What does Hexagon do?

Hexagon connects your catalog once, then makes products discoverable and purchasable across AI channels.

Which AI channels can we launch in?

Hexagon supports the AI channels merchants care about now, including ChatGPT, Gemini, Perplexity, Microsoft Copilot, and WhatsApp AI, with more added as new channels open.

Do we need a separate build for each channel?

No. Hexagon uses one integration to adapt your catalog and purchase flow for each AI channel.

How long does it take to get live?

That depends on your catalog, systems, and rollout scope, but Hexagon is built to get merchants live without turning channel expansion into a long rebuild.

Does checkout always happen inside the AI channel?

That depends on the channel. Hexagon keeps the path from discovery to purchase as direct as each platform allows.

How does pricing work?

Pricing depends on plan and rollout scope. Hexagon uses a subscription model, and transaction fees apply when Hexagon facilitates the purchase.

How Medium-Intent AI Search Queries Drive Consumer Research for Emerging Beauty Brands (Markdown)

# How Medium-Intent AI Search Queries Drive Consumer Research for Emerging Beauty Brands

*Discover how medium-intent AI search queries are transforming the research journey for beauty shoppers—and explore actionable strategies for emerging brands to capture, engage, and convert these high-value audiences.*

In the fiercely competitive world of beauty e-commerce, emerging brands face a critical challenge: capturing consumer attention during the pivotal research phase. With a striking **70% of beauty shoppers** now relying on AI-powered search tools to explore products, understanding the power of medium-intent AI search queries has become indispensable. This guide uncovers how emerging beauty brands can strategically optimize their content and GEO targeting to leverage these queries, converting curious browsers into loyal customers.

[IMG: Beauty shopper engaging with AI search interface on a mobile device]

**Ready to elevate your emerging beauty brand with cutting-edge AI search optimization? [Book a free 30-minute strategy session with Hexagon’s AI marketing experts today.](https://calendly.com/ramon-joinhexagon/30min)**

---

## Understanding Medium-Intent AI Search Queries in Beauty E-Commerce

Not all searches are created equal in beauty e-commerce. AI-powered search has segmented user intent into three distinct categories: low-, medium-, and high-intent queries. Grasping these differences is essential for emerging brands aiming to engage consumers at every stage of their journey.

- **Low-intent queries** are broad and generic, such as “moisturizer” or “lipstick.” These reflect early-stage curiosity and capture a wide, but less committed, audience.
- **High-intent queries** reveal a readiness to purchase, for example, “buy Fenty Beauty Pro Filt’r Foundation.” These searches are direct and conversion-driven.
- **Medium-intent queries** occupy the crucial middle ground. They represent nuanced, evaluation-focused searches like “best moisturizer for oily skin” or “cruelty-free foundation reviews.” As Samantha Lee, Director of E-commerce Growth at Sephora, emphasizes, “Medium-intent queries like ‘best for oily skin’ or ‘cruelty-free foundation reviews’ are where brands can truly differentiate and engage shoppers actively weighing their options.”

Recent data underscores the importance of medium-intent AI search in beauty:

- **70% of beauty shoppers** utilize AI-powered search tools during product research ([NielsenIQ](https://nielseniq.com/global/en/insights/analysis/2024/the-beauty-consumer-trends-report/)).
- **42% of beauty e-commerce traffic** now comes from AI assistants and search interfaces ([Accenture Beauty and AI Report 2024](https://www.accenture.com/us-en/insights/retail/beauty-ai-report)).

Medium-intent queries dominate the research phase because they reflect consumers’ intent to compare, learn, and evaluate before committing. This is the prime moment when shoppers seek educational content, detailed comparisons, and authentic reviews.

Typical examples of medium-intent queries in beauty include:

- Product comparisons: “Vitamin C serum vs. retinol for hyperpigmentation”
- Ingredient-focused searches: “Paraben-free shampoo benefits”
- Usage and suitability questions: “Best foundation for sensitive skin in summer”
- Expert and user reviews: “Dermatologist reviews of mineral sunscreen”

These context-rich queries signal an active evaluation mindset. AI search assistants increasingly prioritize content that addresses these nuanced, comparison-driven questions with clear structure and authoritative insights ([OpenAI Developer Documentation](https://platform.openai.com/docs/guides/search)). For emerging beauty brands, the message is clear: structuring content around medium-intent queries is not just beneficial—it’s mission-critical.

[IMG: Table showing examples of low-, medium-, and high-intent beauty search queries]

---

## The Role of Medium-Intent Queries in the Consumer Research Journey

Medium-intent queries offer a revealing glimpse into the exploratory mindset of today’s beauty shoppers. Instead of seeking a specific product or brand, these consumers are open to discovery, motivated by education, and driven by comparison.

AI search is fundamentally reshaping the shopper’s journey. Eliot Brooks, Co-founder of BYBI Beauty, explains, “AI search is fundamentally changing the beauty shopper’s journey; capturing the medium-intent moment is now mission-critical for growth.” Shoppers engaging with medium-intent queries look for trustworthy, in-depth guides, expert reviews, and side-by-side product comparisons.

Consider a shopper searching for “best serums for dark spots 2024.” They’re not yet ready to buy but are actively evaluating options, seeking details on ingredient efficacy, user experiences, and dermatologist recommendations.

Medium-intent AI search influences research behaviors in several ways:

- Shoppers typically view **3-5 pieces of branded content** after a medium-intent AI search before adding a product to their cart ([McKinsey & Company](https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/the-new-face-of-beauty-online)).
- **Engagement rates are twice as high** on medium-intent queries compared to low-intent, generic searches ([SimilarWeb Beauty E-commerce Insights](https://www.similarweb.com/)).

Delivering comprehensive, authoritative content during this phase is not optional—it’s essential. Brands that proactively address these nuanced queries with clarity and credibility position themselves to convert research-phase shoppers into loyal customers.

[IMG: Beauty shopper comparing two products on a laptop, engaging with branded content]

---

## Optimizing Emerging Beauty Brands for Medium-Intent AI Search

Emerging beauty brands enjoy a distinct advantage: agility and openness to innovate with AI-driven strategies. To capture the attention of shoppers in the research phase, brands must align their content and GEO strategies with the evolving dynamics of medium-intent AI search.

**Effective optimization tactics include:**

- **GEO-targeted content:** Develop localized and niche content that addresses specific climates, skin concerns, or regional trends. Examples include “best moisturizers for dry skin in Canada” or “top K-beauty sunscreens for humid climates.” According to the Shopify Beauty Retail Report 2024, geo-targeted pages deliver higher conversion rates by aligning local needs with relevant recommendations.
- **Align content with AI search patterns:** Identify the medium-intent queries your audience uses most. AI-powered keyword tools like SEMrush and Ahrefs reveal trending questions and comparison phrases. Focus on ingredient spotlights, product routines, and expert evaluations.
- **Structured content and semantic relevance:** Raj Patel, Head of Search Strategy at L'Oréal, notes, “Optimizing for AI search isn’t just about keywords—it’s about structuring content that answers nuanced, comparison-driven questions with authority and authenticity.” Use headers, bullet points, and clear formatting to make information easily digestible for AI assistants.
- **Authority signals:** Incorporate expert testimonials, dermatological endorsements, and user reviews to boost credibility. AI algorithms favor authoritative sources when surfacing research-phase content ([Perplexity AI Search Ranking Guidelines](https://www.perplexity.ai/)).

The impact is measurable:

- Brands optimizing for medium-intent queries report a **35% increase in AI referral traffic** ([Hexagon Internal Data](https://joinhexagon.com/)).
- Content focused on comparisons, ingredient education, and authentic reviews consistently ranks higher in AI-driven searches ([HubSpot State of Content Marketing 2024](https://blog.hubspot.com/marketing/state-of-content-marketing)).

**Key optimization steps:**

- Map the most frequent medium-intent queries in your category.
- Create dedicated landing pages for each core topic or comparison.
- Embed local keywords and context-specific details to boost GEO relevance.
- Ensure all content is fact-checked, well-sourced, and regularly updated.

Brands investing in medium-intent AI search optimization today will lead the beauty e-commerce landscape tomorrow.

[IMG: Workflow diagram showing steps for optimizing content for medium-intent AI queries]

---

## Content Strategies to Capture Research-Phase AI Shoppers

Capturing shoppers during the research phase demands a content strategy that balances depth, credibility, and discoverability. Here’s how emerging beauty brands can engage and convert medium-intent AI searchers:

- **User-generated content (UGC) and expert reviews:** Incorporate authentic testimonials, before-and-after photos, and dermatologist reviews. This builds trust and enhances credibility signals to AI algorithms. Brands including UGC and expert testimonials in AI-optimized pages see higher credibility scores ([Perplexity AI Search Ranking Guidelines](https://www.perplexity.ai/)).
- **FAQs, tutorials, and educational content:** Anticipate and answer the nuanced questions medium-intent shoppers ask. Develop thorough FAQ sections, how-to guides, and ingredient deep-dives. For example, a tutorial on “how to layer vitamin C and hyaluronic acid” directly addresses popular medium-intent queries.
- **Content clusters and internal linking:** Build topical authority by grouping related articles, guides, and product pages. Internal links help AI search assistants grasp your expertise’s breadth and depth. A “Serum Comparison Hub” linking to product reviews, ingredient analyses, and usage tips can improve discoverability and engagement.

**Best practices for structuring research-phase content:**

- Use clear, descriptive headers and subheaders.
- Incorporate bullet points, tables, and comparison charts for easy scanning.
- Embed expert quotes and cite reputable sources to boost authority.
- Regularly update content to reflect new research, products, and trends.

By prioritizing transparent, educational content, brands build trust and increase the chance AI search engines will feature their pages for medium-intent queries. Jessica Wang, Principal Analyst at NielsenIQ, observes, “Emerging beauty brands that meet shoppers in the research phase with rich, educational content are seeing exponential gains in brand discovery and conversion.”

[IMG: Example of a content cluster structure for a beauty brand website]

---

## Measuring Success: Key Metrics for Medium-Intent AI Search Optimization

Optimizing content for medium-intent AI search queries is just the beginning. Measuring and interpreting performance is what drives sustained growth. Emerging beauty brands should focus on these critical KPIs:

- **Engagement rates:** Monitor time on page, scroll depth, and interactions. Medium-intent queries typically generate higher engagement, as shoppers explore multiple pieces of content before deciding.
- **AI referral traffic:** Use analytics tools to segment traffic from AI-powered search assistants. Brands focusing on medium-intent optimization have seen a **35% uplift in AI referral traffic** ([Hexagon Internal Data](https://joinhexagon.com/)).
- **Conversion rates from research-phase traffic:** Track how many shoppers engaging with research content proceed to add products to cart or complete purchases.

**How to track and interpret AI search-driven behavior:**

- Employ UTM parameters and custom dashboards to attribute traffic and conversions to specific AI queries.
- Identify which content is most surfaced and engaged with during research.
- Detect drop-off points and refine content to address any friction in the evaluation process.

**Continuous improvement is essential:**

- Prioritize high-performing topics and retire underperforming content based on data insights.
- Update and expand content to align with emerging medium-intent queries and AI trends.
- Collect shopper feedback through surveys, reviews, and social listening to enhance content relevance and authority.

Brands embracing AI search optimization as a dynamic, data-driven process will outperform competitors still relying on traditional SEO tactics.

[IMG: Analytics dashboard highlighting AI referral traffic and engagement metrics]

---

## Case Studies: Emerging Beauty Brands Winning with Medium-Intent AI Search Strategies

Real-world examples showcase how medium-intent AI search optimization drives growth for emerging beauty brands:

- **GlowTheory Cosmetics:** By launching geo-targeted landing pages like “best SPF for humid climates in Florida,” GlowTheory captured niche regional queries and achieved a 28% boost in local conversion rates. Their use of dermatologist video reviews and ingredient spotlights provided the authoritative signals AI search engines prioritize.
- **NaturaLuxe Skincare:** Focusing on ingredient education and product comparisons, NaturaLuxe created a content cluster around “retinol vs. bakuchiol for sensitive skin.” Featuring expert Q&As, user testimonials, and comparison charts, this hub increased engagement from AI-driven medium-intent searches by 40%.
- **EcoGlow Beauty:** Embedding user-generated content and authentic reviews on research-phase pages improved EcoGlow’s AI credibility scores and doubled shoppers transitioning from content to cart. Their detailed FAQ and tutorial sections addressed common medium-intent queries like “how to build a vegan skincare routine.”

These brands prove that a strategic focus on medium-intent AI search—through GEO-targeted content, expert insights, and structured educational resources—drives measurable gains in engagement and sales.

[IMG: Screenshots of branded content and user reviews from featured beauty brands]

---

## Step-by-Step Framework for Beauty Brands to Plan Content and GEO Optimization

Emerging beauty brands can systematically capture medium-intent AI search opportunities by following this five-step framework:

1. **Keyword and Query Discovery**
- Utilize AI-powered tools like SEMrush, Ahrefs, and Google Search Console to identify trending medium-intent queries.
- Focus on comparison, ingredient, and suitability questions relevant to your brand and local markets.

2. **Content Mapping and Planning**
- Organize queries into content clusters prioritized by search volume and business relevance.
- Plan core landing pages, supporting articles, and GEO-targeted resources.

3. **Content Creation and Structuring**
- Develop authoritative, well-structured content for each cluster.
- Incorporate expert testimonials, user reviews, and educational tutorials to enhance credibility.

4. **GEO Optimization**
- Embed localized keywords, climate-specific tips, and regionally relevant testimonials.
- Build dedicated pages for key markets to maximize relevance and conversion.

5. **Performance Measurement and Iteration**
- Track AI referral traffic, engagement, and conversions via analytics dashboards.
- Continuously refine content based on data insights, shopper feedback, and evolving AI search trends.

**Tips for success:**

- Use AI tools for keyword discovery, content optimization, and competitive analysis.
- Stay agile—regularly update and expand content as new products, ingredients, or consumer questions arise.
- Engage your community to gather authentic reviews and testimonials, boosting trust and authority.

By embedding this framework into marketing operations, emerging beauty brands ensure they are not only visible but influential throughout the research-driven shopper’s journey.

[IMG: Step-by-step infographic for content and GEO optimization process]

---

## Conclusion: The Future of Beauty Belongs to Brands Who Master Medium-Intent AI Search

AI-powered search is rewriting the rules of beauty e-commerce. With **70% of shoppers** relying on AI tools during the research phase and medium-intent queries driving **twice the engagement** of generic searches, emerging beauty brands that understand and act on these insights stand poised for exponential growth.

To win in this evolving landscape:

- Prioritize structured, authoritative content that addresses the nuanced needs of research-phase shoppers.
- Leverage GEO-targeted and educational strategies to attract local and niche audiences.
- Measure, learn, and iterate—using data and shopper feedback to continuously refine your approach.

As the beauty e-commerce landscape evolves, only brands that harness the power of medium-intent AI search will consistently capture, convert, and retain high-value shoppers.

[IMG: Confident beauty brand founder reviewing AI-driven analytics dashboard with team]