50 results about "Customer analytics" patented technology

The invention relates to the technical field of big data and the field of financial science and technology, and discloses a decision generation method based on big data, and the method comprises the steps: collecting multi-dimensional data related to a target business, extracting key features, such as a behavior mode, a potential problem and resource stability, of a customer, constructing a customer analysis model, and carrying out the decision generation. Generating a time sequence data set in combination with the behavior trend data; a behavior data set is generated through scene analysis and quantitative analysis is carried out to obtain a behavior mode and a resource utilization trend of a client, and finally a strategy adapted to each business scene is generated. According to the method, the service strategy is finally generated by collecting the multi-dimensional data, extracting the customer characteristics, constructing the analysis model, analyzing the customer behavior trend, generating the time series data set and combining different service scenes to perform scene analysis and quantitative processing, so that the real-time analysis, scene decision and dynamic adjustment of the multi-dimensional data are realized; the flexibility and accuracy of the system in a complex service scene are improved, and the service decision-making efficiency and accuracy are improved.

The invention discloses a precise financial customer portrait analysis platform based on big data, which aims at the defects of the traditional financial customer analysis means, and comprises a plurality of key modules: a self-adaptive data acquisition module which is provided with an intelligent sensing interface, can automatically adjust an acquisition strategy according to the change of a data source, fuses multi-modal data, and acquires the image of the financial customer through the self-adaptive data acquisition module; the block chain is used for ensuring the reliability and safety of the data; according to the hyper-fusion data storage module, heterogeneous data integrated storage is combined with intelligent layering, and efficient query and low-cost storage are achieved; an intelligent driving data analysis module, an adaptive algorithm recommendation engine on-demand matching algorithm and small sample learning solve sample insufficiency, and cooperate with a dual-mode pipeline to guarantee analysis timeliness and depth; the dynamic evolution portrait construction module is used for updating portraits in real time, customizing personalized tags and comparing reference groups; and a security collaborative application interface module and a multi-tenant isolation interface are matched to realize bidirectional ecological feedback. The platform can accurately draw customer portraits, enable financial businesses and improve the competitiveness of organizations.

The invention provides a customer relationship management system based on big data, and relates to the technical field of information, and the system comprises a customer division module which is used for dividing customers into different customer types according to the industry characteristics, market positioning and business targets of an enterprise; the customer maintenance analysis module is used for acquiring maintenance related information of the customer and analyzing the maintenance related information to obtain a customer analysis result; and the return visit personnel configuration module is used for receiving the client analysis result, performing personnel configuration processing to obtain a corresponding return visit personnel, and sending a corresponding client maintenance list to an intelligent terminal of the return visit personnel. According to the invention, customer information is comprehensively collected by using a big data technology, customer types are accurately divided through a complex algorithm, expected customers and potential customers are accurately identified, a targeted marketing strategy basis is provided for enterprises, the market expansion efficiency is effectively improved, and the competitiveness of the enterprises in the market is enhanced.

The invention discloses a potential customer analysis and mining method and system, relates to the technical field of data mining and customer analysis, and solves the technical problems that multi-modal behavior data is difficult to fuse, consistency quantification of group behaviors of multiple users of an enterprise is lacked, and dynamic intention atlas support is lacked. Comprising the steps of obtaining specific concept behavior data of multiple users of a target enterprise on a public platform; generating a user behavior fingerprint vector and an enterprise average industry fingerprint vector through multi-modal dynamic weighting and federal incremental learning, and calculating a group consistency evaluation value in combination with the behavior intensity score; constructing a dynamic intention map containing concepts, pain points, action nodes and evolution relations; screening high-consistency enterprises and matching the current intention stage; predicting an intention state transition probability based on a graph neural network; fusing the consistency evaluation value and the transition probability to calculate an intention maturity score; and sorting the enterprises according to the scores, and generating a potential customer list and a touch strategy.

The invention discloses a customer potential intelligent evaluation method and system based on dynamic weight adjustment. The method comprises the following steps: collecting related data from an internal system and an external API (Application Program Interface), and carrying out cleaning and standardization processing to obtain a preprocessing result; calculating the score of each customer based on the preprocessing result according to a preset dimension index and a weight so as to determine the customer level; converting the client address in the preprocessing result into a coordinate form, and recommending nearby potential clients based on the current position of the user; historical data are analyzed to construct a transformation prediction model, and the business opportunity loss risk is monitored and predicted in real time; and client data change in the preprocessing result is monitored, and an update notification is sent through an instant messaging tool according to a predefined rule. By implementing the method provided by the invention, the defects of the existing system in the aspects of customer grading, data analysis visualization, business opportunity tracking, field service support and the like can be accurately solved.

The present invention provides a power supply digital management system based on a power system. The system includes a display platform, a metering monitoring and analysis module, a customer analysis module, and a power supply station analysis module. The display platform is used for users to log in, uniformly authenticate user identities, and display the data analysis results from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module, and at the same time display the to-do items from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module. The metering monitoring and analysis module is used to realize off-line analysis of metering terminals, analysis of abnormal metering data, analysis of unsuccessful meter reading, and line loss analysis according to metering information. The customer analysis module is used to realize customer label classification and customer demand analysis according to customer information. The power supply station analysis module is used to realize analysis of power supply station index values and ranking according to the business system data of each power supply station.

The invention relates to the technical field of chain store operation, in particular to a chain operation store classification terminal system based on customer purchase demands, the chain operation store classification terminal system comprises module division, data arrangement and information security, and the module division comprises customer analysis, commodity classification, store layout and inventory management. According to data arrangement, a database is established, an analysis tool is adopted to analyze various kinds of data, and information security comprises identity verification, authority management, data encryption and security audit. According to different types of demands of customers, the sales volume of commodities is counted, and the order volume increase and decrease or the on-shelf and off-shelf adjustment of a single commodity is realized, so that the sales volume of the commodities can be improved to the greatest extent, the sales volume of the regional stores is improved, and the sales volume of the regional stores is improved through the purchase volume of the commodities, the suggestions of the customers for increasing and decreasing the commodities and the demand conditions. Therefore, real-time adjustment of commodities can be carried out, so that the market occupancy ratio of the store in the area is improved.

Disclosed herein is a healthcare management system and method utilizing machine learning based predictive analytics to improve patient adherence rates for chronic care management (e.g., diabetes). An example system may include a computing device configured to establish a customer analytical record to synthetize over a plurality of selected attributes to form a patient centric view of patient behaviors, attitude, characteristics based upon data related to chronic disease state management and social determinants of health, consumer experience to determine, using a predictive artificial intelligence model, a patient's predictive adherence for next 1-3 months, and determine tailored intervention plans to engage patients for continuing adherence.

A method and system for Precision Drive Testing (PDT) of cellular wireless networks (e.g., 2G / 3G / 4G / LTE, 5G, 6G). The PDT system and method are cloud-based, automated, remotely controlled and allow for directed testing of user / device or machine experience of network(s) and service(s) performance by running pre-defined use cases, specific test scripts on pre-defined (pre-calculated) routes or within pre-defined (pre-calculated) areas of interest for the use case. The PDT may be automatically and remotely triggered by AI / ML based network sensing by drive test agents and / or outcomes (results) of network and / or service performance data and / or customer analytics or raw network and / or service and / or customer data, and / or network planning data, and / or new deployments of networks / technologies / services / devices, and benchmarking data.

The invention belongs to the technical field of customer analysis and management, and relates to an articulated naturality web customer intelligent analysis and management method based on an artificial intelligence technology. According to the method, the customer behavior map is constructed by integrating multi-modal data such as the moving track, the staying duration and the micro expression of the customer, progressive analysis from a basic behavior label to a high-order behavior mode is realized, the span from passive recording to active understanding of customer requirements is realized, and bottom data support is provided for accurate operation; a high-flow low-conversion area and a high-contact low-conversion area are identified in real time based on a customer behavior map, and an abnormal cause is accurately positioned based on multi-dimensional data analysis through a preset abnormal judgment rule, so that automatic analysis from problem discovery to cause positioning is realized; and aiming at different abnormal causes, a customized strategy is automatically triggered, an intelligent management closed loop of monitoring-analysis-execution-feedback is formed, and the operation efficiency and the conversion rate are effectively improved.

Disclosed herein is a healthcare management system and method utilizing machine learning based predictive analytics to improve patient adherence rates for chronic care management (e.g., diabetes). An example system may include a computing device configured to establish a customer analytical record to synthetize over a plurality of selected attributes to form a patient centric view of patient behaviors, attitude, characteristics based upon data related to chronic disease state management and social determinants of health, consumer experience to determine, using a predictive artificial intelligence model, a patient's predictive adherence for next 1-3 months, and determine tailored intervention plans to engage patients for continuing adherence.

The embodiment of the invention provides an intention prediction method and device, electronic equipment, a readable storage medium and a chip, and the method comprises the steps: obtaining original passenger flow video data; determining a frame image and frame generation time corresponding to the original passenger flow video data; determining first customer video data in the original passenger flow video data according to the frame image; determining at least one customer batch corresponding to the first customer video data according to the frame generation time and the frame image; determining a first behavior parameter corresponding to the customer batch according to the frame generation time and the frame image; and determining intention prediction data corresponding to the customer batch according to the first behavior parameter. Through the scheme of the invention, the passenger flow data acquired by the video is filtered, invalid data of shop assistants and other non-customer personnel are removed, the customer batches are determined, behavior parameters of different batches of customers are analyzed, the intention degree is predicted, the service follow-up speed is accelerated, and the customer analysis processing efficiency is improved.

The invention belongs to the technical field of artificial intelligence, and relates to a data prediction method, which comprises the steps of collecting feature data of a customer; wherein the feature data comprises portrait feature data, behavior feature data and statistical feature data; preprocessing the feature data to obtain corresponding target feature data; calling a pre-constructed customer group prediction model; performing prediction processing on the target feature data based on a customer group prediction model to obtain probability data that the customer belongs to a target customer group; obtaining a target score threshold value corresponding to the target customer group; and comparing the probability data with a target score threshold, and generating a customer group division result of the customers based on an obtained numerical comparison result. The invention further provides a data prediction device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the probability data can be stored in a block chain. The method can be applied to a customer analysis scene in the field of financial science and technology, and the processing efficiency and accuracy of customer group division processing are improved.

1. Name of the Design Product: Graphic User Interface for Intelligent Voice Input of Electronic Devices. 2. Use of the Design Product: An electronic device. 3. Design Key Points of the Design Product: Lies in the content of the graphic user interface. 4. Picture or Photo that Best Illustrates the Design Key Points: Front View. 5. Use of the Graphic User Interface: Used for voice input of information for customer analysis. 6. Human-Machine Interaction Method of the Graphic User Interface: The front view is the main interface for KYC intelligent voice input of customer basic information; click the voice button at the bottom of the front view to enter the interface change state diagram 1; fill in the fields according to the prompts in the interface change state diagram 1 to enter the interface change state diagram 2, and the entered fields are displayed above the voice button; after completing the voice input, click the "Complete" button at the bottom of the interface change state diagram 2 to enter the interface change state diagram 3; wait for the voice matching to end in the interface change state diagram 3 to enter the interface change state diagram 4; slide the interface change state diagram 4 to the left to enter the interface change state diagram 5 to enter the customer family member information; click the voice button at the bottom of the interface change state diagram 5 to enter the interface change state diagram 6; fill in the fields according to the prompts in the interface change state diagram 6 to enter the interface change state diagram 7, and the entered fields are displayed above the voice button; after completing the voice input, click the "Complete" button at the bottom of the interface change state diagram 7 to enter the interface change state diagram 8; wait for the voice matching to end in the interface change state diagram 8 to enter the interface change state diagram 9; click the "Go to Analysis" button at the top of the interface change state diagram 9 to perform customer analysis. The cross in this design interface represents replaceable text.

The present invention discloses a supply chain optimization method, system and medium based on customer analysis and market trends; it relates to the technical field of supply chain optimization; this solution makes methodological improvements based on the traditional warehouse stocking method based on demand forecasts and historical data, on the one hand, a first inventory strategy is obtained by performing infant stage matching calculations based on customer information and target products, and the impact of changes in infant age groups on product demand is considered to achieve accurate demand calculation for products; on the other hand, the inventory strategy is corrected by considering the impact of seasonal factors and timeliness factors on product demand, and the inventory strategy is optimized for products whose demand is affected by seasons or timeliness, so as to avoid inventory backlogs and expiration problems caused by excessive purchases, balance supply and demand, and reduce costs and losses.

The invention discloses a security customer analysis method, a storage medium and computer equipment. The security customer analysis method based on the RFM model comprises the following steps: acquiring asset data and transaction data of security customers; constructing a preference score matrix between the user and the product based on the asset data and the transaction data; constructing a preference propagation network based on the preference score matrix between the user and the product; calculating a target probability based on a preference value output by the preference propagation network and the expanded RFM model; the extended RFM model introduces three factors of transaction popularity, asset score and return score into asset matching parameters. Through the above mode, the interaction behavior analysis between the security user and the product can be accurately carried out.

The invention relates to the technical field of eyelash beautification, in particular to a seven-nourishing eyelash beautification grafting method which comprises the following steps: (1) customer analysis and customization; (2) analyzing an eyelash growth cycle; (3) preparing tools and environments; (4) grafting process; and (5) post-processing and nursing, which covers the whole process from customer analysis, material selection, operation technology to post-nursing and training. Personalized customization, accurate operation, health and safety and long-term nursing are emphasized, and comprehensive improvement of the eyelash beautifying industry is embodied.

To provide an advertisement distribution system in a coin laundry store capable of not only efficiently operating and managing advertisement information but also greatly contributing to customer analysis and customer retention.SOLUTION: The display 12 is disposed in the vicinity of the laundry apparatus 11 in the real store 10, the customer terminal 3 reads the identification code displayed on the display 12, the first server 6 to which the real store ID and the settlement availability information of the use of the laundry apparatus 11 are transmitted through the network is provided, the first server 6 lists, registers, and stores the customer information and the advertisement information, and the second server 7 that transmits the operation permission signal through the network to set the laundry apparatus 11 to the operation state when the first server 6 determines that the settlement is permitted is provided. The operation permission signal transmitted from the second server 7 is received, and the first server 6 selects and outputs the advertisement information corresponding to the attribute information of the customer.SELECTED DRAWING: Figure 1

1. The name of the design product: customer information data display graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the content of the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for monitoring and analyzing customer information data. 6. The human-computer interaction mode of the graphical user interface: ① the front view is the main interface for displaying customer information data; ② clicking "historical list" in the front view enters interface change state diagram 1 to display a customer information list; ③ clicking the first "go to management" in interface change state diagram 1 enters interface change state diagram 2 to display the current customer management progress; ④ clicking the detail button on the left of the customer analysis in interface change state diagram 2 enters interface change state diagram 3 to pop up a customer data pop-up window similar to other customers; ⑤ after the pop-up window disappears, interface change state diagram 4 is entered to display a customer portrait detailed data interface; ⑥ sliding down in interface change state diagram 4 enters interface change state diagram 5 to display the customer purchasing power situation; ⑦ in interface change state diagram 5, clicking "precise calculation" enters interface change state diagram 6 to display a calculation method selection interface.

Provided is technology for performing customer analysis that captures changes in values that appeal to customers or in products or the like in a timely manner. This customer analysis system comprises a computer having at least an arithmetic device and a storage device. The storage device stores a customer feature score associating a customer with a score of a feature of the customer, an object-for-sale feature appeal score associating an object-for-sale with a score of the appeal the object-for-sale has to the feature of the customer, and customer feedback about the object-for-sale from the customer. The arithmetic device updates the customer feature score and the object-for-sale feature appeal score by using the customer feedback, and outputs the customer feature for which the score increases and the object-for-sale which appeals to the feature.

The invention relates to a gap monitoring system for monitoring switch machine conversion resistance, which adopts an acquisition extension set 5 to integrate and record conversion resistance data under different conditions according to specific conditions, and then sends the conversion resistance data to a room through the acquisition extension set 5 to form a corresponding data curve for customer analysis; by adding a hardware interface and modifying software to process data and upload through an acquisition extension set, a conversion resistance data acquisition function is added, outdoor equipment is mainly modified, only a software interface for displaying data is modified indoors, parameters capable of being monitored are added, and the working states of a point switch and a turnout can be analyzed through more data. The sensor structure used by the system is high in reliability; the data real-time performance is high; regular battery replacement is not needed; and maintenance is not needed except equipment faults.

Disclosed herein is a healthcare management system and method utilizing machine learning based predictive analytics to improve patient adherence rates for chronic care management (e.g., diabetes). An example system may include a computing device configured to establish a customer analytical record to synthetize over a plurality of selected attributes to form a patient centric view of patient behaviors, attitude, characteristics based upon data related to chronic disease state management and social determinants of health, consumer experience to determine, using a predictive artificial intelligence model, a patient's predictive adherence for next 1-3 months, and determine tailored intervention plans to engage patients for continuing adherence.

The present invention discloses a suspicious customer identification and reporting method and system based on multivariate data, comprising the following steps: obtaining customer information, including external and financial data, and constructing a customer dataset based on the customer information; constructing a suspicious customer identification model and using the customer dataset to identify suspicious customers; identifying the transaction structure graph of the suspicious customer through graph computing and identifying suspicious features within the transaction structure graph; constructing a suspicious group identification model to identify the core transaction structure of the transaction structure graph, analyze capital flow routes, and perform group risk scoring; and constructing a report generation model to generate a suspicious customer analysis report that meets reporting requirements based on the identification results of the suspicious customer identification model, the suspicious features within the transaction structure graph, and the identification results of the suspicious group identification model. This invention can improve the accuracy of suspicious customer identification and the efficiency of reporting report generation.

The invention discloses an automobile consignment customer analysis and management method and system, and belongs to the technical field of customer analysis and management, and the method comprises the following steps: collecting customer information; according to the method, a client database establishment process is set in the method, so that multi-dimensional data information of different clients can be obtained, different information can be gathered together, a huge data system is established, the information of different clients can be quickly retrieved subsequently, accurate client analysis can be performed according to the multi-dimensional information, and the client analysis efficiency is improved. Meanwhile, a perfect customer feedback opinion management and customer customization service system is further arranged in the method, the feedback opinions of the customers can be rapidly input in real time, the opinions can be beneficial to improvement of a subsequent system, personalized customization services can be provided for different customers, and the user experience is improved. Meanwhile, strategy adjustment can be conducted on the market in real time according to customer information, and automobile consignment profit maximization can be improved.

The invention relates to the technical field of big data, and discloses a CRM-based customer data analysis system and method, and the system comprises a main data view construction module which is used for carrying out the data processing of multi-source customer data, and generating a customer main data view of a target customer; the customer value grouping module is used for constructing a customer grouping feature set of the target customers according to the customer main data view, and performing clustering analysis on the target customers to obtain a multi-level value customer group; the customer data analysis module is used for constructing a multi-layer customer analysis network of target customers, extracting basic information and enterprise characteristics of the target customers, analyzing purchase cycle fluctuation coefficients and service response preferences of the target customers, and calculating potential demand probabilities and loss risk probabilities of the target customers; the customer portrait construction module is used for generating a multi-dimensional customer portrait of the target customer; and the customer analysis report module is used for generating a customer analysis report of the target customer. According to the invention, the comprehensiveness and accuracy of customer data analysis can be improved.

The invention discloses a customer information management method and system based on data processing, and belongs to the technical field of customer management. The system comprises a data sensing module, a client analysis module, a work order distribution module and a visualization and storage module. The data sensing module is used for receiving business work orders and collecting historical logs and service parameters of all customer service objects; the client analysis module is used for analyzing a client object in the business work order and calculating a first coefficient through a historical log; drawing a state curve graph for the customer service objects according to the service parameters, and calculating a matching index between the customer object and each customer service object; the work order distribution module distributes business work orders for the customer service objects according to the matching indexes, analyzes the service parameters, calculates the service indexes of the customer service objects in real time, and distributes the business work orders which are being executed again according to the service indexes; and the visualization and storage module is used for displaying the service index of each customer service object, generating a work order record after the business work order is processed, and storing the work order record in a historical log.

1. The name of the design product: transaction event analysis graphical user interface for electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: interface change state diagram 2. 5. The use of the graphical user interface: the design product is used to display the human-computer interaction interface for querying event customer analysis in the bank abnormal transaction secondary screening system. The front view is used to display the initial interface of the bank abnormal transaction secondary screening system; click the "event customer analysis" button of the front view to enter interface change state diagram 1, which is mainly used to display the customer list including private customers and public customers; click the "view" button in the private customer portrait list of interface change state diagram 1 to enter interface change state diagram 2, which is mainly used to display the customer portrait analysis information of the customer; enter interface change state diagram 3 by scrolling the scroll bar on the right side of interface change state diagram 2, which is mainly used to display the customer transaction information and due diligence information in the customer portrait analysis information of the customer; enter interface change state diagram 4 by scrolling the scroll bar on the right side of interface change state diagram 3, which is mainly used to display the annual customer transaction information in the customer portrait analysis information of the customer; enter interface change state diagram 5 by scrolling the scroll bar on the right side of interface change state diagram 4, which is mainly used to display the customer transaction information in the customer portrait analysis information of the customer.

The invention discloses a customer behavior insight method, a customer behavior insight device and a marketing strategy putting method. The customer behavior insight method comprises the following steps: firstly, acquiring real-time multi-level O-domain original data; extracting target network quality data, target position trajectory data, target user behavior data and target APP behavior data corresponding to the user unique identifier from the real-time multi-level O-domain original data; then, comparing the target data with preset features to generate a network awareness tag, a position preference tag, a user preference tag, a terminal tag and an interest preference tag; and finally, summarizing the labels to form a customer behavior insight portrait. According to the method, data of multiple dimensions can be integrated, dynamic customer analysis on the basis of real-time data perception is realized, and full-link insight is provided, so that powerful technical support is provided for precision marketing, network optimization and intelligent service of enterprises.