Dynamic Content Optimization With Intrinsic Factor Separation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Traditional optimization methodologies fail to distinguish between intrinsic and extrinsic factors affecting marketing content performance, leading to suboptimal outcomes due to the influence of external variables, as seen in Simpson's paradox.

Innovation Solution

A dynamic optimization method that segregates content into batches with fixed proportions, uses mathematical models to disentangle intrinsic and extrinsic factors, and adjusts variant delivery based solely on intrinsic factors to maximize high-quality content delivery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional optimization methodologies are used to maximize content delivery based on observed performance, then productivity is improved, but measurement precision deteriorates due to extrinsic factors causing Simpson's paradox

Engineering Contradiction:

Improvecontent delivery efficiencyVSAvoidcontent variant quality measurement

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent segments the performance measurement into two distinct components: intrinsic factors (content quality) and extrinsic factors (environmental conditions). By dividing the overall performance metric into these separable elements, the system can independently evaluate content variant quality without contamination from external variables, thereby resolving Simpson's paradox while maintaining delivery efficiency

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extracts extrinsic factors from the performance measurement equation by explicitly modeling them as separate variables. This extraction allows the system to isolate and measure only the intrinsic content quality, eliminating the distortion that occurs when extrinsic factors are inadvertently included in aggregate performance metrics

Inventive Principle:

Principle #2Taking out (Extraction)

2Device complexity

If content optimization is performed without accounting for extrinsic factors, then device complexity is reduced, but reliability deteriorates due to incorrect optimization conclusions

Engineering Contradiction:

Improveoptimization system complexityVSAvoidoptimization conclusion accuracy

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent introduces an intermediary statistical model that mediates between observed performance data and optimization conclusions. This model acts as a filtering layer that separates the influence of extrinsic factors from intrinsic content quality, providing reliable optimization decisions without requiring direct observation of all underlying factors

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent changes the parameters used in optimization from raw performance metrics to adjusted metrics that account for extrinsic factors. By transforming the performance measurement parameters to isolate intrinsic content quality, the system achieves reliable optimization conclusions while maintaining manageable system complexity

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250384453A1Intrinsic and extrinsic factors in dynamic optimization experiments

Publication Date: 2025.12.18 JACQUARD GROUP LTD

AI summary

A method for optimizing the transmission of data transmitted from a system computer via a network to a plurality of user computers where a first batch of data comprising a plurality of content variants is transmitted to a select percentage of the plurality of user computers and performance metrics are gathered for each of the content variants where intrinsic and extrinsic factors are quantified such that proportions of the content variants are adjusted for inclusion in a second batch of data based solely on the intrinsic data.