Innovation and R&D Teams

Guided example for innovation and R&D teams with Claude Desktop

Use Case

A beauty brand plans to expand its skincare line with an anti-acne serum formulated for combination skin and aimed at Gen-Z consumers. The team wants to pair consumer-trusted acne-fighting ingredients with a fragrance profile that resonates with younger noses.

The Innovation and R&D team connects Claude to CosmetiQ-MCP and begin digging into the dataset for actionable insights.

Ask Claude to connect to CometiQ-MCP

Prompt the following into Claude Desktop to connect ComsetiQ's demo envirnonment:

Connect to CosmetiQ-MCP!

Generate a Market-Overview Dashboard

Let's query CosmetiQ's dataset with:

My team is developing an anti-acne serum for combination skin, targeted at Gen-Z consumers through an optimal fragrance strategy. 
Please generate a comprehensive market-overview dashboard to guide our research case, with focus on consumer-trusted ingredients and fragrance profiles loved by younger nose.

Here's the dashboard (made with Claude in seconds by analysing ComsetiQ-MCP data):

Here's the key insights from the dashboard:

Here's the tep-by-step process Claude used to generate that comprehensive dashboard and insights:

🔗 Step 1: Database Connection

First, I connected to the CosmetiQ database using the cosmetiq_connect function. This gave me:

  • A unique connection ID for all subsequent queries

  • Overview of available schemas (core, ref, information_schema)

  • Understanding of my role as "Q" - the AI agent for cosmetic industry insights

🔍 Step 2: Data Structure Exploration

I explored the database structure to understand what data was available:

  • Checked column names in olyoung_essence_reviews_ai table

  • Discovered the exact naming conventions (e.g., "SkinType Combination" vs "SkinType_Combination")

  • Found star rating columns like "Review stars 1-5 product general"

  • Located ingredient columns with pattern "Ingredient [name]"

🎯 Step 3: Target Market Analysis

I ran specific queries to analyze anti-acne products for combination skin:

-- Example query structure
SELECT columns
FROM core.olyoung_essence_reviews_ai 
WHERE "SkinType Combination" = 1 
    AND "Effect reduced Acne" > 0

🧪 Step 4: Ingredient Performance Analysis

I analyzed the top-performing ingredients by:

  • Using UNION queries to compare multiple ingredients

  • Calculating average ratings, review counts, and effectiveness scores

  • Focusing on key anti-acne ingredients: Niacinamide, Centella Asiatica, Salicylic Acid

🌸 Step 5: Fragrance Preferences Research

I queried the fragrance-specific table (olyoung_essence_reviews_ai_fragrance) to understand:

  • Scent family preferences (fruity, citrus, floral, aromatic)

  • Pleasantness scores and intensity preferences

  • Comfort levels with different fragrance profiles

🌍 Step 6: Global Market Insights

I analyzed consumer demographics by:

  • Grouping reviews by "Origin" (language as proxy for region)

  • Calculating satisfaction scores by market

  • Identifying primary and emerging markets

📊 Step 7: Dashboard Creation

I created an interactive HTML dashboard with:

  • Chart.js for data visualizations (doughnut and bar charts)

  • Responsive CSS Grid layout for optimal viewing

  • Modern design with gradients, shadows, and hover effects

  • Real data integration from my SQL queries

💡 Step 8: Insight Synthesis

Finally, I synthesized all data into actionable insights:

  • Quantified recommendations (e.g., "343 reviews", "4.86/5 satisfaction")

  • Strategic priorities ranked by data strength

  • Clear next steps for product development

This methodology ensures data-driven, actionable insights while maintaining visual appeal and professional presentation for your team's decision-making process.

Evaluate which “support” ingredients pair best with Niacinamide or Centella Asiatica (CICA)

After having analysing key insights from CosmetiQ-MCP, we can sharpen the research topic with a new angle by prompting:

Based on the same research topic, which are the secondary ingredients consumers love most when paired with Niacinamide and with Centella Asiatica in anti-acne products for combination skin?

Here's a new dashboard for decision making on the topic:

Here's the key findings:

🎯 Evidence-Based Anti-Acne Insights

🏆 Real Performance Champions

1. Niacinamide + Zinc PCA

  • 7.69% acne success rate (vs 2.93% market baseline)

  • +163% improvement over market baseline

  • +179% improvement over Niacinamide alone

  • Highest efficacy but smaller sample (143 reviews)

2. Centella + Madecassoside

  • 7.08% acne success rate

  • +142% improvement over market baseline

  • 1,215 reviews validation (high statistical significance)

  • Best balance of efficacy + validation

3. Centella + Hyaluronic Acid

  • 4.00% acne success rate

  • +37% improvement over market baseline

  • 2,500 reviews (mass market validated)

  • Solid improvement with maximum consumer validation

🔬 Key Market Realities

Baseline Performance:

  • Market baseline: 2.93% acne success rate

  • Niacinamide alone: 2.75% (slightly below market)

  • Centella alone: 5.57% (clearly superior base ingredient)

Strategic Insights:

  1. Centella outperforms Niacinamide as a base anti-acne ingredient

  2. Zinc PCA is the ultimate booster (+179% improvement potential)

  3. Real cosmetic efficacy rates are low (2-8% range is normal)

  4. Combinations that show 2x+ improvement are genuinely significant

🚀 Strategic Recommendations

  1. Maximum Efficacy: Niacinamide + Zinc PCA for premium positioning

  2. Validated Leader: Centella + Madecassoside for evidence-based claims

  3. Mass Market: Centella + Hyaluronic Acid for broad consumer appeal

  4. Base Ingredient Choice: Consider Centella over Niacinamide for anti-acne focus

The corrected dashboard now shows realistic success rates while highlighting combinations that genuinely outperform market baseline - providing actionable insights for your formulation strategy.

Analyse Pleasantness vs Duration vs Intensity and Comfort for Candidate Fragrances

A new angle for our research topic could be:

For GenZ fragrance preferences, plot pleasantness vs duration. 
Combine pleasantness-duration findings with intensity to understand how to develop our anti-acne seerum for combination skins.

Here's a new dashboard for decision making on the topic:

+

Here's the key findings:

🎯 Critical Gen-Z Fragrance Discoveries

🏆 Teen-Specific Winner: Citrus

  • 1.50 pleasantness score (highest among teens)

  • 0.25 intensity (perfect light presence)

  • 0.0 duration (neutral, not overpowering)

  • Direct teen validation shows citrus is the clear favorite

📊 Pleasantness × Duration Sweet Spot

  • Optimal Duration Range: -0.1 to +0.1 (moderate duration)

  • 760 reviews in this range achieve 1.01 average pleasantness

  • Avoid quick-fading (< -0.3): drops to 0.65 pleasantness

  • Avoid too persistent (> +0.2): may overwhelm Gen-Z preferences

⚡ Intensity-Comfort Critical Findings

  • Sweet Spot: 0.7-0.8 intensity with 0.5+ comfort

  • Risk Zone: 0.9+ intensity significantly reduces comfort

  • Youth Preference: Light presence allows personal fragrance layering

🚀 Strategic Recommendations

🥇 Primary Strategy: Water/Aquatic

Pleasantness: 1.20 (highest overall)
Duration: -0.02 (perfect neutral)
Intensity: 0.74 (youth sweet spot)
Positioning: "Pure, clean, fresh" - ideal for anti-acne messaging

🥈 Alternative Strategy: Fruity

Pleasantness: 1.09 (strong Gen-Z appeal)
Duration: -0.05 (optimal range)
Intensity: 0.78 (comfortable for youth)
Positioning: "Playful, optimistic" - makes skincare fun vs medicinal

🎯 Guidelines

  1. Target Duration: -0.1 to +0.1 range for optimal acceptance

  2. Intensity Cap: Maximum 0.85 to maintain comfort

  3. Teen Focus: Citrus notes for authentic Gen-Z appeal

  4. Daily Routine: Light enough for morning use + makeup compatibility

⚠️ Critical Avoidances

  • Intensity > 0.9: Drops comfort significantly

  • Duration < -0.3: Consumers feel shortchanged

  • Green/Aromatic: Only 0.71 pleasantness (risky for Gen-Z)

This data provides a clear roadmap for creating a Gen-Z optimized fragrance that balances pleasantness, appropriate duration, and comfortable intensity levels specifically for anti-acne combination skin serums.

Next Steps

PreviousWhy CosmetiQ-MCPNextMarketing and Product Teams

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