Product delivery data processing method and platform for multi-end clients

Abstract

The invention discloses a multi-end customer-oriented product delivery data processing method and platform, and relates to the technical field of data processing, and the method comprises the steps: constructing a one-stop customer interaction platform which comprises a customer interface layer, a business logic layer, a data management layer and a product service layer; client demand information is obtained through the client interface layer; the data management layer obtains a target product delivery scheme; the business logic layer generates product delivery order information and product delivery bill information; payment encryption processing is carried out through the product service layer to obtain product delivery data information; and data verification processing is carried out through the product service layer. The technical problems of poor product delivery efficiency and accuracy, low customer satisfaction degree and difficulty in adapting to rapid change of modern markets and diversification of customer requirements due to information isolated island, tedious process and response lag existing in existing product delivery are solved. The technical effect of improving the product delivery efficiency, accuracy, pertinence and customer satisfaction is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to data processing, and specifically to a product delivery data processing method and platform for multi-end customers. Background Art

[0002] With the popularization of the Internet and the widespread use of mobile devices in the digital age, users' expectations for product experience and service delivery are increasing, no longer limited to a single channel or platform. Enterprises are faced with the challenge of how to efficiently and accurately meet the diverse needs of different end customers. The traditional product delivery process often has problems such as information islands, cumbersome processes, and delayed responses. It is difficult to adapt to the rapid pace of change in the modern market and the diversity of customer needs. Customers usually need to express their purchasing needs by phone, email or in person in physical stores. These needs are then manually recorded and passed to relevant departments such as sales, inventory and logistics for further processing. Due to the delays and errors that may exist when information is transmitted between multiple departments, traditional product catalogs and inventory management systems are difficult to update shared information in real time, making the response to customer needs slow and prone to misunderstandings or omissions; during the order processing stage, sales personnel need to manually check inventory and fill in order information. Due to the untimely update of logistics information, customers often find it difficult to track the order status, resulting in a poor experience; the traditional settlement method is also relatively cumbersome. Customers need to wait for the bill to be generated before completing the payment, which has delays in capital flow and payment security risks; the product delivery process has obvious deficiencies in efficiency, accuracy and customer experience.

[0003] Therefore, at the current stage, the technologies related to product delivery data processing have information islands, cumbersome processes, and delayed responses, which in turn lead to poor product delivery efficiency and accuracy, low customer satisfaction, and are difficult to adapt to the rapid changes in the modern market and the diversity of customer needs. Summary of the invention

[0004] This application solves the technical problems of information silos, cumbersome processes, and delayed responses in existing product delivery by providing a product delivery data processing method and platform for multi-end customers, which leads to poor product delivery efficiency and accuracy, low customer satisfaction, and difficulty in adapting to the rapid changes in the modern market and the diversity of customer needs. It achieves the technical effect of improving the efficiency, accuracy, pertinence and customer satisfaction of product delivery.

[0005] The present application provides a product delivery data processing method for multi-terminal customers, the method comprising: building a one-stop customer interaction platform, the one-stop customer interaction platform comprising a customer interface layer, a business logic layer, a data management layer and a product service layer; acquiring customer multi-contact point social consultation information through multi-terminal access of the customer interface layer, performing semantic analysis on the customer multi-contact point social consultation information, and obtaining customer demand information; the data management layer integrates product catalog information and a product basic database, and obtains a target product delivery plan based on matching the customer demand information with the product catalog information and the product basic database; the business logic layer generates product delivery order information according to the target product delivery plan and the inventory database, and calculates the product delivery order information according to a preset settlement rule to generate product delivery bill information; based on the product delivery order information and the product delivery bill information, a data product voucher is obtained, and the target customer performs payment encryption processing on the data product voucher through the product service layer to obtain product delivery data information; after the logistics inspection, the product delivery data information is subjected to data verification processing through the product service layer, and if the verification result passes, the ownership of the data product voucher is transferred and delivered to the target customer.

[0006] In a possible implementation, the obtaining of customer demand information further performs the following processing: constructing a multi-format data preprocessing program set based on a customer consultation data format set; classifying the data format of the customer multi-contact point social consultation information to obtain multi-format types of customer social consultation data information; mapping and preprocessing the multi-format types of customer social consultation data information based on the multi-format data preprocessing program set to obtain customer social consultation standard data information; utilizing intelligent IM to perform diversion extraction and semantic analysis on the customer social consultation standard data information to obtain the customer demand information.

[0007] In a possible implementation, the obtaining of the customer demand information further includes the following processing: performing data diversion and extraction on the customer social consultation standard data information to obtain customer consultation data information and customer social data information; performing semantic analysis on the customer consultation data information using a natural language processing algorithm to obtain consultation entity demand information; performing product relevance analysis on the customer social data information to obtain product demand feature information within a predetermined correlation threshold; performing demand portrait analysis based on the consultation entity demand information and the product demand feature information to obtain the customer demand information.

[0008] In a possible implementation, the target product delivery plan is obtained by performing the following processing: obtaining product attribute element information, classifying and representing the product basic database according to the product attribute element information, and obtaining a product attribute database; performing associative indexing on each product information in the product catalog information based on the product attribute database, and constructing a product attribute index database; determining product characteristic matching rules based on the product attribute element information; and matching and analyzing the customer demand information with the product attribute index database based on the product characteristic matching rules to obtain the target product delivery plan.

[0009] In a possible implementation, the obtaining of the target product delivery plan also performs the following processing: assigning criticality to each matching attribute in the product feature matching rule to obtain product matching attribute criticality factor information; performing multidimensional similarity calculation on the customer demand information and each product attribute in the product attribute index database based on the product feature matching rule to obtain a product attribute multidimensional similarity matrix; performing weighted fusion processing on the element values ​​in the product attribute multidimensional similarity matrix based on the product matching attribute criticality factor information to obtain a product demand matching degree set; and screening the product attribute index database in descending order according to the product demand matching degree set to determine the target product delivery plan.

[0010] In a possible implementation, the product delivery data information is obtained and the following processing is also performed: the target customer initiates a delivery request to the product service layer based on the data product voucher and creates a product delivery task number; the order payment is made based on the product delivery task number and the order payment parameters are obtained; the product service layer returns the configuration voucher encryption parameters and generates an encryption key based on the product delivery task number and the order payment parameters; based on the voucher encryption parameters and the encryption key, the data product voucher is delivered and encrypted to obtain the product delivery data information.

[0011] In a possible implementation, the product delivery data information is verified through the product service layer, and the following processing is also performed: the digital signature information of the target customer is obtained, the digital signature information is authenticated through the product service layer, and when the verification is passed, a request is made to obtain the decryption key and the credential encryption parameters based on the encryption key; the product delivery data information is decrypted based on the decryption key and the credential encryption parameters to obtain the product decryption credential; the data hash values ​​of the data product credential and the product decryption credential are calculated and compared to obtain the credential data verification result.

[0012] The present application also provides a product delivery data processing platform for multi-terminal customers, including: a one-stop customer interaction platform construction module, used to construct a one-stop customer interaction platform, the one-stop customer interaction platform includes a customer interface layer, a business logic layer, a data management layer and a product service layer; a customer demand information acquisition module, used to obtain customer multi-contact point social consultation information through multi-terminal access of the customer interface layer, perform semantic analysis on the customer multi-contact point social consultation information, and obtain customer demand information; a target product delivery plan acquisition module, used for the data management layer to integrate product catalog information with a product basic database, and obtain a target product delivery plan based on matching the customer demand information with the product catalog information and the product basic database; a product delivery account A single information generation module is used for the business logic layer to generate product delivery order information according to the target product delivery plan and the inventory database, and at the same time calculate the product delivery order information according to the preset settlement rules to generate product delivery bill information; a product delivery data information acquisition module is used to obtain a data product certificate based on the product delivery order information and the product delivery bill information, and the target customer performs payment encryption processing on the data product certificate through the product service layer to obtain the product delivery data information; a data verification processing module is used to perform data verification processing on the product delivery data information through the product service layer after the logistics inspection, and if the verification result passes, the ownership of the data product certificate is transferred and delivered to the target customer.

[0013] It is planned to build a one-stop customer interaction platform through the product delivery data processing method and platform for multi-end customers proposed in this application, including customer interface layer, business logic layer, data management layer and product service layer; obtain customer demand information through the customer interface layer; obtain the target product delivery plan through the data management layer; generate product delivery order information and product delivery bill information through the business logic layer; perform payment encryption processing through the product service layer to obtain product delivery data information; and perform data verification processing through the product service layer. It solves the technical problems of information islands, cumbersome processes, and delayed responses in existing product delivery, which lead to poor product delivery efficiency and accuracy, low customer satisfaction, and difficulty in adapting to the rapid changes in the modern market and the diversification of customer needs, and achieves the technical effect of improving the efficiency, accuracy, pertinence and customer satisfaction of product delivery. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure are briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A flowchart of a method for processing product delivery data for multiple clients provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a product delivery data processing platform for multiple customers provided in an embodiment of the present application.

[0016] Explanation of the reference numerals: one-stop customer interaction platform construction module 10, customer demand information acquisition module 20, target product delivery plan acquisition module 30, product delivery bill information generation module 40, product delivery data information acquisition module 50, data verification processing module 60. DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a product delivery data processing method for multiple customers, such as Figure 1 As shown, the method includes: Step S100, construct a one-stop customer interaction platform, which includes a customer interface layer, a business logic layer, a data management layer, and a product service layer. By integrating the four core parts of the customer interface layer, the business logic layer, the data management layer, and the product service layer, a one-stop customer interaction platform is constructed to provide an efficient and convenient customer interaction experience, and to achieve full process coverage from customer input to business processing to data management. Specifically, the customer interface layer is a direct window for users to interact with the platform, and is mainly responsible for the presentation of data and the processing of user input. It provides users with a graphical operation interface, such as a browser, a dialog box, a menu, etc., to achieve information input and output and interactive operations, and supports multi-terminal access, including PC terminals, mobile terminals, smart devices, etc., to ensure that no matter where the customer is and what device he uses, he can communicate with the enterprise conveniently; the data management layer is mainly responsible for the storage, management and maintenance of data, and includes a wealth of product catalog information, database systems, product basic data warehouses and other infrastructure, which are used to store key information such as customer information, product data, transaction records, etc., to quickly respond to customer needs. Based on powerful data processing capabilities, it can quickly and accurately match customer needs with product information and generate personalized target product delivery plans. , greatly improving the accuracy of product recommendations and customer satisfaction; the business logic layer, as the core of the entire platform, is responsible for processing business rules and data logic. The business logic layer usually contains multiple business modules, each of which is responsible for handling specific business scenarios, such as order processing, payment settlement, customer service, etc. It is mainly responsible for converting product delivery plans into executable order information, and automatically generating product delivery bills based on preset settlement rules, to achieve seamless connection from customer demand to actual delivery; the product service layer is the level at which the platform provides specific products and services to customers. According to business needs and market changes, various product functions and service modules are designed and developed, such as online customer service, self-service, product recommendations, etc. By introducing a payment encryption processing mechanism, the security and convenience of the transaction process are ensured. After the product passes the logistics inspection, the product service layer will perform data verification processing to ensure the accuracy of the delivery information. After the verification is passed, the platform automatically completes the transfer of ownership of the data product certificate, marking the formal completion of product delivery, improving delivery efficiency, and enhancing customers' trust and satisfaction with product delivery.

[0021] Step S200, obtain the customer's multi-contact point social consultation information through the multi-terminal access of the customer interface layer, perform semantic analysis on the customer's multi-contact point social consultation information, and obtain customer demand information. As a bridge between the enterprise and the customer, the customer interface layer provides a variety of access methods, for example, through multiple customer contact points such as web pages, mobile apps, social media, and emails, collect different forms of customer multi-contact point social consultation information, which may include text, pictures, videos, etc., covering customers' questions and needs in various aspects such as products, services, prices, and after-sales, and then perform semantic analysis on the customer's multi-contact point social consultation information, deeply understand and identify the customer's intentions, entities and other key information, such as judging the specific purpose and needs of customer consultation; extracting key information such as problem description and contact information; and analyzing the attitudes expressed by customers during the consultation process (satisfaction, dissatisfaction, doubts, etc.); and then converting them into structured customer demand information, such as requirements for product functions, performance, price, appearance, etc., to facilitate rapid response to customer questions.

[0022] In a possible implementation, step S200 further includes step S210, constructing a multi-format data preprocessing program set based on a customer consultation data format set; step S220, classifying the data format of the customer multi-contact point social consultation information to obtain multi-format type customer social consultation data information; step S230, mapping and preprocessing the multi-format type customer social consultation data information based on the multi-format data preprocessing program set to obtain customer social consultation standard data information; step S240, using intelligent IM to perform diversion extraction and semantic analysis on the customer social consultation standard data information to obtain the customer demand information.

[0023] Preferably, the customer consultation data format set includes data in multiple formats such as text, image, and voice. Different customer consultation data needs to be preprocessed using different preprocessing program steps. For example, image and voice formats include preprocessing steps such as noise removal, text conversion, and text segmentation, thereby constructing a multi-format data preprocessing program set; classifying the data format of customer multi-touchpoint social consultation information, specifically into text (such as messages, chat records, emails, website form submission content, etc., customer questions, suggestions, complaints, or needs), images (customers upload product photos to show damage or functional problems), videos (showing product operation process or usage, etc.), audio (customer voice messages, phone recordings), etc., thereby obtaining multi-format types of customer social consultation data information; using the constructed multi-format data preprocessing program set to map and match multi-format types of customer social consultation data information to obtain customer social consultation data information of the same format, and performing corresponding preprocessing steps on it to obtain multi-format types of customer social consultation data information. Standard data information for consultation; Smart IM is a fusion of instant messaging and artificial intelligence. It is a comprehensive communication platform that integrates intelligent, automated and personalized service features. It uses smart IM to divert, extract and semantically analyze customer social consultation standard data information. Specifically, it identifies the received customer consultation standard information, determines its source, format and content type, and classifies and labels the consultation information according to preset classification standards (such as problem type, urgency, consultation channel, etc.). According to the classification results and diversion strategies (such as customer service staff's expertise, current workload, service time, etc.), the consultation standard information is assigned to the most appropriate customer service staff for processing; then NLP natural language processing technology is used for semantic analysis. For example, when a customer asks about the product's usage, price information, after-sales service, etc., smart IM needs to accurately judge the customer's intentions and the emotional tendencies expressed during the consultation process (such as satisfaction, dissatisfaction, neutrality, etc.), and give corresponding replies or suggestions, and finally extract specific customer demand information.

[0024] In a possible implementation, step S240 further includes step S241, performing data diversion and extraction on the customer social consultation standard data information to obtain customer consultation data information and customer social data information; step S242, performing semantic analysis on the customer consultation data information using a natural language processing algorithm to obtain consulting entity demand information; step S243, performing product relevance analysis on the customer social data information to obtain product demand feature information within a predetermined correlation threshold; step S244, performing demand portrait analysis based on the consulting entity demand information and the product demand feature information to obtain the customer demand information.

[0025] Preferably, the standardized customer social consultation data is segmented and classified according to its content, type or source and other characteristics. For example, the consultation data is divided into product consultation, service complaint, technical support, etc. according to its content, and the customer social consultation standard data information is divided into customer consultation data information and customer social data information, wherein the customer consultation data information mainly focuses on the customer's direct consultation and problems, and the customer social data information includes the customer's activities, comments, sharing, etc. on social media; the customer consultation data information is semantically analyzed by using a natural language processing algorithm, including word segmentation, part-of-speech tagging, syntactic analysis, entity classification, etc., to extract consultation entity demand information, that is, the needs or problems clearly expressed by the customer, such as product function requirements, performance requirements, price inquiries, product name, brand, model, etc.; the customer's social The information collected can be used to identify product-related content, such as activities, comments, and sharing on social media, and to evaluate the degree of correlation between these contents and specific products. This may include keyword matching (matching keywords in social media data with product attributes or features to identify product-related content) and correlation calculation (calculating the correlation between social media data and specific products). This can lead to the acquisition of product demand feature information within a predetermined correlation threshold, i.e., the customer's preference, demand or focus on a certain type of product as shown on social media. The information on consulting entity demand and product demand feature can be combined to construct a customer demand portrait through data analysis and mining technology, so as to fully and deeply understand customer needs and preferences, thereby obtaining customer demand information and providing strong support for the company's product development, marketing and customer service.

[0026] Step S300, the data management layer integrates the product catalog information with the product basic database, matches the customer demand information with the product catalog information and the product basic database, and obtains the target product delivery plan. The data management layer integrates the product catalog information with the product basic database. Specifically, the product catalog information includes but is not limited to the basic information of the product such as the name, model, specification, and function description, which usually comes from the internal system or external data source of the enterprise, such as ERP (Enterprise Resource Planning) system, CRM (Customer Relationship Management) system, etc. The product basic database contains more detailed and comprehensive product basic information, such as product technical parameters, design documents, production processes, cost structure, etc.; then the customer demand information is compared and matched with the product catalog information and the product basic database to find the product or product combination that best meets the customer's needs. Based on the matching results, the data management layer generates the target product delivery plan, which may include the specific model, configuration, price, delivery date and other information of the product, as well as possible customized suggestions or alternatives, to ensure that customers can be provided with high-quality, personalized products and services.

[0027] In a possible implementation, step S300 further includes step S310, obtaining product attribute element information, classifying and representing the product basic database according to the product attribute element information, and obtaining a product attribute database; step S320, associating and indexing each product information in the product catalog information based on the product attribute database, and constructing a product attribute index database; step S330, determining a product characteristic matching rule based on the product attribute element information; and step S340, matching and analyzing the customer demand information with the product attribute index database based on the product characteristic matching rule, and obtaining the target product delivery plan.

[0028] Preferably, product attribute element information is obtained, including but not limited to product type, function, performance, specification, price, product credit, etc., to jointly describe product characteristics, and then the product basic database is classified and represented according to these product attribute element information, that is, each item of attribute information of each product is extracted from the basic database, and is sorted and stored according to a certain classification system (such as type, function, etc.) to form a product attribute database, and each product in the database is characterized by its attribute element information; based on the product attribute database, each product information in the product catalog information is associated and indexed, specifically referring to matching these products with their attribute information in the product attribute database, and constructing a product attribute index database, which can quickly retrieve and match relevant product information according to one or more attributes of the product (such as type, function, performance parameters, etc.); based on the product attribute element information, the product characteristic matching rules are determined to guide how to match customer needs with product attributes to determine which products can meet the specific needs of customers. Requirements, such as functional matching, evaluating whether the functions of the product match the functions required by customers, performance parameter comparison, comparing the performance parameters of the product with the performance parameters expected by customers to determine whether the performance of the product meets customer needs, price range matching, screening out products with appropriate prices based on customer sensitivity to price or budget range, product credit evaluation, evaluating the reliability and credibility of the product based on historical product evaluations, user feedback and other information; based on product feature matching rules, matching and analyzing customer demand information with the product attribute index database, that is, parsing customer needs, and then searching for qualified products in the product attribute index database based on the parsing results. After the matching analysis is completed, a target product delivery plan is generated based on the matching results, including a recommended list of products. Each product is accompanied by detailed attribute information, price, advantages and other descriptions so that customers can make a choice. At the same time, it may also contain some additional information, such as product purchase recommendations, delivery methods, after-sales service, etc., to help customers fully understand the product and make decisions.

[0029] In a possible implementation, step S340 further includes step S341, assigning criticality to each matching attribute in the product feature matching rule to obtain product matching attribute criticality factor information; step S342, performing multidimensional similarity calculation on the customer demand information and each product attribute in the product attribute index database based on the product feature matching rule to obtain a product attribute multidimensional similarity matrix; step S343, performing weighted fusion processing on the element values ​​in the product attribute multidimensional similarity matrix based on the product matching attribute criticality factor information to obtain a product demand matching degree set; step S344, screening the product attribute index database in descending order according to the product demand matching degree set to determine the target product delivery plan.

[0030] Preferably, criticality is assigned to each matching attribute in the product feature matching rule, that is, a criticality factor (or weight) is assigned to each attribute according to its importance in meeting customer needs. For example, for some customers, product performance is the most important, and the criticality factor of performance attribute is relatively high. For other customers, price is the decisive factor, and the criticality factor of price attribute is higher. The criticality factor information of product matching attributes is obtained, which reflects the relative importance of different attributes in the matching process. Multidimensional similarity calculation refers to the simultaneous calculation of the similarity between customer demand information and multiple product attributes (such as function, performance, specification, price, etc.) in the product attribute index database to generate a product attribute multidimensional similarity matrix, in which each element value represents the similarity between customer demand and a certain product attribute. Based on product matching, the product attribute matching rule is used to match the customer demand information with the product attribute index database. According to the information of attribute criticality factors, weighted fusion processing of element values ​​in the multidimensional similarity matrix of product attributes means multiplying the similarity value of each attribute by its corresponding criticality factor, and then aggregating or merging the weighted similarity values ​​of all attributes to obtain multiple comprehensive matching values, and then obtaining a product demand matching set, which includes the comprehensive matching value between each product and customer demand; based on the product demand matching set, the products are sorted from high to low according to their matching degree with customer demand, and then the product with the highest matching degree is selected as the target product. If there are multiple products with similar matching degrees, they can be further screened according to other factors (such as inventory, delivery time, after-sales service, etc.), and finally the target product delivery plan is obtained, including the optimal product selection and related information that meet customer needs.

[0031] Step S400, the business logic layer generates product delivery order information according to the target product delivery plan and the inventory database, and calculates the product delivery order information according to preset settlement rules to generate product delivery bill information. The business logic layer first extracts detailed information about the product from the target product delivery plan obtained by the data management layer, including product model, quantity, specifications, special requirements, etc., and then interacts with the inventory database, that is, intelligently dispatches inventory to verify whether the inventory of the required products is sufficient. If the inventory is insufficient, it may be necessary to adjust the delivery plan or communicate with the customer; if the inventory is sufficient, it automatically generates product delivery order information based on the extracted order parameters and inventory verification results, usually including order number, customer information, product information, delivery address, expected delivery time, etc., to ensure omni-channel inventory synchronization and accurate management, and can quickly match product inventory logistics corresponding to the delivery plan; at the same time, the business logic layer loads the preset settlement rules, such as the calculation method of product unit price, discount, logistics cost, etc., and calculates the generated product delivery order information, including the total price of the product, discount amount, freight, etc., and then generates product delivery bill information, including the details and total amount of various fees, for subsequent payment and accounting processing. In addition, the business logic layer also needs to handle possible abnormal situations, such as insufficient inventory, incorrect customer information, payment failure, etc., and give corresponding prompts or solutions.

[0032] Step S500, based on the product delivery order information and the product delivery bill information, obtain the data product voucher, and the target customer performs payment encryption processing on the data product voucher through the product service layer to obtain product delivery data information. According to the product delivery order information and the product delivery bill information, integrate the data product voucher containing key information such as order details, bill amount, payment status, etc. This data product voucher is electronic, unique and traceable, and is used to confirm the products purchased by the customer and related information; the target customer encrypts the data product voucher through the advanced encryption technology of the product service layer, such as SSL / TLS protocol, AES encryption algorithm, etc., to effectively prevent the payment information from being stolen or tampered with during the transmission process. Specifically, the target customer enters the payment information (such as bank card number, payment password, etc.) through the payment interface provided by the product service layer. The platform first verifies the validity of the payment information, and then The payment information is encrypted through encryption technology and then sent to the payment institution for processing. After receiving the encrypted payment information, the payment institution will decrypt it and verify its authenticity, and then perform operations such as fund transfer. After the payment is completed, the payment institution will feedback the payment result to the product service layer. The product service layer updates the payment status of the data product voucher according to the payment result, and notifies the customer whether the payment is successful. After the payment is successful, the corresponding product delivery data information is prepared according to the order information in the data product voucher, which may include the product serial number, activation code, download link, etc., for customers to obtain and use the purchased products, such as through email, SMS notification, download link within the product service layer, etc.

[0033] In a possible implementation, step S500 further includes step S510, wherein the target customer initiates a delivery request to the product service layer based on the data product voucher and creates a product delivery task number; step S520, wherein order payment is made based on the product delivery task number and order payment parameters are obtained; step S530, wherein the product service layer returns the configuration voucher encryption parameters and generates an encryption key based on the product delivery task number and the order payment parameters; and step S540, wherein the data product voucher is delivered and encrypted based on the voucher encryption parameters and the encryption key to obtain the product delivery data information.

[0034] Preferably, the target customer uses the obtained data product voucher to initiate a delivery request to the product service layer. At the same time as the request is initiated, the platform will create a product delivery task number for the request, which is used to uniquely identify and track the processing of the delivery request; after the delivery request is received, the order payment is made according to the product delivery task number, that is, the payment is made according to the product pricing and payment terms. After completion, the order payment parameters are generated, including but not limited to the payment amount, payment time, payment method, etc., which are used to verify the validity of the payment and subsequent processing; if the order payment is successful, the product service layer will verify the validity of the payment according to the product delivery task number and the order payment parameters. After the verification is passed, the product service layer will return the configuration voucher encryption parameters to the target customer, such as encryption algorithm, encryption mode, initialization vector, etc., and generate an encryption key for encrypting the data product voucher to ensure the security of the voucher during transmission; finally, based on the voucher encryption parameters and encryption key, the original data product voucher is delivered and encrypted, which may be symmetric encryption or asymmetric encryption of the voucher, depending on the requirements of the encryption parameters, and finally the product delivery data information is obtained, including the encrypted data product voucher information.

[0035] Step S600, after the logistics inspection, the product delivery data information is verified through the product service layer. If the verification result is passed, the ownership of the data product certificate is transferred and delivered to the target customer. The product is inspected according to the established inspection process, including checking whether the quantity, specifications, models, appearance, etc. of the product are consistent with the order information, and checking whether the product is damaged or defective. After the inspection is completed, the logistics inspection results and related data (such as inspection reports, product photos, etc.) are passed to the product service layer. After receiving the logistics inspection results, the product service layer will automatically or manually verify the product delivery data information, including comparing the order information, inspection report and product delivery data information for consistency, to ensure the accuracy and compliance of product delivery. If the verification result is passed, that is, the product delivery data information is consistent with the order information and inspection results, the subsequent delivery process will continue, and the ownership of the data product voucher will be transferred to the target customer. The target customer becomes the owner of the product, and the product delivery data information is securely delivered to the customer through the product service layer, that is, delivered electronically (such as sending serial numbers, activation codes, etc.). During the ownership transfer and delivery process, the data product voucher will also be processed accordingly to generate a voucher containing ownership transfer information and send it to the target customer as proof of ownership transfer. At the same time, the original data product voucher may be marked as delivered or invalid.

[0036] In a possible implementation, step S600 further includes step S610, obtaining the digital signature information of the target customer, authenticating the digital signature information through the product service layer, and requesting to obtain the decryption key and the credential encryption parameters based on the encryption key after the verification; step S620, decrypting the product delivery data information based on the decryption key and the credential encryption parameters to obtain the product decryption credential; step S630, calculating and comparing the data hash values ​​of the data product credential and the product decryption credential to obtain the credential data verification result.

[0037] Preferably, the digital signature information of the target customer is obtained, wherein the digital signature is used to verify the identity of the sender of the information and the integrity of the information. The target customer uses his own private key to sign a piece of information (which may be an identity identifier, request information, etc.) and sends the signed information to the platform. The product service layer authenticates the digital signature information, which usually includes decrypting the signature using the target customer's public key and verifying whether the decrypted information is consistent with the original information. If they are consistent, the signature is considered valid, that is, the identity of the target customer is verified. After the digital signature verification is passed, the decryption key and credential encryption parameters are requested from the product service layer according to the product delivery task number or related identification; then the obtained decryption key and The encrypted product delivery data information is decrypted using the certificate encryption parameters, and the product decryption certificate is obtained after decryption; then the data hash value is calculated for the original data product certificate and the product decryption certificate respectively to verify whether the decryption process is correct and ensure the integrity of the product decryption certificate. The hash value is a function output that converts data of any length into a fixed-length string, and is very sensitive to any slight changes in the original data. Specifically, the two hash values ​​are compared and judged. If the hash values ​​are consistent, it means that the data product certificate has not been tampered with during the encryption, transmission, decryption, etc., and the certificate data verification result is successful. If they are inconsistent, it means that the data may have been tampered with, and the verification result is failed. This ensures the security, integrity and traceability of the product delivery data information, while also verifying the identity of the target customer and preventing illegal access and tampering.

[0038] In the above, refer to Figure 1 The product delivery data processing method for multiple end customers according to an embodiment of the present invention is described in detail. Figure 2 A product delivery data processing platform for multiple clients according to an embodiment of the present invention is described.

[0039] The product delivery data processing platform for multi-end customers according to the embodiment of the present invention is used to solve the technical problems of information islands, cumbersome processes, and delayed responses in existing product delivery, which lead to poor product delivery efficiency and accuracy, low customer satisfaction, and difficulty in adapting to the rapid changes in the modern market and the diversification of customer needs, thereby achieving the technical effect of improving the efficiency, accuracy, pertinence and customer satisfaction of product delivery. The product delivery data processing platform for multi-end customers includes: a one-stop customer interaction platform construction module 10, a customer demand information acquisition module 20, a target product delivery plan acquisition module 30, a product delivery bill information generation module 40, a product delivery data information acquisition module 50, and a data verification processing module 60.

[0040] A one-stop customer interaction platform construction module 10 is used to construct a one-stop customer interaction platform, and the one-stop customer interaction platform includes a customer interface layer, a business logic layer, a data management layer, and a product service layer; a customer demand information acquisition module 20 is used to obtain customer multi-contact point social consultation information through multi-terminal access of the customer interface layer, and perform semantic analysis on the customer multi-contact point social consultation information to obtain customer demand information; a target product delivery plan acquisition module 30 is used to integrate product catalog information with a product basic database at the data management layer, and obtain a target product delivery plan based on matching the customer demand information with the product catalog information and the product basic database; a product delivery bill information generation module 40 is used to The business logic layer generates product delivery order information according to the target product delivery plan and the inventory database, and calculates the product delivery order information according to the preset settlement rules to generate product delivery bill information; the product delivery data information acquisition module 50 is used to obtain the data product certificate based on the product delivery order information and the product delivery bill information. The target customer performs payment encryption processing on the data product certificate through the product service layer to obtain the product delivery data information; the data verification processing module 60 is used to perform data verification processing on the product delivery data information through the product service layer after the logistics inspection. If the verification result passes, the ownership of the data product certificate will be transferred and delivered to the target customer.

[0041] The specific configuration of the customer demand information acquisition module 20 will be described in detail below. The customer demand information acquisition module 20 may further include: constructing a multi-format data preprocessing program set according to a customer consultation data format set; classifying the data format of the customer multi-touchpoint social consultation information to obtain multi-format types of customer social consultation data information; mapping and preprocessing the multi-format types of customer social consultation data information based on the multi-format data preprocessing program set to obtain customer social consultation standard data information; using intelligent IM to perform diversion extraction and semantic analysis on the customer social consultation standard data information to obtain the customer demand information.

[0042] The specific configuration of the customer demand information acquisition module 20 will be described in detail below. The customer demand information acquisition module 20 may further include: performing data diversion extraction on the customer social consultation standard data information to obtain customer consultation data information and customer social data information; performing semantic analysis on the customer consultation data information using a natural language processing algorithm to obtain consultation entity demand information; performing product relevance analysis on the customer social data information to obtain product demand feature information within a predetermined relevance threshold; performing demand portrait analysis based on the consultation entity demand information and the product demand feature information to obtain the customer demand information.

[0043] The specific configuration of the target product delivery solution acquisition module 30 will be described in detail below. The target product delivery solution acquisition module 30 may further include: obtaining product attribute element information, classifying the product basic database according to the product attribute element information, and obtaining a product attribute database; performing an associated index on each product information in the product catalog information based on the product attribute database, and constructing a product attribute index database; determining a product characteristic matching rule based on the product attribute element information; matching and analyzing the customer demand information with the product attribute index database based on the product characteristic matching rule, and obtaining the target product delivery solution.

[0044] The specific configuration of the target product delivery solution acquisition module 30 will be described in detail below. The target product delivery solution acquisition module 30 may further include: assigning criticality to each matching attribute in the product feature matching rule to obtain product matching attribute criticality factor information; performing multidimensional similarity calculation on the customer demand information and each product attribute in the product attribute index database based on the product feature matching rule to obtain a product attribute multidimensional similarity matrix; performing weighted fusion processing on the element values ​​in the product attribute multidimensional similarity matrix based on the product matching attribute criticality factor information to obtain a product demand matching degree set; and screening the product attribute index database in descending order according to the product demand matching degree set to determine the target product delivery solution.

[0045] The specific configuration of the product delivery data information acquisition module 50 will be described in detail below. The product delivery data information acquisition module 50 may further include: the target customer initiates a delivery request to the product service layer according to the data product voucher, and creates a product delivery task number; makes an order payment according to the product delivery task number, and obtains order payment parameters; the product service layer returns the configuration voucher encryption parameters and generates an encryption key according to the product delivery task number and the order payment parameters; based on the voucher encryption parameters and the encryption key, performs delivery encryption processing on the data product voucher to obtain the product delivery data information.

[0046] The specific configuration of the data verification processing module 60 will be described in detail below. The data verification processing module 60 may further include: obtaining the digital signature information of the target customer, authenticating the digital signature information through the product service layer, and requesting to obtain the decryption key and the credential encryption parameters according to the encryption key after the verification is passed; decrypting the product delivery data information based on the decryption key and the credential encryption parameters to obtain the product decryption credential; calculating and comparing the data hash values ​​of the data product credential and the product decryption credential to obtain the credential data verification result.

[0047] The product delivery data processing platform for multiple clients provided in the embodiment of the present invention can execute the product delivery data processing method for multiple clients provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0048] Although the present application makes various references to certain modules in the platform according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0049] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A product delivery data processing method for multiple customers, characterized in that: The method comprises: Building a one-stop customer interaction platform, which includes a customer interface layer, a business logic layer, a data management layer, and a product service layer; Acquire customer multi-touchpoint social consultation information through multi-terminal access of the customer interface layer, perform semantic analysis on the customer multi-touchpoint social consultation information, and obtain customer demand information; The data management layer integrates the product catalog information with the product basic database, matches the customer demand information with the product catalog information and the product basic database, and obtains a target product delivery plan; The business logic layer generates product delivery order information according to the target product delivery plan and the inventory database, and calculates the product delivery order information according to the preset settlement rules to generate product delivery bill information; Based on the product delivery order information and the product delivery bill information, a data product voucher is obtained, and the target customer performs payment encryption processing on the data product voucher through the product service layer to obtain product delivery data information; After the logistics inspection, the product delivery data information is verified through the product service layer. If the verification result is passed, the ownership of the data product certificate is transferred and delivered to the target customer.

2. The method for processing product delivery data for multiple clients according to claim 1, characterized in that: The obtaining of customer demand information includes: Build a set of multi-format data preprocessing programs based on the set of customer consulting data formats; Classifying the data format of the customer's multi-contact point social consultation information to obtain multi-format type customer social consultation data information; Based on the multi-format data preprocessing program set, mapping preprocessing is performed on the multi-format type customer social consultation data information to obtain customer social consultation standard data information; Intelligent IM is used to perform diversion extraction and semantic analysis on the customer social consultation standard data information to obtain the customer demand information.

3. The method for processing product delivery data for multiple clients as claimed in claim 2, characterized in that: The obtaining of the customer demand information includes: Performing data diversion and extraction on the customer social consultation standard data information to obtain customer consultation data information and customer social data information; Using a natural language processing algorithm to perform semantic analysis on the customer consultation data information to obtain consultation entity demand information; Performing product relevance analysis on the customer social data information to obtain product demand feature information within a predetermined relevance threshold; Demand profiling is performed based on the consulting entity demand information and the product demand feature information to obtain the customer demand information.

4. The method for processing product delivery data for multiple clients according to claim 1, characterized in that: The target product delivery plan includes: Acquire product attribute element information, classify the product basic database according to the product attribute element information, and obtain a product attribute database; Based on the product attribute database, each product information in the product catalog information is associated and indexed to construct a product attribute index database; Determining product characteristic matching rules according to the product attribute element information; Based on the product characteristic matching rules, the customer demand information is matched and analyzed with the product attribute index database to obtain the target product delivery plan.

5. The method for processing product delivery data for multiple clients as claimed in claim 4, characterized in that: The obtaining of the target product delivery plan includes: Allocating criticality to each matching attribute in the product characteristic matching rule to obtain product matching attribute criticality factor information; Based on the product characteristic matching rule, multi-dimensional similarity calculation is performed on the customer demand information and each product attribute in the product attribute index database to obtain a product attribute multi-dimensional similarity matrix; Based on the product matching attribute key factor information, weighted fusion processing is performed on the element values ​​in the multidimensional similarity matrix of the product attributes to obtain a product demand matching degree set; The product attribute index database is sorted and screened in descending order according to the product requirement matching degree set to determine the target product delivery plan.

6. The method for processing product delivery data for multiple clients according to claim 1, characterized in that: The obtained product delivery data information includes: The target customer initiates a delivery request to the product service layer according to the data product certificate and creates a product delivery task number; Make order payment according to the product delivery task number and obtain order payment parameters; The product service layer returns the configuration credential encryption parameters and generates an encryption key according to the product delivery task number and the order payment parameters; Based on the certificate encryption parameter and the encryption key, the data product certificate is subjected to delivery encryption processing to obtain the product delivery data information.

7. The method for processing product delivery data for multiple clients according to claim 6, characterized in that: The data verification process of the product delivery data information by the product service layer includes: Obtain the digital signature information of the target customer, authenticate the digital signature information through the product service layer, and request to obtain the decryption key and the credential encryption parameter according to the encryption key after the authentication is passed; Decrypt the product delivery data information based on the decryption key and the credential encryption parameter to obtain a product decryption credential; The data hash values ​​of the data product certificate and the product decryption certificate are calculated and compared to obtain the certificate data verification result.

8. Product delivery data processing platform for multiple customers, characterized by: The platform is used to implement the product delivery data processing method for multiple clients according to any one of claims 1 to 7, and the platform includes: A one-stop customer interaction platform construction module, used to construct a one-stop customer interaction platform, wherein the one-stop customer interaction platform includes a customer interface layer, a business logic layer, a data management layer, and a product service layer; A customer demand information acquisition module is used to obtain customer multi-contact point social consultation information through multi-terminal access of the customer interface layer, perform semantic analysis on the customer multi-contact point social consultation information, and obtain customer demand information; A target product delivery solution acquisition module is used for the data management layer to integrate the product catalog information with the product basic database, and obtain the target product delivery solution based on the customer demand information and the matching of the product catalog information with the product basic database; A product delivery bill information generation module, which is used in the business logic layer to generate product delivery order information according to the target product delivery plan and the inventory database, and calculate the product delivery order information according to the preset settlement rules to generate product delivery bill information; A product delivery data information acquisition module, which is used to obtain a data product voucher based on the product delivery order information and the product delivery bill information. The target customer performs payment encryption processing on the data product voucher through the product service layer to obtain product delivery data information; The data verification processing module is used to verify the product delivery data information through the product service layer after the logistics inspection. If the verification result is passed, the ownership of the data product certificate is transferred and delivered to the target customer.

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