What challenges did The Estée Lauder Companies face before AI implementation?

Translating in-store scent consultation into digital commerce where customers struggle to choose fragrances online without sensory cues. Bridging the gap between consumer language and the brand's expert olfactive taxonomy.

What was the impact of the AI solution?

Reported improved conversion and high customer satisfaction. Research showed customers visit physical stores to discuss and try recommendations from the digital experience.

Source

GCPEvidence: Low40/100

Jo Malone London AI Scent Advisor

Use case typeConversational commerceUpdated Jun 13, 2026

Launched a conversational, AI-powered digital experience for fragrance discovery. Maps natural language to deep scent expertise for bespoke fragrance recommendations using Google Cloud AI.

Organization: The Estée Lauder Companies
Industry: Consumer & Food
Location: United Kingdom
Published: June 2026

Reported outcomes

Strategic outcomes

New product / capabilityLaunched a conversational, AI-powered digital experience for fragrance discoveryCustomer experience & trustImproved conversion and customer satisfactionCustomer experience & trustDrove in-store follow-up from digital recommendations

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: The Estée Lauder Companies, Jo Malone London
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Story

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

1Conversational Commerce
2Product Discovery
3Personalized Recommendations

Translating in-store scent consultation into digital commerce where customers struggle to choose fragrances online without sensory cues.
Bridging the gap between consumer language and the brand's expert olfactive taxonomy.

Built an interactive AI agent using Gemini models and Gemini Enterprise Agent Platform.
The agent asks customers natural-language questions, maps subjective descriptions to olfactive data, ranks fragrance candidates, and generates personalized explanations.
Google Cloud services including Cloud Run, Pub/Sub, Firestore, BigQuery, and Model Armor support processing, data foundation, and safety.

Technologies

Gemini Gemini Enterprise Agent Platform Cloud Run Pub/Sub Firestore BigQuery Model Armor

Reported improved conversion and high customer satisfaction.
Research showed customers visit physical stores to discuss and try recommendations from the digital experience.

Architecture

An interactive AI agent built with Gemini and Gemini Enterprise Agent Platform translates natural-language fragrance preferences into structured queries over Jo Malone London's olfactive taxonomy. Cloud Run services and worker pools with Pub/Sub handle continuous data processing, while Firestore and BigQuery provide operational and analytical data foundations. Model Armor enforces safety policies for nuanced beauty terminology and controlled generation ensures responses follow a precise format.

Sources & evidence1

Evidence: Low40/100Evidence strength