Tight and precise delivery promises are fundamental at Zalando. In some countries, however, our ML models led to unwished overly broad promise windows. Postal codes historically exhibit different delivery behaviors, justifying a move from a country to a regional-level. However, clustering methods are not available for partially observable time series data structures. By extracting empirical probability distributions to cluster postal codes, we obtained regions having tighter promise windows.