Metrics
Overview
Arvind Fashions operates two separate business entities under one group: one managing the Calvin Klein and Tommy Hilfiger licenses, processing upwards of 25,000 styles per year across new season and carryover catalogues; and a second covering US Polo Assn, Arrow, and Flying Machine, processing approximately 6,000 styles per season across six marketplaces.
Despite operating as distinct entities with separate teams and workflows, both faced a shared structural problem. Catalog production was slow, manual, and increasingly difficult to scale as marketplace volume and compliance requirements grew.
Problem
The challenge was not isolated to one brand or one team. Across both entities, catalog operations were held back by the same underlying friction points.
Product data was fragmented across multiple internal systems and upstream sources, requiring significant manual effort just to consolidate inputs before enrichment could begin
Marketplaces enforced strict submission requirements around MRP, SKU structure, image specifications, and mandatory attribute fields, and any errors at submission meant rejection and rework
Both new season and carryover catalog operations ran simultaneously, creating competing workload demands on the same teams
Each brand published to a different combination of channels, each with its own formatting rules, meaning distribution was not a single step but a separate reformatting exercise for every marketplace
With no shared governance framework across the two entities, quality standards and turnaround expectations varied, making it difficult to benchmark or improve performance consistently
Opportunity
Arvind Fashions needed a platform that could standardize the pre-submission stage of catalog production without flattening the differences between brands.
The goal was a centralized system that enforced data quality before anything reached a marketplace, eliminated the manual effort spent consolidating and reformatting inputs, and gave both entities a shared operational baseline while preserving brand-level flexibility.
With marketplace competition intensifying and first-day-of-sale performance increasingly tied to catalog readiness, the business case for cutting turnaround from days to hours was clear. Every cycle saved was inventory made available sooner, which in fashion translates directly to full-price sell-through.
Solution
Streamoid gave both Arvind Fashions entities a single platform to manage catalog production across all five brands, from the moment product data enters the system to the moment a listing goes live on a marketplace.
What changed for the teams on the ground:
Product data pulled directly from existing internal systems, removing the manual step of consolidating inputs at the start of every catalog cycle
Product tags were read automatically to extract details like MRP and country of origin, eliminating a time-intensive keying task that had previously been done by hand
AI generated product titles, descriptions, and fashion attributes from imagery, so teams were approving and refining content rather than writing it from scratch
Every image was checked and formatted to meet marketplace requirements before it left the platform, removing the back-and-forth that came with submission rejections
Each brand's marketplace rules were built into the publishing workflow, so the same style could be sent to multiple channels simultaneously, correctly formatted for each one
Results
Both entities saw consistent improvements in speed, accuracy, and team efficiency.
For Calvin Klein and Tommy Hilfiger:
20,000 to 25,000 styles processed annually, covering both new season and carryover collections
Turnaround reduced from up to nine days to 48 to 72 hours per batch
Marketplace acceptance rate reached 95 to 98 percent across 8 channels
Data accuracy maintained above 95 percent
For US Polo Assn, Arrow, and Flying Machine:
6,000 styles processed per season with 2 to 3 batches completed per week
Turnaround reduced from 7 days to 48 to 72 hours
90 percent marketplace acceptance rate across 6 channels
Data accuracy maintained above 95 percent
Across both entities, catalog teams shifted from building product content manually to reviewing AI-generated content, compressing the most time-intensive part of the production cycle without reducing output quality.
Sidebar Fields
Products used: Catalogix
Industry: Fashion and Retail
Entities: 2
Brands: Calvin Klein, Tommy Hilfiger, US Polo Assn, Arrow, Flying Machine
Annual volume: 25,000+ styles (Entity 1), 6,000 styles per season (Entity 2)
Channels: Up to 8 marketplaces
