## How Rhone Optimized Google Shopping Performance with Stylitics Catalog Enrichment

## **Challenge**

Rhone initially partnered with Stylitics to bring their curated in-store merchandising experience to their e-commerce platform. While AI-powered outfitting delivered exceptional results—including a [39% increase in AOV](/content/resources/case-studies/rhone/index.html)—Rhone recognized a further opportunity to optimize the foundation of their e-commerce engine: product metadata.

The core challenge was ensuring premium products remained visible in a competitive SEM landscape. Existing metadata lacked the granular, shopper-centric language required to match evolving search intent, potentially limiting the reach of their high-performance catalog.

**Key Objectives:**

1. **Bridge the Intent Gap:** Align product metadata with the actual natural language used by shoppers in search engines.

2. **Scale Without Overhead:** Find an enterprise-grade solution to enrich thousands of SKUs without the manual burden of internal tagging or experimental R&D projects.

3. **Prove Incremental Lift:** Quantify the direct performance impact of enrichment on Google Shopping metrics through a rigorous, isolated test.

## **Solution**

Stylitics implemented a controlled A/B test to evaluate the performance lift generated by enriched metadata delivered via Rhone’s Google Merchant Center (GMC) instance. By choosing a proven, production-ready platform over an internal “build” project, Rhone bypassed the 12–18 month learning curve typical of in-house AI experiments.

**Test Methodology:**

- **Randomized Product Split:** 96% of Rhone’s product catalog was split into test (50%) and control (50%) groups.

- **Daily Enrichment:** The test group received Stylitics’ enriched metadata while the Control group remained unchanged.

- **Balanced Distribution:** Groups were balanced by attribute distribution to eliminate bias and ensure a fair comparison.

- **Unified Campaign Management:** Both groups ran within a single GMC campaign using identical bidding strategies and budgets to isolate the impact of enrichment.

> "Stylitics provides the production infrastructure we need to bridge the gap between our premium product catalog and actual shopper intent. Moving to AI Catalog Enrichment delivered a +16.3% lift in CTR and a +4.5% increase in ROAS on Google Shopping by aligning our metadata with how shoppers actually search. This is proven, scalable intelligence that ensures our products are discoverable at every touchpoint." — Sally Pullman, Vice President of Ecomm & Digital, Rhone

## **Results**

The test confirmed that enriched metadata results in a better match to shopper intent, driving higher-quality traffic and a significant lift in ROAS.

**Performance & Efficiency Impact:**

- **Significant CTR Lift:** Enriched listings produced higher quality clicks, driving a **+16.3% increase in CTR** despite lower overall impressions.

- **Conversion Growth:** High-intent traffic led to a **+3.5% lift in CVR** as well as down funnel volume growth with a **+3.1% increase in total conversions** and a **+4.7% increase in Conversion Value.**

- **Improved ROAS:** Efficiency gains led to a **+4.5% increase in ROAS**, proving that enrichment more than pays for itself through higher-quality shopper matching.

- **AOV Lift:** Downstream metrics showed a **+1.5% increase in AOV,** reflecting increased basket value.

## Looking Ahead

Rhone’s expansion into catalog enrichment demonstrates the power of treating AI as a strategic, enterprise-grade investment rather than a one-off experiment. By transforming raw data into high-intent signals, Rhone has not only boosted immediate performance but has future-proofed its catalog for the next generation of AI-driven discovery.

[Download the case study.](/content/wp-content/uploads/2026/04/Rhone-x-Stylitics-Catalog-Enrichment-Case-Study.pdf)