4 weeks post-launch monitoring & optimization done · 47 → 11 third-party apps · Brand's 2-person e-commerce team fully trained on the new headless stack
Who we worked with
A Canadian direct-to-consumer (DTC) activewear brand generating $9.2M in annual online revenue, running their e-commerce platform on a heavily customized Shopify Plus store with 47 third-party apps bolted on — creating a fragile stack where every app update risked breaking checkout.
Their mobile experience was particularly painful: a 4.8-second average load time, a 6-screen checkout flow, and a 74% mobile cart abandonment rate. With no personalization beyond Shopify's default widget and a 180K-email subscriber list receiving the same blast every Tuesday, the brand was leaving an estimated $1.5M/year on the table from the mobile conversion gap alone.
| Metric | Before | After | Change |
|---|---|---|---|
| Mobile page load time | 4.8 seconds | 1.3 seconds | 73% faster |
| Cart abandonment (mobile) | 74% | 51% | 31% reduction |
| Average order value | $72 | $93 | 29% increase |
| Online sales (first quarter post-launch) | $2.3M quarterly baseline | $3.1M | 35% increase |
| Mobile revenue share | 38% of total | 54% of total | 42% increase |
| Third-party app dependencies | 47 apps | 11 apps | 77% reduction |
47 apps, a broken checkout, and $1.5M in mobile revenue left on the table
A fragile Shopify Plus stack accumulated over 5 years, a mobile experience that was hemorrhaging conversions, and a marketing team with no tool beyond a weekly email blast to 180K people who'd largely stopped opening it.
Fragile App Stack Breaking Checkout
47 third-party apps each injecting their own JavaScript into the storefront — loyalty programs, reviews, upsell popups, countdown timers, SMS marketing, and more. When Shopify pushed updates or an app developer changed their code, checkout broke. In the 6 months before engaging us, 4 checkout-breaking incidents each lasted 2–6 hours. One incident during a product launch cost an estimated $28K in lost sales over 4 hours.
4 checkout outages in 6 months · $28K single incidentMobile Experience Killing Conversions
Mobile loaded in 4.8 seconds — well above the 2-second threshold where most shoppers bounce. The checkout flow required 6 separate screens. Google PageSpeed mobile score was 29/100. Mobile traffic accounted for 67% of all visits but only 38% of revenue — a conversion gap estimated at $1.5M/year. The 6-screen checkout was a particular friction point for one-handed mobile shoppers.
67% of traffic · only 38% of revenue · $1.5M gapGeneric Shopping Experience for Every Visitor
Every visitor saw the same homepage, same product grid, and same "bestsellers" regardless of whether they were a first-time browser or a loyal customer who'd purchased 12 times. AOV had been flat at $72 for 2 years. The "recommended products" widget was Shopify's default algorithm — essentially showing the same popular items to everyone. Email open rates had declined from 22% to 14% over the prior year.
$72 AOV flat for 2 years · open rates fell to 14%High Return Rate Hurting Margins
The brand's return rate was 24% — significantly above the DTC apparel average of 18%. Most returns were size-related: customers ordering multiple sizes and returning what didn't fit. Without fit prediction, the brand had no way to guide sizing at the point of selection. Each return cost approximately $12 in processing and reshipping, totaling roughly $530K/year in return-related costs.
24% return rate · $530K/year in return costsFive phases, headless frontend to AI personalization
A 40-week delivery — full audit through phased traffic rollout — with A/B testing on every major change (headless vs. legacy, 2-screen vs. 6-screen checkout, AI vs. Shopify default) before committing to 100% traffic.
Audit & Architecture
Wks 1–4Headless Frontend Build
Wks 4–16AI Personalization Engine
Wks 12–28Marketing Automation
Wks 20–32A/B Testing & Rollout
Wks 30–40- Full app stack audit — documented all 47 apps; found 18 unused/redundant, 12 replaceable by native Shopify features, 6 consolidatable into custom-built alternatives; target: 11 essential integrations only
- Built the new storefront using Shopify Hydrogen (React + Remix) with server-side rendering for SEO, Cloudflare CDN for edge caching, and WebP image optimization with lazy loading
- Designed a mobile-first 2-screen checkout: cart + shipping in one view, payment + confirmation in the second; Apple Pay and Google Pay as primary default payment options (one-tap)
- Migrated all 11 essential third-party integrations to API-based connections instead of injected JavaScript — payments, shipping, returns
- Built recommendation engine on AWS SageMaker, trained on 2 years of data: 126K customer profiles, 680K browsing sessions, 290K orders, and 68K returns with size and reason data
- 4 personalization surfaces: homepage product ranking by affinity, "Complete the look" outfit recommendations, size prediction showing "We recommend size M based on your history" at point of selection, and personalized product blocks in email
- Size prediction alone reduced return rate from 24% to 17% — $155K saved annually in processing and reshipping costs
- Replaced single weekly email blast with 14 behavior-triggered campaign flows via Klaviyo: browse abandonment (1hr trigger), cart recovery (2hr + 24hr + 72hr), post-purchase cross-sell (day 3 and day 14), win-back (45 days inactive)
- Added restock reminders based on product lifecycle — e.g., leggings average 8 months between repurchases — and loyalty milestone rewards and personalized new arrival alerts by category affinity
- Email open rates recovered from 14% to 31%; email revenue per recipient grew 3.2×; quarterly email revenue from $68K to $218K
- A/B tested every major change: headless vs. legacy theme (4 weeks, 50/50 split), 2-screen vs. 6-screen checkout, AI recommendations vs. Shopify default — all tests showed statistically significant improvements before full rollout
- Phased traffic rollout: 20% (week 34) → 50% (week 36) → 100% (week 38) with no customer-facing disruption
- 4 weeks of post-launch monitoring and optimization; trained the brand's 2-person e-commerce team on the new headless stack, Klaviyo flows, and SageMaker dashboards
Custom models — size prediction + product recommendations
126K profiles · 680K sessions · 68K returns
Weekly blast → behavior-triggered · open rate 14% → 31%
Every choice made for DTC commerce at speed
| Technology | Role | Why This Choice |
|---|---|---|
| Shopify Hydrogen (React + Remix) | Headless frontend | Native Shopify headless framework; SSR for SEO and sub-second load times |
| Shopify Plus (Storefront API) | E-commerce backend | Proven commerce infrastructure for inventory, orders, and payments — retained without disruption |
| AWS SageMaker | AI personalization engine | Custom recommendation and size prediction models trained on 2 years of behavioral data |
| Cloudflare | CDN + edge caching | Global edge network delivering sub-second load times; key to PageSpeed 29 → 84 |
| Klaviyo | Marketing automation | Deep Shopify integration; 14 behavior-triggered flows replacing single weekly blast |
| Node.js | Custom microservices | Personalization API and data sync between SageMaker models and Shopify storefront |
| PostgreSQL (AWS RDS) | Customer data platform | Unified customer profiles merging Shopify purchase data with browsing and return behavioral data |
| Google Analytics 4 + Looker | Analytics & reporting | E-commerce tracking and custom dashboards for the brand's 2-person marketing team |
Results that transformed the brand
Across mobile performance, revenue, personalization, and returns — all delivered in 40 weeks with A/B-validated changes and a phased rollout that reached 100% traffic with zero customer disruption.
First Quarter
Annually
Per Quarter
Dependencies Removed
6 engineers, mobile-first DTC delivery
A specialist team covering solution architecture, React headless frontend, Node.js backend microservices, ML engineering, and quality — with post-launch training built into the engagement for the brand's internal e-commerce team.
Solution Architect
App stack audit (47 apps), headless architecture design, AWS + Shopify target state, personalization and marketing automation platform design
Backend Developer × 2
Node.js personalization API microservices, SageMaker data pipeline, PostgreSQL unified customer data platform, Klaviyo and Shopify integrations
Frontend Developer
Shopify Hydrogen (React + Remix) headless storefront, mobile-first 2-screen checkout, Apple Pay / Google Pay integration, Cloudflare CDN optimization
ML Engineer
AWS SageMaker recommendation models, size prediction trained on 68K returns, behavioral data pipeline from 680K browsing sessions and 290K orders
QA Engineer
A/B test design and analysis (headless vs. legacy, 2-screen vs. 6-screen, AI vs. default), phased traffic rollout monitoring, post-launch optimization
40-Week Full Delivery
A/B validated before every rollout · 20% → 50% → 100% phased traffic · Brand's 2-person team trained on full new stack
What the client said
"We were spending $4,200/month on apps that were literally breaking our checkout. I-Verve stripped out the bloat, rebuilt our mobile experience properly, and the AI recommendations are doing things our team couldn't do manually with twice the headcount. The size prediction alone saved us a small fortune in returns. We went from dreading product launches to being excited about them again."
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