Rebuilding Size Curves for a Menswear Brand After Two Seasons of Stock-Outs
Returns and stock-outs cleaned out of the history before the curves were recalculated per market.
Menswear Size Curve Challenge
Two seasons of stock-outs had taught the size curves the wrong lesson: sizes that sold out looked unpopular in the data.
- Stock-outs recorded as low demand
- Returns counted as sales
- One curve for all markets
What Was Done to Rebuild the Size Curves
Sales history cleaned
Stock-out weeks and returns removed.
Curves recalculated per market
By category and fit.
Size integrity monitoring
Weekly check of broken size runs.
Size Curve Project Results in Numbers
placeholder figuresbroken size runs
full-price share
Tools Used in the Size Curve Project
Excel curve model
Cleaned history and curves per market.
Power BI size integrity view
Weekly monitoring.
Related Service: Assortment Planning and Range Management
Size and colour curves calculated from cleaned history, per market.
A sold-out size is not an unpopular size.
Retail and Fashion Analytics Case Studies
Standardising Product Data Across European and Asian Markets in a PLM System
Multi-market fashion brand. One attribute dictionary replaced many local conventions.
Rebuilding the Womenswear Range Plan for a European Fashion Distributor
Option count cut by a fifth, depth moved into proven sizes and colours. Sell-through up, markdown down.
Building a Price Ladder and Margin Report for a Fashion E-commerce Retailer
Entry and exit prices per category, aligned across three markets and monitored weekly in Power BI.