AI Automations for E-commerce & D2C
Order queries, delivery status and return requests handled one message at a time.
AI automation replaces repetitive operational work — lead routing and qualification, follow-up sequences, data entry, reporting and content pipelines — with systems that run continuously and escalate to a human when judgement is required. For a D2C or e-commerce brand, the work is judged on contribution margin per order, after shipping, returns and ad cost. Automated status responses from real order data, with returns triaged and escalated by policy.
What is costing you money today
Order queries, delivery status and return requests handled one message at a time.
Optimising ads to purchase events reported by a browser pixel that ad blockers and iOS have already broken, then scaling on numbers that overstate revenue.
What changes once this is in place
Automated status responses from real order data, with returns triaged and escalated by policy.
How e-commerce & d2c actually buys
Minutes to days for impulse categories, weeks for considered ones — and heavily concentrated into a few sale periods a year.
- The unit of value
- contribution margin per order, after shipping, returns and ad cost
- The common mistake
- Optimising ads to purchase events reported by a browser pixel that ad blockers and iOS have already broken, then scaling on numbers that overstate revenue.
- What we do instead
- Server-side tracking with order value and margin passed through, reconciled weekly against what the payment gateway actually settled.
What it has to talk to
A build for a D2C or e-commerce brand is mostly integration work. These are the systems we expect to exchange data with:
- Shopify / WooCommerce
- Payment gateway
- Logistics & courier APIs
- Meta CAPI & Google Enhanced Conversions
- Klaviyo / WhatsApp
The words your buyers actually use
Generic service copy loses to copy written in the vocabulary of the vertical. These are the terms that carry intent here, and the ones the pages we build are structured around:
- cash on delivery
- free shipping threshold
- return policy
- size guide
- abandoned cart
- average order value
The rules this sits under
India's Legal Metrology rules on displayed pricing and country of origin; consumer protection rules on returns; FTC substantiation for claims in the US; VAT display requirements in the UAE.
What you get
- Process audit — The repetitive work in your operation, with volume and time cost attached, ranked by what automation is worth in each case.
- Automation design — Triggers, steps, decision points, escalation rules and failure handling — documented before anything is built.
- Build and integration — Implemented against your real systems — CRM, ERP, WhatsApp, store, spreadsheets — rather than in a demo environment.
- AI components where they help — Extraction, classification, summarisation and conversation, used where a rule genuinely cannot do the job. Rules are cheaper and more predictable where they can.
- Retrieval over your data — Grounding answers in your own documents and records, so responses are specific to your business rather than generic.
- Human-in-the-loop — Review queues for low-confidence decisions, with the interface for a person to correct and approve.
- Monitoring and logging — Every run recorded, failures alerted, and a dashboard showing what the automations did this week.
- Documentation and training — How each automation works, how to pause it, and what to do when it misbehaves — written for your team.