69 results about "Customer acquisition" patented technology

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 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 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 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.

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 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.

1. Name of the product in this design: Taika (Laipengpeng Tuoke Card). 2. Purpose of this design: A table card for placement on a desktop. 3. The key design elements of this product are the combination of shape, pattern, and color. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The design for which protection is sought includes color.

The invention belongs to the technical field of data processing and guest acquisition analysis, and provides a multi-channel guest acquisition behavior sequence sub-minute level alignment method and system, and the method specifically comprises the steps: firstly, recognizing each signal source for acquiring behavior signals from an application scene, carrying out the real-time monitoring of the signal sources, and obtaining an observation array; then, performing false collision analysis on each obtained observation array and obtaining an alignment offset risk; and finally, dynamically adjusting the size of a sub-minute level alignment window according to the alignment offset risk. The occurrence degree of high-frequency behavior false collision risks induced by heterogeneous link transmission and asynchronous backhaul mechanism instability in the multi-channel behavior sequence alignment process is effectively quantified, so that a high-precision mathematical basis is provided for accurately positioning time domain offset errors and causal displacement; and the time domain analysis precision of the attribution model under the sub-minute scale is improved, so that the correctness of causal path judgment and the execution efficiency of an attribution optimization decision are greatly improved in the whole multi-channel customer obtaining analysis process.

The system according to this embodiment aims to fully automate the telemarketing process and achieve efficient new customer acquisition. [Solution] The system according to the embodiment comprises a target selection unit, a calling unit, a talk generation unit, a listening unit, and an appointment acquisition unit. The target selection unit selects a target. The calling unit automatically makes a call to the target selected by the target selection unit. The talk generation unit generates introductory talk and transition talk using AI after the call has been made by the calling unit. The listening unit conducts a listening session using the talk generated by the talk generation unit. The appointment acquisition unit acquires an appointment based on the information gathered by the listening unit.

The application belongs to the technical field of queuing system, and discloses a service network business handling method and system based on a number calling device. The method comprises the following steps: obtaining the identity information and business information of a customer to generate a ticket number, and displaying the ticket number on the display panel of a number calling device; sending a first instruction to the number calling device to make it pop up and be obtained by the customer; sending a second instruction to the number calling device to remind the customer to go to a business window to handle the business; sending a third instruction to obtain the number calling device, and sending a fourth instruction to a staff when the ticket number in the number calling device is consistent with the ticket number of the customer to be served, and meanwhile, the number calling device is recovered and the ticket number in the number calling device is initialized; otherwise, a fifth instruction is sent to the number calling device to remind the customer to go to a correct business window or not to handle the business. The application not only avoids the waste of resources caused by the limitation of paper tickets in the existing queuing system, but also ensures the normal handling of various businesses.

The invention provides an accurate customer obtaining marketing platform and method based on real estate big data, and belongs to the technical field of marketing management, and the method specifically comprises the steps: carrying out the determination of a change strategy of a push optimization target based on the push optimization target data and the associated user portrait data of the push optimization target, according to the method, the change strategy is utilized to change the marketing label of the push optimization target, and the switching processing scheme of the change strategy of the push optimization target is determined according to the identification result of the platform user of the associated user portrait of the push optimization target, so that the customer obtaining processing efficiency is improved.

The invention relates to the technical field of artificial intelligence and digital marketing, in particular to an AI-based full-automatic intelligent customer obtaining system and method, and the system comprises a data storage module, an AI intelligent processing module, a business analysis processing module, a function application module, a data interface integration module, and a verification and auxiliary traceability module. According to the method, an intelligent decision core composed of a simulation and prediction engine and a multi-target optimization engine is constructed, virtual simulation verification and multi-target automatic optimization can be performed on the generated initial strategy, and the strategy can be automatically optimized before real resources are input. In a simulation environment, a strategy effect is predicted, and a Pareto optimal solution under a plurality of conflict targets such as touch, conversion and cost is automatically searched, so that the limitation of human decision is effectively overcome, a marketing decision is upgraded from a head shooting empirical mode to a data-driven and globally optimal intelligent calculation mode; therefore, the scientificity of the strategy and the customer input-output ratio are remarkably improved.

The invention discloses a client agent collaborative transformation closed-loop system based on social media touch and private domain fission, which belongs to the technical field of social media operation and comprises an intelligent touch module, a private domain traffic construction module, a fission activity management module, a data analysis module and a privacy protection module. The system is in butt joint with a social media API through an intelligent touch module, carries out user portrait analysis and precise content delivery, and imports a user into a private domain traffic construction module for tagging management. The fission activity management module may invoke user tags, configure differentiated activity rules to promote growth. The data analysis module integrates data of all links to generate a visual report, and the privacy protection module ensures compliance of whole-process data processing. According to the method, the problem of low marketing efficiency caused by scattered tools and data islands in the prior art is solved, a full-link automatic closed loop from obtaining customers in a public domain to fission in a private domain is constructed, and the marketing precision and the conversion efficiency are improved.

The application discloses a customer service work order distribution method based on work order source and customer correlation degree, relates to the technical field of customer service work order transfer, and comprises the following: the method encapsulates multi-source customer service events generated by a customer service system, a refined operation system, a touch platform, a customer acquisition system and an intelligent delivery system into to-be-distributed work order objects; calculates customer correlation degrees according to customer identity fields, business correlation fields, source tracing fields and conflict fields, and forms bound work orders, to-be-confirmed work orders, conflict work orders and independent work orders; generates customer work order groups based on the bound work orders, and determines main work orders, accompanying work orders, main processing positions and cross-position cooperation identifiers; determines target customer service in the main processing position through acceptance gating and score-based seat assignment; and writes back processing results, effective correlation fields, mis-correlation fields and acceptance information after processing, which are used for subsequent work order distribution, and improve customer service continuity and processing consistency.

The application relates to the technical field of platform operation, and discloses a platform traffic lock-in and repeat purchase operation system based on consumption accumulation, which solves the problems of current offline entity merchant traffic dispersion, high customer acquisition cost and low repeat purchase rate, and comprises a platform core control module, a global traffic aggregation module, a stock merchant transformation module, a ladder discount lock-in module, a dormant user activation module, a multi-format adaptation module and a data statistical analysis module; the global traffic aggregation module, the stock merchant transformation module, the ladder discount lock-in module, the dormant user activation module, the multi-format adaptation module and the data statistical analysis module are connected with the platform core control module; the modules work cooperatively to realize 100% traffic attribution to the platform, global traffic connection, stock traffic activation, repeat purchase locking and multi-format expansion; the system can realize traffic centralized control, stock activation, repeat purchase locking and multi-format adaptation.

The invention discloses a digital marketing customer obtaining method and system oriented to traditional enterprise multi-platform data, and belongs to the technical field of computers. The method comprises the following steps: collecting heterogeneous data by calling APIs of a plurality of external platforms; converting the heterogeneous data into standard features by using a preset unified data specification, and storing the standard features into a central database; integrating a third-party statistical tool to collect user behavior data, and calculating real-time and delayed return on investment according to different conversion attribution time windows; taking the fused features and the ROI data as input, and adopting a logistic regression model to train and output a guest obtaining probability prediction value; and automatically generating a multi-dimensional marketing strategy suggestion according to the predicted value. According to the method, the problems that traditional enterprise marketing data are dispersed and are difficult to integrate, analyze and accurately predict are solved. The invention also relates to a system for realizing the method.

The invention discloses a multi-channel intelligent customer acquisition and cost optimization method and system, and the method comprises the steps: integrating a plurality of customer acquisition channels, such as a social media platform, a search engine, an offline store, a cooperative merchant, and the like through building a standardized data interface, and collecting customer flow data, marketing activity data and channel putting cost data; the system carries out cleaning, duplicate removal and normalization preprocessing on collected data, and a prediction model is established by using big data technologies such as time sequence analysis, geographic information system analysis and customer portrait analysis in combination with machine learning algorithms such as a decision tree and a random forest. Based on cost-benefit ratio calculation and a Markov decision process, the system dynamically adjusts marketing resource distribution of each channel, including advertisement putting budget and popularization personnel configuration. According to the method, the customer obtaining cost can be remarkably reduced, the customer obtaining efficiency is improved, the market competitiveness is enhanced, scientific data support is provided for management decision, and intelligent customer obtaining and refined cost management of a consumer financial institution are realized.

The application discloses an insurance industry potential customer mining method, and is applied to the technical field of data mining. The method provided by the application comprises the following steps: acquiring a customer information set of a target customer to be analyzed from a preset customer acquisition channel; performing analysis on the customer information to obtain a user portrait label of the target customer; processing the user portrait label of the target customer according to a first screening rule to obtain target customer data to be trained; performing machine learning training on the target customer data to be trained by using a Spark computing platform to obtain a potential customer prediction model; inputting the target customer data to be trained into the customer prediction model to obtain first potential customer data; processing the user portrait label of the target customer according to a second screening rule to obtain second potential customer data; pushing the first potential customer data and the second potential customer data to an operation platform; and tracking changes of the first potential customer data and the second potential customer data.

The invention discloses a customer recommendation method and system, a storage medium and a program product, and relates to the technical field of financial science and technology, and the method comprises the steps: obtaining a non-account-opened customer list which comprises a plurality of non-account-opened alternative enterprises; determining a potential customer list in the non-account-opened customer list according to the scale evaluation parameter and the growth evaluation parameter of each alternative enterprise; and outputting recommendation information corresponding to the potential customer list. The invention aims to improve the bank customer obtaining efficiency and the customer mining accuracy and improve the account opening customer quality.