Platform-Specific User Persona Determination for Retail Recommendations

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Solution Overview

Problem

Current recommendation systems on retailer websites fail to provide platform-specific, personalized item recommendations, leading to decreased customer interaction and satisfaction due to irrelevant or embarrassing suggestions, as they do not account for varying user personas across different platforms and browsing habits.

Innovation Solution

The system automatically determines platform-specific user personas by scoring and ranking potential personas based on historical user data, catalog data, and co-purchase data, allowing for personalized item recommendations tailored to each platform, increasing user interaction and relevancy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If the same item recommendations are provided to a customer on all different platforms in a global and static manner, then the recommendation system is simple to implement, but customer interaction and interest decrease due to irrelevant recommendations

Engineering Contradiction:

Improvesimplicity of recommendation systemVSAvoidcustomer interaction

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent segments the monolithic recommendation system into platform-specific components. Each platform (email, homepage, advertisement page) has its own persona determination and recommendation generation logic. This allows the system to tailor recommendations to each platform's context and user behavior patterns, thereby increasing customer interaction while maintaining manageable complexity through modular design.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent implements dynamic persona determination that adapts to different platforms and user contexts. Instead of static, global recommendations, the system dynamically adjusts recommendations based on platform-specific user personas, browsing habits, and interaction patterns. This dynamic approach increases relevance and customer engagement.

Inventive Principle:

Principle #15Dynamics

2Productivity

If platform-specific user personas are determined and personalized recommendations are provided for each platform, then customer interaction and relevancy increase, but the system complexity increases

Engineering Contradiction:

Improvecustomer interactionVSAvoidcomplexity of recommendation system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent employs a universal persona framework that functions across all platforms. The core persona determination logic and data structures are designed to be platform-agnostic, allowing the same underlying system to serve multiple platforms with different configurations. This reduces complexity by avoiding complete redesign for each platform while still enabling platform-specific personalization.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent manages complexity by changing parameters rather than restructuring the entire system. Platform-specific configurations are implemented through parameter adjustments (e.g., platform weights, persona thresholds, recommendation algorithms) rather than fundamental architectural changes. This allows the system to adapt to different platforms while maintaining a cohesive core structure.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If irrelevant item recommendations are displayed on platforms, then the recommendation system covers more item categories, but customer satisfaction decreases and customers may leave the website

Engineering Contradiction:

Improvecoverage of item categoriesVSAvoidcustomer satisfaction

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent applies local quality by making recommendations specific to each platform's context and user persona rather than applying a uniform approach across all platforms. Each platform receives recommendations optimized for its specific user base and interaction patterns, ensuring higher relevance and customer satisfaction while maintaining broad item category coverage through platform-specific curation.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11776016B2Systems and methods for determining user personas for a user

Publication Date: 2023.10.03 WALMART APOLLO LLC

AI summary

This application relates to apparatus and methods for automatically determining and providing personalized user personas of a customer for specific platforms (e.g., applications). In some examples, a computing device receives a persona request identifying a user and a platform. In response, the computing device obtains user data associated with the user and a plurality of potential user personas from a database. For each of the plurality of potential user personas, the computing device then determines a combination score for the user based on the user data. The combination score indicates user's affinity to a corresponding potential user persona within the platform. The computing device selects at least one potential user persona of the plurality of potential user personas as a final user persona for the user and the platform based on the corresponding combination score.