Case Study Showcase

Retail Giant Transforms Customer Experience at Scale

Personalized Shopping Experiences with Generative AI

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Company Profile

A global retail leader with 500+ stores and a massive online presence.

Industry

Retail & E-Commerce

Region

North America & Europe

About the Client

The client is a Fortune 500 retailer with a footprint spanning over 500 physical locations and a multi-billion dollar e-commerce platform. For decades, they have been at the forefront of the retail industry, but in recent years, they faced a critical hurdle: how to bridge the gap between their massive physical inventory and the rapidly shifting, highly personalized demands of the modern digital shopper.

Conversion Rate Increase

Stores Integrated

0M+

Daily Active Users

Challenge

The primary challenge was the fragmentation of customer data across dozens of legacy systems. Online behavior was disconnected from in-store purchase history, making it impossible to create a unified customer profile. When users visited the website, they were met with static product grids and search results that didn't reflect their current intent.

The client needed a way to ingest millions of data points—from clickstreams to inventory levels—and deliver a hyper-personalized response in milliseconds.

The fragmentation of the digital ecosystem created several core business risks:

Siloed customer data across disparate online and offline channels.
Inability to process and act on real-time behavioral signals.
Generic search results leading to high bounce rates and abandonment.
High operational costs for manual merchandising and curation.

To overcome these hurdles, the client required a transformative approach to data orchestration and real-time intelligence.

The Solution

Enterprise RAG Architecture

WebbyButter engineered a pioneering Retrieval-Augmented Generation (RAG) architecture tailored for retail scale. We built a real-time data orchestration layer that unifies customer interactions from mobile, web, and point-of-sale systems into a high-performance vector database. The AI engine uses this data to drive a natural language search experience—allowing customers to search for "outfits for a summer wedding in Tuscany" and receive a curated, inventory-aware selection immediately.

The Outcome

Measurable Business Impact

Within the first quarter of deployment, the client saw a 45% increase in conversion rates for users interacting with the AI personal shopper. By automating the merchandising process, the team saved over 60% of the time previously spent on manual product tagging and curation.

Revenue Uplift

Reduction in Merchandising Time

0/10

Customer Satisfaction Score

"WebbyButter's AI solution didn't just improve our metrics; it fundamentally changed how we understand and serve our customers."

CTO, Global Retail Brand

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