Automated Creative Generation from User Content
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Solution Overview
Problem
Current methods for presenting content on the internet, such as advertisements, lack efficiency in automatically generating creatives from user-published content that effectively capture user attention and interest, especially in social networks, and fail to adapt to various formats and user preferences.
Innovation Solution
A computer-implemented method that parses user-published content to identify candidate text, video, and images, ranks them based on criteria, and generates creatives in different formats such as banners, skyscrapers, or boxes, using activity history and social network data to optimize relevance and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual creative creation methods are used, then creatives can be customized, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables automated self-service creative generation by parsing user-published content and automatically creating creatives in multiple formats without manual intervention. The computer-implemented method extracts text, video, and images from published content, ranks candidates based on engagement metrics, and generates creatives autonomously, eliminating the need for manual creative design while maintaining customization through user-specific content selection.
2Ease of operation
If generic advertisement formats are used, then implementation is simple, but user engagement and interest are low
Solution Approach 1:
The system applies local quality by selecting and ranking specific text, video, and image candidates from user-published content based on user-specific engagement metrics and preferences. Different creatives are generated with locally optimized content selections tailored to individual user characteristics, while maintaining a standardized automated generation process that handles multiple formats systematically.
3Adaptability or versatility
If multiple creative formats are generated manually, then format versatility is achieved, but the complexity and time required increase significantly
Solution Approach 1:
The system achieves universality by implementing a single automated creative generation platform that produces multiple format types (banners, skyscrapers, boxes, and other advertisement formats) from the same parsed user content. The computer-implemented method generates creatives in various formats simultaneously through automated processes, eliminating the need for separate manual design workflows for each format while maintaining format-specific optimizations.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, and including a method for creating content. The method comprises receiving an indication to promote a published content item, and parsing content in the published content item to identify candidate text/video/images for inclusion in a creative. The method further comprises assigning ranks to the candidate text/video/images based on one or more criteria. The method further comprises identifying a plurality of creative formats. The method further comprises, for each of the identified creative formats, identifying a corresponding set of text/video/images from the candidate text/video/images for inclusion in a candidate creative formatted in accordance with a given creative format and based at least in part on the ranked candidate text/video/images. The method further comprises ranking the candidate creatives, and generating at least one creative including a corresponding set of text/video/images based on the ranking of the candidate creatives.