# US 12,762,610 B1 · System and method for AI-driven marketing automation across digital channels > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,762,610 B1 - Document ID: US12762610B1 - Status: Granted - Kind: B1 - Application number: 19/206,829 - Filed: 2025-05-13 - Granted: 2026-10-13 - Earliest claimed: 2025-05-13 - Applicants: Derrick Bliss - Inventors: Derrick Bliss - Web page: https://patentgrep.com/patent/US12762610B1 ## CPC - G06Q 30/0641: {utilising user interfaces specially adapted for shopping} - G06Q 10/40: Business processes related to social networking or social networking services - G06Q 30/0276: {Advertisement creation} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract An artificial intelligence (AI)-driven system of performing automated digital marketing includes a graphical user interface configured to be displayed on a user device and including an adjustable graphical selector, such as a sliding lever, that allows a user to select a desired level of marketing services by adjusting the selector across a service scale including multiple service tiers. A machine learning model receives a selected position of the graphical selector, determines one or more marketing services associated with the selected service tier, and collects marketing input corresponding to a business of the user and associated with the selected services. Using the marketing input, the machine learning model generates at least one digital marketing asset. The system then transmits the generated digital marketing asset to at least one digital delivery endpoint for publication or deployment, enabling dynamic and scalable execution of marketing campaigns with minimal human intervention. ## Claims ### Claim 1 A system of performing automated digital marketing, comprising: an artificial intelligence (AI)-driven digital marketing system in communication with a machine learning model and comprising at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the AI-driven digital marketing system to generate a graphical user interface including an adjustable graphical selector configured to be displayed on a user device, wherein the adjustable graphical selector is part of the graphical user interface and is configured to receive an input, from a user via the user device, indicating a desired level of marketing services in response to the user adjusting the adjustable graphical selector across a service scale including a plurality of service tiers, and wherein movement of the adjustable graphical selector to a given position causes the AI-driven digital marketing system to: dynamically configure a set of marketing services corresponding to a selected service tier; and display one or more corresponding form fields for collecting the marketing input associated with the configured services, wherein displaying the one or more corresponding form fields comprises dynamically modifying a structure of the graphical user interface by automatically adding, removing, or rearranging the one or more corresponding form fields based on the given position of the adjustable graphical selector; wherein the machine learning model includes a reinforcement learning component and is configured to: receive, from the adjustable graphical selector, a selected position corresponding to the selected service tier; determine at least one marketing service associated with the selected service tier by analyzing the selected position of the adjustable graphical selector; receive marketing input corresponding to a business of the user and associated with the determined at least one marketing service, from the user, via the graphical user interface; generate, using the marketing input, at least one digital marketing asset; generate, using an artificial neural network (ANN), onboarding data associated with the determined at least one marketing service; transmit the onboarding data to at least one third-party digital platform, wherein transmitting the onboarding data causes the at least one third-party digital platform to activate the at least one marketing service, and wherein transmitting the onboarding data comprises configuring the determined at least one marketing service on the at least one third-party digital platform based on the onboarding data; transmit the at least one digital marketing asset to the at least one third-party digital platform; receive, from the at least one third-party digital platform, campaign performance data comprising at least one of impressions, clicks, conversions, or engagement statistics; adjust weights or parameters of the reinforcement learning component based on the campaign performance data; update the at least one digital marketing asset based on the campaign performance data; and generate and send an automated status update to the user indicating that the at least one marketing service corresponding to the selected service tier has been activated. ### Claim 2 (depends on 1) The system of claim 1, wherein the adjustable graphical selector comprises a sliding lever displayed horizontally along the service scale. ### Claim 3 (depends on 1) The system of claim 1, wherein the machine learning model is further configured to: retrieve online data associated with the business of the user from the at least one third-party digital platform, using the ANN; and supplement the marketing input with the retrieved online data, using the ANN. ### Claim 4 (depends on 1) The system of claim 1, wherein the machine learning model comprises a convolutional neural network (CNN), and is further configured to: analyze at least one visual asset or image associated with the business of the user, using the CNN; and supplement the marketing input with metadata extracted from the at least one visual asset or image, using the CNN. ### Claim 5 (depends on 1) The system of claim 1, wherein the at least one digital marketing asset includes at least one of an advertisement, website content, search engine optimization (SEO) metadata, and social media content. ### Claim 6 (depends on 1) The system of claim 1, wherein the at least one third-party digital platform includes at least one of a paid advertising network, a website hosting platform, and a social media platform. ### Claim 7 (depends on 6) The system of claim 6, wherein the machine learning model is further configured to: generate and send an automated optimization summary to the user indicating that campaign performance has been adjusted. ### Claim 8 (depends on 6) The system of claim 6, wherein the machine learning model is further configured to: generate and send an automated status update to the user indicating that the at least one marketing service corresponding to the selected service tier has been activated. ### Claim 9 (depends on 1) The system of claim 1, wherein the machine learning model comprises a deep learning component trained on a training data set, and is further configured to: dynamically update the graphical user interface to prompt the user for additional input based on at least one of previously received user input, learned user behavior patterns, and predicted marketing goals. ### Claim 10 (depends on 1) The system of claim 1, wherein the graphical user interface further includes one or more sub-selectors corresponding to the selected service tier, wherein each sub-selector is displayed in association with a particular marketing service enabled by the selected service tier, wherein each sub-selector is configured to receive additional input from the user indicating one or more service-specific options for that particular marketing service. ### Claim 11 A computer-implemented method of performing automated digital marketing, comprising: displaying, via a graphical user interface displayed on a user device, an adjustable graphical selector; receiving, via the graphical user interface, an input from a user indicating a desired level of marketing services in response to the user adjusting the adjustable graphical selector across a service scale including a plurality of service tiers; dynamically configuring a set of marketing services corresponding to a selected service tier; displaying one or more corresponding form fields for collecting the marketing input associated with the configured services; receiving, via the graphical user interface, a selected position from the adjustable graphical selector corresponding to the selected service tier; determining, by a computer including at least one processor and at least one memory, at least one marketing service associated with the selected service tier by analyzing the selected position of the adjustable graphical selector; receiving, via the graphical user interface, marketing input corresponding to a business of the user and associated with the determined at least one marketing service; generating by the computer and using the marketing input, at least one digital marketing asset; generating, by a machine learning model comprising an artificial neural network (ANN), onboarding data associated with the determined at least one marketing service; transmitting the onboarding data to at least one third-party digital platform, wherein transmitting the onboarding data causes the at least one third-party digital platform to activate the at least one marketing service, wherein transmitting the onboarding data comprises configuring the determined at least one marketing service on the at least one third-party digital platform based on the onboarding data; transmitting, by the computer, the at least one digital marketing asset to the at least one third-party digital platform; receiving, from the at least one third-party digital platform, campaign performance data comprising at least one of impressions, clicks, conversions, or engagement statistics; adjusting weights or parameters of a reinforcement learning component of the machine learning model based on the campaign performance data; updating the at least one digital marketing asset based on the campaign performance data; and generating and sending an automated status update to the user indicating that the at least one marketing service corresponding to the selected service tier has been activated. ### Claim 12 (depends on 11) The computer-implemented method of claim 11, wherein the adjustable graphical selector comprises a sliding lever displayed horizontally along the service scale. ### Claim 13 (depends on 11) The computer-implemented method of claim 11, further comprising: retrieving, by the ANN, online data associated with the business of the user from the at least one third-party digital platform; and supplementing, by the ANN, the marketing input with the retrieved online data. ### Claim 14 (depends on 11) The computer-implemented method of claim 11, further comprising: analyzing, by the machine learning model, which further comprises a convolutional neural network (CNN), at least one visual asset or image associated with the business of the user; and supplementing, using the CNN, the marketing input with metadata extracted from the at least one visual asset or image. ### Claim 15 (depends on 11) The computer-implemented method of claim 11, wherein the at least one digital marketing asset includes at least one of an advertisement, website content, search engine optimization (SEO) metadata, and social media content.