Adaptive User Modeling in Visual Merchandising: Balancing Brand Identity with Operational Efficiency

Maintaining a consistent brand identity across a global network of retail stores while adhering to local constraints has long challenged Visual Merchandisers.Legacy processes, often reliant on subjective "by-eye" adjustments, can drive up operational costs and lead to inconsistent in-store execution.We formalize a user modeling framework implementing a multi-criteria utility function that balances brand identity and operational overhead.We integrated our framework in a 3D virtual tour design platform, deploying it in the ecosystem of OVS, a global fashion firm.Through a preliminary user study, we showcase that our solution enables lower iteration cycles and decreases store-to-store discrepancies.

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3699682.3730976
Primary Topic
Consumer Retail Behavior Studies
Type
article
Field-Weighted Citation Impact
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article

Adaptive User Modeling in Visual Merchandising: Balancing Brand Identity with Operational Efficiency

Azzurra Ragone, Vito Walter Anelli, Fedelucio Narducci, Potito Aghilar et al.
Consumer Retail Behavior Studies
article

Adaptive User Modeling in Visual Merchandising: Balancing Brand Identity with Operational Efficiency

Azzurra Ragone, Vito Walter Anelli, Fedelucio Narducci, Potito Aghilar, Andrea Lops, Michelantonio Trizio, Sabino Roccotelli
article en

Abstract

Maintaining a consistent brand identity across a global network of retail stores while adhering to local constraints has long challenged Visual Merchandisers.Legacy processes, often reliant on subjective "by-eye" adjustments, can drive up operational costs and lead to inconsistent in-store execution.We formalize a user modeling framework implementing a multi-criteria utility function that balances brand identity and operational overhead.We integrated our framework in a 3D virtual tour design platform, deploying it in the ecosystem of OVS, a global fashion firm.Through a preliminary user study, we showcase that our solution enables lower iteration cycles and decreases store-to-store discrepancies.

University of Bari Aldo Moro (IT), Polytechnic University of Bari (IT)
Openalex Percentile: Top 83%
Consumer Retail Behavior Studies
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