Predictive Analysis of Retail Promotion Strategies in the Context of Consumer Shopping Behavior - Ima Pratiwi; Muhammad Fikry; Sujacka Retno (Faculty of Engineering, Malikussaleh University, 2024)
In this paper, we examine the impact of various promotional strategies on consumer shopping interest, focusing on the Alfamart retail chain in Lhokseumawe City, Indonesia, which saw rapid expansion from five to fifteen stores between 2017 and 2023. Despite this growth, expected sales increases have not been met, raising concerns about the effectiveness of current promotional tactics. Utilizing multiple linear regression analysis, we investigate the influence of three specific strategies, Promo Spesial Mingguan, Serba Gratis, and Tebus Murah on shopping interest across the 15 stores. Findings reveal that Tebus Murah is the most effective strategy in boosting shopping interest, showing the smallest error margin between predictive and actual sales figures. This study provides comprehensive insights into the broader effects of promotional strategies on consumer interest, highlighting the need for Alfamart to focus on optimizing the Discounted Redemption approach to maximize sales. The predictive system developed serves as a strategic tool for identifying effective promotions, forecasting sales, calculating return on investment, and analyzing consumer behavior. Our results underscore the value of predictive analysis in refining promotional strategies, enabling Alfamart to adopt a more targeted and efficient marketing approach to enhance sales performance.