Browsing by Author "Pathirana, KPRS"

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    Customer behavior and occupancy patterns in shopping malls: insights for decision-making and future prospects
    (IEEE, 2023-12-09) Pathirana, KPRS; Jayasinghe, GDGML; Ponnamperuma, JAW; Sarathchandra, HRCA; Dassanayake, SM; Mahakalanda, I; Abeysooriya, R; Adikariwattage, V; Hemachandra, K
    Shopping malls have transformed into vibrant hubs that cater to a wide range of social and business activities. Analyzing customer behavior and movement patterns within these malls enables us to make data-driven decisions that optimize operations and enhance the overall shopping experience. The methodology involves data collection through customer footfall analysis and customer retention. Statistical visualizations enable the identification of trends and patterns in customer behavior based on factors such as time of the day, day of the week, and popular attractions. Furthermore, the insights gained from this research hold significant managerial implications, including resource allocation, tenant placements, marketing strategies, operational efficiency improvements, and enhanced customer experiences.
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    Optimizing marketing strategies through occupancy pattern analysis in shopping malls
    (Business Research Unit (BRU), 2023-12-04) Pathirana, KPRS; Jayasinghe, GDGM; Ponnamperuma, JAW; Sarathchandra, HRCA; Dassanayake, SM; Mahakalanda, I
    This study examines the occupancy patterns within a suburban shopping center in Sri Lanka, with more attention to the evolving role of shopping malls as dynamic marketing hubs. It underscores the importance of comprehending customer behavior, optimizing store layouts, and deploying effective advertising strategies in the context of mall marketing. Using a data-driven approach spanning four weeks, we collected and analyzed customer traffic data. Our findings consistently highlight the prominence of entrances 1 and 2, with Fridays emerging as the peak day for customer engagement. Additionally, crowd density analysis uncovers the significant impact of store types and the time of day on mall traffic patterns. These actionable insights serve as valuable guidance for mall management, enabling the optimization of marketing strategies and an enhanced shopping experience. By effectively bridging the gap between theoretical knowledge and practical applications in shopping mall marketing, this research contributes to a deeper understanding of occupancy patterns within these multifaceted commercial spaces.