The 2026 China Brand Going-Global Report: Growth & AI Visibility

Two facts sit awkwardly next to each other in 2026. China's cross-border export machine has never been larger, yet the moment that decides whether an overseas customer ever sees a given brand is quietly migrating away from the channels most exporters have mastered. This report is Ignite Consulting's attempt to hold both facts at once, using only public, sourced data, and to give operators a way to think about where they actually stand.

The numbers throughout are cited to their original sources and linked in full at the end. Where a figure comes from a specific market-research firm with its own definition, we say so, because cross-border e-commerce is measured several incompatible ways and a single "market size" rarely means the same thing twice. Our contribution is not the data. It is the framework we use to interpret it, the synthesis across otherwise disconnected datasets, and the commentary on what it means for a brand deciding where to invest next.

Executive summary

Five findings anchor this report. First, the China cross-border e-commerce market is large and still growing faster than overall trade: total cross-border e-commerce imports and exports reached 2.63 trillion yuan in 2024, up 10.8% year on year, against total goods trade growth of 5.0% (General Administration of Customs, via China News; GAC via gov.cn). Second, the United States is the single most important destination, taking 36.2% of China's cross-border e-commerce exports (GAC via China Daily). Third, the channel mix is shifting: marketplaces dominate, Chinese sellers are now the majority of Amazon's global seller base, and TikTok Shop is growing fastest, while brand-owned direct sites plateau as a share of e-commerce. Fourth, the discovery layer is being absorbed by AI: AI summaries cut click-through roughly in half when they appear, and a record share of searches now end without any click. Fifth, and most important for strategy, none of the export scale matters at the buying moment if the brand is absent from the AI answer the customer reads.

We organize the whole report around a single original framework, the Overseas Visibility Maturity Model, and read every dataset through it.

The framework: the Overseas Visibility Maturity Model

Most going-global advice is a list of tactics with no spine. We use a five-stage model instead, because it lets a brand locate itself honestly before spending a dollar. The model measures one thing: how reliably a brand is seen and chosen at the moment an overseas customer is deciding, across every surface that moment now lives on. The stages are cumulative. You do not skip them, and falling back a stage is common when a channel shifts under you.

1. Stage 1, Channel-dependent. The brand is visible only inside a marketplace it rents. Discovery, ranking, and the customer relationship all belong to the platform. Most exporters start here, and the data shows why it is crowded: Chinese sellers now make up 50.03% of Amazon's global active seller base (Marketplace Pulse).
2. Stage 2, Owned-presence. The brand has a credible, owned destination, a real site rather than a listing, that a customer can verify independently. This is where direct-to-consumer aspirations live, and where the data warns against over-betting: US direct-to-consumer sales are forecast to peak at 14.9% of total e-commerce in 2025, then plateau (EMARKETER).
3. Stage 3, Search-discoverable. When a customer searches in English, the brand appears. This is classic SEO, and it remains the floor on which everything above sits, because generative engines retrieve from the indexed web.
4. Stage 4, Answer-cited. When a customer asks an AI assistant for options, the brand is named inside the generated answer. This is generative engine optimization, and it is where most brands, overseas and domestic alike, are absent today.
5. Stage 5, Trusted-default. The brand is the option the model and the market reach for by default, corroborated by third parties across the open web. This stage is slow to build and slow to erode, which is exactly what makes it a moat rather than a tactic.

Export scale gets you to the warehouse door. Visibility maturity decides whether the customer ever knocks on it.

The rest of this report walks the data through these stages: the market that creates the opportunity (the fuel), the channel shift (Stages 1 and 2), the AI discovery shift (Stages 3 through 5), the economics of moving up, and the friction that keeps brands stuck.

Section 1: The market, the fuel behind every going-global decision

The scale is the easy part of the story, and it is genuinely large. China's total cross-border e-commerce imports and exports reached 2.63 trillion yuan in 2024, up 10.8% year on year, roughly one trillion yuan more than in 2020 (General Administration of Customs, via China News). Exports alone grew 16.9% to 2.15 trillion yuan, crossing two trillion yuan for the first time, with total cross-border trade volume at 2.71 trillion yuan (GAC via China Daily). For context, that growth rate sits well above the broader backdrop: total goods foreign trade reached a record 43.85 trillion yuan in 2024, up 5.0%, with exports up 7.1% (GAC via gov.cn). Cross-border e-commerce is, in other words, one of the fastest-growing slices of an already large export economy.

The momentum carried into 2025. Cross-border e-commerce imports and exports reached 1.32 trillion yuan in the first half of 2025, up 5.7% year on year, with exports of 1.03 trillion yuan and imports of 291.1 billion yuan, again outpacing total foreign trade growth of 2.9% (General Administration of Customs, via CGTN). The policy scaffolding has grown with it: China has expanded its cross-border e-commerce comprehensive pilot zones to 178, with Hangzhou alone surpassing 200 billion yuan in cumulative volume at an average annual growth rate above 30% (Science and Technology Daily).

Two structural facts matter more than the headline totals. First, this is overwhelmingly a consumer-goods export story: consumer goods represented 97.5% of total cross-border e-commerce exports in 2024 (GAC via China Daily). Second, the United States is the anchor destination, taking 36.2% of cross-border e-commerce exports, far ahead of Britain at 11.7% and Germany at 5.7% (GAC via China Daily). For a brand deciding where to invest in visibility, that concentration is the single most actionable number in the market section: the customer you most need to reach is, more often than not, American and shopping for consumer goods.

The operator base is also broad rather than concentrated. Among nearly 700,000 entities with import or export records, more than 120,000 are cross-border e-commerce business entities (General Administration of Customs, via Xinhua). Read through our model, that breadth is the problem hiding inside the opportunity. Tens of thousands of capable operators are competing for the same customers, and at Stage 1 they compete almost entirely on price. The market is the fuel. It does not, by itself, tell a customer which brand to choose.

A note on that last row. IMARC Group estimates China's cross-border e-commerce market at USD 90.85 billion in 2025, projected to reach USD 312.12 billion by 2034 at a 14.70% compound annual growth rate over 2026 to 2034 (IMARC Group). That figure is far smaller than the customs totals because it uses a narrower, business-to-consumer-focused definition. We include both deliberately: the gap between an official trade-flow number and an analyst market-sizing number is a useful reminder that "how big is this market" depends entirely on what you choose to count.

Section 2: The channel shift, marketplaces, owned sites, and TikTok Shop

This section maps directly onto Stages 1 and 2 of the model. The central tension is between renting visibility on a marketplace and owning it on your own destination, and the data tells a more nuanced story than either "marketplaces win" or "build your own site" slogans suggest.

Marketplaces dominate, and Chinese sellers are now the majority on Amazon

At the structural level, marketplaces are where the customers are. Online marketplaces accounted for 62% of global retail e-commerce sales, roughly USD 2.4 trillion, in 2024, and they were the single largest contributor to e-commerce growth, driving over 40% of total growth that year, more than any other channel (Euromonitor International; Cymbio). Within marketplaces, the third-party seller channel, which is where cross-border sellers live, keeps gaining share: third-party sales rose from 72% of total marketplace sales in 2014 to 81% in 2024 (Euromonitor International).

Chinese sellers have responded by flooding the largest marketplace. They crossed the 50% threshold of Amazon's global active seller base for the first time, reaching 50.03% (Marketplace Pulse). But seller count is not revenue, and this is where Stage 1's ceiling shows. Despite holding a majority of seller accounts, Chinese sellers capture roughly 39% of third-party revenue worldwide, because the average US seller generates more than double the revenue of the average Chinese seller, USD 884,958 against USD 393,557 (Marketplace Pulse). Even on the US marketplace specifically, US sellers still out-earn Chinese sellers in absolute terms, roughly USD 157 billion against USD 132 billion of Amazon.com's USD 305 billion in third-party GMV (Marketplace Pulse).

Read through the model, the lesson is blunt. Winning the seller-count race is a Stage 1 achievement that does not, on its own, translate into proportional revenue. The revenue gap between the average US and Chinese seller is the price of being a price-competing listing rather than a chosen brand.

TikTok Shop is the fastest-moving surface, and the US is its key opportunity

The newest channel is also the fastest-growing one. TikTok Shop's global gross merchandise value roughly doubled year on year, growing from USD 33.2 billion in 2024 to an estimated USD 64 to 66 billion in 2025 (TechNode Global). The United States is its second-largest market and grew strongly, with US TikTok Shop GMV reaching roughly USD 15.1 billion in 2025, up 68% year on year (TechNode Global). For a consumer-goods exporter, which is most of them given the 97.5% figure above, this is a live and fast-opening channel. It is still, however, a Stage 1 surface in our model: the platform owns the discovery algorithm and the customer relationship.

The owned-site plateau is a warning against an all-or-nothing reading

The natural reaction to marketplace dependence is "build your own site and escape." The data counsels nuance. US direct-to-consumer sales are forecast to peak at just 14.9% of total e-commerce in 2025, then plateau through 2028 (EMARKETER). In our model, this is why Stage 2 is a step, not the destination. An owned presence is necessary, because it is the only surface a customer can verify independently and the only one a brand fully controls, but treating the direct site as the whole strategy ignores where customers actually transact. The mature posture is to use marketplaces and TikTok Shop for reach while building the owned destination that the higher stages, search and AI citation, ultimately point customers toward.

Section 3: AI search and GEO, the discovery layer is being absorbed

This is the section that reframes everything above, and it maps onto Stages 3 through 5. The channel where a customer first forms an opinion is moving from a list of links to a generated answer, and the data on that shift is now hard to wave away.

AI summaries are absorbing the top of the funnel

Start with what AI summaries do to behavior. In a Pew Research Center study tracking 68,879 unique searches from 900 US adults over March 2025, users clicked a traditional search result link only 8% of the time when Google showed an AI summary, versus 15% when no AI summary appeared, nearly half as often (Pew Research Center). These summaries are not rare: 18% of all Google searches in the study generated an AI summary, and about six in ten US adults ran at least one such search during the month (Pew Research Center).

The broader zero-click trend is at a record. Per Similarweb's web panel, 68.01% of US Google searches ended without a click to the open web in early 2026, up from 60.45% in 2024 and roughly 49% in 2019 (SparkToro, citing Similarweb). For an exporter at Stage 3, this is the uncomfortable implication: ranking is increasingly necessary but no longer sufficient, because a growing share of searches resolve before anyone clicks anything.

The assistants themselves are now a primary research surface

The assistants are not a fringe behavior either. OpenAI's Sam Altman said at DevDay that more than 800 million people now use ChatGPT every week, up from about 400 million in February 2025 (Tech.eu, reporting OpenAI). In the US specifically, monthly generative AI users passed 100.1 million in 2024, up nearly 900% from 7.8 million in 2022 (EMARKETER).

Crucially, buyers use these tools to evaluate vendors, not just to chat. A Gartner survey found 45% of B2B buyers used generative AI, primarily to gather information on vendors and products during their buying journey (Gartner, via Demand Gen Report). That is the buying moment moving into the AI answer. For any China brand selling into the US, whether to consumers or businesses, this is Stage 4 made concrete: the assistant is writing the shortlist.

A calibrating fact: traditional search still dominates discovery today

We will not overclaim. Generative AI engines accounted for just 3.3% of online discovery time in the US as of August 2025, per Comscore data analyzed by EMARKETER (EMARKETER, citing Comscore). Traditional search still owns the vast majority of discovery time. The honest read is not "abandon search for AI." It is that the AI surface is small but growing fast and disproportionately decisive at the evaluation moment, while search remains the foundation. In the model, this is precisely why Stages 3 and 4 are both required and why neither replaces the other.

There is also a reassuring limit worth naming for B2B sellers. Gartner found 69% of B2B buyers prefer to validate AI-generated insights with human sales reps at critical decision points (Gartner, via Demand Gen Report). AI is the starting point of the shortlist, not the final authority. The implication is not that visibility matters less, but that getting named by the AI is what earns the brand the human conversation in which the deal actually closes.

For the underlying mechanics of how generative engines decide what to cite, and how it differs from ranking, our companion guide goes deeper in Why GEO now matters more than SEO and in How to get cited by AI.

Section 4: The marketing economics of moving up the stages

Climbing the model costs money, and the data lets us reason about where that money goes rather than guess. We do not publish a single budget number, because the right split depends on category, margin, and starting stage, and any precise universal figure would be guesswork. What the data does support is a directional logic.

Consider the gravitational pull of Stage 1. With Chinese sellers now the majority of Amazon's seller base (Marketplace Pulse) and the average Chinese seller earning less than half what the average US seller earns (Marketplace Pulse), the marginal dollar spent only on platform visibility buys diminishing, price-competed returns. That is the economic case for funding the higher stages.

The discovery data sharpens it. When AI summaries cut clicks from 15% to 8% (Pew Research Center) and 68.01% of searches now end without a click (SparkToro, citing Similarweb), spend that only buys raw clicks is buying a shrinking asset. Spend that buys being the named option inside the answer is buying access to the decision itself. The catch is timing. The AI surface is only 3.3% of discovery time today (EMARKETER, citing Comscore), so a sessions-only view will always conclude the channel is not worth it, right up until a competitor owns every recommendation query in the category. The economically rational posture is to judge the higher stages by whether the brand is named at the decision moment and by pipeline contribution, not by raw traffic that the AI layer is actively shrinking.

A useful way to frame the budget conversation is to spread spend across the stages rather than concentrate it. Foundation work, the owned site and technical search health (Stages 2 and 3), is largely a front-loaded cost that everything above depends on. Content and citation work (Stage 4) is the ongoing cost that scales with how many buying questions a brand wants to own. Third-party authority (Stage 5) is the slowest to pay off and the hardest to fake, which is exactly why it produces the most durable advantage. The common, expensive mistake is to keep pouring money into Stage 1 reach because it feels controllable, while underfunding the stages that actually decide whether a customer chooses the brand. We make the full budget argument in our SEO and GEO guide.

Section 5: The friction, why brands stay stuck at Stage 1

If the higher stages are where the value is, why do so many capable exporters stay at Stage 1? The friction is structural, not a failure of effort, and naming it precisely is half the fix.

The first source of friction is that Stage 1 works well enough to be a trap. Marketplaces own 62% of global retail e-commerce (Euromonitor International) and a TikTok Shop or Amazon listing produces orders quickly. The order flow masks the fragility: the platform owns the customer, the discovery, and the pricing pressure, and the average Chinese seller's revenue sits at less than half the average US seller's (Marketplace Pulse). A busy, profitable-looking Stage 1 business is quietly the most exposed when a platform changes its rules.

The second source is a language-and-entity gap that the AI shift makes more punishing. When a buyer asks an assistant for the best supplier or compares two brands, the model can only name what the English-language open web has taught it to trust. A capable manufacturer with an excellent product but no coherent English presence is simply not in the answer. With 45% of B2B buyers already using generative AI to research vendors (Gartner, via Demand Gen Report), absence from the model's sources is absence from the shortlist. This is the friction that keeps a Stage 1 brand from reaching Stage 4 even when the product would win on merit.

The third source is measurement. Because the AI surface is only 3.3% of discovery time today (EMARKETER, citing Comscore), a team watching only traffic dashboards sees no reason to invest in being cited, and so never builds the durable authority that Stage 5 requires. The friction is a reporting habit, and it resolves only when a brand starts measuring whether it is named when a customer asks for a recommendation. We map the China-specific version of this gap in our China B2B export playbook and in building a brand instead of renting marketplaces.

What this means for a China brand going global

Pulled together, the data points to a clear sequence rather than a single tactic. The market gives a brand fuel and a clear target, the US consumer buying consumer goods. Marketplaces and TikTok Shop give reach and early orders, but at a revenue ceiling that the seller-count majority cannot escape on price alone. The owned site is the verifiable destination, but it is a step, not the whole game, given the direct-to-consumer plateau. Search remains the foundation, and the AI answer is the new, fast-growing, disproportionately decisive surface where the shortlist now gets written.

The brand that wins in 2026 is not the one with the cheapest listing. It is the one that climbs the stages deliberately: a credible owned presence, a search-discoverable footprint, citation inside the AI answers customers actually ask, and the third-party corroboration that turns a name into a default. That is a reputation problem as much as a marketing problem, and reputation, unlike a paid placement, compounds.

Methodology

This report synthesizes publicly available data from the sources listed below, each cited inline at the point of use and linked in full in the Sources section. We did not commission new survey data; every numeric claim in this report comes from one of those public sources. Figures are reported as their original publishers stated them, including the units and time periods they used. Where two sources size the same market differently, we present both and explain the definitional gap rather than reconciling them into a false single number.

The original contribution here is analytical, not statistical. The Overseas Visibility Maturity Model is Ignite Consulting's framework, as is the synthesis that reads otherwise disconnected datasets, customs trade flows, marketplace seller economics, and AI search behavior, as one connected story about visibility at the buying moment. Interpretive statements, stage definitions, and commentary are Ignite's analysis and judgment, and are labeled as such. They are not guarantees of any particular outcome; market conditions and platform behaviors change quickly, and the figures cited are point-in-time. This report is informational and does not constitute a promise of results.

Sources

All figures above are drawn from the following public sources. Definitions and time periods are as reported by each publisher.

1. General Administration of Customs (海关总署), via China News / Xinhua. China's cross-border e-commerce reached 2.63 trillion yuan in 2024, up 10.8%. chinanews.com.cn/cj/2025/01-13/10352215.shtml
2. General Administration of Customs (GAC), via China Daily / Xinhua. Cross-border e-commerce exports up 16.9% to 2.15 trillion yuan; US 36.2% of exports; consumer goods 97.5%. chinadaily.com.cn/a/202506/17/WS6850d61fa310a04af22c6b49.html
3. General Administration of Customs (海关总署), via Xinhua. Over 120,000 cross-border e-commerce business entities. news.cn/fortune/20250113/f55022d76631432baa869da6a9a9f114/c.html
4. General Administration of Customs, via CGTN. Cross-border e-commerce 1.32 trillion yuan in H1 2025, up 5.7%. news.cgtn.com/news/2025-07-21/China-s-e-commerce-sales-rise-8-5-in-H1-1FbJvUYw5K8/p.html
5. Science and Technology Daily (stdaily.com). 178 comprehensive pilot zones; Hangzhou over 200 billion yuan cumulative. stdaily.com/web/English/2025-07/07/content_366052.html
6. General Administration of Customs, via gov.cn (The State Council). Total goods trade 43.85 trillion yuan in 2024, up 5.0%. english.www.gov.cn/archive/statistics/202501/13/content_WS6784a546c6d0868f4e8eec59.html
7. IMARC Group. China cross-border e-commerce market USD 90.85 billion in 2025, 14.70% CAGR to 2034 (B2C-focused definition). imarcgroup.com/china-cross-border-e-commerce-market
8. Marketplace Pulse. Chinese sellers reach 50.03% of Amazon's global active seller base; revenue-per-seller and GMV comparisons. marketplacepulse.com/articles/china-reaches-global-majority-on-amazon
9. TechNode Global. TikTok Shop global and US GMV figures, 2024 to 2025. technode.global/2026/02/11/tiktoks-southeast-asia-doubles-gmv-year-on-year-to-45-6b-in-2025/
10. Euromonitor International. Marketplaces 62% of global retail e-commerce (~USD 2.4T) and third-party share rising to 81%. euromonitor.com/article/digital-disruptors-the-global-online-marketplace-landscape-in-2025
11. EMARKETER. US D2C sales peak at 14.9% of e-commerce in 2025, then plateau. emarketer.com/content/us-direct-to-consumer-ecommerce-forecast-2024
12. Cymbio. Marketplaces drove over 40% of total e-commerce growth in 2024. cym.bio/blog/marketplaces-growth-2024
13. Pew Research Center. Click-through 8% with vs 15% without AI summary; 18% of searches showed a summary. pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results
14. Gartner, via Demand Gen Report. 45% of B2B buyers used generative AI; 69% validate AI insights with sales reps. demandgenreport.com/industry-news/news-brief/gartner-ai-is-reshaping-b2b-buying-but-human-sellers-still-close-the-confidence-gap/53046
15. Tech.eu, reporting OpenAI / Sam Altman. ChatGPT more than 800 million weekly active users. tech.eu/2025/10/07/chatgpt-has-more-than-800m-weekly-active-users-says-altman
16. EMARKETER. Generative AI just 3.3% of US online discovery time as of August 2025 (Comscore data). emarketer.com/content/ai-will-dominate-search-just-not-2026
17. EMARKETER. US passed 100.1 million monthly generative AI users in 2024. emarketer.com/content/generative-ai-hits-100-million-users-milestone-us
18. SparkToro, citing Similarweb. 68.01% of US Google searches ended with zero clicks in early 2026. sparktoro.com/blog/in-2026-less-than-one-third-of-google-searches-still-send-a-click