Open Access
Validation of The Global Influence Network Framework (GINF): A Proprietary AI-Driven Methodology for Optimizing International Luxury Event ROI
4
Founder & CEO EventIQ
Abstract
The article presents the development and empirical validation of the proprietary methodology Global Influence Network Framework (GINF), an AI-oriented system designed to optimize international premium-segment events. The aim of the study is to demonstrate the economic performance of GINF in the context of luxury and technology events. The proposed framework, which represents an evolutionary continuation of the author’s data-driven model Social Stars Influence Analytics (SSIA), integrates behavioral analytics, psychographic profiling, and AI tools for audience assessment in terms of compatibility, relevance, and cultural sensitivity. The empirical part of the study is based on an applied analysis that includes the testing of GINF on representative cases such as Token2049 (Singapore), Step Conference Dubai 2024 and Luxury Tech Forum (Istanbul). The obtained data convincingly confirm the economic efficiency of the framework: its implementation ensured an increase in lead conversion by +63%, an improvement in the accuracy of speaker selection by +40% and an increase in the average event ticket value by +27%. The developed model underpins the Magnetic.AI platform and has been recognized by industry leaders (including Yandex, VK, Forbes Russia) as a new standard of measurable influencer marketing. The results of the study possess substantial practical value for event organizers, marketers and managers in the luxury industry, as well as scientific significance for researchers in the fields of marketing and information systems.
Keywords
global Influence Network Framework (GINF),
Social Stars Influence Analytics (SSIA),
AI-driven event management,
practice-led research,
predictive analytics,
return on investment (ROI),
influencer marketing,
psychographics,
luxury segment,
high-net-worth individuals (HNWI),
Token2049,
Magnetic.AI
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