DTC / own-store brands Creators on Xiaohongshu (RED): 167 Indexed

This is the pool of DTC / own-store brands creators on Xiaohongshu (RED) within E-commerce / DTC — 167 of them. The narrower the niche, the higher the reply rate; searching broadly for "E-commerce / DTC creators" usually spends budget on audiences that do not overlap yours.

How this slice differs from the index as a whole

• Median following is 13,200, 3.2× the index-wide median of 4,155 — expect higher rate cards.
• A and B grades are 45% of this slice versus 37% overall — a denser pool, so the same screening effort yields more usable names.

How to read these numbers: this covers creators indexed and validated inside Koinon Link, not every creator on the platform. Suspected bought-follower accounts are quarantined and excluded from the table above (shown separately). The authenticity score is our own anomaly detection over follower/engagement structure, not a platform-official metric. Figures update as collection continues.

Creators in this slice

• 晴晴外贸韩系工厂 (@11412505612) — Clearance sale

• 深夜种草的翠花 (@429994378) — Beauty enhancement ideas for ordinary people

• 甜腻腻 (@tiannini123) — Affordable makeup and base makeup reviews

• 小鱼外贸韩系穿搭 (@271202433) — Korean style outfits

• 木三 (@100568253) — Affordable beauty and skincare recommendations

• 大老板波哥外贸 (@9525744981) — Factory direct home appliances, clearance stock

• 一颗枣枣 (@Eccomi) — Affordable whitening serums and full-body whitening

• 若若外贸 (@49328746337) — Hemp pants recommendations

• 小废物种草日记 (@1571103150) — Anime merchandise unboxing and card pulling

• 云海外贸仓 (@6852159982) — high-value high-pressure cooker recommendations

Ordered by follower tier, first 10 shown. Each link opens that creator’s public profile: what they post about, who reads it, and recent samples — no contact details.

Top 6 countries

Why this niche deserves its own view

"DTC / own-store brands" is defined by who the audience is and what job they do, not by what the creator posts about. Two creators can both cover AI tools while their audiences barely overlap — one talks to media buyers who care about creative and bids, the other to engineers who care about APIs and deployment. Searching by topic mixes them together; searching by audience function does not.