Impact of Artificial Intelligence-Based Visual Merchandising on Customer Experience and Sales Performance in Retail Stores

Abstract

Artificial intelligence is progressively transforming retail merchandising from a largely experience-based and manually monitored practice into a data-driven, adaptive and predictive system. Visual merchandising has traditionally focused on display aesthetics, window presentation, shelf visibility, lighting, colour, signage, category adjacency and promotional arrangement. In organised retail stores, however, the effectiveness of these elements increasingly depends on real-time understanding of customer movement, category demand, product interaction, stock availability and store-zone performance. The present study examines the impact of artificial intelligence-based visual merchandising on customer experience and sales performance in retail stores. The study is designed as an analytical and empirical research paper using a structured survey of 420 customers and 60 retail managers from selected organised retail stores, supported by store-level indicators such as sales per square foot, conversion rate, average basket value and planogram compliance. The paper applies reliability analysis, descriptive statistics, chi-square test, correlation, regression, ANOVA, t-test, factor analysis and merchandising performance index calculations. The findings suggest that AI-based visual merchandising has a significant positive association with customer convenience, product discovery, perceived store attractiveness, impulse buying, dwell-time quality and sales productivity. The study concludes that AI-enabled shelf monitoring, heat-map analysis, customer segmentation, dynamic display recommendation and personalised digital signage can improve both experiential and financial retail outcomes when implemented with ethical data governance and local market sensitivity.

Keywords