Automated Creative Generation System Using Entity Attribute Matching
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Solution Overview
Problem
Novice advertisers face challenges in generating effective ad creatives with high click-through and conversion rates due to a lack of necessary skills and data.
Innovation Solution
A system and method for generating creatives by identifying entity attributes, selecting suitable creative templates based on these attributes, and generating creatives from them, with performance monitoring to optimize template selection for higher rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If novice advertisers generate creatives manually without guidance, then they can create custom creatives, but the click-through and conversion rates are low due to lack of skills and data
Solution Approach 1:
The system enables novice advertisers to generate high-quality creatives automatically without requiring expert knowledge. The automated creative generation system queries entity data, selects appropriate templates, and produces creatives independently, allowing users to benefit from professional-grade creatives without needing advertising expertise
Solution Approach 2:
The patent introduces an intermediary automated system that bridges the gap between novice advertisers and high-performance creatives. This intermediary system uses template selection logic and entity data processing to translate simple user inputs into professionally optimized creatives, eliminating the need for users to directly create or manually optimize creative content
2Reliability
If creative templates are selected based on high performance rates, then click-through and conversion rates increase, but the system complexity increases due to performance monitoring and template selection logic
Solution Approach 1:
The system pre-establishes a library of creative templates that have been predetermined to perform well for specific entity types. By preparing and categorizing templates in advance based on entity categories and characteristics, the system eliminates the need for complex real-time optimization while maintaining high performance rates
Solution Approach 2:
The patent simplifies complexity by changing the selection parameter from complex performance metrics to simpler entity category matching. Instead of analyzing multiple performance parameters in real-time, the system uses entity category as the primary selection criterion, which naturally aligns with pre-optimized templates and reduces computational complexity
3Reliability
If the system monitors creative performance to optimize template selection, then future creatives have higher performance rates, but the time and resources required for monitoring increase
Solution Approach 1:
The system implements a feedback mechanism where creative performance data is collected and used to refine template selection. High-performing templates are identified and prioritized for future use, creating a continuous improvement cycle that enhances creative performance over time without requiring extensive manual intervention
Solution Approach 2:
The patent uses successful creative templates as reusable patterns that can be copied and applied to similar entities. By identifying and replicating high-performing template structures across multiple creatives, the system leverages past successes without requiring extensive new creative development or monitoring time
Data Source
AI summary
Attribute data regarding an entity, such as a business entity, are identified. Thereafter, one or more creative templates are selected based on the attribute data related to the entity. Creatives for the entity are then generated from the creative templates and the entity attribute data.