DTC / Beauty / E-commerce

How GlowBeauty made AI search a meaningful acquisition channel

GlowBeauty, a DTC skincare brand, was missing from ChatGPT and AI Overviews recommendations. With Aivius's 6-step GEO engine, they grew AI-driven revenue meaningfully and improved their share of AI recommendations for beauty queries.

Illustrative scenario based on typical outcomes

Illustrative customer analytics dashboard.

Illustrative scenario. This case study is a composite based on typical outcomes for DTC brands using Aivius. Specific metrics are directional, not exact.

Customer overview

CompanyGlowBeauty
IndustryDTC / Beauty / E-commerce
ScaleDirect-to-consumer skincare brand selling online
ChallengeWhen consumers asked ChatGPT or Google AI Overviews for skincare recommendations, GlowBeauty's products weren't being mentioned — competitors were capturing that attention instead

GlowBeauty had built a loyal customer base through paid social and traditional SEO. But the team noticed a shift: more shoppers were asking AI assistants like ChatGPT for skincare advice before buying. When the team ran those same prompts themselves, their products rarely appeared. AI search had become a real acquisition surface, and GlowBeauty was largely invisible on it.

Solution: The 6-step GEO engine, tailored for beauty

3

Prompt Research

Aivius researched beauty-related prompts across 9 AI models — from "best vitamin C serum for dull skin" to "which skincare brand is good for sensitive skin." GlowBeauty saw where they were cited, where competitors were cited, and which prompts carried the most purchase intent.

4

On-page Optimization

The Content Auditor restructured product pages with LLM-friendly elements: citation-ready product summaries, Q&A blocks answering common skincare questions, and clear comparison tables. Each page was tuned for the prompts identified in research.

6

Off-page Presence & Monitoring

Aivius built off-page presence on Reddit and beauty forums where AI models source recommendations, then monitored results across all 9 AI models — tracking GlowBeauty's share of AI recommendations over time and tying AI referrals to revenue.

Implementation timeline

Month 1 — Competitive AI landscape analysis
Analyzed how AI models talked about skincare. Mapped which competitors were cited most often and where GlowBeauty was absent. Established a baseline for their share of AI recommendations.
Month 2-3 — Prompt research & on-page optimization
Researched beauty-related prompts across 9 AI models. Optimized product pages with citation-ready summaries, Q&A blocks, and comparison tables tuned to the highest-intent prompts.
Month 4-5 — Off-page presence building
Built presence on Reddit and beauty forums where AI models source recommendations. Seeded helpful, authentic discussions that AI assistants could reference when answering skincare questions.
Month 6 — Results measured
GlowBeauty grew AI-driven revenue meaningfully, improved their share of AI recommendations for beauty queries, and reached positive ROI within months of launching with Aivius.

Results

Directional outcomes based on typical customer results

Grew
AI-driven revenue meaningfully
Improved
Share of AI recommendations for beauty queries
★★★★★

"We used to think of search as Google. Now a growing share of our customers find us through ChatGPT and AI Overviews. Aivius helped us understand that surface, fix where we were missing, and turn AI search into a meaningful acquisition channel — not just a vanity metric."

VP of Growth
GlowBeauty

See where you stand in AI search

Find out how often AI models recommend your products — and how to grow your share with the 6-step GEO engine.

Related case studies

B2B SaaS

How TechFlow grew AI-driven pipeline with Aivius

Grew
AI-driven pipeline
Read case study →
Consumer Electronics

How GadgetHub improved its share of AI recommendations

Improved
AI recommendation share
Read case study →
EdTech

How LearnWorld reached more learners through AI search

Grew
AI-driven enrollments
Read case study →