E-ticaret iş analitiği uygulamaları: Türkiye'de perakende sektörü için bir vaka çalışması

This study investigates the impact of business analytics adoption on sales performance in the e-commerce sector, using X company as a case study. Leveraging monthly sales data from 2021 to January 2025, the research applies quantitative methods including multiple linear regression and ARIMA-based time-series forecasting to evaluate both the effect and predictive accuracy of analytics tools post-adoption. The regression model examines key internal and external factors such as purchasing power, industry growth, seasonality, and retail branch expansion. While the dummy variable capturing post-2021 analytics adoption was not statistically significant, the findings highlight seasonality as a major sales driver. ARIMA forecasting results for 2024 closely align with actual figures, indicating strong predictive capabilities of Company X's analytics systems. The study concludes that although analytics adoption may not directly boost sales in the short term, it enhances planning accuracy and operational responsiveness. Recommendations are provided to help business managers strategically embed analytics into decision-making processes, emphasizing alignment with business goals, data quality, and cultural readiness. Keywords: Business Analytics, E-commerce, Sales Forecasting, Data-Driven Strategy.