Category, intent & merchandising SEO
Category-page SEO against shopper intent, programmatic PDPs tied to PIM attribute data, and AEO-optimized content for the answer engines DTC shoppers increasingly use.
09 Verticals · E-commerce
Marketing & AI for
e-commerce & DTC brands.
We run performance marketing and AI automation for DTC brands and B2B e-commerce operators — SEO, paid, and lifecycle on one side; content-at-scale, merch agents, and support copilots on the other. Plus the RevOps layer that connects Shopify or BigCommerce to the rest of the business.
KacificSatellite Internet · SG
FlexxonNAND Solutions · SG
X-PHY IncCybersecurity · US
Gauze CareMedical Products · US
NDAB2B SaaS · US
NDAFintech · SG
NDAClimate & Energy · APAC
NDALogistics · US
E-commerce compounds on both sides.
The DTC brands that scale past $10M GMV don't pick between paid growth and AI automation — they run both as one growth model. The lifecycle program needs the product-content pipeline to feed it; the merchandising agent needs the paid-traffic signal to learn from; the returns copilot needs the same CX data the CX team uses to optimize the funnel.
We work with DTC brands scaling past $5M GMV and B2B e-commerce operators (industrial, medical, office supply) where the buyer flow looks more like procurement than consumer.
Finyki is remote-first, with teams across Singapore and the United States. Our stack experience spans Shopify, BigCommerce, Magento, and custom commerce platforms.
02 What we run in E-commerce
Service shapes across marketing
and AI, tuned to commerce operators.
Every engagement targets a commerce workflow with a clear margin or conversion impact — not a vanity chatbot or a vanity campaign.
Performance marketing & retention
Google, Meta, and TikTok performance scoped against contribution margin — not ROAS theater. Plus lifecycle automation and retention campaigns driven by behavioral signals, not calendar blasts.
Headless commerce platform
Headless Shopify / BigCommerce / custom commerce with AI wired in at PDP, search, and checkout — where it earns its place, not where the vendor slide said to put it.
Product content at scale
PDP generation, category-page drafting, and listing optimization against your brand voice and the SKU attribute data your PIM already holds. Shipped with a human-review gate.
Merchandising & category agents
Agent-assisted sorting, collection curation, and cross-sell recommendation against live conversion data. Plus the A/B harness to prove every change.
Customer support & returns copilots
Tier-one ticket resolution, returns triage, and order-status copilots on your actual order data. Handover to humans with full context when confidence drops.
Why most e-commerce agencies plateau.
Content sounded like ChatGPT. Paid looked like SaaS. Generic LLM PDPs tank brand voice and get caught in Google's low-quality filter. And a SaaS-playbook paid program built on lead-gen metrics bleeds cash when your actual metric is contribution margin per order. We scope both to commerce.
Nobody integrated to the PIM, the warehouse, or the ad accounts. AI that generates descriptions from a spreadsheet fails when the PIM updates. And attribution models that ignore the warehouse-level order truth are fiction. We integrate to sources of truth.
Support copilot hallucinated a policy. Paid campaign hallucinated an audience. Return-window hallucinations are credit issues. And a generic lookalike audience built on stale pixel data burns budget. We build with policy retrieval, real audience data, and confidence thresholds.
The attribution model was fiction. Most 'AI attribution' tools are regressions on top of a click-stream nobody trusts. We build on a warehouse layer with deterministic matching first, probabilistic on top — with assumptions documented.
03 Proof
E-commerce teams already operating
on what we built.
US · Medical Products E-commerce · Content + UX + Paid
Gauze Care
Redesigned the e-commerce and B2B ordering experience, ran the SEO and paid-media programs, plus a content AI pipeline that drafts category and product pages inside MLR review.
- +48%Organic sessions
- 3.1×B2B inquiries
- 100%MLR-compliant
APAC · DTC Brand · Lifecycle + Support AI
NDA · DTC Wellness Brand
Built the support and returns copilot now handling 54% of incoming tickets, plus the lifecycle automation and paid-media program driving 2.8x return on contribution margin.
- +54%Auto-resolved
- 2.8×CM ROAS
- +21ptsCSAT
How an engagement usually starts.
Week 0 — Scoping call (free). Forty-five minutes on your call, not ours. You describe the workflow that's bleeding time, the demand program that's plateaued, or the system that's stuck. We tell you which lever is the right first move, and roughly what shape the engagement would take.
Week 1 — Written scope. A one-page scope with the specific agent, workflow, or marketing program, the success metrics, the eval or measurement plan, and the cost. No 60-slide proposal.
Weeks 2–6 — Build. You see working output by the end of week 2, iterated weekly. Evals, analytics, or campaigns run against real production data from week 3. Your team joins the build reviews.
Week 6+ — Handover & operate. Full documentation ships to your repo, your CRM, your ad accounts. Your team runs it. We stay on for operate-and-improve retainer if you want us — many clients keep us for 18+ months. Many don't. Both are fine.
04 Questions E-commerce teams ask
Usually in this order.
Do you run both paid media and AI for DTC brands?
Yes. Performance marketing, SEO, and lifecycle on one side; content-at-scale, merch, and support AI on the other. Both feed the same growth model.
Do you work with Shopify, BigCommerce, or custom commerce?
All three. Shopify Plus, BigCommerce Enterprise, and custom Magento / headless. Platform choice is usually settled before we arrive.
Can AI generate product descriptions without killing brand voice?
Yes, with a voice harness and eval. Brand-voice model → retrieval over your PIM → draft → eval against brand rules → human review gate. We reject the 'just set it loose' pattern.
How do you handle Google's AI-content policies?
Every published page passes a quality eval before ship: uniqueness, factual grounding in the PIM, brand-voice consistency, E-E-A-T signals. We don't mass-publish un-reviewed LLM output.
What metrics do you optimize against?
Contribution margin per order, LTV-to-CAC, and repeat rate — not ROAS alone. We scope against the one the CFO is graded on.
Do you build recommendation engines?
Yes, on your warehouse data. Vector search over product embeddings + collaborative filtering on order history. Tuned against revenue-per-session, not CTR vanity metrics.
How long do e-commerce engagements take?
First production system (content or support): 4–8 weeks. Full re-platform with AI built in: 12–20 weeks. Paid programs activate in 2–3 weeks.
Your turn
Book the scoping
call.
Forty-five minutes, your agenda, no slides. You'll leave with a clear read on what the right first move is for your E-commerce team — and a rough shape for the first engagement if it is.