26 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.

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.

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.

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 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 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.

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.

A customer support system for improving engagement as a customer navigates a software product is provided. The customer support system includes a session recording module configured to capture a screen recording of a customer session. It further includes a session analysis module coupled to the session recording module and configured to analyse the screen recoding to generate a corresponding summary of the customer session and to tag a plurality of issues faced by the customer during the customer session. The customer support system further includes a suggestion module configured to provide a plurality of suggestions in real-time to the customer.

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. The system also includes storage for relevant data and a microprocessor to execute parts of the recommendation engine. 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.

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.

Previously, it was not possible to obtain comprehensive engagement information based on various customer actions. [Solution] An information processing device 1 comprises an engagement acquisition unit 132 that acquires engagement information about a user's customer engagement using one or more action information pieces, which are information about a user's actions toward one or more different types of objects, and other action information pieces, which are information about actions of non-users corresponding to each of the one or more action information pieces, and an engagement output unit 141 that outputs the engagement information acquired by the engagement acquisition unit 132, thereby enabling the acquisition of comprehensive engagement information based on various customer actions.

A system and method for collecting, organizing, and curating customer engagements across multiple interactions and touch points. The disclosed method allows for a discovery of purposes, an accretion of micro-journeys for a plurality of customers and a contextual nurturing of those customers on respective journeys towards their next milestones using numerical, graphical, statistical, and heuristics-based methods and proposed memory layouts of the same. Real-time staging and processing of inbound factual data and inferential dimensions into a multipartite multidimensional space of the factual and inferential dimensions to enable the mapping of customer interactions with a brand and the digital encoding thereof.

A method for automatically identifying a root cause of customer dissatisfaction with a software product and creating feedback items to improve the software product includes collecting engagement data pertaining to interactions between a customer and a flow of visual elements presented by the software product and detecting a trigger event indicating that the customer is dissatisfied with the software product. In response to the trigger event and based at least in part on the engagement data, a potential deficiency of the software product is automatically identified and a repair ticket is generated for a development team. The repair ticket identifies the potential deficiency of the software product.

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.