100 results about "E loyalty" patented technology

A system for providing context-specific item recommendations is provided, for example in support of customer loyalty programs. In examples, a contextual offer recommendation engine utilizes a deep neural network in an epsilon-greedy agent to implement a contextual multi-arm bandit. The contextual multi-arm bandit is used to explore optimal solutions regarding correspondence between offers and customers. The optimal solutions may represent customer-offer combinations which may be published to a campaign manager for display to a customer, e.g., via a retail server. The deep neural network may be continually and adaptively retrained an extended based on observed actions between customers and new or preexisting offers.

An intelligent, predictive customer loyalty system for social media marketing, consisting of: a data acquisition unit configured to collect user interaction data, demographic attributes, and sentiment analysis metrics from multiple social media platforms via platform-specific application programming interfaces (APIs), web scraping techniques, and direct data ingestion pipelines; a real-time engagement prediction engine comprising a machine learning model trained on historical engagement patterns, sentiment fluctuations, and content performance metrics, with the model dynamically predicting user responses, determining the optimal engagement time, and prioritizing interaction opportunities based on a probabilistic ranking technique; a real-time engagement prediction processing unit configured to generate and optimize social media posts, ads, and interactive media using a neural network-based natural language generation (NLG) model, where the model processes contextual user behavior and trending topics to dynamically adapt marketing content; an AI-powered automation unit for interactive engagement, comprising a deep learning-based chatbot engine integrated into a dialogue management system, with the chatbot engine analyzing the user's intentions, sentiment development, and engagement history to enable predictive, context-aware conversations with users; a cloud-connected processing unit that includes an AI inference accelerator configured to perform deep learning calculations for real-time engagement prediction units, personalized content recommendations, and chatbot response generation, with the processing unit integrated into a distributed computing framework to optimize inference latency.

The invention relates to a system which allows transactions of a user, such as collecting, sharing and selling NFTs (non-fungible tokens) and / or tokens to be executed and the loyalty programs to be used more effectively, wherein the system converts NFTs (non-fungible tokens) and / or tokens transferred to a three-dimensional world by an augmented reality technology into loyalty scoring systems and / or cryptocurrencies of sellers operating in different industries.

A computer-implemented method, a computer program product, and a computer system for phygital integration in commerce-based checkout experiences. A computer aggregates data from one or more personal devices of a user and data from one or more biosensors of the user. A computer trains a machine learning model on features extracted from aggregated data. A computer uses the machine learning model to predict purchase preferences of the user and to generate for the user personalized recommendations, promotions, and loyalty rewards. A computer generates notifications about the personalized recommendations, promotions, and loyalty rewards. A computer transmits the notifications to the one or more personal devices. A computer monitors interactions of the user with the personalized recommendations, promotions, and loyalty rewards. A computer uses information of the interactions to train the machine learning model for future prediction of the purchase preferences and future generation of the personalized recommendations, promotions, and loyalty rewards.

Decentralized computer systems and methods are disclosed for establishing and conducting payment processing with loyalty points using distributed ledger. One method includes: receiving a consumer identification, an issuer identification, and transaction information from a point of sale system when the loyalty card is presented for a transaction of a good or service at a merchant, identifying the network node containing distributed ledger associated with the issuer according to received issuer identification prompting, to participants of the shared ledger, to validate whether the consumer distributed ledger has required loyalty points for the transaction; if all of the participants of the shared ledger accepts the transaction, generating, a new immutable entry to the distributed ledger for the transaction with remaining loyalty points in the loyalty card after deducting the points required for the transaction; and sending a transaction approved message to the point of sale system at the merchant.

A loyalty program management system associated with an enterprise location is provided. The loyalty program management system is programmed to: a) receive a plurality of input data associated with a plurality of patrons, wherein the plurality of input data represents actions of the plurality of patrons; b) determine a current location of a patron of the plurality of patrons, wherein the current location of the patron is not at the enterprise location; and c) transmit a message to a computer device associated with the patron including a prize to be awarded if the patron visits the enterprise location.

Various aspects disclosed herein are directed to intelligent advantage spin techniques implemented in wager-based games conducted on electronic gaming devices. The intelligent advantage spin techniques may be incorporated into wager-based slot games for offering players various types of re-spin opportunities via the use of Advantage Spin (AVS) credits, loyalty points, or game credits. During gameplay, the system provides real-time analysis of game outcomes, identifying strategic moments such as near-miss scenarios to dynamically present customized advantage spin offers to players. Players can leverage AVS credits to selectively re-spin individual reels and / or symbols. AVS credits may also be employed as promotional incentives, redeemable across different game themes or EGMs, and can persist across gaming sessions, different EGMs, different venues, etc. Integration with systems like TITO and player loyalty accounts ensures seamless credit management, allowing casinos to issue, track, and incentivize credits based on both gaming and non-gaming activities.

A system for reward generation on a social media platform is disclosed. The system includes a processing subsystem having a. registration module linking multiple social media accounts for a user. An engagement calculation module identifies key metrics like likes, comments, and shares, calculating individual metrics for each engagement type. The engagement calculation module computes a total engagement value for specific posts or overall accounts. The training module uses historical data, to train machine learning models, fine-tuning hyperparameters for iterative improvement. The reward generation module establishes a conversion rate between total engagement and reward points, dynamically assigning loyalty through trained models. A reward redemption module facilitates the accumulation of points in a virtual wallet, converting them into various assets like money or cryptocurrency using blockchain integration. This comprehensive approach ensures a fair and personalized reward system based on user engagement levels.

A system and process to generate product brand loyalty and provide incentives at the agent-to-agent level of the supply network tree is disclosed. Exemplary embodiments provide a “dynamic coupon” which is a dynamic electronic file construct that includes a changing value associated with a product / service. The dynamic coupon improves for example the effectiveness of existing cashback coupon programs. The coupon may be integrated into a digital wallet, which may be provided to user members (for example agents in the supply chain) on a loyalty network. Each owner of a digital wallet may have dynamic coupons in their wallet that are accrued based on consumer activity with products or services they are involved with. The coupon may be product specific, attached directly to the finished consumer good / service.

A system for reward generation on a social media platform is disclosed. The system includes a processing subsystem having a registration module linking multiple social media accounts for a user. An engagement calculation module identifies key metrics like likes, comments, and shares, calculating individual metrics for each engagement type. The engagement calculation module computes a total engagement value for specific posts or overall accounts. The training module uses historical data to train machine learning models, fine-tuning hyperparameters for iterative improvement. The reward generation module establishes a conversion rate between total engagement and reward points, dynamically assigning loyalty through trained models. A reward redemption module facilitates the accumulation of points in a virtual wallet, converting them into various assets like money or cryptocurrency using blockchain integration. This comprehensive approach ensures a fair and personalized reward system based on user engagement levels.

The present disclosure generally relates to the use of loyalty accounts, private label payment accounts, and general payment accounts using an electronic device with an electronic wallet. Various accounts are linked to the electronic device. In some examples, the electronic device is NFC-enabled. The electronic device may be used to provide loyalty account information and payment account information to a payment terminal, such as an NFC-enabled payment terminal.

The present application relates to the field of operation optimization technology, and specifically discloses a franchise store operation optimization method and system based on big data, which first extracts a set of evaluation data for franchise stores from customer feedback data, and uses data processing technology based on deep learning to semantically encode each evaluation data, extracts the semantic embedding feature representation of each evaluation data, and then, through multi-scale temporal context semantic association analysis of each evaluation data, to dig out the implicit customer emotion change trend in the evaluation data, so as to realize intelligent recognition of customer emotion polarity change. In this way, the needs and preferences of customers can be grasped more accurately, so as to adjust the menu, promotion strategy and business strategy to improve customer satisfaction and loyalty, and then achieve better business benefits.

A system for configuring a digital wallet application for implementing a casino player loyalty program includes a memory storing reward configuration data associated with digital wallet awards and a processor configured to: (a) provide an award type user interface for receiving player loyalty award types; (b) receive award type data corresponding to one or more selected player loyalty award types; (c) provide an award threshold user interface for receiving at least one indication corresponding to player loyalty award thresholds; (d) receive award threshold data corresponding to one or more selected player loyalty award thresholds; (e) provide an award trigger user interface for receiving player loyalty award triggers; (f) receive award trigger data corresponding to selected player loyalty award triggers; and (g) configure a rules engine for a mobile wallet based, at least in part, on the award type data, the award threshold data and the award trigger data.

Methods, system and devices for managing loyalty incentive schemes are provided. In particular, payment terminals are provided that each comprise an electronic screen for displaying information to a user relating to a payment transaction, data input means, including at least one payment instrument interface for interfacing with a customer payment instrument, and at least one telecommunication module. A terminal management server is provided for managing the operation of the payment terminals. An incentive management server is also provided, for managing incentives to be applied at the payment terminals.

The invention relates to the technical field of enterprise data intelligent management, in particular to a service optimization method and system based on multi-dimensional enterprise data fusion, and the method comprises the following steps: taking a unified social credit code as a main key, and combining an enterprise name and an operation address as auxiliary matching keys; industrial and commercial registration data, tax declaration data, energy consumption monitoring data, social insurance payment data and operation development data are fused; the method has the beneficial effects that a real-time calculation framework and an intelligent algorithm are adopted, the sudden risk of an enterprise, such as sudden energy consumption increase and tax decline, can be captured in time, and an early warning and service intervention mechanism is automatically triggered. Therefore, enterprises can quickly respond to market changes, the operation risk is reduced, and the competitiveness is improved. And by accurately sensing enterprise demands and service states, the system can realize optimal configuration and efficient utilization of the service resources. Therefore, the service cost can be reduced, the service quality can be improved, and the customer satisfaction and loyalty can be enhanced.

Examples provide a system, method, and computer storage device for automatically presenting a loyalty index for a user. A loyalty index is calculated using transaction details for a plurality of users for a time period. The calculation involves calculating a total entity transaction amount, a total user transaction amount, and an entity proportion for each entity per user. The exclusivity loyalty factor proportion is an average value of the entity proportion for each entity in the favorite entities list weighted by the total entity transaction amount of each user with that entity. The examples present each entity and corresponding exclusivity loyalty factor proportion as an index icon in a user interface and automatically move the index icons to a list in the user interface in descending order of exclusivity loyalty factor proportion.

A method and system for leveraging an existing issuer user application, associated with a payment network, to create centralized merchant loyalty platform. The centralized merchant loyalty platform consolidates computing resources from different merchant systems to a centralized processing system. The centralized processing system creates a scalable computing platform that allows for loyalty programs associated with a plurality of different merchants to be seamlessly accessed through the existing issuer user application.

Systems and methods which offer a loyalty program affiliated with different entities associated with an enterprise.

Aiming at the problems of low detection precision and the like caused by uneven enterprise customer loss prediction data samples and complex features at present, the invention provides a customer loss prediction model based on a hybrid model. The method comprises the following steps: preprocessing original data, constructing features according to an RFM model, carrying out standardization processing on the data, clustering clients by using a K-means algorithm, carrying out loss prediction on categories with low loyalty after clustering, and carrying out accurate classification on the users with low loyalty by using a random forest algorithm. Experimental results show that the method improves the detection precision, reduces the detection workload, carries out comprehensive analysis, can provide certain guidance for an enterprise to predict customer loss, and has a good application prospect.

The invention discloses a gas station customer loyalty model training method, a gas station customer loyalty model application method and a gas station customer loyalty model training device. The training method comprises the following steps: determining a to-be-analyzed home station and a plurality of competitor gas stations corresponding to the home station; according to the collected customer refueling amount information and each competitor gas station, generating a loyalty score of each customer to the station; according to the acquired track data of the freight vehicles and gas station fences included in the gas station information, determining refueling parking details of each freight vehicle in the acquired vehicle data; according to the refueling parking details of each freight vehicle, constructing a characteristic data set of a refueling station, a refueling customer and a vehicle dimension; training a linear regression model through the feature data set to obtain a loyalty score of each customer predicted by the model; and obtaining a pre-trained gas station customer loyalty model according to the loyalty score of each customer to the station and the loyalty score of each customer predicted by the model. By adopting the method and the device, the loyalty of the customer in the market can be accurately reflected.

A method, apparatus, and computer readable storage to implement an augmented game system. A player can play an online game and accumulate loyalty points without have to pay cash. The player can enter a physical casino and play an electronic gaming machine which can retrieve the player's information from the online game including the number of loyalty points the player has and any other incentives or game add-ons the player would be entitled to. The player would then play a physical game on the electronic game normally (by depositing cash and playing) but the game play would be augmented by virtue of the player having the loyalty points or other incentives or add-ons. For example, the game can be augmented by giving the player a better paytable.

The invention is titled "User Interfaces for Loyalty Accounts and Private Label Accounts for Wearable Devices". This disclosure generally relates to the use of loyalty accounts, private label payment accounts, and general payment accounts using a wearable electronic device having an electronic wallet. Various accounts are linked to the electronic device. In some examples, the electronic device supports NFC. The electronic device can be used to provide loyalty account information and payment account information to a payment terminal such as an NFC-enabled payment terminal.

A player loyalty kiosk, system, method, and program product provide a loyalty game machine game with an enhanced player interface. A display system of the player loyalty kiosk displays the gaming interface including an animated game effect in a first area of the display system with one or more moving elements. Responsive to a player input a player input rate measurement is adjusted based on a rate of player inputs over time. A velocity of a first one of the moving elements is adjusted based on the player rate input measurement and adjusting a conclusion of the animated game effect based at least in part on the movement of the adjusted moving element.

A digital promotion processing system may include a shopper device associated with a given shopper associated with respective loyalty programs at different retailers, and a promotion processing server. The server may generate a promotion identifier associated with a digital promotion. The promotion may be redeemable at the different retailers and having a redeemable value associated therewith. The server may communicate the promotion to the shopper device, cooperate with the shopper device to display the promotion, and determine a corresponding loyalty program redemption value corresponding to the redeemable value of the promotion for each of the different retailers. The server may also permit shopper-selection of one of the different retailers for redemption, and determine when the given product has been purchased by the given shopper, and when so, apply the corresponding loyalty program redemption value according to the shopper-selected one of the different retailers and based upon the promotion identifier.

The invention relates to a method performed by a processor unit (10) associated with at least one memory unit (20) to determine, based on actions taken by at least one user with at least one user device, at least one loyalty score of said user to at least one service provider, and to present personalized content tailored to the user based on said loyalty score.

A method for exchanging loyalty points includes storing one or more user loyalty profiles including a user identifier and one or more merchant identifiers associated with a loyalty point total; receiving a transaction request from a computing system including at least a user identification, a merchant identification, and a transaction amount; identifying a user loyalty profile including a user identifier that matches the user identification; in response to identifying the user loyalty profile, determining the merchant identification matches one of the one or more merchant identifiers; determining the loyalty point total associated with the matching merchant identifier is lower than a loyalty point total required to cover the transaction amount; and exchanging a first amount of loyalty points associated with a different merchant identifier of the one or more merchant identifiers for a second amount of loyalty points associated with the merchant identifier that matched the merchant identification.

The invention relates to a public transportation and customized public transportation collaborative dynamic pricing method and system. The method comprises the following steps: acquiring and fusing passenger behaviors, a vehicle Internet of Things, an external environment, a competition situation and operation cost data; constructing a dynamic user portrait based on the fused data, carrying out clustering and grouping, and generating price sensitivity, time sensitivity, comfort preference and service loyalty portrait tags; predicting payment willingness of the user based on the portrait; a collaborative pricing and travel recommendation strategy for different groups is generated by taking the system state and the user group portrait vector as input through a reinforcement learning pricing engine; executing the strategy and carrying out differentiated ticket price adjustment and service recommendation; passenger feedback data are collected, and user portraits and reinforcement learning model parameters are updated. According to the invention, the conversion from static splitting pricing to dynamic collaborative pricing is realized, the problems of poor collaboration and lack of elasticity of the system are solved, and the revenue capability and resource allocation efficiency of the system are remarkably improved.

A computer-implemented method, a computer program product, and a computer system for phygital integration in commerce-based checkout experiences. A computer aggregates data from one or more personal devices of a user and data from one or more biosensors of the user. A computer trains a machine learning model on features extracted from aggregated data. A computer uses the machine learning model to predict purchase preferences of the user and to generate for the user personalized recommendations, promotions, and loyalty rewards. A computer generates notifications about the personalized recommendations, promotions, and loyalty rewards. A computer transmits the notifications to the one or more personal devices. A computer monitors interactions of the user with the personalized recommendations, promotions, and loyalty rewards. A computer uses information of the interactions to train the machine learning model for future prediction of the purchase preferences and future generation of the personalized recommendations, promotions, and loyalty rewards.

A method for changing operation modes includes receiving disaster information from trending data, a newsfeed, or an alert message; upon detecting at least one redirection trigger from the disaster information, configuring a loyalty system to operate in a redirection mode; receiving or accessing data associated with a transaction between a customer and a merchant; determining, from at least one of customer information and merchant information in the data associated with the transaction, a donation amount and a location associated with the transaction; when the loyalty system is configured to operate in a redirection mode, generating signals to cause accrual of at least a portion of the donation amount to a redirection account based on the location associated with the transaction; and generating signals to cause accrual of any remaining portion of the donation amount to one or more defined donation accounts based on charity catchment area parameters.