How to Build a Demand Forecasting System for E-commerce

Demand forecasting is the foundation of profitable e-commerce growth. Without it, you're either constantly out of stock or constantly carrying too much inventory. Neither is sustainable.

Start With Historical Sales Data

The foundation of any forecast is historical sales velocity. Calculate your daily, weekly, and monthly sales by SKU for at least the last 12 months. Identify seasonality patterns — when does each SKU peak and trough? This baseline is your starting point for every future forecast.

Layer in Growth Rate

Historical data tells you what happened. Your growth rate tells you what to expect. If you're growing 20% year-over-year, apply that growth rate to your historical baseline to get your forward forecast. But be careful — apply growth rate by SKU, not at the total business level. Products grow at different rates.

Account for Planned Events

Marketing campaigns, promotional events, and seasonality all affect demand in ways your baseline won't capture. Add a planned events layer to your forecast that accounts for any known drivers of demand change — a Q4 promotion, a product launch, a media feature.

Build in Supplier Lead Time

Your forecast doesn't just tell you what you'll sell — it tells you when to order. Work backwards from your forecast using your supplier lead time to determine your order placement date. Your reorder point should trigger when on-hand inventory plus on-order inventory falls to a level that covers your forecast plus safety stock through the lead time period.

The fix: Build a simple 13-week rolling forecast for your top 10 SKUs. Update it weekly. The discipline of maintaining it will improve your forecasting accuracy more than any tool.