AI automation that sounds like your brand, not like slop
Product content, support triage, email personalisation for DTC and multi-brand retailers. Brand-voice guardrails, human-in-the-loop where it matters. $3,000/mo.
Who this is for
DTC or multi-brand ecommerce ops director doing $2M to $30M, where product content is slow, support spikes during sales, and email personalisation is weak.
The pain today
- Product content is slow to ship for new SKUs
- Support tickets spike during sales and overwhelm team
- Email personalisation is generic despite rich customer data
- AI content from other attempts sounded off-brand
- Gorgias AI and Klaviyo AI covered some but not all of the need
The outcome you get
- AI automations for ecommerce ops on $3,000/mo retainer
- Brand-voice-preserving product content at scale
- Support triage with drafts matching your tone
- Email personalisation using unified customer data
- Costs per automation tracked and optimised monthly
Highest-ROI AI automations for ecommerce
Three places deliver clear ROI. Product content — LLM drafts descriptions, bullet points, and SEO metadata from structured product data (specs, category, brand positioning). Human reviews before publish. Cuts content time 60 to 80 percent. Support triage — LLM categorises and drafts first-response for every ticket. Human agent reviews and sends. Cuts handle time 30 to 50 percent. Email personalisation — LLM generates segment-specific variations of campaigns. Marketer reviews variants. Lifts open and click rates meaningfully. Each is 2 to 4 weeks of work.
Product content generation that converts
Generic AI content sounds like AI content. The fix: brand-voice system prompts based on actual brand guidelines and top-performing existing copy. Structured product data feeds the prompt (category, features, benefits, keywords). LLM drafts; human reviews and edits. Over time, the prompts improve based on what humans edit. Result: product content that converts like hand-written copy for a fraction of the cost. I have built these systems for content-heavy platforms; the pattern applies to ecommerce directly.
Support triage plus on-brand response drafting
Most ecommerce support issues are repeatable — shipping questions, return requests, product questions, discount codes. LLM reads incoming ticket, categorises, and drafts a response using your brand voice and policy. Agent reviews, edits if needed, sends. For simple categories (shipping status), LLM suggestion often sends with minimal edit. For complex (complaints, custom requests), LLM triages priority but agent writes response. The system learns from agent edits over time. Reduces support cost without replacing human agents.
Pricing and engagement model
$3,000/mo retainer. Covers AI integration, prompt engineering, monitoring, and iteration. 14-day money-back guarantee. Cancel anytime. 100 percent code ownership under Work Made for Hire. LLM API costs pass through. For ecommerce with heavy content or support volume, API costs can reach $500 to $2,000/month — cost optimisation (prompt compression, model routing, caching) is part of the monthly work. You own LLM provider accounts directly. I never hold client keys.
Case: Instill — structured prompt library applied to brand voice
I built Instill as a self-initiated AI skills platform — structured prompts work across any AI tool. Current state: 30+ active users, 1,000+ skills saved, 45+ projects powered. Stack: Next.js 16, React 19, TypeScript, PostgreSQL, Vercel, MCP Protocol. The structured-prompt pattern transfers directly to ecommerce brand voice — a library of brand-voice prompts (hero copy, product descriptions, email subject lines, support responses) that your marketing team iterates on without touching code. Brand voice becomes structured, shareable, and continuously improving.
When a plug-and-play tool (Gorgias AI, Klaviyo AI) is enough
Gorgias AI handles basic support triage if your team already uses Gorgias. Klaviyo AI handles basic email personalisation if you are a Klaviyo user. Shopify's Magic handles basic product content. For brands with simple needs and already-deep integration, these tools cover most cases at low monthly cost. My target AI clients are ecommerce operators where brand voice, customisation, or integration beyond what tools offer matters. If your need is covered by platform AI, staying with the platform is the right call.
Recent proof
A comparable engagement, delivered and documented.
A prompt library that works with every AI tool
A home for your best AI prompts. Save them once, then use them in Claude, Cursor, or any AI tool you work with. No more copy-paste.
Frequently asked questions
The questions prospects ask before they book.
- How do you preserve brand voice?
- System prompts built from your actual brand guidelines, top-performing existing copy, and explicit do-not-use patterns. For brands with rich voice documentation, prompts capture tone, cadence, and vocabulary. For brands without formal voice docs, we extract voice from your best existing content and iterate. Human review catches drift; prompts update based on edits. Over 2 to 3 months, output quality often matches or exceeds mid-level copywriter work for product content and email — because the brand voice is encoded explicitly.
- What are the guardrails on product content?
- Structured data feeds only — LLM cannot invent facts about products. Categorical constraints (never claim unsupported health benefits, never promise specific outcomes in supplements, etc) encoded as system rules. Human review always before publishing. Output flagged for review if it touches sensitive claim categories. For brands in regulated categories (supplements, skincare, medical), legal-team review for first 100 AI-generated pieces to confirm compliance.
- How do you integrate with Shopify?
- Shopify Admin API for product data read and write. For content generation, we pull product data, generate content, human reviews, content writes back to product. For support, integrates with Shopify Inbox or Gorgias (whichever you use). For marketing, integrates with Klaviyo or Mailchimp. Shopify's native AI (Magic) can coexist — custom retainer work targets needs Shopify AI does not cover.
- What does it cost in API fees?
- Typical ecommerce: $200 to $2,000/month in LLM API costs depending on volume. Product content at $0.01 to $0.05 per product. Support drafts at $0.001 to $0.01 per ticket. Email variants at $0.05 to $0.50 per segment-variant. Cost optimisation is part of the retainer — caching common outputs, compressing prompts, routing simple tasks to cheaper models. I track cost per outcome monthly; we kill automations that are not paying back.
- Can you help with evals?
- Yes. Brand-voice evals (golden set of ideal outputs vs actual outputs scored by humans). Accuracy evals for product content (factual correctness against source data). Support response evals (would the agent send this as-is?). Each gets a golden set and a monthly review. For brands serious about AI quality, evals become a shared artifact that improves over time. Without evals, AI quality drifts silently — with evals, regressions are caught early.
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