Product copy is a constant backlog
Your team can't keep pace with catalogue growth. New arrivals sit unlisted or with placeholder descriptions. Poor copy means poor rankings and poor conversion — every day costs you revenue.
£2M
Revenue scaled (Folk + Field, 2 quarters)
+22%
Repeat purchase rate after retention loop deploy
4,200
On-brand product pages shipped in 6 weeks (Lumen Retail)
[ Intro ]
Catalogue depth × personalisation = AI's real e-commerce advantage.
Most e-commerce brands are sitting on two untapped assets: a deep product catalogue they’ve never fully described, and a customer base they’ve never truly segmented.
Manual content teams can write maybe 50 product descriptions a week. AI content engines — trained on your brand voice, your category knowledge, and your customer language — produce thousands. Not generic filler. On-brand, SEO-structured, conversion-tested copy that ranks and sells.
The same principle applies to retention. You already have purchase history, browse behaviour, and email engagement data. AI-powered retention loops use that data to build individual pathways — automatically.
[ The problem ]
The hidden cost of doing e-commerce the manual way.
Growth in e-commerce is expensive when it runs on human bandwidth. Every new SKU needs copy. Every new customer needs a journey. Every return needs a response. Scale the catalogue or the customer list — and the bottlenecks multiply.
The brands winning in 2026 aren’t working harder. They’ve rebuilt the engine.
Retention is still break-fix
You have a welcome flow, an abandoned cart sequence, and maybe a win-back email. That's not retention — it's plumbing. You're leaving repeat purchase revenue on the table every month.
Customer support is burning your team
"Where's my order?" "Can I return this?" "What size should I get?" Your support team answers the same 30 questions on repeat. Every ticket costs you time and margin.
You can't personalise at scale
Segmentation takes hours in Klaviyo. You know your best customers behave differently, but you're sending the same campaigns to everyone.
At-risk customers disappear silently
By the time you realise a customer has churned, they're already shopping elsewhere. Without a churn prediction model, you're always reacting.
[ AI Plays ]
Five AI plays that move the needle in e-commerce.
We don't build AI for the sake of it. Every system we deploy has a named outcome and a measurable result.
AI Product Copy Engine
We train a custom content model on your brand guidelines and best-performing existing copy. The output: thousands of on-brand, SEO-structured product descriptions — produced in days, not months. Integrated directly with Shopify, WooCommerce, or your PIM.
Retention Loop System
Behavioural-trigger email and SMS sequences personalised per customer, not per segment. Purchase recency, category affinity, and browse signals feed a dynamic decision engine. Set up once, compound forever.
Churn Prediction Model
We build a churn risk score from your purchase history, email engagement, and support data. At-risk customers trigger automatic win-back sequences 30 days before they would have lapsed.
AI Customer Support Agent
A custom-trained AI agent handles order status, return requests, sizing questions, and product queries — 24/7, in your brand voice. Escalations routed to your team with full context.
SEO & GEO Content at Scale
AI-powered content clusters targeting high-intent buyer search terms — built to rank in Google and get cited by ChatGPT and Perplexity. One content engine. Two search channels.
[ How it works ]
How an e-commerce AI engagement works.
Discovery & Stack Audit (Week 1)
We map your current tech stack — Shopify/WooCommerce, Klaviyo, Gorgias, GA4 — and your biggest revenue leakage points. You receive a prioritised opportunity map ranked by ROI.
Build & Train (Weeks 2–5)
We design and build the agreed AI systems — trained on your data, integrated with your stack, tested against your benchmarks. No black boxes.
Deploy & Validate (Week 6)
Systems go live. We monitor the first 7–14 days intensively. Every output is checked against quality thresholds. Runbooks are written.
Compound & Optimise (Ongoing)
AI systems improve with data. Monthly performance reviews and system expansion keep the engine compounding. Most clients add a second or third AI play within 90 days.
We went from manually writing product descriptions to having a system that produces 200 a week at our exact brand standard. The retention lift was the real surprise — we saw it in the numbers within the first month.
London Property Group 3× Their Qualified Leads in 90 Days
↗ 3× qualified pipeline in 90 days
Vantage Hotels Lifts RevPAR 18% With AI Rate Engine
↗ RevPAR +18% in 6 months
Northgate Capital Builds Connected RevOps in 90 Days
↗ Net revenue retention +12%
Houseguest Cuts Itinerary Quote Time by 55% With AI Builder
↗ Time-to-quote down 55%
Lumen Retail Ships 4,200 Product Pages in 6 Weeks
↗ 4,200 pages in 6 weeks
E-commerce Fashion Brand Scales to £2M Revenue With AI-Powered Retention
↗ £2M ARR within 2 quarters
[ FAQ ]
Common questions.
Do you work with Shopify brands?
Yes. The majority of our e-commerce clients run Shopify or WooCommerce. We've also worked with custom-built platforms. Our AI systems integrate via API, so platform specifics rarely block us.
How quickly can you build a product copy engine?
From discovery to first batch of live copy, typically 3–4 weeks. The bottleneck is usually getting access to your brand guidelines, existing copy examples, and product data feeds — not the build itself.
Will AI copy sound like our brand?
Only if we train it correctly. We spend the first week of any content engagement doing brand voice training — analysing your best existing copy, interviewing your team, and running test batches until outputs are indistinguishable from human-written.
We already use Klaviyo flows — do we need this?
Standard Klaviyo flows are segment-based. AI-powered retention is individual: every customer gets a unique sequence based on their specific behaviour. The lift from moving from segment to individual is typically 15–30% on repeat purchase rate.
What is the minimum catalogue size for the copy engine?
We've run it for catalogues as small as 200 SKUs and as large as 50,000. The economics are strongest above 500 SKUs, but the brand voice training value applies at any size.
Ready to stop writing product pages manually?
Book a 30-minute fit call. We'll audit your current stack, identify your three biggest AI opportunities, and give you an honest answer on whether we can move the needle for your business.