Non-Profit Venue Recommendation Systems Using Visitor Interaction Data

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Solution Overview

Problem

Conventional methods for providing information to visitors of non-profit venues like museums and zoos fail to offer personalized experiences based on individual interests, leading to a lack of engagement and missed opportunities for philanthropic activities.

Innovation Solution

Utilizing location tracking and interaction analysis through mobile devices to provide personalized recommendations, multimedia content, and campaign participation opportunities, enhancing the visitor experience with features like augmented reality and real-time communication.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional generic information methods (printed placards, audio-visual guides) are used to provide information to visitors, then the implementation is simple and low-cost, but the visitor experience lacks personalization and engagement

Engineering Contradiction:

Improvepersonalization of visitor experienceVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by collecting visitor data (demographics, interests, interaction patterns) before generating personalized recommendations. This advance preparation enables the recommendation engine to provide tailored suggestions without adding complexity during the actual visitor experience.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces a recommendation engine as an intermediary between the venue's information systems and the visitors. This mediator processes visitor data and generates personalized recommendations, bridging the gap between generic information delivery and personalized engagement without requiring complete system reconstruction.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If personalized recommendations and tracking systems are implemented to enhance visitor experience, then visitor engagement and philanthropic participation improve, but the system complexity and data processing requirements increase

Engineering Contradiction:

Improvefundraising efficiencyVSAvoidtracking and recommendation system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements feedback loops by continuously monitoring visitor interactions with exhibits and dynamically adjusting recommendations. This feedback mechanism enables the system to learn from visitor behavior patterns and improve fundraising efficiency by presenting relevant philanthropic opportunities based on actual engagement data.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent utilizes parameter changes by analyzing variations in visitor interaction data (dwell time, movement patterns, exhibit preferences) to dynamically adjust recommendation parameters. This enables the system to optimize fundraising efficiency by adapting recommendations to individual visitor profiles without requiring complete system redesign.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If detailed interaction tracking and analysis systems are deployed to capture visitor behavior, then personalized recommendations can be generated, but the loss of visitor privacy and data security concerns increase

Engineering Contradiction:

Improvevisitor data privacyVSAvoidpersonalization capability

Core Design Contradiction:

Loss of informationVSAdaptability or versatility

Solution Approach 1:

The system extracts only the necessary information elements needed for personalization (demographics, exhibit preferences, interaction patterns) while leaving out sensitive personal data. This selective extraction enables personalized recommendations while minimizing privacy intrusion and data security risks.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies local quality by processing and analyzing visitor data locally at edge devices or distributed systems rather than centralizing all data collection. This approach enables personalized recommendations to be generated based on local interaction patterns while reducing the security risks associated with centralized data storage and processing.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12462279B2Methods and systems for personalizing a prospective visitor experience at a non-profit venue

Publication Date: 2025.11.04 OLIVE SEED IND LLC

AI summary

A method for providing personalized non-profit venue visit recommendations to a visitor at a non-profit venue, comprising: providing a management interface for management of a set of multimedia assets; receiving a mapping of multimedia assets to a display in at least one site plan; receiving metadata for the set of multimedia assets; providing an interface for receiving data indicating personal interests of a visitor, including visitor-provided preference data and passively-collected visitor interaction data; receiving personal interest data for a plurality of non-profit venue visitors; receiving preference data relating to a prospective visitor; applying a machine learning system to analyze the metadata, the data indicating personal interests of the visitor, the personal interest data for the plurality of non-profit venue visitors, and the preference data relating to the prospective visitor; and generating a selection or sequence of non-profit venue location recommendations for the prospective visitor.