How Kendra Scott Captured 5% of Traffic From AI Search — An E-Commerce GEO Blueprint

A Jewelry Brand Wrote the E-Commerce GEO Playbook

While most e-commerce brands are still debating whether Generative Engine Optimization matters, Kendra Scott has already proven it does. The Austin-based jewelry retailer did not just experiment with GEO. They went all in, and the results are reshaping how the industry thinks about AI search.

Working with agency partner DEPT, Kendra Scott launched one of the most ambitious GEO programs in e-commerce history: 8,000 new thematic landing pages designed specifically to capture traffic from AI-driven and conversational search queries. The results speak for themselves, and they offer a detailed blueprint for any e-commerce brand serious about winning in the age of AI search.

The Kendra Scott Strategy: 8,000 Pages That Changed Everything

The Insight

Kendra Scott's marketing team recognized a critical shift: consumers were no longer searching for "gold necklace" or "drop earrings." Instead, they were asking AI engines questions like "What jewelry should I wear to a summer wedding?" or "Best gifts for mom under $200" or "Trendy everyday necklaces that do not tarnish."

These conversational, intent-rich queries were fundamentally different from the keyword-based searches that traditional e-commerce SEO targets. They required a fundamentally different content strategy.

The Execution

Working with DEPT Agency, Kendra Scott created 8,000 new thematic landing pages, each targeting a specific conversational query cluster. These were not thin doorway pages stuffed with keywords. They were rich, curated content experiences that combined:

• Editorial styling advice matched to specific occasions and contexts
• Curated product collections organized by theme, occasion, and price point
• Detailed product information including materials, sizing, care instructions, and styling tips
• User-generated content featuring real customer photos and reviews
• FAQ sections answering the follow-up questions AI engines anticipate

Each page was built to answer the full scope of a conversational query, not just match a keyword.

The Results

The results of this initiative exceeded expectations on every metric:

Let those numbers sink in. In less than a year, a single GEO initiative generated 5% of all web traffic, and the AI Copilot integrated into their shopping experience now influences 6% of total e-commerce sales. Year-over-year revenue from AI interactions grew by 160%.

Beyond Kendra Scott: How Other Brands Are Winning

Kendra Scott is the most visible e-commerce GEO success story, but they are not the only brand proving the model works. Two other case studies reveal how different approaches to GEO can drive results across different product categories.

Cetaphil: Owning the Symptom-Driven Search

Cetaphil, the skincare brand owned by Galderma, took a different approach to GEO. Instead of creating thousands of landing pages, they focused on owning the conversational queries that lead to skincare purchases.

The insight: Consumers do not search for "moisturizer with ceramides." They ask AI, "What should I use for dry, sensitive skin that breaks out in winter?" Cetaphil restructured their content strategy around these symptom-driven searches.

Key tactics:

• Created content addressing specific skin concerns and conditions rather than product features
• Partnered with influencer Nara Smith for authentic, educational content that AI engines could reference
• Built a knowledge base of dermatologist-backed answers to common skincare questions
• Structured product pages with symptom-to-solution mapping

The result: Cetaphil's products began appearing consistently in AI responses to skincare queries, with their content cited as authoritative dermatological advice rather than marketing material.

Batteries Plus: The AI Citation Audit Approach

Batteries Plus, a specialty retailer with over 700 locations, took yet another approach. Their strategy centered on understanding exactly how AI engines currently perceive and present their brand, then systematically improving those perceptions.

Key tactics:

• Audited AI citations: Systematically queried every major AI platform to understand where Batteries Plus appeared, where it did not, and what information was being cited
• Updated knowledge bases: Ensured their Wikipedia page, Better Business Bureau profile, and Google Business listings contained accurate, comprehensive, and current information
• Reddit engagement: Launched a genuine community engagement strategy on Reddit, where team members provided helpful advice on battery and lighting questions
• Local SEO integration: Combined GEO with local search optimization to appear in AI answers for location-specific queries

The result: While Batteries Plus reported that only about 1% of their referral traffic currently comes from AI sources, they noted the growth rate is significant and accelerating. Their proactive approach positions them to capture this traffic as AI search volume continues its exponential growth.

Comparing the Three Approaches

The key takeaway: there is no single right approach to e-commerce GEO. The best strategy depends on your product category, catalog size, budget, and competitive landscape. But all three approaches share common principles: structured content, authoritative information, and systematic measurement.

The 5-Step E-Commerce GEO Blueprint

Drawing from these case studies and dozens of other e-commerce GEO implementations, here is a step-by-step blueprint any online retailer can follow.

Step 1: Map Your Conversational Query Landscape

Before creating any content, understand exactly how consumers are asking AI about your product category.

How to do it:

• Query ChatGPT, Gemini, Perplexity, Claude, and Copilot with 50-100 variations of questions about your products
• Document which brands appear in responses and why
• Identify query clusters: occasion-based ("gifts for"), problem-based ("best for dry skin"), comparison-based ("X vs Y"), and intent-based ("affordable", "luxury", "everyday")
• Map your product catalog against these query clusters to identify gaps

Output: A query matrix showing every conversational query cluster relevant to your products, which competitors currently own each cluster, and where your opportunities are.

Step 2: Audit Your Current AI Presence

Once you understand the query landscape, assess your current visibility.

Key questions:

• For how many target queries does your brand appear in AI responses?
• Is the information AI presents about your products accurate?
• Which competitors are cited most frequently and for which query types?
• What content sources are AI engines citing (your site, reviews, Reddit, press)?

Output: A scorecard showing your AI Share of Voice, citation accuracy rate, and competitive gaps.

Step 3: Build Your Content Architecture

Design a content strategy that maps directly to the conversational queries you identified in Step 1.

Content types to create:

Critical rules for content:

• Lead with facts, not marketing copy
• Include specific prices, measurements, ratings, and specifications
• Structure with question-based headings that match conversational queries
• Add FAQ schema to every page
• Include comparison tables wherever relevant

Step 4: Amplify Your Authority Signals

Content alone is not enough. AI engines need to see your brand validated across multiple independent sources.

Priority actions:

1. Generate 100+ detailed reviews on platforms AI trusts (G2, Trustpilot, Reddit, category-specific review sites)
2. Earn press coverage in publications that AI cites (Wirecutter, industry trade publications, mainstream media)
3. Update all knowledge base entries (Wikipedia, Google Business Profile, BBB, Crunchbase)
4. Build genuine Reddit presence through helpful community participation
5. Partner with credible influencers who create substantive, educational content (not just sponsored posts)

Step 5: Measure, Optimize, and Scale

Set up a measurement framework that tracks AI visibility alongside traditional e-commerce metrics.

Weekly measurements:

• AI Share of Voice across target query clusters
• Citation accuracy rate
• AI-referred traffic (GA4 segments for AI platform referrals)
• AI-referred conversion rate and revenue

Monthly optimization:

• Identify which content types earn the most AI citations
• Double down on high-performing formats
• Address any new hallucinations or inaccuracies
• Expand content to new query clusters based on emerging search patterns

Quarterly scaling:

• Expand to new product categories and query clusters
• Increase content velocity based on ROI data
• Evaluate AI Copilot or chat integration for your own site
• Benchmark against competitor AI visibility trends

What Makes E-Commerce GEO Different

E-commerce GEO is distinct from B2B or SaaS GEO in several important ways:

Product data is king. AI engines need specific, structured product information: prices, specs, ratings, availability. The brands with the most comprehensive, accurate product data win.

Visual context matters. While AI engines primarily process text, the pages they cite need to provide rich visual experiences for the humans who do click through. Pages that combine strong product imagery with fact-dense text earn both AI citations and human conversions.

Seasonality creates urgency. E-commerce has pronounced seasonal peaks (holiday season, Prime Day, back-to-school). AI search traffic during these peaks is growing at extraordinary rates, as evidenced by the 3,300% YoY growth on Prime Day 2025. Brands need their GEO strategy in place before these peaks, not during them.

Competitive density is extreme. In most e-commerce categories, dozens or hundreds of brands compete for the same conversational queries. Early movers who establish AI citation patterns have a compounding advantage that becomes increasingly difficult to displace.

The Cost of Waiting

Every month an e-commerce brand delays its GEO strategy, competitors are:

• Publishing content that AI engines will cite instead of yours
• Building review volume that strengthens their AI recommendation position
• Establishing conversational query patterns that become self-reinforcing
• Capturing the early-mover advantage in a rapidly growing channel

Kendra Scott did not wait. They committed to 8,000 pages and an AI Copilot integration. The result: 5% of all web traffic and 6% of e-commerce sales from AI channels, with 160% revenue growth.

The blueprint is proven. The question is whether your brand will follow it.

See how your products perform in AI shopping recommendations. Huginn's E-Commerce GEO Audit maps your AI visibility across every major platform and delivers a prioritized action plan. Request your free audit today.