19 results about "Customer analytics" patented technology

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.

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 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.

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 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 service method and device of a financial institution and a storage medium. The method relates to the field of financial science and technology, and comprises the following steps: obtaining customer information of a target customer under the condition of obtaining authorization of the target customer of a financial institution; inputting the customer information into a customer analysis model, and outputting a customer portrait label of the target customer through the customer analysis model; the customer information of the target customer and the customer portrait label of the target customer are input into a target prediction model, prediction response probabilities of the target customer to different services are output through the target prediction model, and the target prediction model is a model obtained through training according to the customer portrait label of the sample customer and the customer information of the sample customer; and determining the target service strategy of the target customer according to the predicted response probability of the target customer to different services, and providing services for the target customer by adopting the target service strategy, thereby solving the technical problem of customer experience feeling caused by inaccurate service strategy provided for the customer.

The invention discloses a semantic induction analysis system and method based on an artificial intelligence large model, and relates to the technical field of semantic induction analysis, and the method comprises the steps: recognizing the intention degree of an enterprise customer for an enterprise, and obtaining an intention customer; analyzing the key degree of the historical chat text in the historical chat record to the intentional user; analyzing the demand condition of the intentional customer for the enterprise product in the historical chat record to obtain product demand data; evaluating the product demand data of the historical chat records under different historical time spans and the product demand influence degree of the intentional customer in the current time period to obtain demand influence duration data; the enterprise product demand of the intentional customer in the current time period is predicted to obtain the predicted product demand data of the intentional customer, and the predicted product demand data is sent to the related personnel of the intentional customer through the enterprise platform to help the related personnel of the enterprise to better chat with the customer, so that the user experience is improved. And the enterprise and customer communication efficiency and the enterprise service capability are improved.

Provided is a technology with which it is possible to heighten the experience value of consumers, who are to become clients, during a series of purchasing experiences, which include experiences before and after purchasing behaviors, by accurately analyzing factors that obstruct the buying of products by consumers, and proposing measures to decrease these factors on the basis of analytical findings. An experience value analysis system 100 is a system that analyzes the experience value gained by consumers, who are clients, through purchasing experiences, wherein a computer comprising at least a processor 101 and storage devices (102, 103): acquires external information which is information acquired externally via a network 120; acquires client information which is information concerning a client that includes at least behavioral information, which is information indicating the behavior of the client inside a store; analyzes a behavioral process, which is the sequential string of behaviors conducted by the client inside the store, on the basis of the acquired external information and client information; calculates a pain index, in which obstructive factors to purchasing behaviors are indexed, with respect to each behavior that makes up the analyzed customer behavioral process and connecting factors before and after each behavior, and then infers improvement points in the behavioral process on the basis of the calculated pain index; and recommends measures to actualize a different behavioral process, which will decrease the total value of the pain index, on the basis of the inferred improvement points.

The invention relates to the technical field of data mining of financial and medical scenes, and discloses a potential customer analysis mining method and device, computer equipment and a storage medium. Generating an initial potential score and reason description by utilizing the internal reasoning ability of the large language model; and then, sample data reflecting human preferences are constructed in combination with historical potential tags, and parameter adjustment is performed on the large language model by adopting a direct preference optimization algorithm, so that the large language model better fits judgment logic for high-potential customers in actual services on the basis of reserving general knowledge. And finally, scoring and attributing the target customer by using the optimized large language model, and supporting a precise marketing decision. According to the embodiment of the invention, the strong reasoning ability of the large language model is combined with a preference learning mechanism, and the end-to-end automatic mining process from data to strategy is realized.

[Problem] To provide an advertisement distribution system in a self-service laundry establishment, said advertisement distribution system being capable not only of efficiently managing the application of advertisement information, but also of greatly contributing to customer analysis and customer retention. [Solution] A display 12 is positioned in the vicinity of a laundry machine 11 in a brick-and-mortar establishment 10. There is a first server 6 to which a brick-and-mortar establishment ID and information about the possibility of payment for the use of the laundry machine 11 are transmitted via a network due to a customer terminal 3 reading an identification code that is displayed on the display 12. The first server 6 creates a list of customer information and advertisement information and registers and stores the result. There is a second server 7 that, when the first server 6 determines that payment is permitted, transmits an operation permission signal via the network and causes the laundry machine 11 to be in an operating state. The operation permission signal that was transmitted from the second server 7 is received, and the first server 6 selects and outputs advertisement information corresponding to attribute information for the customer.

The application discloses a potential customer analysis mining method and system, relates to the technical field of data mining and customer analysis, and solves the technical problems that it is difficult to fuse multi-modal behavior data, there is lack of consistent quantification on group behavior of multi-users of an enterprise, and there is lack of dynamic intention graph support, and comprises the following steps: acquiring specific concept behavior data of multi-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 combining behavior intensity score to calculate group consistency evaluation value; constructing a dynamic intention graph containing concepts, pain points, action nodes and evolution relations; screening high-consistency enterprises and matching a current intention stage; predicting intention state transition probability based on a graph neural network; fusing the consistency evaluation value and the transition probability to calculate intention maturity score; and sorting the enterprises according to the score, and generating a potential customer list and a touch strategy.

This invention concerns an Artificial Intelligence-based business intelligence method and system for performing multi-branch sentiment analysis and automated competitive mapping based on digital customer review data. This invention consists of a customer data collection module, data preprocessing, Artificial Intelligence-based sentiment classification, business branch clustering, interactive data visualization, competitive mapping, and automated strategic insight generation. The system works by processing customer data from various digital sources to produce customer sentiment analysis, branch versus cluster analysis, heatmaps, sentiment gap analysis, and automated strategic recommendations. This invention provides advantages in conducting automatic, fast, integrated, and efficient customer analysis compared to conventional manual analysis methods, thereby supporting data-based business decision-making more effectively and accurately.