Customer data processing method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a client data processing method and device, equipment and a storage medium. The method comprises the following steps: acquiring customer data, wherein the customer data at least comprises historical interaction data for customers in an instant messaging application program; based on the customer data, customer profile information of the customer is determined, the customer profile information at least comprises customer attribute information and / or customer tags, and the customer tags at least indicate preference characteristics of the customer; and synchronizing the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application, the customer profile information being maintained at the customer relationship management system. Therefore, the client profile information is determined by integrating the historical interaction data of the client from the instant messaging application program, and bidirectional maintenance of the client profile information is realized by using the application programming interface between the client relationship management system and the instant messaging application program.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of information technology, and more particularly, to methods, devices, apparatuses, and computer-readable storage media for processing customer data. Background Art

[0002] In the field of customer relationship management, timely and accurate updating of customer information is essential for optimizing sales strategies and improving customer service. Especially when the communication between enterprises and customers is frequent and dynamic, ensuring the real-time updating and accuracy of customer information has a significant impact on the business success of enterprises.

[0003] In the related art, many enterprises use traditional Customer Relationship Management (CRM) systems to manage customer data, and need to manually enter customer information into the CRM system. This process is not only time-consuming and labor-intensive, but also prone to errors, which reduces work efficiency. In addition, after receiving customer data, the CRM system often cannot automatically perform in-depth data analysis and update customer information, resulting in problems such as untimely updates of customer information and incomplete analysis.

[0004] Therefore, a more efficient and comprehensive method for customer data processing is needed. Summary of the invention

[0005] In a first aspect of the present disclosure, a method for processing customer data is provided. The method comprises: obtaining customer data, the customer data at least comprising historical interaction data for a customer in an instant messaging application; determining customer profile information of the customer based on the customer data, the customer profile information at least comprising customer attribute information and / or customer tags, the customer tags at least indicating the customer's preference characteristics; and synchronizing the customer profile information to the instant messaging application using an application programming interface between a customer relationship management system and the instant messaging application, wherein the customer profile information is maintained at the customer relationship management system.

[0006] In a second aspect of the present disclosure, a device for processing customer data is provided. The device includes: an acquisition module configured to acquire customer data, the customer data at least including historical interaction data for a customer in an instant messaging application; a determination module configured to determine customer profile information of a customer based on the customer data, the customer profile information at least including customer attribute information and / or customer tags, the customer tags at least indicating the customer's preference characteristics; and a synchronization module configured to synchronize the customer profile information to the instant messaging application using an application programming interface between a customer relationship management system and the instant messaging application, the customer profile information being maintained at the customer relationship management system.

[0007] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit. When the instructions are executed by the at least one processing unit, the device executes the method of the first aspect.

[0008] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and the computer program can be executed by a processor to implement the method of the first aspect.

[0009] In a fifth aspect of the present disclosure, a computer program product is provided, which is tangibly stored in a computer storage medium and includes computer executable instructions, which when executed by a device cause the device to perform the method according to the first aspect of the present disclosure.

[0010] It should be understood that the content described in this content section is not intended to limit the key features or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0012] Figure 1 A schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

[0013] Figure 2 A flowchart showing a process of customer data processing according to some embodiments of the present disclosure;

[0014] Figure 3A A schematic diagram showing a system for determining customer profile information according to some embodiments of the present disclosure;

[0015] Figure 3B A schematic diagram showing a process of determining customer profile information according to some embodiments of the present disclosure;

[0016] Figure 3C A schematic diagram of a user interface of an instant messaging application program according to some embodiments of the present disclosure is shown;

[0017] Figure 4 A block diagram showing an apparatus for client data processing according to some embodiments of the present disclosure; and

[0018] Figure 5A block diagram of an electronic device capable of implementing one or more embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0019] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0020] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0021] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0022] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0023] It is understood that the data involved in the technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the relevant laws, regulations and relevant provisions. The embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be interpreted as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0024] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may also be included below.

[0025] As briefly mentioned above, in the field of customer relationship management, timely and accurate updating of customer information is crucial to optimizing sales strategies and improving customer service. Especially when the communication between enterprises and customers is frequent and dynamic, ensuring the real-time update and accuracy of customer information has a significant impact on the business success of enterprises.

[0026] Currently, many companies use CRM systems to manage customer information. CRM system refers to customer relationship management system, which is a software tool or platform that integrates various business processes and technical tools to help companies effectively manage information, activities and data related to customer relationships. CRM system is not limited to the software level, it is a set of strategies, processes and technologies that aims to optimize the company's customer service quality, marketing strategy and sales performance by collecting, analyzing and using customer information.

[0027] In the related technologies, with the booming development of mobile Internet technology, instant messaging applications have gradually become the preferred platform for enterprises to communicate with customers due to their convenience and speed. However, the current technical implementation still faces an important challenge: the information island phenomenon between instant messaging applications and CRM systems. After sales staff communicate with customers on instant messaging applications, these communication information cannot be smoothly integrated into the CRM system. At the same time, customer information in the CRM system cannot be synchronized to the instant messaging application in real time, which affects the efficiency of information circulation and resource sharing.

[0028] Secondly, after receiving customer data, CRM systems often lack in-depth data analysis and processing capabilities, are unable to build detailed customer profile information, and have difficulty providing personalized service experience, thus reducing customer satisfaction. This limits the company's in-depth understanding of customer needs and misses the opportunity to use data to optimize services.

[0029] Therefore, in order to cope with the challenges of information synchronization barriers, insufficient data analysis, limited customer management, etc. in the current customer data processing scenarios in related technologies, a more efficient solution for customer data processing is needed to solve the problem of information islands between CRM systems and instant messaging applications, and to achieve deep integration and efficient collaboration between the two.

[0030] In an embodiment of the present disclosure, a solution for customer data processing is provided. According to an embodiment of the present disclosure, customer data is obtained, and the customer data at least includes historical interaction data for a customer in an instant messaging application; based on the customer data, customer profile information of the customer is determined, and the customer profile information at least includes customer attribute information and / or customer tags, and the customer tags at least indicate the customer's preference characteristics; and the customer profile information is synchronized to the instant messaging application using an application programming interface between a customer relationship management system and the instant messaging application, and the customer profile information is maintained at the customer relationship management system.

[0031] Thus, by utilizing the application programming interface between the customer relationship management system and the instant messaging application, the customer profile information maintained in the CRM system is seamlessly embedded in the instant messaging application. This step breaks down the barriers between the CRM system and the instant messaging application, allowing users to view and edit customer profile information without switching platforms. In addition, based on the embedding of customer profile information, real-time data synchronization between the CRM system and the instant messaging application is achieved. When users view or modify customer profile information on the instant messaging application, these changes are immediately synchronized to the CRM system for storage, ensuring the accuracy and consistency of customer information. At the same time, the latest customer information in the CRM system can also be pushed to the instant messaging application in real time for users to check at any time.

[0032] Figure 1 A schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented is shown. In the environment 100, an electronic device 110 obtains customer data. The customer data includes at least historical interaction data for a customer in an instant messaging application 120. Then, the electronic device 110 can determine customer profile information 140 of the customer based on the customer data. In some embodiments, the electronic device 110 can maintain the customer profile information 140 at a customer relationship management system 130, and synchronize the customer profile information 140 to the instant messaging application 120 using an application programming interface between the customer relationship management system 130 and the instant messaging application 120.

[0033] In some embodiments, the instant messaging application 130 may be executed in the electronic device 110 and / or another device (eg, a system maintained by a third party).

[0034] In the environment 100, the electronic device 110 can be any type of device with computing capabilities, including a terminal device or a server device. The terminal device can be any type of mobile terminal, fixed terminal or portable terminal, including a mobile phone, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a personal communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), an audio / video player, a digital camera / camcorder, a positioning device, a television receiver, a radio broadcast receiver, an e-book device, a gaming device, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. The server device can include, for example, a computing system / server, such as a mainframe, an edge computing node, a computing device in a cloud environment, and the like.

[0035] It should be understood that the structure and functionality of environment 100 are described for exemplary purposes only and do not imply any limitation on the scope of the present disclosure.

[0036] Figure 2 1 is a flowchart of a process 200 for processing customer data according to some embodiments of the present disclosure. The process 200 may be implemented in the environment 100, for example, the process 200 may be implemented at the electronic device 110. In the following, for ease of discussion, reference will be made to Figure 1 The process 200 is described below.

[0037] At block 210 , the electronic device 110 obtains customer data.

[0038] In some embodiments, obtaining customer data is a prerequisite for generating customer profile information. Only after the electronic device 110 fully obtains and integrates customer data can accurate and comprehensive customer profile information be constructed through data processing and analysis.

[0039] In some embodiments, the customer data includes at least historical interaction data for the customer in the instant messaging application.

[0040] In some embodiments, the electronic device 110 obtains historical interaction data for the customer from the instant messaging application based on a predetermined time interval.

[0041] As an example, the electronic device 110 can obtain the historical interaction data of the customer on the instant messaging application in real time through the corresponding application programming interface (Application Programming Interface, API). The historical interaction data for the customer may include but is not limited to: chat records: the conversation content in the form of text conversations, voice messages, etc. between the user and the customer in the instant messaging application; customer feedback: various feedback information provided by the customer through the instant messaging application, such as product evaluation, service suggestions, complaints, etc.

[0042] As another example, the electronic device 110 may also periodically import customer data in batches from a CRM system or other data sources, such as basic customer information, historical transaction records, etc.

[0043] In the disclosed embodiments, by automatically acquiring customer data, the workload of sales personnel in manually entering customer information is reduced, and the enterprise can quickly respond to customer requests and questions, thereby improving customer satisfaction and loyalty.

[0044] Continue to refer Figure 2 At block 220 , the electronic device 110 determines customer profile information of the customer based on the customer data.

[0045] In some embodiments, the customer profile information includes at least customer attribute information and / or a customer tag, and the customer tag at least indicates a preference characteristic of the customer.

[0046] In some embodiments, a customer tag is a set of identifiers generated based on customer data, which may describe various characteristics and attributes of a customer. For example, a customer tag may indicate a customer's preference characteristics.

[0047] Figure 3A A schematic diagram of a system 300A for determining customer profile information according to some embodiments of the present disclosure is shown.

[0048] In some embodiments, the electronic device may be based on Figure 3A The system 300A in FIG. 1 determines the customer profile information. Figure 3A As shown, the system 300A may include a data layer 310, a tool layer 320 and an interface layer 330, each layer having its corresponding functions and roles, which together ensure the efficiency and accuracy of data processing.

[0049] In some embodiments, the data layer 310 is the basis for determining customer profile information. The data layer 310 may include database components, including but not limited to MySQL: providing storage capabilities for structured data, suitable for storing basic customer information; Redis: as a high-performance memory database, responsible for caching frequently accessed data to improve data access speed; Elasticsearch: used to store and retrieve large amounts of log or text data, facilitating rapid search and analysis of customer interaction information. The main function of the data layer 310 is to obtain data from instant messaging applications and / or CRM systems and store and manage the data.

[0050] In some embodiments, the tool layer 320 is located above the data layer 310 and includes components such as data analysis, data verification, and algorithm models. Its main task is to obtain data from the data layer 310 and process the data through data analysis and algorithm models to generate accurate customer profile information.

[0051] In some embodiments, the interface layer 330 is a communication bridge between the customer profile information and the CRM system, and is mainly composed of HTTP interfaces and other custom interfaces. Its responsibility is to encapsulate the customer profile information processed by the tool layer 320 into a standardized interface format, and then push it to the CRM system, thereby realizing real-time update of the customer profile information.

[0052] Figure 3B A schematic diagram of a process 300B for determining customer profile information according to some embodiments of the present disclosure is shown. The process 300B may be implemented at the electronic device 110 and / or the system 300A.

[0053] In block 321, the electronic device 110 performs a preprocessing operation on the historical interaction data for the customer. Through the preprocessing operation, the electronic device 110 can remove noise data in the historical interaction data for the customer.

[0054] In some embodiments, the customer data acquired by the electronic device 110 may contain noise data such as duplicates, missing values, and inconsistent formats. The electronic device 110 can remove the noise data in the historical interaction data for the customer through data cleaning and preprocessing operations to improve the data quality. For example, remove duplicate data: if the information of a customer is recorded multiple times, remove the duplicates; handle missing values: if some fields are missing, they can be handled by filling (such as replacing missing values ​​with the mean) or deleting missing items; standardize text format: unify the text format, such as converting all letters to lowercase, removing special characters, etc.

[0055] In block 322 , the electronic device 110 may perform a feature extraction operation on the pre-processed historical interaction data.

[0056] In some embodiments, the electronic device 110 can extract useful features from the pre-processed historical interaction data for the customer, for example, extracting high-frequency words or important words from the chat records; identifying the main topics or themes in the customer chat records, etc.

[0057] In some embodiments, the electronic device 110 extracts keyword features from the pre-processed historical interaction data.

[0058] As an example, the electronic device 110 can first perform word segmentation on the customer's historical interaction data (such as chat records, etc.), that is, divide the continuous text into independent vocabulary units. After word segmentation, the electronic device 110 can count the frequency of each word in the historical interaction data. Word frequency is an intuitive indicator to measure the importance of vocabulary, and high-frequency words can often reflect the customer's main concerns or behavioral characteristics. Based on the word frequency statistics, the electronic device 110 can combine preset thresholds or keyword libraries to filter out representative keywords. These keywords can be product names, service types, question categories, etc., which can directly reflect the customer's interests and needs.

[0059] In some embodiments, the electronic device 110 uses a large language model to determine a result of feature extraction based on keyword features, and the result of feature extraction at least represents the customer's behavioral characteristics and / or preference information.

[0060] As an example, the electronic device 110 can use a large model such as a large language model (LLM) to perform in-depth analysis on historical interaction data and extracted keyword features to obtain key behaviors and preference information of customers. A large model generally refers to a neural network model with a large parameter scale in deep learning. These large models usually have billions or even tens of billions of parameters and require a large amount of computing resources for training and reasoning. With the continuous improvement of computing power and the improvement of algorithms, large models have made remarkable achievements in natural language processing, computer vision, recommendation systems and other fields, and can better capture complex relationships and patterns in data and improve the generalization ability and performance of the model.

[0061] In the disclosed embodiment, by extracting keyword features and analyzing them using a large language model, the behavioral features and preference information of customers in historical interactions can be captured more accurately. These features can better reflect the real needs and interests of customers and improve the accuracy of data analysis.

[0062] In block 323 , the electronic device 110 determines customer attribute information included in the customer profile information based on the result of the feature extraction.

[0063] In some embodiments, the electronic device 110 may integrate multi-dimensional customer features based on the result of feature extraction to make the customer profile information more comprehensive and cover various attributes and needs of the customer.

[0064] In block 324 , the electronic device 110 uses a machine learning model to determine a customer tag included in the customer profile information based on the result of the feature extraction.

[0065] In some embodiments, the electronic device 110 can use a machine learning model to analyze and process the extracted customer behavior characteristics and preference information through a machine learning algorithm to generate specific tags for each customer. These tags are condensed expressions of customer attributes and can help users classify customers more effectively and provide personalized services.

[0066] In some embodiments, the electronic device 110 utilizes a machine learning model to perform cluster analysis on the results of feature extraction.

[0067] In some embodiments, the electronic device 110 may utilize a machine learning model to perform customer classification or cluster analysis based on the extracted features, thereby dividing customers into different groups or types to identify different customer group characteristics.

[0068] In some embodiments, the electronic device 110 determines the customer tags included in the customer profile information based on the results of the cluster analysis.

[0069] As an example, the electronic device 110 determines corresponding customer tags in the customer profile information based on the result of the cluster analysis, such as tags such as “high frequency purchase”, “like discounts”, and “active complaints”.

[0070] In the disclosed embodiment, customer classification and clustering based on the result of feature extraction can more accurately identify different types of customer groups, which helps to formulate more targeted marketing strategies and service plans and improve the effectiveness of marketing and services.

[0071] In some embodiments, the electronic device 110 can verify the generated customer profile information. For example, the electronic device 110 performs technical verification on the customer tag to ensure that its output results are consistent and accurate; or from the perspective of business logic and requirements, the tag is actually confirmed. After double verification to confirm that the tag is accurate, the electronic device 110 can push it to the CRM system to ensure the accuracy and reliability of the data, providing reliable basic support for subsequent business decisions and applications.

[0072] In some embodiments, the electronic device 110 may use some evaluation indicators to judge the accuracy and effectiveness of the customer profile information, and to tune and improve the model.

[0073] As an example, commonly used evaluation indicators include: Accuracy: the proportion of customers correctly classified by customer profile information; Recall: the proportion of customers who actually belong to a certain category and are correctly predicted to be in that category; F1 Score: the harmonic mean of precision and recall, which comprehensively evaluates the performance of the model.

[0074] As another example, commonly used optimization methods include: Feature selection and engineering: reselecting and constructing features to improve the performance of the model. For example, selecting more representative features or combining features; Hyperparameter tuning: adjusting the hyperparameters of the model (such as learning rate, regularization parameters, etc.) to find the optimal parameter combination and improve model performance.

[0075] In some embodiments, when the electronic device 110 uses a machine learning model (such as a deep learning model) to process customer data, a large number of features are usually generated. These features may be extracted from various raw data, including customer behavior data, interaction records, purchase history, etc. These features may include: Low-order features: original features extracted directly from the data, such as purchase frequency, number of interactions, etc. High-order features: combined features generated through preliminary analysis and processing, such as customer lifecycle value (CLV), customer satisfaction, etc. The electronic device 110 can integrate features from different sources or different types to form a higher-order and more comprehensive feature representation. This step helps to improve the model's ability to abstract and characterize data.

[0076] As an example, the electronic device 110 may merge the directly extracted original features. For example, the purchase frequency, average purchase amount, and the time of the most recent purchase may be integrated into a comprehensive purchase behavior feature. The electronic device 110 may also generate more complex high-order features through algorithms and models, for example, combining the customer's interaction frequency and sentiment analysis results to generate a comprehensive customer satisfaction feature. These high-order features can better capture complex relationships and patterns in the data.

[0077] Return to reference Figure 2 At block 230, the electronic device 110 synchronizes the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application. The customer profile information is maintained at the customer relationship management system.

[0078] In some embodiments, the electronic device 110 can achieve real-time data synchronization between the instant messaging application and the CRM system through the API interface between the instant messaging application and the CRM system. After the user communicates with the customer on the instant messaging application, the customer's feedback and demand information will be automatically synchronized to the CRM system to generate updated customer profile information. In addition, the user can view the latest customer profile information in the instant messaging application, so as to follow up with the customer in a timely manner and provide personalized services.

[0079] In some embodiments, the electronic device 110 may send the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application.

[0080] In some embodiments, the electronic device 110 may control the presentation of the client profile information on the display page of the instant messaging application to support the user to view and / or modify the client profile information.

[0081] In some embodiments, the electronic device 110 may control the presentation of the profile information, for example, by sending a presentation instruction to the instant messaging application. After receiving the instruction, the instant messaging application presents the client profile information in a display page.

[0082] As an example, Figure 3C FIG. 3 is a schematic diagram of a user interface 300C of an instant messaging application program according to some embodiments of the present disclosure. Figure 3C As shown, sales staff or users can click on the "CRM Customer" component in the instant messaging application to directly view customer profile information without switching between different systems. This greatly improves the efficiency of obtaining customer information, allowing users to quickly identify customer needs and provide corresponding services.

[0083] In the disclosed embodiment, a two-way synchronization mechanism between the customer relationship management system and the instant messaging application is implemented through an application programming interface between the customer relationship management system and the instant messaging application.

[0084] In some embodiments, electronic device 110 may receive modified customer profile information from the instant messaging application based on an application programming interface between the customer relationship management system and the instant messaging application in response to detecting a modification to the customer profile information at the instant messaging application.

[0085] As an example, the electronic device 110 can monitor the changes of the customer profile information in the instant messaging application in real time. When it is detected that the user has modified the customer profile information in the instant messaging application (such as updating the customer's tag, note information, etc.), the electronic device 110 transmits the modified customer profile information in the instant messaging application to the CRM system through the API interface. The CRM system receives and stores the modified information to ensure the consistency and real-time nature of the data.

[0086] In the disclosed embodiment, after the user views and modifies the customer profile information in the instant messaging application, these modifications can be synchronized back to the CRM system in real time through the API interface to ensure the real-time update and consistency of customer information. This two-way synchronization mechanism eliminates information silos and enhances the consistency and accuracy of data.

[0087] Figure 4 A block diagram of an apparatus 400 for client data processing according to some embodiments of the present disclosure is shown. The apparatus 400 may be implemented as or include the electronic device 110.

[0088] The apparatus 400 includes an acquisition module 410 configured to acquire customer data, the customer data including at least historical interaction data for the customer in the instant messaging application;

[0089] The determination module 420 is configured to determine the customer profile information of the customer based on the customer data, wherein the customer profile information includes at least customer attribute information and / or customer tags, and the customer tags at least indicate the customer's preference characteristics; and the synchronization module 430 is configured to synchronize the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application, and the customer profile information is maintained at the customer relationship management system.

[0090] In some embodiments, the acquisition module 410 is further configured to acquire historical interaction data for the customer from the instant messaging application based on a predetermined time interval.

[0091] In some embodiments, the determination module 420 is further configured to perform a preprocessing operation on the historical interaction data for the customer to remove noise data in the historical interaction data for the customer; perform a feature extraction operation on the preprocessed historical interaction data; determine the customer attribute information included in the customer profile information based on the result of the feature extraction; and use a machine learning model to determine the customer label included in the customer profile information based on the result of the feature extraction.

[0092] In some embodiments, the determination module 420 is further configured to extract keyword features of the preprocessed historical interaction data; and determine the result of feature extraction based on the keyword features using a large language model, wherein the result of feature extraction at least characterizes the customer's behavioral characteristics and / or preference information.

[0093] In some embodiments, the determination module 420 is further configured to perform cluster analysis on the result of feature extraction using a machine learning model; and determine the customer tags included in the customer profile information based on the result of the cluster analysis.

[0094] In some embodiments, the device 400 includes a synchronization module 430 configured to utilize an application programming interface between the customer relationship management system and the instant messaging application to send customer profile information to the instant messaging application; and control the presentation of customer profile information on a display page of the instant messaging application to support users to view and / or modify the customer profile information.

[0095] In some embodiments, the synchronization module 430 is further configured to receive modified customer profile information from the instant messaging application based on an application programming interface between the customer relationship management system and the instant messaging application in response to detecting a modification to the customer profile information at the instant messaging application.

[0096] The modules included in the device 400 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the units in the device 400 can be implemented at least in part by one or more hardware logic components. As an example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0097] Figure 5 1 shows a block diagram of an electronic device 500 in which one or more embodiments of the present disclosure may be implemented. It should be understood that Figure 5 The electronic device 500 shown is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein.

[0098] like Figure 5As shown, the electronic device 500 is in the form of a general electronic device. The components of the electronic device 500 may include, but are not limited to, one or more processors or processing units 510, a memory 520, a storage device 530, one or more communication units 540, one or more input devices 550, and one or more output devices 560. The processing unit 510 may be an actual or virtual processor and is capable of performing various processes according to a program stored in the memory 520. In a multi-processor system, multiple processing units execute computer executable instructions in parallel to improve the parallel processing capability of the electronic device 500.

[0099] The electronic device 500 typically includes a plurality of computer storage media. Such media may be any available media accessible to the electronic device 500, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 520 may be a volatile memory (e.g., registers, caches, random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 530 may be a removable or non-removable medium, and may include a machine-readable medium, such as a flash drive, a disk, or any other medium, which may be capable of being used to store information and / or data and may be accessed within the electronic device 500.

[0100] The electronic device 500 may further include additional removable / non-removable, volatile / non-volatile storage media. Figure 5 As shown in , a disk drive for reading or writing from a removable, non-volatile disk (e.g., a "floppy disk") and an optical drive for reading or writing from a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to the bus (not shown) by one or more data media interfaces. The memory 520 may include a computer program product 525 having one or more program modules that are configured to perform various methods or actions of various embodiments of the present disclosure.

[0101] The communication unit 540 implements communication with other electronic devices through a communication medium. Additionally, the functions of the components of the electronic device 500 can be implemented in a single computing cluster or multiple computing machines that can communicate through a communication connection. Therefore, the electronic device 500 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

[0102] The input device 550 may be one or more input devices, such as a mouse, a keyboard, a tracking ball, etc. The output device 560 may be one or more output devices, such as a display, a speaker, a printer, etc. The electronic device 500 may also communicate with one or more external devices (not shown) through the communication unit 540 as needed, such as a storage device, a display device, etc., communicate with one or more devices that allow a user to interact with the electronic device 500, or communicate with any device that allows the electronic device 500 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0103] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which one or more computer instructions are stored, wherein the one or more computer instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0104] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products implemented according to the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0105] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0106] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0107] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some implementations as replacements, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

[0108] The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the marketplace, or to enable other persons of ordinary skill in the art to understand the implementations disclosed herein.

Claims

1. A method for customer data processing, comprising: Acquire customer data, wherein the customer data at least includes historical interaction data for the customer in an instant messaging application; Determine customer profile information of the customer based on the customer data, wherein the customer profile information at least includes customer attribute information and / or a customer tag, and the customer tag at least indicates a preference feature of the customer; as well as The customer profile information is synchronized to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application, and the customer profile information is maintained at the customer relationship management system.

2. The method according to claim 1, wherein obtaining customer data comprises: Based on a predetermined time interval, the historical interaction data for the customer is obtained from the instant messaging application.

3. The method of claim 1 , wherein based on the customer data, determining customer profile information comprises: Performing a preprocessing operation on the historical interaction data for the customer to remove noise data in the historical interaction data for the customer; Performing a feature extraction operation on the preprocessed historical interaction data; Based on the result of the feature extraction, determining the customer attribute information included in the customer profile information; and The customer tag included in the customer profile information is determined based on the result of the feature extraction by using a machine learning model.

4. The method according to claim 3, wherein performing a feature extraction operation on the pre-processed historical interaction data for the customer comprises: extracting keyword features of the preprocessed historical interaction data; and The feature extraction result is determined based on the keyword feature by using a large language model, and the feature extraction result at least represents the behavioral characteristics and / or preference information of the customer.

5. The method according to claim 3, wherein determining the customer tag included in the customer profile information based on the result of the feature extraction using a machine learning model comprises: Using a machine learning model, performing cluster analysis on the results of the feature extraction; Based on the result of the cluster analysis, the customer tag included in the customer profile information is determined.

6. The method of claim 1, wherein synchronizing the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application comprises: sending the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application; Controlling the presentation of the client profile information on a display page of the instant messaging application to support a user to view and / or modify the client profile information.

7. The method according to claim 1, further comprising: In response to detecting a modification of the customer profile information at the instant messaging application, receiving the modified customer profile information from the instant messaging application based on an application programming interface between the customer relationship management system and the instant messaging application.

8. A device for processing customer data, comprising: An acquisition module is configured to acquire customer data, wherein the customer data at least includes historical interaction data for the customer in the instant messaging application; A determination module, configured to determine customer profile information of the customer based on the customer data, wherein the customer profile information at least includes customer attribute information and / or a customer tag, and the customer tag at least indicates a preference feature of the customer; as well as The synchronization module is configured to synchronize the customer profile information to the instant messaging application using an application programming interface between the customer relationship management system and the instant messaging application, wherein the customer profile information is maintained at the customer relationship management system.

9. An electronic device, comprising: at least one processing unit; as well as At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 7 when executed by the at least one processing unit.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program can be executed by a processor to implement the method according to any one of claims 1 to 7.

11. A computer program product tangibly stored in a computer storage medium and comprising computer executable instructions which, when executed by a device, cause the device to perform the method according to any one of claims 1 to 7.

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