From rule to intelligence: a review of algorithmic heuristics in fashion retailing

Abstract

Purpose This study systematically explores the literature on algorithmic heuristics used in fashion retailing. While reviewing major scopes where algorithmic heuristics contribute to fashion retail marketing, the study explores the relative issues and practical implications of employing those heuristics. Design/methodology/approach This study employed a narrative literature review to facilitate a flexible synthesis of research across multiple disciplines. The review was systematically conducted with a clear search strategy and defined criteria for inclusion and exclusion. Findings This review describes the scope of algorithmic heuristics in fashion retail and marketing, identifying three major focus areas that emphasise their application: (1) Pricing, Demand Forecasting and Inventory Optimisation, (2) Recommendation Systems via Customer Segmentation and Personalisation and (3) Visual Intelligence for Merchandising and Product Display. The analysis discusses four main challenges related to technical aspects, three main issues related to strategic and operational barriers of implementing heuristics and two issues related to ethical usage and regulations, particularly when using optimisation and AL/ML heuristics. Practical implications This review offers a comprehensive overview of algorithmic heuristics implementation within the fashion retail and marketing context, aiming to inspire fashion marketers, fashion analysts and data scientists. The integration of algorithmic heuristics is evolving. Heuristics have influenced consumer behaviour and decision-making in pricing and inventory. In Fashion 5.0, these strategies are being redefined through ethical, collaborative human–AI systems for personalised experiences. Originality/value This review examined algorithmic heuristics in fashion retail marketing, aiding researchers and practitioners in understanding their uses, potential and prospects.