90 results about "Omnichannel" patented technology

The present invention discloses a method and system for intelligent switching of communication protocols for an omni-channel contact center, the method comprising the steps of: evaluating the performance of each communication protocol according to user needs and the current system status, selecting the optimal communication protocol and opening the corresponding communication service for the user; continuously monitoring the communication quality under the selected current communication protocol, and triggering the reselection of the communication protocol if it is detected that the communication quality is lower than expected; re-evaluating the performance of each communication protocol under the current system state to select the target communication protocol, and switching the current communication service from the current communication protocol to the target communication protocol. The present invention realizes smooth switching between different communication protocols, can intelligently identify and automatically select the optimal communication method, while maintaining the continuity and quality of the call unaffected. In addition, the present invention also supports dynamic adjustment of the communication method according to network conditions, ensuring that users can obtain the best communication experience regardless of the network environment.

The invention relates to the technical field of digital marketing, and discloses an omni-channel marketing funnel intelligent attribution model and an automatic budget distribution system, and the model comprises a data collection module which is used for collecting data through a contact recording device and a user identification device which are disposed at a marketing terminal, and a behavior tracking device and a channel classification device which are disposed at a user side. Acquiring information such as multi-channel marketing contact interaction data, user behavior data and channel types; the path analysis module realizes data path analysis through time sequence synchronization of a time alignment unit, feature matching of a path association unit and dynamic adjustment of a computing power scheduling unit; the attribution calculation module generates the conversion attribution weight of each channel based on the matching data; and the budget mapping module establishes a dynamic mapping relationship between the weight and the budget and updates the dynamic mapping relationship. The system outputs the attribution result through the model application module, and the budget execution module distributes the budget according to the dynamic mapping, so that the channel contribution can be accurately evaluated, the scientific distribution of the marketing budget is realized, and the marketing efficiency and the rate of return on investment are improved.

Systems, methods and user interfaces are provided for generating real-time and / or diagnostic omnichannel interaction insights. The method may include obtaining transcripts corresponding to digital service channels. The method may also include generating and inputting channel-specific prompts to machine learning models to obtain insights. The method may also include generating and / or displaying analytical insights. The method may also include obtaining a natural language question, via a conversational interface, directed to a benefits database. The method may also include parsing the question. The method may also include ranking benefits using a recommendation algorithm. The method may also include generating a context by applying a language template. The method may also include inputting the context to a large language model. The method may also include providing a response to an agent to cause the agent to perform one or more actions. The method may also include generating and displaying a dashboard.

Systems, methods, and / or articles of manufacture that utilize omnichannel Artificial Intelligence (AI) restaurant management modeling to accurately compute and update order fulfillment times in an omnichannel ordering environment.

A multi-tiered optimization and machine learning framework is provided in which operational decisions as far as driver capacity allocation are taken at three different levels or stages, namely, long-term, short-term, and real-time. While decisions at each stage have individual importance for the operations at different time horizons, this framework utilizes decisions upstream to inform better results downstream. This synergy helps improve allocations when compared to solutions that assign driver capacity for each stage individually.

Systems and methods for assessing trustworthiness of customer accounts in retail and e-commerce systems using machine learning are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a trust assessment request regarding a customer account; generating at least one trust-related feature or quantitative attribute associated with the customer based on historical transaction data and relevant account information of the customer; computing, using at least one machine learning model, trust score data of the customer based on the at least one trust-related feature; and transmitting, in response to the trust assessment request, the trust score data of the customer to the computing device.

Systems and methods for providing omnichannel cognition in a campaign are disclosed. An example platform can include a strategy hub configured to generate and provide a unified and real-time graphical interactive interface displaying an effectiveness of the campaign, wherein the strategy hub is further configured to allow users to dynamically connect strategies to tactics and track key performance indicators (KPIs) while making real-time adjustments and rebalancing of efforts across multiple channels to optimize campaign engagement; a tactic engine configured to utilize a generative artificial intelligence (GenAI) model for analysis and restacking of the tactics to generate an optimal tactic mix that improves engagement efficiency and outcomes based on predicted impact levels of the tactics; and an impact simulator configured to provide a virtual platform for simulating the campaign through virtual trials, to assess an effectiveness of the campaign prior to roll-out of the campaign.

The invention discloses a full-channel consumer behavior tracking and market investigation integrated platform, which adopts federated learning and differential privacy technologies to construct a privacy-friendly multi-feature identity analysis model, and realizes high-precision matching of cross-channel users. The platform uses a graph attention neural network to represent consumer omni-channel behaviors as a heterogeneous directed graph, and proposes a new structural friction index to identify conversion obstacle nodes in a decision trip. Dominant survey data and recessive behavior data are jointly embedded by using an auto-encoder, a causal forest model is introduced to estimate the causal effect of attitude factors on purchase behaviors, and a comprehensive value function is constructed to fuse behavior preference, attitude tendency, causal effect and journey resistance. And the decision support layer automatically triggers personalized marketing intervention according to the friction index and the value score, and feeds back a dynamic optimization model in combination with an A / B test. According to the invention, balance between privacy protection and accurate identification is realized, consumer decision-making journey can be deeply observed, and causal-driven value prediction is provided.

Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to implement automated responses to data representing electronic messages, among other things, and, more specifically, to an automated predictive response computing system independent of electronic communication channel of an electronic message payload, the automated predictive response computing system being configured to, for example, implement a universal data space based on, at least in part, conversational data flows, which may be classified and used to provide a predictive response to assist resolution, such as assisting an agent among other things. In an example, a method may include augmenting at least a subset of one or more portions of communication data, implementing augmented communication portion data to determine a predicted response, and generating data to facilitate the predicted response based on the subset of inbound electronic messages.

The invention discloses an Internet of Things industry intelligent customer service supervision and control system based on artificial intelligence, and belongs to the technical field of customer service supervision. Comprising an omni-channel intelligent access and intention understanding module, an AI intelligent center and complex decision module, an intelligent supervision and ethical regulation and control module, a man-machine cooperation and humanistic care module, a data-driven optimization and edge intelligent module and a security privacy and controllable treatment module, and the omni-channel intelligent access and intention understanding module is used for integrating multiple channels. Unified request distribution is achieved, data input by a user are analyzed through voice recognition, NLU natural language understanding and image recognition technologies, composite intentions are accurately captured, interaction strategies are dynamically adjusted in combination with device state data, user historical behaviors and real-time positions, and pacified talking skills or manual intervention are triggered through voiceprint / text emotion analysis. On the basis of realizing customer service supervision and regulation, all-channel fusion and intention accurate analysis can be realized, and ethical safety integrated design can be realized.

The invention discloses a customer service omni-channel-oriented multi-modal arrangement system, and the system comprises an omni-channel access module which integrates ASR, OCR and MLLM technologies and is used for translating multi-modal data input into unified text semantic representation in real time; the logic arrangement module integrates NLP, LLM and IT interface components, supports extension and is used for logic arrangement based on business requirements, and the arranged service has multiple mechanisms and can realize a low-delay and high-availability service chain; the multi-modal generation module integrates TTS, T2I and MLLM technologies and is used for generating corresponding modal data according to channel requirements and supporting streaming and non-streaming output; and the full-process service monitoring module is used for monitoring the state, the time delay and the error rate of each module in real time and guaranteeing the service stability and the user experience. The cross-modal data unified processing is effectively realized, the system development and maintenance cost is reduced, and the customer service efficiency and quality are improved.

The invention provides a bank omni-channel message intelligent management and control method and system, and the method comprises the steps: accessing a standard structured event pushed by a business system, carrying out the compliance and anti-repetition verification, and obtaining a standardized event object; performing three-dimensional dynamic strategy matching on the received standardized event object to obtain a decision result containing a trigger rule ID; selecting a message sending channel based on the decision result containing the trigger rule ID, adopting a policy mode to realize multi-channel routing, and setting in a failover mechanism to obtain a channel execution context; and carrying out data storage on the standardized event object, the decision result containing the trigger rule ID and the channel execution context, and meanwhile, establishing an index to construct a full-link tracking index. According to the method, unified management and control of the messages are realized through standardized access and intelligent routing, accurate touch is ensured by adopting dynamic strategy matching, and unified management and control, dynamic optimization and visual monitoring of the whole message sending process are finally realized by combining failover and full-link tracking.

The invention discloses a data-driven omni-channel retailer inventory replenishment and distribution optimization algorithm, particularly relates to the technical field of retail inventory management, and aims at efficiently solving the problems of multi-SKU inventory management, demand uncertainty, inventory transfer cost and the like by adopting a PPO algorithm in deep reinforcement learning to optimize inventory replenishment and distribution decision. And automatic and intelligent inventory management is realized in actual operation.

The present invention provides an omnichannel notification push method and device, which relates to the technical field of automatic programming. The method includes: obtaining transaction information; determining the initiating channel information according to the transaction information; generating an omnichannel notification push message according to the initiating channel information; and sending the omnichannel notification push message to the front end. Based on the analysis of the transaction information, the present invention obtains the initiating channel information of the transaction information, then generates notification push information for other channels based on the initiating channel information, and further sends the omnichannel notification push message to the front end, enabling customers to receive message reminders of transactions occurring on all channels at a certain channel end, improving the customer experience and reducing the occurrence of customer misoperations.

An example system comprises a processor and storage containing instructions for generating: a micro front-end (MFE) registry with domain-specific language conformant micro frontends; a first channel control plane UI extension to display certain micro frontends; and a second similar extension; a control messaging module to communicate micro frontends between the registry and the first extension while obtaining user contexts; and one or more federated experience engines to select micro frontends for the second extension based on the obtained user contexts.

Systems, methods and user interfaces are provided for generating real-time and / or diagnostic omnichannel interaction insights. The method may include obtaining transcripts corresponding to digital service channels. The method may also include generating and inputting channel-specific prompts to machine learning models to obtain insights. The method may also include generating and / or displaying analytical insights. The method may also include obtaining a natural language question, via a conversational interface, directed to a benefits database. The method may also include parsing the question. The method may also include ranking benefits using a recommendation algorithm. The method may also include generating a context by applying a language template. The method may also include inputting the context to a large language model. The method may also include providing a response to an agent to cause the agent to perform one or more actions. The method may also include generating and displaying a dashboard.

The present invention proposes a client-side multi-channel aggregated advertising delivery system and method based on Electron, the method comprising: obtaining the advertising business information required for advertising delivery through the advertiser client built by Electron, and sending the advertising business information to the Web server; the Web server receives the advertising business information, adapts the media advertising platform corresponding to the advertising business information and the advertising business data corresponding to the media advertising platform through the omni-channel API adaptation service, converts the advertising business data, and sends the converted advertising business data to the channel server; the channel server receives the converted advertising business data, and delivers the converted advertising business data to the corresponding media advertising platform through the channel API of the media advertising platform. The present invention enables advertisers to deliver advertisements across systems, media platforms and accounts, integrates all head media advertising platforms, and improves delivery efficiency and effectiveness.

A system, apparatus, method, and non-transitory computer readable medium for providing an omni-channel content mapper framework may include a server caused to receive a content request from at least one user device, the content request including a unique content identifier associated with the requested content and desired content type information corresponding to the requested content, determine a desired content mapper (CM) plugin corresponding to the desired content type information from a plurality of CM plugins, obtain content data corresponding to the unique content identifier from a content database, generate an application-agnostic structured data document using the determined content mapper plugin, the application-agnostic structured data document including the obtained content data, and transmit the application-agnostic structured data document to the at least one user device in response to the content request.

The invention provides a novel customer relationship management method, and belongs to the technical field of artificial intelligence and application. Establishing a data base which is used for gathering and integrating multi-source data and consists of client omni-channel interaction data and enterprise business data; based on feature engineering and RFM, the FCI model defines customer feature portraits including behavior preferences, management cycle stages and marketing response laws based on a data base. And taking the customer feature portrait as an input parameter of the random forest model, training the random forest model in combination with historical data, and outputting a marketing strategy including a recommendation category, a communication channel, an interaction frequency, a discount threshold value and a docking person level. According to the invention, based on the multi-dimensional marketing strategy output by the random forest model, the execution link can be directly connected, and manual secondary adjustment is not needed; and meanwhile, the model can quickly adapt to different customer group characteristics, so that'homogenization 'and'hysteresis' of traditional manual strategy formulation are avoided, and manual dependence and management cost are reduced.

A system and method for omnichannel text-based routing, transfer, and customer-to-enterprise communications. The system is a cloud-based network containing an interaction control server, a routing engine, an optimization engine, a media translation server, a mobile application, a business entity portal, mobile and compute devices for business enterprise and customer, and an enterprise database. Taken together or in part, said system optimizes customer interactions by delivering context aware text message, chat or email to customers; and when requested by customer, optimally routes with context, based upon a multitude of variables, to best available resource to handle the customer interaction. The system may be accessed through web browsers or purpose-built computer and mobile phone applications.

The invention relates to the field of big data analysis, and discloses an omni-channel retail enterprise cross-channel return management system based on a big language model, which comprises a return application module, a return information integration module, an automatic return processing module, a refund and compensation module, an intelligent analysis module and a feedback module, the goods return application module is used for initiating goods return requests in different sales channels, the system automatically examines and approves the goods return requests meeting conditions, the goods return information integration module is used for integrating goods return data from different sales channels, and the automatic goods return processing module automatically generates corresponding goods return processes according to goods return types. The refund and compensation module automatically calculates and processes refund according to the state of a returned commodity and a return policy, the intelligent analysis module is used for analyzing return data and identifying a return trend and potential problems, and the feedback module is used for collecting feedback and optimizing user experience. The method has the advantages of realizing automatic goods return processing and providing personalized goods return service.

The invention provides a safety protection method for a terminal application based on an omni-channel system and the omni-channel system.The method comprises the steps that events of the terminal application are obtained through a data collection system of the omni-channel system, and the events comprise one or more of an APP event, a light application event and a flow use event; according to the type of the event, a corresponding evaluation system of the omni-channel system is adopted for risk evaluation, an evaluation result is obtained, and the evaluation system comprises one or more of an APP evaluation system, a light application evaluation system and a flow evaluation system; and under the condition that the assessment result represents that the risk exists, a linkage analysis system of the omni-channel system is adopted to generate a defense instruction according to the assessment result, and the defense instruction is sent to a server used by the financial institution. The method solves the problem of low safety protection capability caused by fragmentation of a traditional application monitoring mode in the prior art.

Introduced here is a computer-implemented virtual assistant used for completing tasks in an omnichannel environment. The virtual assistant is a common entry point for task completion at an electronic device in a network and can be operable based on a model trained on user activity and network activity. The virtual assistant can receive a request to perform a task associated the electronic device. The virtual assistant can facilitate performance of a first action via a first channel of the network in furtherance of completing the task. Upon detecting performance of the first action, the virtual assistant can present instructions to perform a second action via a second channel (different from the first channel) in furtherance of completing the task. The virtual assistant can detect performance of the second action and present an indication of the completion of the task at the electronic device.

This invention relates to a method for creating a customer profile map and intelligent attribution analysis based on omnichannel data fusion. The method includes: obtaining a first feature set from multi-source heterogeneous raw data; extracting the time offset baseline and clock drift coefficient of nodes, compensating for discrepancies in conflicting timestamps, and obtaining a unified time-series benchmark through constraint propagation; extracting service commitment subjects and business process elements, using link association to obtain implicit associations between commitment elements and business nodes, and embedding business data under the unified time-series benchmark with the commitment link to obtain a second feature set; obtaining implicit associations and transmission paths between nodes to generate associated data for customer profile nodes; identifying abnormal nodes in complaint feedback and problem representation through cross-dimensional fusion; and tracing the source of the problem through reverse link tracing to obtain intelligent attribution results based on cause deconstruction. This method achieves a customer profile map and intelligent attribution analysis based on omnichannel data fusion.

This invention discloses a cloud-based omnichannel sales management method for electronic products, relating to the field of e-commerce supply chain management technology. The method includes: under the constraints of a channel product consistency benchmark table, aggregating and decomposing inventory quantities to generate an inventory status ledger and formulating inventory occupancy instruction rules; statistically analyzing inventory fulfillment capability indicators from the inventory status ledger and aggregating them into a supply capability score, and combining this with fulfillment path generation rules to generate a set of candidate fulfillment paths; performing structured processing and matching data retrieval on a preset pricing strategy configuration to generate a channel price snapshot table, and generating transaction judgment records through solidification and verification; evaluating the set of candidate fulfillment paths based on the transaction judgment records and inventory occupancy instruction rules, and, in conjunction with the channel price snapshot table, performing path selection and price verification to generate order confirmation records. This invention achieves end-to-end resource optimization and efficient collaborative decision-making.

AI ENHANCING OMNICHANNEL SHOPPING COMPUTER DEVICE

Described herein is a cloud-based omnichannel customer interaction service, also referred to as a contact center service, that deploys an improved data model for capturing customer interaction data. From the data model, a database schema is instantiated to include a set of related database tables. The arrangement and relationship of the data and the database tables improves the functioning of the contact center service in a variety of ways, to include seamless concurrent communications between customer and agent across multiple channels, and seamless transitions between agents, who can be added to a customer interaction with relative ease.

An omni-channel coupon system may link electronic coupons across several couponing channels by storing the electronic coupons in association with a user profile or loyalty account. A user may clip electronic coupons from several couponing channels, such as a mobile application, retail web page, social networking web page, email, short message service (SMS) message, a physical coupon, a manufacturer / third-party web page or other affiliated web page, a manufacturer / third-party application, etc. Each clipped electronic coupon may be stored with a user profile for the user. When the user purchases products or items at an online or retail store, the electronic coupons may be retrieved from the user profile and redeemed.

The invention provides a deep intention mining method and system based on omni-channel user feedback, and the method comprises the steps: S1, collecting omni-channel user feedback historical data and intention result data, constructing a multi-channel vector library, and maintaining lexicon map data; s2, retrieving a full-channel user feedback data source, performing retrieval threshold judgment, and if the similarity is smaller than a preset value, executing lexicon map preparation; otherwise, giving a conclusion through LLM intelligent analysis in combination with similar historical results; s3, multi-dimensional evaluation including rule evaluation, non-keyword library evaluation and keyword library evaluation is carried out on the feedback content in combination with the lexicon graph, and evaluation results are integrated; s4, deep intention mining is completed through LLM intelligent analysis in combination with a multi-dimensional evaluation result, and an analysis result is fed back to a data acquisition link to optimize a data system; and S5, the mining result is visually displayed through Echarts. Through deep mining of omni-channel feedback data, intentions of banking business users are accurately captured, and business optimization and resource matching are assisted.

The embodiment of the invention discloses a multi-source data integration method and device based on a graph algorithm, a platform and a medium. The method comprises the steps that business data from multiple different channels are acquired, the business data comprise multiple pieces of consumer data, and the consumer data comprise multiple pieces of consumer attribute data; generating consumer identifiers respectively corresponding to the consumer data; grouping the plurality of consumer data based on a preset graph algorithm and a preset identity recognition rule to obtain a plurality of consumer data groups; for each consumer data group, generating a unified identity identifier corresponding to the consumer data group, and associating the unified identity identifier with each consumer identifier in the consumer data group to obtain an identifier integration graph; and for each identification integration graph, performing association integration processing on the consumer data associated with the identification integration graph to obtain omni-channel consumer integration data. According to the embodiment of the invention, the consumer data of the same consumer in different channels can be associated and integrated.