Cross-border Creators on WeChat: 1,130 Indexed

This is the pool of Cross-border creators on WeChat within E-commerce / DTC — 1,130 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

• A and B grades are 91% of this slice versus 37% overall — a denser pool, so the same screening effort yields more usable names.
• 56% have recent content captured for judgement versus 46% overall — better-evidenced than average.
• 0% publish an email or IM handle against 6% index-wide — more dependent on platform DMs, so outreach costs more here.

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

• @2Cshop跨境研究社 — TikTok product promotion strategies

• @OUSITES有站出海 — TikTok US AI Tools: Real Tests & Policy Response

• @WeAreSellers — TikTok product selection tools

• @eBay 海淘 — eBay overseas digital goods

• @一个忙着建站的Kris — Independent site payment processing

• @亿恩 — Amazon operations and job market

• @亿邦动力 — Cross-border e-commerce for global expansion

• @企业成长陪跑者 — Cross-border e-commerce compliance in China

• @企业税账管理服务办 — Cross-border e-commerce company registration in China

• @千惠说房 — In-depth property project review

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.

Why this niche deserves its own view

"Cross-border" 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.