Case Study

Reformation increased Revenue by 4% - with Zoovu

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Customer: Reformation Segment: B2C Industry: Fashion, Luxury & Lifestyle Go-live: 2 weeks Experiences: Recommendations
The Challenge

Improving product discovery for a fast-moving, data-driven DTC fashion brand

Reformation, a dynamic online-first direct-to-consumer fashion brand known for its best-in-industry sustainability outcomes, super-fast supply chain, extensive product catalog, and data-driven merchandising model sought an AI-based solution to improve product discovery online.

Their goal was to support their business strategy by leveraging AI technology. Key requirements included a solution that could be swiftly and seamlessly implemented, offering both immediate impact and compatibility with their long-term AI strategy. Zoovu's Composable AI approach gave them the flexibility to experiment and achieve tangible business results.

The Solution

AI-personalized recommendations on Product Detail Pages — live in 2 weeks

Zoovu deployed a sophisticated AI model to personalize the highly trafficked Product Detail Pages. Front-end event tracking ran for approximately one week to gather the minimum data required to train the customer's AI model before go-live.

The HRNN model was trained with the optimal goal of maximizing revenue. Zoovu created and rendered recommendation carousels seamlessly on the website for the test. The performance A/B test ran in the US market, with Zoovu Recommendations present on Product Detail Pages only.

  • ~1 wkFront-end event tracking to gather training data
  • 2 wksTotal time to go-live
  • 3 wksTo reach statistical significance
The Results

A measurable revenue lift over SFCC Einstein

During the test, Zoovu delivered a +4% lift in Revenue Per User for the group exposed to Zoovu recommendations, compared to the Salesforce Commerce Cloud (SFCC) Einstein recommendations.

+4%
Revenue Per User
2 wks
Go-Live Period
3 wks
To Statistical Significance

KPI lift with Zoovu Recommendations

  • +4%Revenue Per User vs. SFCC Einstein recommendations
Products Used

Zoovu Recommendations

A composable AI recommendations engine that personalizes product discovery at the individual level, trained to maximize revenue and deployed seamlessly into existing site experiences.

Simple integration
Dynamic experiences
Composable AI
The Takeaway

For fashion brands ready to outperform incumbent recommendations

Off-the-shelf recommendation engines leave revenue on the table. This DTC fashion brand proved that a composable, revenue-optimized AI model, live in just two weeks, can meaningfully outperform established incumbents and deliver measurable impact fast.

Ready to outperform your existing recommendations?

See how Zoovu Recommendations helps fashion and lifestyle brands replace off-the-shelf engines with composable AI and drive measurable revenue lifts fast.

Book a demo with Zoovu