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The effectiveness of a retail store layout plays a crucial role in supporting operational efficiency, service flow, and customer experience. Brother Parfume, a perfume refill retail store, currently applies a bar-service layout designed based on intuition and daily operational needs rather than systematic planning. This often results in inefficient movement patterns, limited space utilization, and suboptimal coordination among functional areas. This study aims to redesign the store layout by applying the Entity Relationship Chart (ERC) and Total Closeness Rating (TCR) methods to identify functional relationships and determine the ideal spatial arrangement. Data were collected through direct observation and semi-structured interviews with the store owner to understand the interaction between service areas, product displays, and storage sections. The ERC analysis shows that the service area, perfume display, and bottle display have the highest functional interdependence, while the storage area has the lowest necessity for proximity. TCR results confirm these findings, with the service area and perfume display each scoring 90, bottle display 21, and storage 3. Based on these results, two alternative layouts are proposed that integrate high-priority areas into a unified service zone and position storage separately to minimize unnecessary movement. The redesigned layout is expected to enhance service speed, optimize space utilization, support operational procedures, and strengthen the store’s servicescape. This research contributes practical insights into the application of ERC and TCR methods for small-scale retail operations, particularly in the perfume refill sector, where service efficiency and spatial constraints are critical.

This research aims to determine the influence of Social Media, Price, and Servicescape on Purchase Decisions at Warkop Mie Aceh Hijrah Jaya Medan Amplas. In this research, data collection was conducted using purposive sampling, with a sample of 84 respondents. All analyses in this research were assisted by the SPSS 25.0 software. The data analysis techniques used included classical assumption tests, multiple linear regression analysis, and hypothesis testing. Based on the t-test results, it was found that the significance value (Sig.) of Social Media was 0.000 < 0.05 and the t-count value (3.783) > t-table (1.664). Therefore, it can be concluded that the Social Media variable has a positive and significant influence on the Purchase Decision variable. Furthermore, the significance value for the Price variable was 0.000 < 0.05, and the t-count value (5.435) > t-table (1.664). Thus, it can be concluded that the Price variable significantly influences the Purchase Decision variable. Next, the significance value for the Servicescape variable was 0.000 < 0.05, indicating a significant influence on the Purchase Decision variable. Based on the data, the t-count value was (9.892) > t-table (1.664). Therefore, it can be stated that the Servicescape variable has a positive and significant influence on the Purchase Decision variable.