Ecommerce AEO, GEO & AI Search Services in Singapore

The first step is scoping your category and target markets together, turning real shopper questions — best X under budget, is it worth it, how it compares — into a monitoring list. Once that list goes into the nine-engine dashboard, daily runs begin and your first baseline arrives quickly: who gets recommended on each question today, which review and community sources AI cites, and where you and each competitor stand. With the baseline agreed, managed execution starts, reconciled by a weekly report from then on.

It comes down to mechanics, not promises: AI answers follow the source layer, and recommendations shift only after engines re-crawl and start trusting new review articles, community threads, and structured product information. The consistent pattern is that niche questions move first — recommendations for a specific audience or use case change earlier than broad category terms — and pace also depends on how contested your category is and the review coverage you already have. We commit to no dates, but monitoring runs daily, so the day any tracked question changes, you see it — no waiting for a quarterly review.

Three metrics live on the dashboard: visibility — the share of monitored shopping questions where your brand appears in the answer; recommendation rate — the share where you are explicitly listed as a buying suggestion; and source citations — which review and community content each answer draws on, drillable to the exact link. The weekly report reconciles against the same data and includes a competitor comparison. Billing is tied to the same yardstick: Base plus Bonus, with the Bonus paid only after the KPIs agreed upfront are met — the definition of success is written down at signing.

Asking Doubao or Yuanbao before buying is becoming as natural for Chinese consumers as browsing Xiaohongshu, and those engines cite Chinese sources only — Xiaohongshu, Zhihu, SMZDM, WeChat content — so none of the review reputation you built overseas carries over. Brands selling into China have to treat that Chinese source layer as a separate asset, and even pure-export brands usually have Chinese touchpoints: distributors, resellers, and Chinese-speaking shoppers doing their homework on DeepSeek and Doubao. The dashboard gives you a Chinese-side baseline first, so you decide whether to invest after seeing the numbers.

With a clear division of labor there is no conflict: paid buys reach, SEO competes for links on a results page, and GEO competes for the recommendation AI speaks out loud — three different stages of the same buyer journey. Your existing product content, review partnerships, and press coverage are GEO's raw material: we first diagnose on the dashboard which assets AI already cites and which it ignores, then align with your content and growth teams on what to add or fix, taking over no existing channel. The weekly report is shared across teams, so everyone argues from the same data.

E-commerce is where fake reviews and astroturfing run thickest, which is exactly why our boundaries are built into the delivery model: no poisoning, no fake volume, no manufactured reviews, no mass-produced community posts — tactics that in this industry also carry platform-ban and false-advertising risk. What we do instead is make accurate product information machine-readable, supply legitimate information to real review media and communities, and correct stale or wrong citations. Every cited source can be drilled into and verified on the dashboard — provenance is fully traceable, and the work stands up to your legal team and to platform rules.