E-commerce AI Recommendations DTC

A 340% AOV Lift for a DTC Storefront

How an AI recommendation engine and a rebuilt storefront transformed Trove's commerce metrics in 90 days.

About the Client

A 340% AOV Lift for a DTC Storefront

Trove had strong products and a storefront that hid them. We were brought in to fix discovery, speed, and conversion — and to do it fast.

The Challenge

Product discovery was poor, pages were slow, and checkout leaked customers. Average order value had plateaued despite healthy traffic.

Our Approach

We rebuilt the storefront on Next.js for speed and merchandising control, integrated Algolia for instant search, and trained an AI recommendation engine on real purchase behaviour.

The Solution

A faster, smarter storefront with contextual recommendations and a friction-free checkout — shipped and measured against a clear baseline.

Results

Average order value rose 340% and conversion more than doubled within the first 90 days post-launch.

Brought in for a storefront rebuild and got a genuine growth partner. They measured everything, shipped fast, and the results spoke for themselves.

Priya Sharma
VP Product, Trove
Tech Stack

What we used

Next.js Shopify TypeScript Algolia Vercel OpenAI API

Building Something
Data-Intensive?

We've solved hard engineering problems before. Tell us what you're building and we'll tell you honestly if we can help.