How Chinese agencies syndicate hot brands and talent — and what that looks like in the US

American brands on TikTok Shop tend to think about creators one at a time. You find a creator, you send product, they post, you see what happens, you repeat. It works, slowly.

The Chinese live commerce industry stopped working that way years ago. When a product starts to move there, an operating layer sits between the platform, the creators and the brand, and its job is to put that product in front of as many audiences as possible in as short a window as possible. That layer is the MCN, and the mechanic is syndication.

What an MCN actually is

MCN stands for multi-channel network, which is an unhelpful name inherited from YouTube in the 2010s, where the original companies bundled channels together to optimise advertising revenue. The Chinese version mutated into something considerably more powerful: an operating company that recruits and trains creators, produces content, negotiates campaigns, runs livestream rooms, distributes across platforms, and takes a percentage of what sells.

They grew because Chinese social commerce became too fragmented and too fast for brands to run directly. A campaign might need one platform for conversion, another for trust, another for retention, another for subcultures, and a marketplace for the actual transaction. No brand marketing team can operate that surface alone. So an intermediary industry grew into the gap, numbering in the tens of thousands of firms.

Syndication: the part the US has not copied

Here is the mechanic that matters. When a Chinese MCN has a product that converts, it does not rely on one host or one account. It deploys the product across a matrix — dozens or hundreds of accounts and livestream hosts the network controls or has relationships with, running in parallel, across multiple platforms, inside a compressed window.

The scale involved is difficult to convey with adjectives, so here are some numbers. One Chinese MCN reportedly manages roughly 90,000 signed creators with a combined following in the billions. The agency behind one of China's best-known livestreamers worked with more than 1,600 brands in a single year. Another, at its peak, reportedly partnered with more than 20,000 businesses. Individual livestream sessions from top networks have averaged tens of millions of RMB in sales.

The consequence is that a winning product in China gets a coordinated, simultaneous, multi-account push rather than a sequential creator-by-creator rollout. Velocity is manufactured rather than hoped for. On a platform whose algorithm rewards early momentum, manufactured velocity is close to decisive.

Why the US does not work this way

Three reasons, and none of them is that Americans have not thought of it.

1. Talent representation here was built for brand deals. The American influencer industry grew up selling sponsorships and ad integrations. The commercial muscle, the contracts and the compensation models are all built around a flat fee for a post, not a commission on units moved over four hours of live selling.
2. The networks are not concentrated. Chinese MCNs control large stables of creators under contract. US creator relationships are looser, more transactional and spread across many smaller agencies, so nobody can flip a switch and light up 200 accounts on the same product.
3. Live selling is still young here. US livestream e-commerce reached roughly $14.6 billion in 2025, up nearly 50% year over year — but that remains around 5% of US e-commerce. In China the equivalent market is measured in the hundreds of billions of dollars. The host talent pool simply has not been built yet at comparable scale.

What is starting to change

The interesting development is not that Chinese MCNs are opening American offices, although some are. It is that the syndication model can be assembled here from parts that already exist.

The parts are: agencies with real US creator networks in specific categories, the US offices of China-based agencies that bring their own channels and talent, brand-side operators who can keep a product in stock, and a platform that rewards concentrated velocity. What has been missing is the connective layer that coordinates them on one product at one time.

That is the layer DCA is building. When we have a brand or a creator that is working, the objective is not to run our own channel harder. It is to put that product in front of every network we can reach simultaneously — our own creators, partner specialist networks with thousands of vetted US creators in the relevant category, and the American arms of China-based agencies that arrive with their own talent and their own channels.

One thing worth knowing if you go looking for partners

China introduced new rules governing MCN-style services that took effect on 1 September 2026. They require these service providers to register properly, obtain the relevant licences, verify the identities of the people operating accounts, strengthen information security, and take more responsibility for the content that goes out. The rules also tighten obligations around misleading content and livestreaming claims.

The practical implication for a brand is that partner due diligence has become a real exercise rather than a formality. It is no longer enough to ask who has the longest creator list or the cheapest package. Worth asking: are their partners properly registered, which accounts do they actually control, how are creators vetted, who approves scripts, and what happens when a live host makes a claim they should not have.

Those are good questions to ask in any market, including this one.

What to take from this

If you are a brand on TikTok Shop, the thing to understand is that creator-by-creator rollout is not the only available model, and it is not the one used in the market that is five years ahead. Ask any agency you are speaking to how they scale a winner: whether they can put a working product in front of many networks at once, or whether they will work through their own list sequentially.

The answers differ more than you would expect.