Filter Activity Analysis for Targeted Content Recommendations

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Solution Overview

Problem

Existing electronic catalogs lack effective methods to analyze user filter parameter selections for targeted marketing strategies, failing to utilize incidental browsing data to recommend optimal marketing approaches for advertisers.

Innovation Solution

A system and method that collect and analyze past filter parameter selections to infer marketing strategies by monitoring user activity data, comparing it with current filter data to provide content recommendations, utilizing a taxonomy-based database and user interface to generate targeted marketing efforts.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If filter parameter selections are monitored and analyzed to generate marketing recommendations, then marketing effectiveness and user engagement are improved, but system complexity and data processing requirements increase

Engineering Contradiction:

Improvemarketing effectivenessVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces a monitoring module and analysis module as intermediaries between the filter parameter selections and marketing recommendations. The monitoring module captures filter selections, and the analysis module processes this data to generate marketing insights, thereby resolving the complexity issue by structuring the data flow through dedicated intermediary components rather than embedding analysis throughout the system.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs preliminary monitoring and analysis of filter parameter selections to build a database of user preferences before generating marketing recommendations. By pre-processing and storing filter selection data, the system prepares marketing insights in advance, improving effectiveness without increasing real-time processing complexity.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If user filter activity data is collected and analyzed, then targeted content recommendations are improved, but user privacy concerns and data security requirements worsen

Engineering Contradiction:

Improvetargeting accuracyVSAvoidprivacy concerns

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent transforms detailed filter parameter selections into aggregated user preference patterns and categories. By changing the parameter representation from specific filter values to generalized preference categories, the system maintains targeting accuracy while reducing the granularity of personal data that could raise privacy concerns.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

Instead of directly using raw user filter data for marketing decisions, the system creates anonymized copies and aggregated representations of user preferences. This allows the system to analyze and target content based on user behavior patterns without exposing or storing sensitive personal information, thereby addressing privacy concerns while maintaining targeting effectiveness.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS10304116B2System and method for targeting content based on filter activity

Publication Date: 2019.05.28 CBS INTERACTIVE INC

AI summary

Various embodiments are presented which comprise an electronic catalog of products, wherein the catalog comprises a taxonomy of product categories and products within the categories, wherein various users input filter parameters and these are monitored, whereupon a new set of filter parameters are accepted and compared to the past set of filter parameters to generate content recommendations.