US-20260127496-A1 - SYSTEM AND METHOD FOR TARGETED MESSAGING AND OFFERS VIA MOBILE AND ADVERTISING PLATFORMS

US20260127496A1US 20260127496 A1US20260127496 A1US 20260127496A1US-20260127496-A1

Abstract

Digital marketing and customer relationship management systems, particularly to systems and methods designed for businesses to send targeted messages, referred to as “Nudges™” and “Reverse Nudges™” to engage customers, enhance customer loyalty, and increase sales through personalized offers and interactions. The system includes a “Dine Savvy™ Media Feed”—an AI-powered social content platform that aggregates and personalizes dining-related Posts, Nudges™, Super Nudges™, and Savvy Nudges™ using Vibe Vector-based emotional matching, contextual targeting, aesthetic refinement, and automated moderation.

Inventors

Jennifer GANTHER
Myles LEIGHTON

Assignees

Dine Savvy LLC

Dates

Publication Date: 20260507
Application Date: 20251104

Claims (14)

1 . A system comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive product or service information from a business and customer preference information from a database; generating a data set comprising a plurality of transformations of said product or service information; apply, to each of said transformations, a trained machine learning model to obtain respective classifications with associated confidence scores derived from the customer preference information; compute a consensus classification and corresponding confidence score based on the classifications and scores; construct a re-training dataset comprising at least some of said transformations annotated with the consensus classification; re-train the machine learning model using the re-training dataset; and output personalized product or service offers (Nudges™) to customers via the Internet, mobile applications, or advertising platforms based on the consensus classification and confidence score.
2 . The system of claim 1 , further comprising a Reverse Nudge™ feature wherein customers solicit offers from businesses, and the system processes responses using the trained machine learning model to personalize and deliver counter-offers.
3 . The system of claim 1 , wherein the Nudges™ are generated by suppliers or distributors and distributed through merchants to end customers, integrating supply chain communications.
4 . The system of claim 1 , wherein the output personalized offers are delivered via a social media feed comprising a plurality of content types including Posts, Nudges™, SuperNudges™, and SavvyNudges™.
5 . The system of claim 4 , wherein the social media feed is personalized using a multi-stage AI pipeline comprising: a. generating a Vibe Vector for each content item; b. generating a User Vibe Vector based on user behavior, preferences, and context; c. computing similarity between User and Content Vibe Vectors; d. applying generative AI for aesthetic refinement; and e. performing automated content moderation before display.
6 . A method comprising: receiving product or service information from a business and customer preference information from a database; generating a data set comprising a plurality of transformations of said product or service information; applying, to each of said transformations, a trained machine learning model to obtain respective classifications with associated confidence scores derived from the customer preference information; computing a consensus classification and corresponding confidence score based on the classifications and scores; constructing a re-training dataset comprising at least some of said transformations annotated with the consensus classification; re-training the machine learning model using the re-training dataset; and outputting personalized product or service offers (Nudges™) to customers via the Internet, mobile applications, or advertising platforms based on the consensus classification and confidence score.
7 . A computer program product comprising: a non-transitory computer-readable storage medium having program instructions embodied therewith, the program instructions executable by at least one hardware processor to: receive product or service information from a business and customer preference information from a database; generate a data set comprising a plurality of transformations of said product or service information; apply, to each of said transformations, a trained machine learning model to obtain respective classifications with associated confidence scores derived from the customer preference information; compute a consensus classification and corresponding confidence score based on the classifications and scores; construct a re-training dataset comprising at least some of said transformations annotated with the consensus classification; re-train the machine learning model using the re-training dataset; and output personalized product or service offers (Nudges™) to customers via the Internet, mobile applications, or advertising platforms based on the consensus classification and confidence score.
8 . A system for generating a personalized media feed, comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions executable to: receive a plurality of content items from brands, merchants, and consumers; generate a Vibe Vector for each content item using a trained machine learning model; generate a User Vibe Vector from user profile, behavior, and context; compute similarity scores between User and Content Vibe Vectors; rank and filter content based on similarity, location, and time; apply generative AI to refine visual and textual elements; perform automated moderation to remove objectionable content; and output a personalized Dine Savvy™ Media Feed to the user, integrating targeted Nudges™.
9 . The system of claim 8 , wherein content items include SavvyNudges™ sponsored by brands and created by a platform operator.
10 . The system of claim 8 , wherein user actions including “Cheers!”, “Share”, and “Go there!” are used to update the User Vibe Vector in real-time.
11 . The system of claim 8 , wherein the media feed includes interactive elements enabling navigation to physical merchant locations based on geolocation data.
12 . A method for personalizing a social media feed, comprising: receiving content from multiple sources; extracting a Vibe Vector for each content item; computing a User Vibe Vector; ranking content by Vibe Vector similarity and contextual relevance; refining content aesthetics using generative AI; moderating content for safety; and delivering a personalized feed integrating Nudges™.
13 . The method of claim 12 , wherein the feed supports Reverse Nudges™ by allowing users to solicit and receive personalized offers in response to content interactions.
14 . A computer program product comprising a non-transitory computer-readable storage medium having program instructions embodied therewith, the program instructions executable by at least one hardware processor to perform the method of claim 12 .

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Ser. No. 63/715,783 , filed Nov. 4, 2024, titled “System and Method for Targeted Messaging and Offers via Mobile and Advertising Platforms,” the contents of which are incorporated herein by reference in their entirety. FIELD OF THE INVENTION The present invention relates generally to digital marketing and customer relationship management systems, particularly to a system and method designed for businesses to send targeted messages, referred to as “Nudges™” to engage customers, enhance customer loyalty, and increase sales through personalized offers and interactions. The invention further includes a social media feed system, referred to as the “Dine Savvy™ Media Feed,” that aggregates and personalizes content from brands, merchants, and consumers using AI-driven contextual ambiance targeting. BACKGROUND In today's modern era, consumers use web-based apps and smartphone-based apps to order food from restaurants on a regular and frequent basis. In certain areas, there are thousands of existing restaurants to choose from, and accordingly, consumers are often left with a decision of which restaurant to choose. Such a situation can be frustrating, especially when traveling, out with friends, or worse, on a date. On the restaurant side of a commercial exchange, restaurants need to direct consumers to their restaurants to purchase and consume food produced by the restaurant, and due to large restaurant competition, that exists. Accordingly, there is a need to connect consumers with restaurants according to the consumer's dining preferences through web-based and smartphone-based apps, to drive sales to restaurants, and to help users choose the specific restaurant to dine-in at or to order from. Furthermore, there is a need for targeted digital marketing provided by restaurants to consumers, based upon consumer preferences through customized marketing and promotion, to drive business to restaurants to create increased sales and revenues for restaurants. Furthermore, this is a need for digital targeted marketing provided by restaurants to consumers, based upon consumer preferences through customized marketing and promotion to drive business to restaurants to create increased sales and revenues for restaurants. SUMMARY OF THE INVENTION Accordingly, it is an object of the invention to provide customized digital marketing and targeted marketing to consumers. It is an object of the invention to provide a business-facing system for creating and distributing Nudges™ and a customer-facing system for receiving personalized offers. A “Nudge™” is an inventive system and method for businesses to send targeted messages and offers to their customers. It is an object of the invention to provide a “Reverse Nudge™” feature which allows consumers to solicit offers from businesses. It is an object of the invention to provide a “Dine Savvy™ Media Feed”—a social media-style content aggregation and personalization system and method that delivers hyper-personalized dining-related content including Posts, Nudges™, Super Nudges™, and Savvy Nudges™, using a multi-stage AI pipeline based on “Vibe Vectors,” dynamic user profiling, aesthetic refinement, and automated content moderation. It is an object of the instant invention to provide a system for generating and personalizing a media feed comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive a plurality of content items from a plurality of sources; generate a Vibe Vector for each content item using a trained machine learning model; generate a User Vibe Vector based on user behavior, preferences, and context; compute similarity scores between the User Vibe Vector and each content item's Vibe Vector; rank and filter content based on said similarity scores and contextual relevance; apply aesthetic refinement to selected content using generative AI; perform automated content moderation; and output a personalized media feed to the user. It is an object of the invention to provide customized digital marketing and targeted messaging to consumers based on preferences, behavior, and context. It is object of the invention to provide a business-facing system for creating and distributing Nudges™ (targeted messages and offers) and a customer-facing system for receiving personalized offers, including integration with advertising platforms and mobile applications. It is an object of the invention to provide a “Reverse Nudge™” feature that allows consumers to solicit offers from businesses. It is an object of the present invention to provide a “Nudge™ direct communication system” that enables businesses (including suppliers, distributors, and merchants) to communicate offers or Nudges™ directly to “on-th