37 results about "Customer engagement" patented technology

Transactional Neural Reasoning AI (TNRAI) is a novel class of artificial intelligence designed to simulate human-like reasoning during live, multimodal user sessions. TNRAI departs from traditional static inference models by integrating a five-pillar architecture: (1) delta-path modeling for real-time outcome deviation detection, (2) skew-based adversarial recognition, (3) vector memory recall for behavioral context, (4) ambient reasoning overlays to incorporate situational data, and (5) a multi-logic arbitration engine that fuses rule-based, statistical, situational, and historical reasoning. The system evolves continuously via a CI / CD feedback loop, adjusting its logic and thresholds based on live outcomes. TNRAI supports overlays such as time or location constraints to influence reasoning and can activate conditional triggers based on logic patterns or confidence thresholds. This architecture enables adaptive, deliberative decision-making in real time, extending the utility of AI across domains such as automation, compliance enforcement, customer engagement, and transaction-based system control.

A method and system for optimizing a goal using artificial intelligence (AI) models. The system employs large language models (LLMs) for data normalization and message generation, alongside machine learning (ML) models for continuous training and optimization. It integrates structured and unstructured data into embeddings to evaluate performance metrics and iteratively refine outputs aligned with predefined criteria. The approach dynamically adapts to changes, enabling real-time decision-making and improved efficiency in applications such as customer engagement, sales, and marketing.

This disclosure includes systems and method to manage customer incentivization and participation in virtual power plant (“VPP”) opportunities. A customer may enroll energy assets into VPP and may receive requests to participate in VPP opportunities as a grid has an impending demand for power greater than the supply of the grid. By participating, a user may earn rewards. By committing energy assets and not participating, or by not responding to requests for enrolled energy assets to participate in VPP, a user may receive a penalty. Participation in VPP may be requested on a grouped basis where some groups may have greater rewards and greater penalties but require more reliable participation from a user. Users may be automatically reassigned between groups based on a reliability metric.

Aspects of the disclosure relate to computing platforms that utilize machine learning to perform output generation based on intent identification. The computing platform may train intent orchestration models (e.g., intent identification, output generation, or communication channel) using historical data. The computing platform may data corresponding to an individual. Based on the data, the computing platform may select intent identification models, and may use them to identify an intent. Based on the intent of the individual, the computing platform may select engagement output generation models, and may use them to generate a customer engagement output. The computing platform may use a communication channel model to identify a communication channel. The computing platform may send commands directing display of the customer engagement output, which may cause a user device to display the customer engagement output using the communication channel.

Artificial intelligence (AI) supported interactive platforms for generating captive insurance policy proposals based on standard market insurance policy data are described. An example system includes one or more processors configured to execute machine-readable instructions to ingest standard market insurance policy documents, extract structured policy data from the standard market insurance policy documents, generate a captive insurance policy proposal based on the structured policy data, implement client engagement features configured to facilitate generation and delivery of an email that includes the captive insurance policy proposal as an attachment thereto, and implement a graphical user interface including a dashboard having one or more dashboard layers, the dashboard including first, second, and third areas respectively configured to enable a user of the system to invoke the ingestion of the standard market insurance policy documents, invoke the generation of the captive insurance policy proposal, and invoke the implementation of the client engagement features.

In an illustrative embodiment, systems and methods for an augmented reality (AR) system enable merchant-to-customer engagement through context-aware digital content placement. In an embodiment, one element of the system allows merchants to upload, customize, and place AR media objects, and another element allows customers to discover and interact with said content in real-world environments. In an embodiment, another element of the system dynamically ranks and serves AR content based on user behavior, demographics, time, and location. In alternative embodiments, an artificial intelligence engine dynamically generates personalized AR media objects based on real-time user preferences, history, and environmental context. In some embodiments, features include interactive merchant storefronts, digital promotions, real-time analytics, user rewards, breadcrumb-based AR trails, and dynamically personalized AR experiences to encourage repeated engagement.

This application is directed to methods of driving customer engagement on ecommerce platforms by using games as an incentive after a purchase. The inventive subject matter involves assigning tokens to a user who completes a purchase, granting the user access to a set of games, receiving a game selection, granting user entry to the game, and enabling the user to redeem the tokens to play the game. Embodiments also involve defining a prize pool structure and a prize distribution structure for each game and adjusting them based on the number of entrants. Some embodiments further involves using customer tracking and analytics tools, artificial intelligence, and social features to enhance the customer experience and loyalty.

The invention discloses an activity strategy construction method and device and a financial service system, and relates to the field of financial science and technology, and the construction method comprises the steps: configuring business parameters and product parameters; acquiring target data of a client terminal associated with a client under the condition that client authorization is acquired, and acquiring consumption data of the client; adjusting the service parameters and the product parameters according to the target data to obtain adjusted service parameters and adjusted product parameters; and constructing an activity strategy according to the consumption data, the adjusted service parameters and the adjusted product parameters. The technical problem that the customer participation degree is low due to the fact that an accurate activity strategy cannot be constructed in the prior art is solved.

Systems and methods are provided for building message records and managing communications relating to transactions (e.g., real estate or other transactions) and / or other information from engagement platforms and other applications. System architecture and integration, customizable message creation, dynamic message retrieval, client type and information, and market trends and client specialty values are used to provide efficient communication management, personalized client engagement, real-time updates and responsiveness, comprehensive information delivery, and adaptability to client specifics to facilitate transactions and which can be used by human and / or artificial intelligence agents to enhance the particular application.

The invention provides an insurance customer demand matching and efficiency management and control method based on multi-source data fusion. The method comprises the following steps: S1, collecting and inputting customer basic information and user-defined tags; s2, receiving customer basic information and a self-defined label, and performing customer demand analysis; s3, performing matching degree evaluation on a customer evaluation result and a company platform product; s4, the salesperson determines whether to invitation according to the evaluation result, and the management personnel performs platform quality control according to the evaluation result; s5, acquiring a customer participation platform record and a transaction product record; and S6, performing model optimization according to the customer participation platform record and the transaction record to further improve the accuracy of the prediction information. According to the invention, accurate screening of platform customers is realized, a scientific sales basis is provided, and the problems of large flow and low transaction efficiency of an insurance sales platform are solved.

Methods and a system for personalizing self-checkout terminals based on customer loyalty information includes receiving customer preferences during registration, generating themed personas with specific color schemes, graphics, and animations relevant to the customer's registered interests, and dynamically applying personalized interface themes when customers are identified at self-checkout terminals. The system maintains cached personas tagged with attributes like interests, religious preferences, and dietary restrictions, enabling sub-second personalization by matching customer preferences to pre-generated themes. The system avoids showing inappropriate content by filtering themes based on offensive content, collects user feedback on displayed themes through a rating mechanism, and employs time-delay factors to prevent theme repetition. New personas and corresponding themes are periodically generated to maintain customer engagement while keeping processing costs manageable.

A device may receive text data associated with a conversation of a user, and may process the text data, with large language models (LLMs), to generate conversation tags. The device may generate user attribute tags based on user data, and may classify the conversation tags and the user attribute tags to generate classified tags. The device may convert the text data and the classified tags to a searchable document, and may process the searchable document and historical tag data, with a statistical model, to identify multiple users that match the user. The device may determine degrees of match between the multiple users and the user, and may identify one of the multiple users based on the degrees of match. The device may utilize the historical tag data associated with the one of the multiple users to generate a response for the user, and may provide the response to the user.

The invention discloses a bank task platform process management system and a method thereof, which realize automatic distribution, execution, monitoring and feedback of tasks through a digital platform, improve task processing efficiency and accuracy, reduce manual intervention cost, enhance customer participation degree and satisfaction degree and improve customer experience. Comprising a task creation module, a task distribution module, a task execution module, a task monitoring module, a task feedback module, a data analysis module and a user management module, all the modules work cooperatively, and digital management of a bank task process is achieved. According to the invention, automatic distribution, execution, monitoring and feedback of tasks are realized through a digital platform, the task processing efficiency and accuracy are improved, and the manual intervention cost is reduced.

The invention relates to the technical field of computers, and discloses a forwarding scheme generation method and device based on a dialogue system, equipment and a medium, according to the scheme, dialogue data of a current user and the dialogue system is analyzed, key information is extracted, a forwarding intention of the current user is recognized, a forwarding content text is extracted, and a scheme generation request is generated. And the forwarding scheme generation interface is called to analyze the forwarding key information, so that the pre-stored scheme template matched with the forwarding key information is quickly queried, and the scheme generation efficiency is improved. And when the matching fails, the scheme generation algorithm can dynamically generate a personalized scheme according to the key information, thereby realizing the generation of a forwarding scheme which better conforms to the user demand and scene, enhancing the information attraction and accuracy, improving the generation flexibility and content accuracy of a target forwarding scheme, and improving the customer experience and communication efficiency. In the fields of finance and medical treatment, personalized recommendation and popularization can improve the participation degree of customers, and further improve the business conversion rate.

The invention discloses a digital banquet marketing management method based on a multi-dimensional decision algorithm, and relates to the field of digital banquet marketing management. According to the method, multi-dimensional extraction and coding of banquet features are realized through a self-adaptive excitation generation optimization algorithm based on event feature vectors, and the excitation effect is predicted in combination with historical implementation records, so that an optimal excitation scheme template is generated. And furthermore, comprehensive scoring is performed on real-time banquet records through a multi-modal verification algorithm and a confidence fusion algorithm, so that accurate evaluation and automatic reward distribution of the incentive effect are realized, the incentive scheme is more intelligent, personalized and efficient, and the management level and customer participation degree of banquet marketing activities are remarkably improved.

A financial institution computing system includes an account database with a plurality of transaction parameters with respect to a financial account of a customer, a receptiveness metrics circuit structured to extract the plurality of transaction parameters from the account database, the transaction parameters including at least one financial transaction record, and indicative of a mode of the customer, and determine one or more receptiveness metrics attributed to the customer based on the mode of the customer, the one or more receptiveness metrics indicating likelihoods of the customer converting an interaction from the financial institution, wherein the interaction includes an avatar that is an aged version of the customer, and an interaction generation circuit structured to transmit the interaction to the customer at an optimal time based on the one or more receptiveness metrics.

The embodiment of the invention discloses a predictive outbound method and device, equipment and a storage medium, and the method comprises the steps: obtaining historical telephone traffic data at preset intervals, inputting the historical telephone traffic data into a target long-short-term memory network, and obtaining a corresponding target outbound number of the next outbound period; based on the target call-out number, executing call-out operation on clients in the list to be called out, and determining a corresponding call-out result; and under the condition that the outbound call result is that answering is agreed, performing voice dialogue operation with the answering customer based on the target large language model. According to the technical scheme provided by the embodiment of the invention, the problems of low prediction precision and high call loss rate in the existing predictive call-out technology are solved, the call-out initiation quantity can be accurately predicted by combining the time sequence prediction capability of the long-short-term memory network, and the accuracy and efficiency of predictive call-out are improved; and flexible and natural voice interaction with clients is performed based on the intelligent interaction capability of the large model, so that the participation degree and satisfaction degree of the clients are improved, and the call loss rate is reduced.

A system for processing transactions can include a point of sale (“POS”) device, a payment server, a device monitoring server, a customer engagement server, a checkout assistance server, and a Harmonized Identity Management (“HIDM”) server. The POS device can transmit data associated with a transaction to gain approval of the transaction from the payment server. The device monitoring server can monitor and optimize the performance of the POS device. The customer engagement server can advance a promotion, track a loyalty plan, and distribute coupons and vouchers based on the data associated with the transaction. The checkout assistance server can reduce shrinkage associated with unexpected items in a bagging area near the POS device. The HIDM server can receive requests for authorization tokens from the other servers and provide the tokens.

The invention provides a data processing method and system. The method comprises the steps of obtaining historical arrearage data of a target customer according to customer information; inquiring and acquiring public service data and family associated business data associated with the payment scene and participated by the target customer in a public service platform according to the customer information; analyzing and determining a target collection scene and a risk conduction level corresponding to the target customer according to the historical arrearage data, the public service data and the family associated business data, wherein the risk conduction level is used for representing the influence degree of the arrearage behavior of the target customer on the target customer and business associated personnel; determining target collection information according to the target collection scene and the risk conduction level; and sending the target collection information to the client terminal. According to the invention, the intelligence and collaboration of data processing can be improved, so that the payment reminding efficiency and the rate of return can be improved.

This system provides a technical solution for managing product sales, inventory, and deliveries through QR codes and predictive analytics. It incorporates algorithms that generate and assign unique QR codes to products based on real-time sales data from farmers. These QR codes provide direct links to product information, facilitating efficient inventory management and customer engagement. The system also leverages predictive analytics to forecast product demand by analyzing historical sales data, adjust inventory levels, and optimize delivery driver assignments based on proximity to farms. The hardware supporting the system includes servers, processors, network components, and scanning devices to ensure reliable operation and data synchronization. By automating QR code generation, integrating sales data, and dynamically assigning drivers, the system improves operational efficiency, minimizes errors, and enhances the customer experience.

Methods and apparatuses are described for automated customer engagement prediction and classification. A server generates a feature vector comprising variables corresponding to historical user activity data for a user. The server encodes, for each feature vector, each variable in the feature vector into a corresponding weight-of-evidence value. The server transforms each encoded feature vector into an embedding in a multidimensional vector space. The server generates, for each user, a user engagement probability value by identifying embeddings of other users in proximity to the user embedding using a similarity measure and determining an engagement outcome for the identified embeddings. The server assigns each user to an engagement probability cluster based upon the engagement probability value for the user. The server generates instructions for a remote device to initiate communications to each user based upon the assigned engagement probability cluster.

A method executed by an information processing apparatus that includes a controller, an imager, and an input interface includes executing, by the controller, operations including acquiring consent from a customer regarding recording of customer engagement audio via the input interface, starting audio recording after the consent is acquired, detecting a staff member from an image of the imager, and interrupting the audio recording in a case in which a predetermined condition is met, and the predetermined condition includes a first condition that the staff member has disappeared from the image of the imager.

A method executed by an information processing apparatus that includes a controller, an imager, and an input interface includes executing, by the controller, operations including acquiring consent from a customer regarding recording of customer engagement audio via the input interface, starting capturing an image using the imager after the consent is acquired, and starting audio recording when a predetermined condition is met, and the predetermined condition includes a first condition that a staff member is reflected in an image of the imager.

An e-commerce system and associated methods are provided to facilitate the cross-selling of products and services across virtual and physical stores, as well as through social media platforms. The system typically includes a store manager that allows a store owner to manage the characteristics of an e-commerce store, and a machine learning system trained to identify combinations of products that are likely to sell well together. A recommendation engine, including a store parser, inventory analysis logic, and recommendation logic, utilizes the machine learning system to generate recommendations for additional products to add to the e-commerce store based on a set of products available from external e-commerce stores and the store's current inventory. An optional product browser enables the store owner to review and select products from the generated recommendations. Methods for managing an e-commerce store and adding products to a social media feed are also disclosed, leveraging the machine learning system to enhance sales and customer engagement by recommending products based on store characteristics, social media content and customer interactions.

Methods and apparatuses for customer engagement include: receiving a first product search query from a visitor identified in a visitor session, wherein the first product search query includes at least a visitor identifier associated with customer segments; returning first product search results based on the first product search query; updating, after the first product search query, the customer segments associated with the visitor identifier based on real time evaluation of visitor characteristics and / or actions; receiving a second product search query that is the same as the first product search query from the visitor, wherein the second product search query includes at least the visitor identifier associated with the updated customer segments; and returning second product search results based on the second product search query that is different from the first product search results.

The invention discloses a method for supporting real-time development of marketing activities, and the method comprises the steps: enabling branches to autonomously maintain activity numbers, standard judgment types and white list data through a branch intelligent management platform which comprises a data storage module, a parameter checking module, a judgment execution module and an interface calling module; when a customer participates in an activity, a head office platform forwards a standard judgment transaction to a branch system, after the branch system checks parameters, judgment is executed in three types including white list judgment, real-time judgment and white list and real-time judgment, whether the customer is in a white list or not is judged and verified in the white list, and the state of the customer is verified by calling an external interface in real time. According to the method, the problems of slow response and incapability of real-time judgment of the head office are solved, the activity period is shortened, and the marketing efficiency is improved.

A method and system of providing customer-specific information and guidance to insurance policyholders during claims processing. The information is created based on outputs from a claims complexity model, customer segmentation model, and claims service level objective (SLO) model. The resulting information is tailored to the individual policyholder and their claim, and includes a summary of their claim activity, guidance regarding their next steps, and predicted wait times for each stage in their claim's processing. In some embodiments, the information is presented as messaging delivered over the policyholder's preferred communication channel(s) that can differ based on which stage of the claims process the claim is in.

The invention discloses a product verification and customer reward method and system based on a block chain and a non-temporary computer readable medium. The method includes: receiving, by a decentration application executing on an electronic device associated with a customer, information including a unique code associated with a consumer product; comparing the unique code with an authorization record stored on a block chain account book to verify the authenticity of the consumer product; upon successful verification, distributing a portion of the collective non-homogenized tokens linked to the consumer product to a digital wallet associated with the customer; and enabling pledge of cryptocurrency tokens derived from a portion of the collective non-homogenized tokens, and distributing awards to customers according to pledge conditions. Therefore, the authenticity of consumer products can be ensured, tamper-proof auditing tracking is provided, and the customer participation degree and brand loyalty are improved through a token motivation mechanism.

The embodiment of the invention discloses an online marketing user activity prediction method and device, equipment and a storage medium. The method comprises the following steps: acquiring parameter information corresponding to an online marketing activity, and taking the parameter information as a sample set; using each sample in the sample set to construct a plurality of symmetric trees in a preset CatBoost model; generating corresponding new feature vectors based on the plurality of symmetric trees; aiming at the new feature vector, searching an optimal solution of the new feature vector based on a preset model champion challenge strategy, and outputting a model corresponding to the optimal solution as a user activity prediction model; and using the user activity prediction model to predict a user to be subjected to activity prediction to obtain a prediction result. According to the technical scheme, on the basis of reducing the computing power, the active degree of user marketing can be effectively and reliably evaluated, and the accuracy of online marketing user active prediction is improved, so that the customer participation probability is more accurately evaluated.

The invention provides a compliance management and control method and system for a futures industry internet financial service, and the method comprises the steps: obtaining the communication information between a futures industry internet financial service platform and a customer in real time, and checking the communication information according to a checking rule, thereby obtaining a checking result; performing risk monitoring and early warning on the behavior of the customer participating in the futures industry internet financial service through a preset risk early warning condition to obtain a risk early warning result; and according to the audit result and the risk early warning result, performing compliance management and control on the futures industry Internet financial business. The invention aims to provide an automatic compliance management and control method for Internet financial services in the futures industry, and the method comprises the steps of real-time monitoring, automatic auditing, risk early warning, data filing and dynamic regulation of a rule model, so as to improve the compliance management efficiency and accuracy of the Internet financial services in the futures industry.