Demand Forecasting for Fashion
Demand forecasting in fashion blends historical sell-through data with forward-looking signals to predict what customers will buy, when, and in what quantities.
What is demand forecasting in fashion?
Demand forecasting is the process of estimating future customer demand for specific products, categories, or channels over a defined time period. In fashion and apparel, forecasting is difficult because of seasonal product lifecycles, trend volatility, and newness: every seasonal line deliberately includes styles that have never been sold before, so part of every buy is placed with no sales history of its own.
For startup and small apparel brands, the forecasting challenge is sharper: limited historical data, fewer selling locations, and tighter margins for error. The cost of getting it wrong — excess inventory, stockouts on winners, missed margin — also lands harder, because one misjudged style is a larger share of a smaller range.
The two forecasting approaches
Historical pattern forecasting
This is the traditional approach: look at what sold last season, adjust for growth or decline, and project forward. It works well for:
- Carryover styles with sell-through history of their own
- Basics and core programs where demand is stable
- Replenishment categories with predictable velocity
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