Client Overview
Leading D2C E-commerce Brand
The Challenge
The client was experiencing a 78% cart abandonment rate on their existing Shopify store due to slow load times and a generic, unoptimized user journey. They needed a custom solution that could handle high traffic spikes and provide personalized product recommendations.
Our Solution
We migrated their frontend to a lightning-fast custom Next.js application, integrating directly with a Headless ecommerce backend. We implemented an AI recommendation engine built on user browsing patterns and integrated advanced cart recovery email sequences.
The Results
- 3x improvement in checkout completion rate
- 45% increase in average order value via AI upselling
- Page load speeds reduced from 4.2s to sub-second
- 120% increase in mobile conversion rates
From Shopify Template to Custom Revenue Machine
When this D2C brand came to us, they were doing decent revenue on Shopify — but they'd hit a ceiling. Their standard Shopify theme was slow, generic, and had zero personalization. Every visitor saw the same homepage, the same product ordering, and the same checkout flow regardless of their browsing history or purchase intent.
The numbers told the story: a 78% cart abandonment rate and a mobile bounce rate over 65%. For a brand spending ₹3L+ per month on Meta and Google Ads, this was a revenue leak they could no longer ignore.
Phase 1: Performance Foundation (Weeks 1-2)
We started by migrating the frontend to a custom Next.js 14 application with ISR (Incremental Static Regeneration). This alone dropped page load times from 4.2 seconds to under 800 milliseconds — a 5x improvement.
Key technical decisions:
- Image pipeline: All product images served via a custom optimization pipeline — WebP with AVIF fallbacks, responsive srcsets, and lazy loading below the fold
- Font strategy:
font-display: swapwith metric overrides to eliminate CLS from web font loading - Edge caching: Deployed on Vercel with aggressive edge caching for product pages. Dynamic prices updated via ISR every 60 seconds.
Phase 2: AI Recommendation Engine (Weeks 3-5)
The biggest conversion lever was personalization. We built a lightweight recommendation engine that tracked:
- Browse history (categories and price ranges viewed)
- Cart behavior (what was added, what was removed)
- Purchase history (for returning customers)
- Session context (time of day, referral source, device type)
The engine surfaced personalized product tiles on the homepage, product pages ("Customers also bought"), and the cart page ("Complete your look"). The upsell suggestions alone increased average order value by 45%.
Phase 3: Checkout & Recovery Optimization (Weeks 6-8)
The original checkout flow had 4 steps, required account creation, and had no express payment options. We rebuilt it as:
- Single-page checkout with real-time validation
- Guest checkout by default with optional account creation post-purchase
- UPI + Razorpay integration for one-tap mobile payments
- AI-powered cart recovery via WhatsApp (not just email) — triggered at 1 hour, 6 hours, and 24 hours
The WhatsApp recovery sequences converted at 23% (vs. 4% for email), making it the single highest-ROI feature in the build.
Results After 90 Days
The transformation was dramatic. With the same ad spend, the brand saw a fundamental shift in unit economics — more customers converting, spending more per order, and returning more frequently.
The checkout completion rate tripled. Mobile conversion rates jumped 120%. And the AI recommendation upsells paid for the entire project cost within the first two months.
"Vyarah didn't just build us a faster website; they built a revenue machine. The ROI from the AI recommendations alone paid for the project in the first two months."