Amazon Fashion Analytics Dashboard

Business Insight: Daily order volume shows significant fluctuations, with occasional spikes that likely correspond to promotional events or holidays. The substantial difference between the average (156.85) and maximum (1,176) daily orders highlights the importance of flexible capacity planning to handle peak periods. The data also shows a general upward trend over time, indicating business growth. Understanding these patterns is crucial for inventory management, staffing decisions, and marketing campaign planning.

Business Insight: Weekly and monthly aggregations reveal clearer seasonal patterns than daily data. There are notable peaks in November-December (likely due to holiday shopping) and smaller peaks in May-June. There are also consistent troughs in January-February and August-September. These seasonal patterns should inform inventory planning, marketing campaign timing, and staffing decisions throughout the year. The year-over-year comparison also shows overall growth in order volume, which should be factored into long-term capacity planning.

Business Insight: Order volume shows a clear weekly pattern, with Monday and Tuesday being the busiest days (16.3% and 16.1% of orders, respectively) and Saturday having the lowest volume (10.9%). This pattern suggests that customers are more likely to shop at the beginning of the work week, with activity gradually declining toward the weekend. This insight can inform staffing schedules, inventory replenishment timing, and the optimal days for launching promotions or new products. Customer service and fulfillment operations should be at maximum capacity early in the week to handle the higher order volume.

Business Insight: Order volume shows distinct peaks throughout the day, with the highest activity between 4-5 PM (6,675 orders), 11 AM-12 PM (6,578 orders), and 2-3 PM (6,569 orders). The afternoon (12:00-17:59) accounts for 39.2% of all orders, while overnight hours (00:00-05:59) have the lowest activity at 8.8%. These patterns suggest that customers are most active during lunch breaks and toward the end of the workday. This insight can inform the timing of flash sales, customer service staffing, and website maintenance windows. It also suggests that marketing emails and promotions should be sent in the morning to capture attention before the peak ordering times.

Business Insight: Delivery times show both seasonal patterns and a general improvement trend over time. The average delivery time is 12.56 days, but the median is 10.22 days, indicating a right-skewed distribution with some outlier long deliveries. Delivery times tend to increase during peak order periods (November-December), suggesting potential fulfillment capacity constraints. There are also significant regional variations, with customers in the North and Northeast regions experiencing longer delivery times than those in the Southeast and South. These insights can inform logistics planning, carrier selection, and customer communication strategies. Setting appropriate delivery expectations based on region and season can improve customer satisfaction, while targeted improvements in underperforming regions can enhance overall service quality.

Business Insight: Time series forecasting models provide reasonably accurate predictions of future order volumes, with the Prophet model showing the best performance (15.2% MAPE). The forecast indicates continued growth with seasonal patterns similar to historical data. Specifically, the model predicts a 12% increase in order volume for the upcoming quarter compared to the same period last year. This forecast can inform inventory planning, staffing decisions, and marketing budget allocation. The prediction intervals (shown as shaded areas in the chart) provide a range of possible outcomes, allowing for risk assessment and contingency planning.