Sales Forecasting with Exponential Smoothing for Webrooming–Showrooming Strategy at Yumna Batik - Syarthini Indrayani; Mira Mira; Nur Mayasari; Wiwid Astuti; Resky Angguna Anastasya; Nur Amalia Agus Mulyadi (Studi Akuntansi, Keuangan, dan Manajemen, 2025)
Purpose: This study explores the effectiveness of webrooming and showrooming as marketing strategies in increasing sales, revenue, and customer satisfaction at Yumna Butik in Makassar. It aims to forecast sales trends and analyze consumer shopping behaviors using sales forecasting methods Methodology/approach: A quantitative exploratory approach was employed, utilizing secondary data on sales through webrooming and showrooming. The research applied the Single Exponential Smoothing (SES) method to forecast sales and identify shopping patterns. Interviews with sales representatives and analysis of sales transaction records were conducted to understand consumer behavior and spending trends. Results/findings: The findings reveal a significant monthly increase in sales volume, influenced by strategic store locations, competitive pricing, and high-quality customer service. Among the products analyzed, hijabs were identified as the highest-selling item. The majority of customers preferred webrooming over showrooming, emphasizing the practicality of online searches followed by in-store purchases. Conclusion: The study concludes that webrooming is more effective than showrooming in driving customer purchases at Yumna Butik. Implementing both strategies, supported by accurate sales forecasting, enables better business planning, customer engagement, and revenue growth. Limitations: This study focuses on a single business and specific products, which may limit generalizability. Future research could incorporate advanced software such as RShiny for more detailed and dynamic sales forecasts. Contribution: This study demonstrates the relevance of integrating webrooming and showrooming strategies to enhance sales and customer satisfaction. It also highlights the utility of SES in predicting sales trends and improving inventory management, offering actionable insights for fashion retailers.