Customized Content Data Feeds for Personalized Marketing
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Solution Overview
Problem
Current marketing technologies struggle to provide personalized and tailored content effectively, as they rely on mass advertising and fail to account for individual customer preferences and behaviors, leading to a need for improved customized content delivery methods.
Innovation Solution
A method and system for generating and feeding customized content data using a combination of static and dynamic content components, where AI-driven data analytics selects and combines content variables such as music, videos, and images to create tailored content feeds that match individual user preferences, enhancing user engagement and acceptance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mass advertising and consistent branding are used to retain customers, then brand recognition is improved, but customer personalization and individual preference matching deteriorate
Solution Approach 1:
The patent segments customers into different groups based on their preferences, behaviors, and characteristics. By dividing the customer base into distinct segments, the system can deliver personalized content to each segment while maintaining overall brand consistency, thus resolving the contradiction between mass advertising and personalization.
Solution Approach 2:
The patent implements dynamic content delivery that adapts to individual customer preferences and behaviors in real-time. The system dynamically adjusts the content, timing, and delivery channels based on customer data, enabling both brand consistency and personalized adaptation simultaneously.
2Productivity
If standardized content is used for mass advertising, then production efficiency is improved, but content relevance to individual customers deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-segmenting customers and pre-configuring content templates before actual advertising campaigns. This allows standardized content production to be combined with personalized delivery, maintaining production efficiency while improving content relevance through advance preparation of customized content paths.
Solution Approach 2:
The patent changes content parameters dynamically based on customer segmentation and individual preferences. By adjusting content parameters such as format, timing, channel, and specific messaging elements according to customer data, the system maintains standardized production processes while delivering relevant personalized content.
3Adaptability or versatility
If detailed customer data collection is implemented to personalize content, then content personalization is improved, but system complexity and data processing requirements deteriorate
Solution Approach 1:
The patent segments customer data into manageable categories and groups based on preferences, behaviors, and characteristics. This segmentation simplifies data processing by organizing vast amounts of customer information into structured segments that can be efficiently analyzed and applied for personalization without overwhelming system complexity.
Solution Approach 2:
The patent introduces intermediary processing layers that mediate between raw customer data and personalized content delivery. These intermediaries include data segmentation modules, preference analysis engines, and content matching systems that simplify the complexity of transforming detailed customer data into personalized content recommendations.
Data Source
AI summary
A system can be configured to generate customized content data suitable for marketing, advertising, or campaigns. The customized content data can be feedable or can be streamed to devices, such as end user devices. The customized content data can include a static content component, e.g., referring to a product, such as a car, or a service, and a dynamic content component, e.g., a product version, such as a color of the car. The customized content data can alternatively include a static content component and one or more dynamic content components, e.g., a music or music track selected to be combined with the static content component. Two or more components can be combined at the time of rendering the customized content data on an end-user device. The customized content data can also be generated for streaming or transferring to the end-user device.