Color-Matched Supplemental Content for Digital Displays
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Solution Overview
Problem
In electronic content delivery, supplemental content often clashes aesthetically with primary content due to uncontrolled appearance characteristics, leading to reduced user engagement.
Innovation Solution
Systems and methods that determine and match the colors of supplemental content with those of primary content using color analysis and machine learning to recommend or automatically apply optimal color palettes, improving aesthetic harmony and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If supplemental content is displayed with primary content, then user engagement is improved, but aesthetic harmony deteriorates due to uncontrolled color differences
Solution Approach 1:
The system dynamically changes the color parameters of supplemental content based on the detected color characteristics of primary content. By analyzing the primary content's color palette and adjusting supplemental content colors to complement or contrast appropriately, the system maintains aesthetic harmony while preserving user engagement benefits
Solution Approach 2:
The system introduces an intermediary color analysis and matching mechanism between primary and supplemental content. This intermediary process detects color characteristics of primary content and uses them as a basis for selecting or generating visually harmonious supplemental content, resolving the conflict between engagement and aesthetics
2Stability of the object's composition
If color matching is implemented for supplemental content, then aesthetic harmony is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically detecting color characteristics of primary content and autonomously selecting or generating color-matched supplemental content without requiring manual designer intervention for each instance. This automation maintains aesthetic harmony while managing complexity through algorithmic processing
Solution Approach 2:
The system performs preliminary color analysis of primary content before supplemental content is finalized or displayed. By pre-determining the color characteristics and using them as a foundation for supplemental content selection, the system streamlines the process and reduces complexity compared to post-hoc adjustments
Data Source
AI summary
Supplemental content is selected or generated based at least in part upon colors of primary content with which the supplemental content is to be displayed. Color data is determined for primary content and that color data is used to select supplemental content that includes complementary or similar colors. Past performance data can be analyzed in order to determine which colors are most effective for a type of opportunity. When an opportunity arises to provide supplemental content, the effective colors can be recommended or, in some cases, automatically applied such that the supplemental content will include colors that improve the overall likelihood of performance of the supplemental content. If a designer is generating supplemental content, a tool can use such performance data to recommend colors based on the type of supplemental content or other such targeting criteria.