162 results about "Customer acquisition" patented technology

The invention relates to the technical field of artificial intelligence, in particular to an AI intelligent customer obtaining processing method and system, and the method comprises the following steps: collecting interaction data of a user and a platform, summarizing click, browsing duration and frequency information, extracting a user activity mode through an RNN and an LSTM network, analyzing the interest and behavior mode of the user, and generating a user behavior feature library. According to the method, the client acquisition process is optimized through data analysis and behavior prediction, the method does not depend on a traditional marketing means, user data are accurately analyzed through a sequence model, deep understanding of user behaviors is achieved, the accuracy of market segmentation is improved through refined analysis, it is ensured that marketing activities are matched with a target client group, and the marketing efficiency is improved. According to the method, the conversion rate is remarkably improved, the marketing means can be rapidly adjusted by means of intention recognition and real-time data analysis, synchronization with user requirements is ensured, the customer extension cost of the entity store is reduced by continuously integrating customer feedback and marketing data, and the problem that an entity store operator is difficult to obtain customers is solved.

The invention relates to the technical field of Internet advertisement putting, in particular to an intelligent huge advertisement putting method, which comprises the following steps of: acquiring and preprocessing multi-dimensional operation data in real time, constructing a user response prediction model based on a deep interest network, and dynamically weighting a user behavior sequence by utilizing an attention mechanism. A dynamic budget allocation optimization model is established; an objective function is set according to the type of an advertiser; a budget weight is adjusted according to a real-time bidding success rate; a real-time decision engine is deployed; according to the method, each link is monitored through an exposure conversion funnel, an abnormal alarm is set, strategy backtracking analysis is started, and continuous optimization is performed in combination with online learning and model gray release, so that the problem of low efficiency of budget allocation in the traditional technology is solved, intelligent and accurate putting of a huge amount of advertisements is realized, the advertisement conversion rate is improved, and the customer obtaining cost is reduced.

The invention provides an intelligent agent system and method for short video marketing customer obtaining based on a large language model.The intelligent agent system comprises an AI short video planning device, an AI short video making device and an AI short video operating device, the AI short video planning device captures topics from a public media platform and performs topic selection recommendation in combination with commercial positioning of customers, and the AI short video making device makes the selected topics according to the selected topics; the customer completes confirmation of short video topic selection; the AI short video making device generates a client IP short video according to the selected question confirmed by the client, and publishes the client IP short video on a whole-network short video media platform; the AI short video operation device captures video playing data and net friend comment content, performs data analysis and summary report on video release conditions, and replies net friend comments. Through an agent application technology driven by a large language model, three key agent devices are constructed in a client, and a new employment normal form which only provides exclusive short video production service for the client for 7 * 24 hours is started.

The invention relates to the field of artificial intelligence, and discloses a customer obtaining analysis method, device and equipment based on transaction data and a medium, and the method comprises the steps: collecting the transaction data of a to-be-analyzed customer group, and carrying out the preprocessing, and generating a standard data set; performing feature screening on the standard data set, and performing individual feature extraction and clustering analysis to obtain individual features and group features; according to the individual features, the group features and behavior time sequence features in the transaction data, user portrait data are constructed and obtained; inputting the user portrait data into the trained behavior prediction model, performing behavior prediction processing on the user portrait data according to a time sequence weighting strategy, and generating intention behavior information; and generating a customer marketing strategy according to the intention behavior information, and sending marketing information to the customer through a specified channel at specified triggering time according to the customer marketing strategy. By constructing comprehensive user portraits and utilizing a time sequence weighting strategy to accurately predict future behaviors of customers, accurate customer acquisition analysis is realized, and customer acquisition efficiency is improved.

A product carbon footprint (PCF) orchestrator can include a controller configured to generate a PCF determination package, where the PCF determination package includes a data contract and instructions, and where the data contract is configured to receive a plurality of inputs in the form of emission-related data. The controller can also be configured to send the PCF determination package to a customer. The controller can further be configured to obtain PCF results from the customer after the customer uses the data contract following the instructions of the PCF determination package. The controller can also be configured to evaluate the PCF results. Emission data used by the customer to generate the PCF results may not be accessed by the controller.

The invention discloses a large-amount consumption scene intelligent customer obtaining method, system and device based on AI multi-modal data and a medium, relates to the technical field of multi-modal data processing, and solves the technical problems of low customer obtaining efficiency, poor customer conversion quality and lagging credit risk management and control in a large-amount consumption scene. According to the technical scheme, the method is characterized in that a trans-modal feature fusion model based on a Transform model and a'large-amount consumption demand prediction-credit adaptation degree evaluation 'dual-prediction model are constructed by fusing four types of multi-modal data of client texts, images, behaviors and time sequences; the technical problems of single data dimension, disjunction of demand and qualification pre-judgment and insufficient strategy dynamics in traditional customer acquisition are solved, accurate identification of potential customers and pre-management and control of credit risks are realized, and customer acquisition efficiency, customer conversion quality and risk management and control capability of a large-amount consumption scene are improved.

The invention relates to the technical field of intelligent customer acquisition, in particular to a cross-border supply chain financial service AI intelligent customer acquisition system based on big data analysis. Functional components such as a big data access engine, an artificial intelligence analysis model, a customer portrait modeling engine, a preference setting interface, a public opinion and risk identification module, an intelligent screening engine and a docking output module are integrated; multi-source data such as customs data, trade data, enterprise industry and commerce data, judicial public data, international manufacture and cutting lists and internet public information from all places around the world are widely fused. The system performs modeling calculation on industry categories, regional distribution, export history, transaction records, public opinion trends and compliance risks of import and export enterprises, establishes customizable customer optimization rules, accurately outputs a target customer list which can be covered by credit insurance and financing service in combination with a machine learning algorithm, and attaches contact information. Various import and export related data resources can be accessed, automatic screening and output of credit insurance and account receivable financing adaptive exporters are realized through preference setting and AI analysis, the customer obtaining efficiency is remarkably improved, the marketing and risk control cost is reduced, and the economic benefit is improved. The problems that traditional cross-border supply chain financial service customer obtaining depends on manual recommendation, offline visit and a static customer library, the efficiency is low, and small and medium-sized export enterprises are difficult to cover are solved.

The invention discloses an intelligent customer acquisition and user behavior analysis system based on AI full ecology, and relates to the technical field of artificial intelligence and big data marketing, and the system comprises a multi-source data collection module which collects internal and external multi-channel data of an enterprise; the data cleaning module processes abnormal and missing values and unifies data formats; the user portrait construction module extracts multi-dimensional labels to describe user features; the intelligent customer obtaining module uses transfer learning to screen high-potential customers, and the user behavior analysis module mines behavior logic by means of Transform; the intelligent recommendation engine is fused with multiple algorithms to realize personalized recommendation, and the real-time decision module is combined with rules and reinforcement learning to optimize marketing. According to the method, multi-source data integration and deep analysis are realized, clients are accurately identified, behavior requirements are mined, the client obtaining efficiency and the conversion rate are improved, the marketing effect is optimized through personalized recommendation and intelligent decision, and a whole-process intelligent marketing solution from data acquisition to decision execution is provided for enterprises.

The invention belongs to the technical field of intelligent marketing, and particularly relates to an intelligent customer obtaining system and method based on multi-source data fusion. The intelligent customer obtaining method based on multi-source data fusion comprises the following steps that S10, geographical location information, e-commerce data information and social data information of a user terminal are collected under the condition that authorization of the user terminal is obtained, and the e-commerce data information comprises transaction information, browsing information and search information; the social data information comprises collection clues, collection shops and browsing information; and S20, analyzing the interest preference of the user according to the social data information. According to the scheme, through comprehensive data collection, dynamic weight distribution and a real-time feedback mechanism, the pushing accuracy, the user participation degree and the conversion rate are remarkably improved, distribution of customer resource clues is optimized, the user experience is enhanced, the problem that in the prior art, the conversion rate is low when marketing users are converted into consumption users is effectively solved, and the user experience is improved. And the customer obtaining efficiency and the user satisfaction are remarkably improved.

The invention relates to the technical field of customer personalized services, in particular to an AI-based smart old-age care management system, which comprises an AI customer service customer obtaining module for obtaining customer information through guided voice interaction, recording and storing customer basic information, obtaining a home environment image, drawing a customer portrait after analysis and generating customer portrait data, meanwhile, different labels are marked according to the customer portrait data, and customer behavior labels are generated. According to the method, physiological data of the elderly are collected and monitored, time sequence analysis is carried out by adopting a long-short-term memory network, the trend of the physiological data is accurately predicted, accurate health condition prediction is provided, physiological data abnormity is detected by adopting a first-class support vector machine, and a normal mode of the physiological data is learned, so that the health condition of the elderly is accurately predicted. The health risk can be quickly recognized, an alarm can be automatically given, when an abnormal condition is detected, an alarm notice can be immediately sent out, a medical institution and family members are contacted, and health suggestions and emergency responses are provided in time.

The invention belongs to the technical field of package data analysis, and particularly provides an information technology consultation method based on big data and related equipment thereof, and the method mainly comprises the steps: dividing a store into a plurality of commodity regions; acquiring video data, identifying a specified customer from the video data, acquiring a behavior record of the specified customer in each commodity area, and acquiring a historical shopping record of the specified customer; identifying the behavior of checking the commodity by the customer, and recording the duration; analyzing a shopping record of a specified customer in the commodity area in history, and calculating a shopping stability factor; quantifying the interest value of the specified customer on the commodity area; and replying the consultation content of the specified customer according to the interest value. According to the method, the store is divided into the different commodity areas, the monitoring videos in the store are analyzed, the interest values of the customer for the different commodity areas are evaluated, and the consultation content is replied according to the interest values, so that the personalized requirements of the customer can be met, and the service quality and competitiveness of the store can be improved.

The invention provides an AI-based vehicle repair store member extension method and apparatus, and an electronic device, and relates to the field of data processing. In the method, multi-modal data for a target automobile repair store and a target customer group is acquired, the multi-modal data comprises text data, image data and time sequence data, the text data comprises customer evaluation and social media information, the image data comprises automobile condition photos and store environments, and the time sequence data comprises maintenance records and consumption tracks; performing feature fusion on the multi-modal data to obtain a multi-modal feature group; and inputting the multi-modal feature group into an AI model to generate a member customer extension strategy for the target customer group so as to perform member customer extension on the target automobile repair store. By implementing the technical scheme provided by the invention, an accurate member extension strategy can be conveniently generated and formulated.

The invention provides a short video full-process customer acquisition system based on agent collaboration, and relates to the technical field of artificial intelligence. An input layer of the system is used for receiving task data input by a user; the scheduling layer adopts an agent scheduling engine, and the agent scheduling engine is used for determining at least one subtask and a subtask execution sequence according to the task data, distributing the subtasks based on a publishing and subscribing mode and distributing computing power resources based on a weighted polling algorithm; the function layer comprises an account positioning module, a benchmarking account disassembling module, an account basic building module, a topic selection base building module, a video creation module and an editing and publishing module which are independently packaged in an intelligent agent form; the account number positioning module, the benchmarking account number disassembling module, the account number basic building module, the topic selection base building module, the video creation module and the editing and publishing module execute corresponding subtasks. According to the invention, automatic short video creation guest obtaining can be realized, and the efficiency is improved.

The invention discloses a new media advertisement putting and monitoring integrated system, and the system comprises a user portrait construction module which obtains the browsing behavior, geographic position and social interaction data of a user at a mobile terminal, a PC terminal and an intelligent terminal through a multi-source data collection unit, and generates a dynamically updated user interest tag; the intelligent advertisement putting engine is used for matching advertisement contents with user portraits in real time based on a deep reinforcement learning algorithm and supporting programmed cross-platform bidding and private market direct putting; according to the invention, through multi-dimensional effect evaluation, emotion analysis and user life cycle value prediction are introduced, and a comprehensive evaluation system is constructed; data security is enhanced, and through homomorphic encryption and block chain technologies, user privacy is guaranteed and a non-tampering effect auditing voucher is provided. The customer obtaining cost of advertisers can be obviously reduced, and the rate of return on investment is improved.

The invention belongs to the technical field of advertisement putting, and discloses an accurate customer obtaining and advertisement putting system and method based on big data. The method comprises the following steps: S1, multi-source data acquisition: acquiring Internet public data, enterprise private domain data and third-party compliance data to form a comprehensive data pool; s2, data structured storage: the collected data are classified and stored, and an index is established. According to the method, through the collaborative application of multiple technologies such as integrated distributed crawlers, generative adversarial networks, Kalman filtering, edge calculation, multiple linear regression and Lasso regularization, full-link optimization from data acquisition to effect landing is realized, the core problems of inaccurate customer acquisition and poor advertisement effect in the prior art are solved, and the service life of the advertisement is prolonged. Manual intervention cost is reduced through an automatic mechanism, the comprehensive goals of improving customer obtaining precision, optimizing advertisement effect, reducing marketing cost and guaranteeing long-term effectiveness are finally achieved, and a more systematic and more efficient technical support is provided for enterprise digital marketing.

The invention discloses an enterprise debt chain intelligent voltage drop and management and control method based on a dynamic knowledge graph. The method comprises the following steps: S1, constructing an enterprise transaction knowledge graph; s2, querying a debt chain based on a knowledge graph; s3, carrying out intelligent voltage drop on account receivable; and S4, carrying out production and fusion linkage customer acquisition and high-frequency path query based on the centrality. According to the invention, a clear debt reduction target can be provided for an enterprise, the debt problem can be solved at the minimum cost, and the qualification and debt ratio is reduced; the receivable account is tracked more effectively, and the risks of bad debts and overdue payment are reduced, so that the transaction cost is reduced, the cash flow management is optimized, and the financial health degree of an enterprise is improved; different degrees of attention to customers and merchants who have close transactions in the group are improved, group production and fusion linkage is assisted, and improvement of production and fusion service capability of group financial enterprises is realized.

The invention belongs to the field of business method processing, determines a target network community hotspot object through an artificial intelligence technology and a corresponding algorithm model, and constructs a business district with an AI Mall core shop and a traditional entity common node shop within the range based on digital assets, a block chain technology and the obtained target network community hotspot object. Business district construction and passenger flow attraction are performed through a core shop taking AI Mall as a center, so that flow conversion from a market public domain to a business district private domain is realized, and the problems of difficulty in financing, high drainage cost, capital burning and the like of traditional small, medium and micro entity enterprises are solved. The invention provides a business district construction method and a corresponding entity business district by taking extraction and display of hot objects, uplink sharing of information data and a bridge taking digital asset real world assets as entity economy WEB3 as basic features. According to the method, the randomness and inaccuracy of dependence on human experience in the hot object and IP extraction process of the traditional joint activity are solved, the traditional form of single fighting and the loose membership state of the shop are abandoned through the systematic business district construction process, and the construction efficiency is improved on the basis of reaching the consensus. And a business entity alliance with close dependency relationship and maximum sharing of passenger flow and revenue is formed.

This invention provides an information processing device, information processing method, information processing system, and program that enable centralized management of patient information by linking an electronic medical record database with databases from multiple customer acquisition media, and that utilize this information to propose medical services. [Solution] The information processing system includes a reception unit that receives patient needs, a patient information acquisition unit that acquires patient information including basic patient information and medical visit history information, a medical information acquisition unit that acquires medical information including medical treatment information and prescription details from medical institutions, an information centralized management unit that centrally manages patient information and medical information, a prompt generation unit that outputs generation commands based on the centrally managed patient information and medical information, and a proposal information generation unit that generates proposal information including medical services, medical institutions, treatment details, etc., suitable for the patient based on the generation commands.

The embodiment of the invention provides an enterprise data processing method and device, electronic equipment and a storage medium, and belongs to the technical field of financial science and technology. The method comprises the following steps: acquiring multi-dimensional enterprise data of a plurality of candidate enterprises; preprocessing the multi-dimensional enterprise data to obtain target enterprise data; performing feature extraction on the target enterprise data to obtain multi-dimensional enterprise features; market change information and enterprise demand information are obtained, and the screening rule weight of the screening model is adjusted according to the market change information and the enterprise demand information to obtain a target screening model; performing matching scoring on each multi-dimensional enterprise feature through a target screening model to obtain an enterprise matching scoring result; and determining a target recommended enterprise from the plurality of candidate enterprises according to an enterprise matching scoring result. Based on this, according to the embodiment of the invention, the enterprise multi-dimensional data is integrated, analyzed and processed, and the customer obtaining strategy is dynamically adjusted according to the market change and the enterprise need, so that the customer obtaining efficiency and quality can be remarkably improved.

The invention discloses an intelligent cloud customer acquisition system based on big data, which relates to the technical field of intelligent cloud customer acquisition and comprises a data acquisition module, a processing module, a calculation module and an analysis module. According to the method, various behavior characteristics of the user in the financial field are combined, so that the accurate customer portrait is constructed, the current state of the customer is reflected, the potential demand and the future trend of the customer are reflected, powerful support is provided for subsequent accurate recommendation, and the customer portrait and the financial product or service characteristics are combined, so that the user experience is improved. According to the method, accurate prediction of potential demands of customers is realized, powerful decision support is provided for financial institutions, and finally, a plurality of factors such as potential demand prediction values, market feedback data and user credit scores are comprehensively considered, so that personalized recommendation priority ranking is obtained; the sorting result not only improves the recommendation accuracy and the conversion rate, but also optimizes the resource configuration and improves the operation efficiency of the financial institution.

The invention discloses an AI-driven full-link user behavior tracking and intelligent customer obtaining conversion system, relates to the technical field of information retrieval and data processing, and aims to deploy a multi-end agent and a sensing node to acquire data, dynamically adjust frequency, encrypt and transmit, construct a distributed storage architecture, process heterogeneous data and establish association mapping. The method comprises the steps of mining behavior characteristics and conversion association through a deep learning model, identifying high-value users and conversion opportunities, constructing a multi-dimensional portrait system, updating label weights in real time, integrating multi-channel interfaces, matching an optimal touch mode and feeding back an effect, monitoring full-link nodes, analyzing conversion obstacles and generating a report, desensitizing storage data and managing and controlling authority. According to the method, accurate tracking and AI intelligent analysis of full-link user behaviors are achieved, dynamic portraits and individuation are achieved, the conversion efficiency is improved, multi-industry customer obtaining requirements are met, and the life cycle value of users is improved.

The application discloses a kind of AIGC content generation and GEO optimization distribution method and system based on knowledge graph constraint.The core of the method is to change the AIGC content generation process from "unconstrained free generation" to "knowledge graph hard constraint generation", and change the content distribution from "passive waiting for inclusion" to "active reverse optimization distribution".The method first establishes the brand exclusive text business travel structured knowledge graph, and uses the hard facts such as merchant coordinates, joint IP and product SKU as mandatory boundary prompt words to constrain the text generation of large language model;At the same time, through the reverse analysis of the recommendation preference of mainstream generative AI engine by automatic probe, the preference vector matrix is formed to guide corpus generation;Then, through the full-automatic distribution platform, the corpus is fed to the whole network in batches through multiple channels;Finally, through the inclusion tracking probe and feedback closed-loop mechanism, the dynamic rectification of strategy is realized.The application realizes the generative engine optimization (GEO) for large model for the first time at the system level, effectively eliminates AI content illusion, realizes more than 80% automation of core operation process, and significantly reduces the cost of enterprise customer acquisition.

To provide quickly and efficiently, statistical information related to new models of game machines.SOLUTION: A management device 50 installed in a game parlor sends (S1) utilization data for each game machine to an information management device 80, and the information management device 80 accumulates (S2) pieces of utilization data received for every model of the game machines. The information management device 80 distributes (S3) on a WEB service for every 15 minutes, the accumulated utilization data for every model. A user of the WEB service accesses the WEB service on a portable terminal 90, thereby browsing the utilization data for every model. For example, according to the present invention, it is possible to browse, as a customer acquisition transition graph, a customer acquisition ratio of "Fist of the South Star" in 20th August in 2023.SELECTED DRAWING: Figure 1

The invention discloses an intelligent customer obtaining system and method for customer driving behavior insurance, and relates to the technical field of insurance science and technology and big data. The system comprises a multi-channel data acquisition module, a privacy protection processing module, a block chain storage module, a driving behavior evaluation module, an intelligent customer obtaining engine module and a user interaction and feedback module. According to the method, driving data is collected through multiple channels, after anonymization, differential privacy disturbance and homomorphic encryption protection, the data credibility is ensured through an alliance chain evidence storage, then a driving behavior comprehensive score is calculated through an innovative mathematical formula, multi-channel accurate customer obtaining is achieved in combination with a customer portrait, and a strategy is dynamically optimized based on the channel conversion rate. According to the method, the problems of fuzzy customer portrait, high data security risk and poor channel collaboration in traditional vehicle insurance customer acquisition are solved, the customer risk matching accuracy is improved by more than 35%, the customer acquisition cost is reduced by 20-25%, and the compliance requirement of the personal information protection method is met.

The application discloses a cloud leasing service platform implementation system and method for third-party robots, and belongs to the technical field of Internet of Things cloud, robot management and control and commercial leasing. The system is provided with six core units of device access, tenant management, service configuration, billing, platform management and control, and service monitoring. The method relies on the processes of standardized access of third-party robots, tenant authentication and selection of a set of packages, allocation of independent management and control space, cloud remote control of machines, automatic billing on demand, real-time monitoring of service status, and the like, to complete unified cloud leasing business of multiple brands of third-party robots. The scheme does not require customers to build platforms and transform robot devices, does not bind specific manufacturer hardware and underlying programs, creates a lightweight and low-cost on-demand leasing operation mode, reduces the access threshold of users, facilitates the platform to scale up customer acquisition, adapts to unified cloud operation of multiple robot models, and is high in universality and outstanding in commercial value.

The invention is applicable to the technical field of artificial intelligence customer acquisition and data acquisition and processing, and provides an artificial intelligence-based multi-source heterogeneous data acquisition system, which comprises a data acquisition module, a data processing module and a data processing module, and the evaluation module is used for determining an evaluation dimension combination when the data processing model performs customer evaluation for the target enterprise and an initial weight corresponding to each evaluation dimension, and obtaining a historical processing record of the data processing model. According to the artificial intelligence-based multi-source heterogeneous data acquisition system provided by the invention, by introducing life cycle stage scoring and data acquisition stability analysis, the specified type of data which gradually loses observability along with the progress of a life cycle can be identified. Although the score of the traditional scoring model may be automatically reduced due to the reduction of the data volume, the method further considers that the acquisition stability of the data in the enterprise evolution process is reduced, and substantially reflects that the interpretation force of the data on the current enterprise state is weakened, so that the weight contribution of the data in the scoring model should be synchronously weakened.

The present invention belongs to the technical field of packaging data analysis, and specifically provides an information technology consulting method based on big data and related devices. The method mainly includes: dividing a store into multiple commodity areas; obtaining video data, identifying a specified customer from the video data, obtaining the behavior records of the specified customer in each commodity area, and obtaining the historical shopping records of the specified customer; identifying the behavior of the customer viewing the commodity and recording the duration; analyzing the shopping records of the specified customer in this commodity area historically, and calculating the shopping stability factor; quantifying the interest value of the specified customer in the commodity area; and replying to the consulting content of the specified customer according to the interest value. By dividing the store into different commodity areas, analyzing the surveillance videos in the store, evaluating the interest values of customers in different commodity areas, and replying to the consulting content based on the interest values, the present application can meet the personalized needs of customers and help the store improve service quality and competitiveness.

The invention provides a house issuing effect improving method and device. The method comprises the following steps: acquiring house resource putting data of each broker account in a broker account set in a target time period; based on a large model, analyzing housing resource release data, and determining a target broker account of which the release effect does not meet a first condition and a target housing resource of which the release effect does not meet a second condition; for each target broker account, based on a large model, analyzing housing resource putting data of the target broker account, and obtaining a first factor and / or a second factor associated with the target broker account, the first factor being a factor affecting the putting effect of the target broker account, and the second factor being a factor affecting the putting effect of the target broker account; the second factor is a factor influencing the putting effect of the target housing resource belonging to the target broker account; and according to the first factor and / or the second factor associated with the target broker account, generating a guidance suggestion for guiding improvement of the delivery effect. Effective room issuing guidance can be performed by analyzing factors influencing the delivery effect, and the customer obtaining effect of brokers is improved.

The application relates to a customer acquisition strategy management method and device based on scene perception. The method comprises the following steps: acquiring multi-dimensional data of a target user group, and acquiring a scene conversion judgment value for representing conversion possibility in a current scene; judging whether a dynamic factor interference exists in a scene where the target user group is located and whether a real-time change occurs in a scene feature; acquiring a first optimization strategy when the dynamic factor interference does not exist and the real-time change does not occur in the scene feature; acquiring a second optimization strategy when the dynamic factor interference exists and the real-time change occurs in the scene feature; determining a final executed customer acquisition strategy scheme; and wherein the customer acquisition strategy scheme is determined based on trial execution feedback data of the first optimization strategy or the second optimization strategy in a sample user group. In this way, the problems of scene factor ambiguity, insufficient dynamic adaptability, lack of scientific verification and the like in the related art customer acquisition strategy can be effectively solved, and the precision, flexibility and economy of the customer acquisition strategy are significantly improved.

The embodiment of the invention provides a data processing method which is applied to a server and comprises the steps that a customer obtaining service request sent by a first client side is received, user attribute information of a target user is obtained, and the customer obtaining service request carries a target channel identifier corresponding to a first interface in the first client side; generating an encrypted transmission parameter based on the user attribute information and the target channel identifier, and sending the encrypted transmission parameter to a first client; receiving a target user adding success message sent by a second client, and decoding the encrypted transmission parameter to obtain a target transmission parameter; and generating target text information based on the target transmission parameter, and updating identification information of the target user on a second client based on the target text information. Through the method, the communication efficiency of users among different clients is improved.