The problem
Chinese companies expanding overseas usually hold a lot of customer and business data. It’s just scattered across systems that don’t talk:
- HQ (China-side) — ERP, PLM, production management, dealer contracts
- Overseas dealers — regional CRMs, orders, warranty records, sales-call reports
- Cross-border e-commerce — Shopee / Lazada / TikTok Shop / Amazon orders, reviews, refunds
- After-sales service — local service-centre tickets, warranty registration, RMAs, social CS (WhatsApp / Line)
- Marketing — ad platforms, offline event lists, direct-site forms
The same overseas customer shows up as several unrelated records across these systems. HQ sees orders and production. The dealer sees visits and intent. After-sales sees complaints and warranties. E-commerce sees reviews and refunds. Nobody sees the whole person.
An AI data platform isn’t about replacing what you already run. It’s a queryable, governed, addressable layer on top — so overseas sales, HQ management and AI all work from the same trusted data.
Where we usually start
The four directions we most often land with manufacturers expanding overseas — appliances, consumer electronics, precision components, industrial consumables:
- Dealer credibility scoring — HQ sales leadership gets a cross-system, explainable dealer rating built from order cadence, refund rate, warranty claims and regional market coverage.
- Warranty registration → customer follow-up — cross-border e-commerce buyers, offline dealer sales, after-sales warranty and follow-up all string into one motion, so the AI assistant can prompt sales to reach out before warranty expiry.
- After-sales ticket knowledge base — HQ tech-support docs, dealer field experience and overseas service-centre tickets all connect, so the AI assistant can answer by model, batch and language.
- Product reviews → R&D feedback — product issues surfaced in cross-border reviews and after-sales tickets flow back to HQ product and quality teams, shortening the feedback loop.
For overseas-expanding tech companies the surface shifts — more direct websites, SaaS back-ends, overseas CRM + CS tools — but the underlying problem is the same: the same customer wears several faces across systems, and management never sees the one person underneath.
How we deliver
- Discovery (2 weeks) — inventory cross-border data sources, agree sync fields and compliance basis, define the first measurable success metric (one overseas-sales or one after-sales scenario).
- Foundation (4–6 weeks) — cross-region identity resolution, real-time pipeline, cross-border compliant sync, consent and retention policy, dealer role-permission model.
- Activation (2–4 weeks) — light up the first business channel — typically an upgraded customer view inside the sales CRM, after-sales knowledge-base retrieval, or cross-border e-commerce buyer write-back to the dealer system.
- Wire the AI copilot (2 weeks) — add an AI assistant on top of the customer view so HQ sales and overseas dealers can ask, in Chinese or English, questions like “which dealers show an abnormal spike in warranty claims” or “where are complaints concentrated in the last 30 days.”
Outcomes with delivered clients
- HQ → overseas dealer customer view unified — 4 source systems merged into one trusted customer master
- Cross-border e-commerce + dealer sales data reconciled — so the AI assistant recognizes the same customer’s full lifecycle across e-commerce and offline dealer sides
- Multi-language after-sales / warranty knowledge base live — front-line after-sales staff pull HQ technical archives directly in English and Chinese
(Client names and specific numbers are shared under permission; comparable industry cases can be discussed under NDA during discovery.)
Compliance & data residency
PDPA first: data stays in Singapore (Azure Southeast Asia), encryption at rest and in transit, audit logs of every read against personal data, configurable retention windows. Aligned with Indonesia UU PDP and Malaysia PDPA 2024 amendments for cross-border transfer mechanisms, combined with our IT integration and data security assessment practices for security hardening.