Chinese AI startups have built strong products in writing, image generation, video editing, companionship and productivity. Many now target the United States first, because willingness to pay is high and English content travels to other markets. The first ninety days decide whether that entry builds momentum or burns budget. Here is a practical three-phase plan we use as a starting framework.
Days 1 to 30: Foundations
Positioning. Write one sentence that explains who the product is for and what it replaces. Test it with ten target users in the US before spending on ads. Many teams discover that their domestic positioning does not translate.
Website and app store pages. Native-quality English copy, a pricing page with clear units, a privacy policy that explains data handling plainly, and support contact details. US users check these before installing an AI app, particularly regarding data use for training.
Measurement. Install analytics and attribution, define activation (for example, first generated output), and set up server-side events for subscriptions. Without this, phase two produces numbers you cannot trust.
Accounts. Open ad accounts on the platforms you plan to test. Allow time for verification. Teams entering several platforms at once often work with an agency to avoid delays.
Days 31 to 60: Testing
Paid channels. Run small tests on two or three channels, typically TikTok, Meta and Google (including App campaigns). Use five to eight creative concepts per channel. Optimise for activation or trial start rather than install.
Organic and community. Post demos on relevant subreddits and communities only where self-promotion is permitted. Reach out to a small number of creators for honest reviews. Product Hunt can work for productivity tools.
AI search visibility. Publish comparison and use-case pages that answer questions people ask assistants, such as "best AI tool for X". Make sure third-party directories describe the product consistently.
Days 61 to 90: Focus
Cut and double. Keep the channel and creative themes with the best cost per activated user and cut the rest. Increase budget gradually, around twenty to thirty percent at a time.
Pricing experiments. Test annual discounts and trial lengths. Watch refund rates and app store reviews alongside revenue.
Retention. Fix the top three drop-off points in onboarding. Paid acquisition is only as efficient as the product's ability to keep users.
Common mistakes
Spreading budget across too many channels, judging results on install cost alone, ignoring privacy questions, and translating Chinese marketing copy literally.
Conclusion
A disciplined ninety-day plan gives an AI startup a clear read on product-market fit in the US and a base to expand from. The key is to measure activation and retention from day one and to treat channels as experiments rather than commitments.
References
- PandaWM, AI going-global user acquisition path: AI going global user acquisition guide
- Apple App Store and Google Play guidelines on privacy disclosures
- Platform documentation for TikTok, Meta and Google App campaigns
Published by PandaWM, an overseas marketing team based in Hong Kong.