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▪ DTC LUXURYUS LUXURY DIRECT-TO-CONSUMER

TURNING LUXURY SHOPPING INTO AI DISCOVERY.

Connected product data, category content and premium shopping intent to increase visibility across AI shopping assistants.

PRIMARY OUTCOME
88
SHOPPING ASSISTANT CITATIONS
GEO · LUXURY COMMERCE

Strengthened product entities, category relevance and recommendation content to earn citations across AI-assisted shopping journeys.

▪ THE PROJECT

MAKING PREMIUM PRODUCTS DISCOVERABLE IN AI SHOPPING

The luxury DTC brand had a strong product catalog, but its premium products were not consistently appearing when shoppers asked AI systems for recommendations.

Luxury purchase journeys involve more than product names. Shoppers compare materials, craftsmanship, design, price, occasion and brand positioning before choosing a premium product.

We rebuilt the search experience around product entities, premium attributes, collection architecture and recommendation intent, creating clearer relationships between what a product is, who it suits and why a shopper should consider it.

PROJECT SPECIFICATION
INDUSTRYUS Luxury Direct-to-Consumer
PRIMARY SERVICEGenerative Engine Optimization
FOCUS AREASProduct SEO · Category SEO · GEO · Shopping Search
TIMELINEOngoing Growth Program
PRIMARY GOALIncrease AI shopping citation visibility
▪ THE SEARCH GAP

PREMIUM PRODUCTS. FRAGMENTED SHOPPING SIGNALS.

The company had strong offerings, but organic and AI search presence fell short because the architecture was not built to scale.

01
PRODUCT DISCOVERY

SHOPPERS SEARCHED BY ATTRIBUTES

Luxury shoppers searched by material, craftsmanship, design, finish and use case rather than relying only on product or collection names.

02
RECOMMENDATION INTENT

THE DECISION NEEDED CONTEXT

Queries such as best luxury gift, designer handbag for travel or premium skincare for dry skin required richer product context.

03
AI SHOPPING

PRODUCTS NEEDED TO BE RECOMMENDABLE

AI assistants needed clear product identity, attributes, pricing, availability and supporting context to confidently include premium products in recommendations.

KEY INSIGHT

The opportunity was not more product content. It was making premium product information easier to compare, understand and recommend.

▪ THE APPROACH

BUILD THE PRODUCT STORY. OWN THE RECOMMENDATION.

We combined technical SEO with scalable search expansion: build the technical foundation first, map intent, and scale the assets that drive business value.

01
PRODUCT SEO

STRUCTURE EVERY PRODUCT

Clarified product identity, materials, specifications, craftsmanship and use cases across priority luxury products.

02
CATEGORY SEO

BUILD PREMIUM COLLECTIONS

Organized categories around luxury product types, shopping intent and commercially relevant attribute searches.

03
SHOPPING INTENT

ANSWER THE BUYING QUESTION

Mapped recommendation, comparison, gift, occasion and “best for” searches to relevant products and collections.

04
GEO

MAKE PRODUCTS CITABLE

Strengthened product entities and answer-ready content so AI shopping systems could interpret and surface relevant products.

▪ WHAT WE DID

FROM TECHNICAL FIXES TO SCALABLE SEARCH GROWTH

Rather than generic tactics, we executed disciplined workstreams engineered for compounding organic and AI search visibility.

▪ THE RESULTS

Main: large 88 metric → result heading → short description.

The new product, category and recommendation architecture increased visibility across AI-assisted shopping experiences.

PRIMARY 6-MONTH BUSINESS OUTCOME
88
SHOPPING ASSISTANT CITATIONS
SHOPPING ASSISTANT CITATION COVERAGECOMPOUNDING TRAJECTORY
Month 1 (Audit)Month 2 (Fixes)Month 3 (Programmatic)Month 4 (Indexation)Month 5 (Expansion)Month 6 (88 Outcome)
PRODUCT-LED
AI DISCOVERY

Strengthened product-level visibility by making key attributes, specifications and use cases easier to interpret.

CATEGORY-LED
SHOPPING RELEVANCE

Connected luxury collections with the product and attribute searches shoppers used during discovery.

RECOMMENDATION-LED
AI SHOPPING

Expanded visibility across gift, comparison, occasion and “best for” shopping questions.

CAMPAIGN PERFORMANCE SNAPSHOT

CAMPAIGN TIMELINE6 Months
SHOPPING ASSISTANT CITATIONS88
AI DISCOVERYPRODUCT-LED
SHOPPING RELEVANCECATEGORY-LED
GROWTH SIGNALVERIFIED
▪ THE BUSINESS IMPACT
The biggest change was seeing our products become part of the recommendation conversation, not just the traditional search results.
US LUXURY DIRECT-TO-CONSUMER MARKETING LEAD

WHAT CHANGED

The combination of stronger product architecture, cleaner indexation, and improved shopping signals created a scalable foundation for product discovery.

  • PRODUCT DISCOVERY: Premium products gained stronger visibility across recommendation-led shopping queries.
  • AI VISIBILITY: The brand achieved 88 shopping assistant citations across priority product searches.
  • PRODUCT CONTEXT: Product attributes, categories and use cases became more consistently connected across the site.