SELF-LEARNING SYSTEMS AND METHODS FOR DIGITAL CONTENT SELECTION AND GENERATION USING GENERATIVE AI

Smart overview of the Invention

The patent application details a system leveraging artificial intelligence to generate and target digital content efficiently. A key component is the use of "nanosegments," which are small, specific customer groups identified for targeted marketing campaigns. This approach reduces memory usage by focusing on fewer, more precisely defined customer groups, enhancing the effectiveness of personalized digital content like offers, taglines, and images.

Technical Field

This innovation falls under the domain of digital content generation and presentation, specifically utilizing generative AI techniques to optimize these processes for diverse consumer bases. The system aims to improve the targeting and personalization of marketing efforts by dynamically adjusting to customer data and campaign objectives.

Background

Traditional marketing campaigns often rely on broad customer segments and generalized models, which can be inefficient and slow to adapt. These conventional methods lack the ability to quickly iterate and refine targeting strategies, leading to suboptimal outcomes in terms of offer acceptance rates and customer engagement. The need for more agile, data-driven approaches is evident in maintaining competitive conversion rates and minimizing customer fatigue.

System Functionality

The disclosed system uses a self-learning AI model that integrates historical campaign data to refine targeting strategies. It optimizes marketing efforts by considering factors like cost, desired conversions, and customer experience. The AI generates customized content based on real-time insights, aiming to increase positive responses from customers through tailored offers that align closely with their preferences.

Implementation Details

The method involves segmenting customers into nanosegments using clustering algorithms based on shared characteristics. A machine learning model selects relevant nanosegments for a campaign, which are then processed by a generative AI component to produce specific digital content elements such as taglines or images. This content is delivered to client devices associated with the targeted customers, enhancing the likelihood of successful campaign interactions.