1001 Mont Clothing B2B Sales Platform

The B2B sales platform we developed for 1001 Mont is a comprehensive digital solution designed specifically for the needs of the ready-to-wear and outerwear sector. 1001 Mont, which offers a wide product range in coats, jackets, and outerwear categories, needed a powerful B2B e-commerce infrastructure to provide fast and reliable supply to clothing stores, dealers, and wholesale buyers. The platform provides real-time integration with ERP systems, enabling product information, size-based stock statuses, color options, seasonal collections, and wholesale price lists to be instantly reflected to dealers. Designed to suit the seasonal dynamics of the outerwear sector, trend changes, and size diversity, the system enables dealers to quickly find the products they need and place bulk orders. Product category management comprehensively categorizes winter coats, autumn overcoats, spring jackets, raincoats, windbreakers, sports coats, classic coats, and puffer jackets. Men's, women's, and children's segments are organized separately within each category, enabling dealers to easily find products suitable for their target customer base. Seasonal collection management ensures that autumn-winter and spring transition collections are presented to dealers on time. Dealers can place pre-orders before the launch of new season coat collections (in July-August), benefit from early order discounts, and optimally plan their beginning-of-season stocks. Size and number management manages S-M-L-XL-XXL standard sizes and special sizes (3XL, 4XL) with detailed stock tracking. Dealers can see which size is in stock in which color for each product model and order all sizes in bulk with "size set" options. Coat type and usage area filtering categorizes thick winter coats, thin mid-season coats, waterproof raincoats, outdoor coats, sports activity coats, casual jackets, and elegant overcoat models. Usage purpose, temperature range, and activity type are specified for each product. Filling and material properties present detailed information for each coat on filling material (goose down, duck down, synthetic filling, fleece), outer fabric properties (waterproof, windproof, breathable), inner lining information, and insulation capacity. Color and style variety management displays detailed trend color palettes for each season, classic color options (black, navy, brown), and bold color alternatives. Dealers can distribute colors according to customer demographics and see the most preferred colors with trend analysis reports. The wholesale pricing system applies tiered discounts based on quantity. Different discount rates are automatically calculated on a tier basis such as "6-11 pieces," "12-23 pieces," "24-47 pieces," and "48+ pieces." Special price advantages are offered for early season orders. Quick order and favorite models enable clothing stores that place regular orders to add their best-selling coat models to favorites and reorder with a single click. "Beginning of season standard order" templates can be created and routine orders can be automated. Stock and shipment tracking optimizes delivery times especially during busy order periods at the beginning of the season. Dealers can see their order statuses in real-time, access cargo tracking information, and benefit from urgent order options. Return and exchange management manages end-of-season returns for unsold products, size change requests, and damaged product exchange processes in a digital environment. End-of-season return limits, return rates, and conditions are automatically calculated for each dealer. Marketing material support offers product photos, window display suggestions, season campaign posters, and social media content that dealers can use in their stores. Brand logo, label designs, and price tags are shared digitally. Dealer performance analysis shows detailed reports on which coat types are selling more, which size distributions are optimal, color preferences, and seasonal sales trends. This data helps dealers create the right product range for the next season.