtain the corresponding marketing activity task data based on the terminal identification data, and generate user access session data corresponding to the marketing activity task data. S5. Based on user access session data, send marketing content data and purchase path data to the user terminal, and receive user interaction data returned by the user terminal. Then, associate the user interaction data with the user access session data to generate user behavior data. S6. Receive transaction data generated based on purchase path data, associate and store the transaction data with user behavior data, and generate scenario transaction data; S7. Collect terminal interaction data uploaded by smart vending terminals and user behavior data uploaded by user terminals, aggregate and analyze terminal interaction data, user behavior data and scenario transaction data, generate marketing analysis data, and send it to the brand management platform.

2. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S1 generates marketing campaign task data including: Perform field parsing on brand product identification data, target consumption scenario identification data, marketing content data, and purchase path configuration data in the marketing campaign configuration data; The format of each parsed data item is validated according to the preset data structure. The validated data is mapped to the corresponding data storage fields to generate basic data for the marketing campaign. Based on the basic data of marketing activities, a marketing activity identifier is constructed, and the relationship between the marketing activity identifier and the brand product identifier data is established to generate marketing activity task data; Marketing campaign task data is written into the campaign task database, which stores marketing campaign task data, and serves as the basis for generating subsequent task data issued by the terminal.

3. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S2, establishing the association between marketing campaign task data and smart vending terminal identification data, includes: Read the target consumption scenario identifier data from the marketing campaign task data; Based on the target consumption scenario identification data query terminal deployment database, obtain the corresponding smart vending terminal identification data and terminal attribute data; The acquired smart vending terminal identification data is filtered based on terminal attribute data; The filtered smart vending terminal identification data is matched with the marketing campaign task data. Generate terminal-issued task data that includes marketing campaign identifiers, smart vending terminal identifiers, and task execution time information, and establish a data index relationship between the terminal-issued task data and the marketing campaign task data.

4. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S3 generates product display control data and user interaction control data, including: Receive task data sent by the terminal, and parse the marketing content data and purchase path configuration data in the task data sent by the terminal. Generate product display control data based on marketing content data to control the display interface; Generate user interaction control data based on purchase path configuration data to control the user interaction process; Product display control data is loaded into the terminal display module of the smart vending terminal, and user interaction control data is loaded into the terminal interaction module of the smart vending terminal. Terminal display control and user interaction control are executed based on product display control data and user interaction control data.

5. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S4, obtaining user access session data, includes: Receive terminal identification data uploaded by user terminals; parse the smart vending terminal identification data and user smart vending terminal identification data in the terminal identification data; Based on the identification data of the smart vending terminal, query the corresponding marketing activity task data; Extract marketing campaign identifiers from marketing campaign task data, and generate user access request data based on marketing campaign identifiers, smart vending terminal identifier data, and user smart vending terminal identifier data; Create an access session identifier based on the user's access request data; Establish the association between access session identifiers and marketing campaign identifiers to generate user access session data.

6. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S5 generates user behavior data including: Marketing content data and purchase path data are sent to user terminals based on user access session data; Receive user interaction data returned by the user terminal. The user interaction data includes page visit data, marketing content click data, and purchase path access data. User interaction data is categorized and processed according to preset behavior classification rules to generate corresponding user behavior event data; Associate and map user behavior event data with user access session data; User behavior trajectory data is constructed in chronological order, and user behavior data is generated based on the user behavior trajectory data.

7. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S6 generates scenario transaction data including: Receive transaction data returned by the transaction system, and parse the order identification data, brand product identification data, and transaction time data in the transaction data; Query the corresponding user access session data based on the order identifier data; Establish a correlation between transaction data and user behavior data; The associated data is collected and processed according to the marketing campaign identifier to generate scenario transaction records that include marketing campaign identifier, smart vending terminal identifier data, user behavior data, and transaction data. The transaction records of the scenario are stored and processed to generate scenario transaction data.

8. The intelligent vending method for directly delivering branded goods to consumption scenarios according to claim 1, characterized in that, Step S7 involves collecting terminal interaction data, including: Receive terminal operation data uploaded by smart vending terminals. The terminal operation data includes terminal display count data, terminal interaction count data, and terminal recognition trigger data. Based on preset data cleaning rules, outlier filtering is performed on the terminal operation data to generate standardized terminal interaction data; Correlate standardized terminal interaction data with user behavior data and scenario transaction data; establish a unified data analysis object; Perform correlation analysis on a unified data analysis object to generate marketing analysis data.

9. A smart vending method for directly delivering branded goods to consumption scenarios according to claim 8, characterized in that, The generated marketing analytics data includes: Read the unified data analysis object and extract terminal interaction data, user behavior data, and scenario transaction data from it; Data is aggregated and processed according to marketing campaign identifiers to generate campaign interaction statistics, campaign access statistics, and campaign transaction statistics. The activity interaction statistics, activity access statistics, and activity transaction statistics are correlated and aggregated to generate marketing activity analysis records; The data is aggregated and processed according to the brand product identification data to generate corresponding marketing analysis data, which is then sent to the brand management platform.

10. An intelligent vending system for direct-to-consumption scenarios of branded goods, characterized in that, include: The activity task generation module is used to receive marketing activity configuration data sent by the brand management platform, and to parse and process the brand product identification data, target consumption scenario identification data, marketing content data and purchase path configuration data in the marketing activity configuration data to generate marketing activity task data. The scene matching module, connected to the activity task generation module, is used to receive marketing activity task data, query the terminal deployment database based on the target consumption scenario identification data, obtain the corresponding smart vending terminal identification data, establish the association between marketing activity task data and smart vending terminal identification data, and generate terminal-issued task data. The terminal control module, connected to the scene matching module, is used to receive task data sent by the terminal, parse and process the task data sent by the terminal, generate product display control data and user interaction control data, and control the smart vending terminal to perform product display and user interaction based on the product display control data and user interaction control data. The session management module communicates with the terminal control module and the user terminal. It is used to receive terminal identification data uploaded by the user terminal, obtain the corresponding marketing activity task data based on the terminal identification data, and generate user access session data corresponding to the marketing activity task data. The behavior analysis module, connected to the session management module, is used to receive user interaction data returned by the user terminal, associate the user interaction data with the user access session data, and generate user behavior data. The transaction association module, connected to the behavior analysis module, is used to receive transaction data returned by the transaction system, associate the transaction data with user behavior data, and generate scenario transaction data. The marketing analytics module is connected to the terminal control module, behavior analysis module, and transaction association module, respectively. It is used to receive terminal interaction data, user behavior data, and scenario transaction data uploaded by smart vending terminals, aggregate and analyze the terminal interaction data, user behavior data, and scenario transaction data to generate marketing analytics data, and send the marketing analytics data to the brand management platform.

Images