A Study on the Impact of Visual Merchandising on Impulse Purchases and Customer Loyalty Intentions with Special Reference to Chennai Silks, Tiruchirappalli

  • S Syed Muthaliff Ph.D Scholar (Part-Time) Alagappa Institute of Management, Alagappa University, Karaikudi
  • S Dhinesh Babu Associate Professor, Department of Business Administration, Sri Meenakshi Government Arts College for Women (Autonomous), Madurai
  • M Thiagarajan Assistant Professor & Head, Department of Business Administration Alagappa Government Arts College, (Affiliated to Alagappa University), Karaikudi
Keywords: Visual Merchandising, Impulsive Buying, Customer Patronage, Promotional Signage, Design & Layout of the Store, Corporate Identity, Merchandise Display, Lightning

Abstract

This study aims to examine the impact of visual merchandising on impulse buying behaviour and customer loyalty intentions, with special reference to Chennai Silks, Tiruchirappalli. A descriptive research design was adopted for this study. Primary research was conducted by collecting data from customers through a structured questionnaire. The results were analysed using appropriate statistical methods. The analysis results revealed that factors of visual merchandising, such as storefront, interior, lighting, and signage, play a significant role in influencing customers’ emotions, creating excitement, and improving impulse buying behaviour and customer loyalty intentions. Thus, the study concluded that effective visual merchandising is essential for attracting customers, influencing their emotions, and improving store performance. Further, the study suggests that the scope of the research can be extended to other types of products, such as electronics and supermarkets, modern malls compared to conventional stores, and demographic and cultural differences in the effectiveness of visual merchandising techniques. The data were analysed using several approaches, such as reliability tests, factor analysis, multiple regression analysis, and structural equation models. The software used was IBM SPSS statistics 20.0. The dataset had a highly reliable reliability coefficient of 0.941, as revealed by the reliability tests. Factor analysis was also conducted to confirm the factors used in the research. Multiple regression analysis was used to determine the effect of the factors on the dataset.

Published
2026-04-01
Section
Articles