While most fabric suppliers are still observing what AI can do, a company rooted in Keqiao's Dongsheng Road market for three years has already integrated AI tools into its sampling process, attempting to upload fabric images to automatically generate trouser samples. This seemingly small move reflects a real turning point in traditional fabric trading from experience-driven to tool-driven operations.
Background
The Dongsheng Road market in Keqiao is one of the core trading areas of China Textile City, hosting numerous fabric storefronts with fierce competition and fragmented customer demands. In this context, this company, named Geling Fashion, has partnered with an online platform for nearly two years, forming a long-term dual-line layout combining offline storefronts and online channels. Its customer base is concentrated in garment industrial belts such as Guangzhou and Wuhan, meaning its products must simultaneously meet aesthetic and cost requirements of different regional markets.
The digital practice of the company's head, Hu Jiabin, is not concept-first but directly lands in the development stage. He is testing a mini-program called AI Cloth, whose core function is to automatically produce trouser samples after uploading fabric materials. If this process runs smoothly, it will compress traditional sampling from several days to a few hours, directly redefining the response speed between fabric suppliers and garment factories. For buyers, this means faster sample availability; for factories, it means the capability boundary of small-order quick-response is being redrawn.
Industry Impact
On the customer operation front, this company adopts a typical dual-track strategy: old customers are maintained through WeChat with regular communication, forming stable contact habits; new customers are identified as having a trial-order mentality, requiring more flexible minimum order quantities and faster delivery commitments. Behind this layered operation is a clear judgment of customer structure—old customers contribute stable orders, new customers are incremental sources, and the two need entirely different service rhythms.
Demand divergence is equally noteworthy. Some customers prioritize cost-effectiveness and are highly price-sensitive; others focus more on fabric texture and finished product quality, showing lower price sensitivity. This divergence is particularly evident in the Keqiao market, where buyers come from different brand tiers and wholesalers. Geling Fashion's approach is to precisely match product lines rather than trying to cover all customer groups with a single product. For peers, this implies that price wars are not the only way; segmented positioning can build deeper customer loyalty.
On product development, the company has built a multi-channel inspiration system: attending fashion shows to capture trends, referencing Guangzhou designer websites and industry member content, and extracting details like embroidered flowers and decorative elements from show images to incorporate into its own fabric designs. Raw material ratios are also flexibly adjusted according to market trends, ensuring that component combinations fit current garment demands. This ability to transform external trends into internal development language is becoming one of the core competitiveness of fabric suppliers.
From a category layout perspective, Geling Fashion mainly deals in knitted jacquard, brushed, rib, and woven fashion fabrics, covering products such as long-sleeve lightweight lined shirts, autumn jackets, denim-look garments, and gender-neutral shirts. Neutral-style fabrics break the boundary between men's and women's wear, expanding application scenarios and aligning with the current gender-fluid fashion trend. This multi-category strategy reduces the risk of fluctuation in a single category while allowing buyers to source multiple fabric types from one supplier, reducing supply chain coordination costs.